var bibbase_data = {"data":"<img src=\"//bibbase.org/img/ajax-loader.gif\" id=\"spinner\"\n  style=\"display: none;\" alt=\"Loading..\" />\n\n<div id=\"bibbase\">\n\n  <script type=\"text/javascript\">\n    var bibbase = {\n      params: {\"jsonp\":\"1\",\"host\":\"bibbase.org\"},\n      data: [{\"title\":\"Air Pollution Monitoring Using WSN Nodes with Machine Learning Techniques: A Case Study\",\"type\":\"article\",\"year\":\"2021\",\"websites\":\"https://academic.oup.com/jigpal/advance-article/doi/10.1093/jigpal/jzab005/6133990\",\"month\":\"2\",\"day\":\"13\",\"id\":\"1aeb55bd-ea97-3fe8-a1e4-f9a523616cae\",\"created\":\"2022-02-02T03:56:08.786Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:08.786Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2021\",\"private_publication\":false,\"abstract\":\"Air pollution is a current concern of people and government entities. Therefore, in urban scenarios, its monitoring and subsequent analysis is a remarkable and challenging issue due mainly to the variability of polluting-related factors. For this reason, the present work shows the development of a wireless sensor network that, through machine learning techniques, can be classified into three different types of environments: high pollution levels, medium pollution and no noticeable contamination into the Ibarra City. To achieve this goal, signal smoothing stages, prototype selection, feature analysis and a comparison of classification algorithms are performed. As relevant results, there is a classification performance of 95% with a significant noisy data reduction.\",\"bibtype\":\"article\",\"author\":\"Rosero-Montalvo, Paul D and López-Batista, Vivian F and Arciniega-Rocha, Ricardo and Peluffo-Ordóñez, Diego H\",\"doi\":\"10.1093/jigpal/jzab005\",\"journal\":\"Logic Journal of the IGPL\",\"bibtex\":\"@article{\\n title = {Air Pollution Monitoring Using WSN Nodes with Machine Learning Techniques: A Case Study},\\n type = {article},\\n year = {2021},\\n websites = {https://academic.oup.com/jigpal/advance-article/doi/10.1093/jigpal/jzab005/6133990},\\n month = {2},\\n day = {13},\\n id = {1aeb55bd-ea97-3fe8-a1e4-f9a523616cae},\\n created = {2022-02-02T03:56:08.786Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:08.786Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2021},\\n private_publication = {false},\\n abstract = {Air pollution is a current concern of people and government entities. Therefore, in urban scenarios, its monitoring and subsequent analysis is a remarkable and challenging issue due mainly to the variability of polluting-related factors. For this reason, the present work shows the development of a wireless sensor network that, through machine learning techniques, can be classified into three different types of environments: high pollution levels, medium pollution and no noticeable contamination into the Ibarra City. To achieve this goal, signal smoothing stages, prototype selection, feature analysis and a comparison of classification algorithms are performed. As relevant results, there is a classification performance of 95% with a significant noisy data reduction.},\\n bibtype = {article},\\n author = {Rosero-Montalvo, Paul D and López-Batista, Vivian F and Arciniega-Rocha, Ricardo and Peluffo-Ordóñez, Diego H},\\n doi = {10.1093/jigpal/jzab005},\\n journal = {Logic Journal of the IGPL}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"López-Batista,  V., F.\",\"Arciniega-Rocha,  R.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"https://academic.oup.com/jigpal/advance-article/doi/10.1093/jigpal/jzab005/6133990\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-lpezbatista-arciniegarocha-peluffoordez-airpollutionmonitoringusingwsnnodeswithmachinelearningtechniquesacasestudy-2021\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":11,\"html\":\"\"},{\"title\":\"Design of a low computational cost prototype for cardiac arrhythmia detection [Diseño de un prototipo de bajo coste computacional para detección de arritmias cardiacas]\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"470-479\",\"volume\":\"2021\",\"websites\":\"https://search.proquest.com/openview/d9dffd8a726c99f54a47adaf372e13b8/1?pq-origsite=gscholar&cbl=1006393\",\"id\":\"2688dd89-0c9d-3427-a6d6-27db7812bf80\",\"created\":\"2022-02-02T03:56:09.036Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:09.036Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Vargas-Muñoz2021470\",\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"This research presents the design of a prototype for the detection of cardiac arrhythmias that incorporates an embedded low-cost computational system in an environment of limited computational resources capable of analyzing characteristics of the QRS complexes. To do this, a strategy for classifying normal and pathological heart beats is developed in long-term electrocardiographic recordings (Holter), which are representative waves of the beat and their analysis allows identifying ventricular arrhythmias. For the development of this initial prototype, it is found that the use of the k nearest neighbors (k-NN) algorithm together with a stage of selection of variables from the training set is a good alternative and represents an important contribution of this work to experimental level. The experiments were carried out on the basis of cardiac arrhythmia data from the Massachusetts Institute of Technology (MIT). The results are satisfactory and promising. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.\",\"bibtype\":\"article\",\"author\":\"Vargas-Muñoz, A M and Chamorro-Sangoquiza, D C and Umaquinga-Criollo, A C and Rosero-Montalvo, P D and Becerra, M A and Peluffo-Ordóñez, D H and Revelo-Fuelagán, E J\",\"journal\":\"RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao\",\"number\":\"E40\",\"bibtex\":\"@article{\\n title = {Design of a low computational cost prototype for cardiac arrhythmia detection [Diseño de un prototipo de bajo coste computacional para detección de arritmias cardiacas]},\\n type = {article},\\n year = {2021},\\n pages = {470-479},\\n volume = {2021},\\n websites = {https://search.proquest.com/openview/d9dffd8a726c99f54a47adaf372e13b8/1?pq-origsite=gscholar&cbl=1006393},\\n id = {2688dd89-0c9d-3427-a6d6-27db7812bf80},\\n created = {2022-02-02T03:56:09.036Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:09.036Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Vargas-Muñoz2021470},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {This research presents the design of a prototype for the detection of cardiac arrhythmias that incorporates an embedded low-cost computational system in an environment of limited computational resources capable of analyzing characteristics of the QRS complexes. To do this, a strategy for classifying normal and pathological heart beats is developed in long-term electrocardiographic recordings (Holter), which are representative waves of the beat and their analysis allows identifying ventricular arrhythmias. For the development of this initial prototype, it is found that the use of the k nearest neighbors (k-NN) algorithm together with a stage of selection of variables from the training set is a good alternative and represents an important contribution of this work to experimental level. The experiments were carried out on the basis of cardiac arrhythmia data from the Massachusetts Institute of Technology (MIT). The results are satisfactory and promising. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.},\\n bibtype = {article},\\n author = {Vargas-Muñoz, A M and Chamorro-Sangoquiza, D C and Umaquinga-Criollo, A C and Rosero-Montalvo, P D and Becerra, M A and Peluffo-Ordóñez, D H and Revelo-Fuelagán, E J},\\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao},\\n number = {E40}\\n}\",\"author_short\":[\"Vargas-Muñoz,  A., M.\",\"Chamorro-Sangoquiza,  D., C.\",\"Umaquinga-Criollo,  A., C.\",\"Rosero-Montalvo,  P., D.\",\"Becerra,  M., A.\",\"Peluffo-Ordóñez,  D., H.\",\"Revelo-Fuelagán,  E., J.\"],\"urls\":{\"Website\":\"https://search.proquest.com/openview/d9dffd8a726c99f54a47adaf372e13b8/1?pq-origsite=gscholar&cbl=1006393\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"vargasmuoz-chamorrosangoquiza-umaquingacriollo-roseromontalvo-becerra-peluffoordez-revelofuelagn-designofalowcomputationalcostprototypeforcardiacarrhythmiadetectiondiseodeunprototipodebajocostecomputacionalparadeteccindearritmiascardiacas-2021\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Addressing the Data Acquisition Paradigm in the Early Detection of Pediatric Foot Deformities\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"academic editor,children,data analysis,embedded systems,emmanouil,machine learning,plantar pressure\",\"pages\":\"1-17\",\"websites\":\"https://www.mdpi.com/1424-8220/21/13/4422\",\"id\":\"e3698b0d-af9d-3acd-980b-72b08352f328\",\"created\":\"2022-02-02T03:56:09.307Z\",\"file_attached\":\"true\",\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:13.096Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The analysis of plantar pressure through podometry has allowed analyzing and detecting different types of disorders and treatments in child patients. Early detection of an inadequate distribution of the patient’s weight can prevent serious injuries to the knees and lower spine. In this paper, an embedded system capable of detecting the presence of normal, flat, or arched footprints using resistive pressure sensors was proposed. For this purpose, both hardware- and software-related criteria were studied for an improved data acquisition through signal coupling and filtering processes. Subsequently, learning algorithms allowed us to estimate the type of footprint biomechanics in preschool and school children volunteers. As a result, the proposed algorithm achieved an overall classification accuracy of 97.2%. A flat feet share of 60% was encountered in a sample of 1000 preschool children. Similarly, flat feet were observed in 52% of a sample of 600 school children.\",\"bibtype\":\"article\",\"author\":\"Rosero-montalvo, Paul D and Fuentes-hernández, Edison A and Morocho-cayamcela, Manuel E\",\"journal\":\"Sensors\",\"bibtex\":\"@article{\\n title = {Addressing the Data Acquisition Paradigm in the Early Detection of Pediatric Foot Deformities},\\n type = {article},\\n year = {2021},\\n keywords = {academic editor,children,data analysis,embedded systems,emmanouil,machine learning,plantar pressure},\\n pages = {1-17},\\n websites = {https://www.mdpi.com/1424-8220/21/13/4422},\\n id = {e3698b0d-af9d-3acd-980b-72b08352f328},\\n created = {2022-02-02T03:56:09.307Z},\\n file_attached = {true},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:13.096Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The analysis of plantar pressure through podometry has allowed analyzing and detecting different types of disorders and treatments in child patients. Early detection of an inadequate distribution of the patient’s weight can prevent serious injuries to the knees and lower spine. In this paper, an embedded system capable of detecting the presence of normal, flat, or arched footprints using resistive pressure sensors was proposed. For this purpose, both hardware- and software-related criteria were studied for an improved data acquisition through signal coupling and filtering processes. Subsequently, learning algorithms allowed us to estimate the type of footprint biomechanics in preschool and school children volunteers. As a result, the proposed algorithm achieved an overall classification accuracy of 97.2%. A flat feet share of 60% was encountered in a sample of 1000 preschool children. Similarly, flat feet were observed in 52% of a sample of 600 school children.},\\n bibtype = {article},\\n author = {Rosero-montalvo, Paul D and Fuentes-hernández, Edison A and Morocho-cayamcela, Manuel E},\\n journal = {Sensors}\\n}\",\"author_short\":[\"Rosero-montalvo,  P., D.\",\"Fuentes-hernández,  E., A.\",\"Morocho-cayamcela,  M., E.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3/file/6edcd1ce-608a-db0f-48fa-413a482fbe37/2021_Sensors_AddressingtheDataAcquisition.pdf.pdf\",\"Website\":\"https://www.mdpi.com/1424-8220/21/13/4422\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-fuenteshernndez-morochocayamcela-addressingthedataacquisitionparadigmintheearlydetectionofpediatricfootdeformities-2021\",\"role\":\"author\",\"keyword\":[\"academic editor\",\"children\",\"data analysis\",\"embedded systems\",\"emmanouil\",\"machine learning\",\"plantar pressure\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Raspberry Pi-based IoT for shrimp farms Real-time remote monitoring with automated system\",\"type\":\"inproceedings\",\"year\":\"2021\",\"keywords\":\"atmega328p,cyberphysical system,dissolved oxygen,ecuador,salinity,shrimp farming,temperature,xbee\",\"pages\":\"7-10\",\"websites\":\"https://ieeexplore.ieee.org/document/9542907\",\"id\":\"c403ae99-57f9-3597-802a-a0981d13b1a3\",\"created\":\"2022-02-02T03:56:09.567Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:09.567Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"This project analyses the optimal parameters for the shrimp farming, trying to help the aquaculture of Ecuador, using a cyberphysical system, which includes temperature, salinity, dissolved oxygen, and pH sensors to monitor the water conditions and an embedded system to control it using an XBee andATMega328p microcontrollers to remotely activate and deactivate aerators to maintain the quality of each pool in neat conditions.\",\"bibtype\":\"inproceedings\",\"author\":\"Capelo, Jesús and Ruiz, Erick and Asanza, Víctor and Toscano-quiroga, Tonny and Sánchez-pozo, Nadia N and Lorente-leyva, Leandro L and Peluffo-ordóñez, Diego Hernan\",\"booktitle\":\"2021 International Conference on Applied Electronics, AE\",\"bibtex\":\"@inproceedings{\\n title = {Raspberry Pi-based IoT for shrimp farms Real-time remote monitoring with automated system},\\n type = {inproceedings},\\n year = {2021},\\n keywords = {atmega328p,cyberphysical system,dissolved oxygen,ecuador,salinity,shrimp farming,temperature,xbee},\\n pages = {7-10},\\n websites = {https://ieeexplore.ieee.org/document/9542907},\\n id = {c403ae99-57f9-3597-802a-a0981d13b1a3},\\n created = {2022-02-02T03:56:09.567Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:09.567Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {This project analyses the optimal parameters for the shrimp farming, trying to help the aquaculture of Ecuador, using a cyberphysical system, which includes temperature, salinity, dissolved oxygen, and pH sensors to monitor the water conditions and an embedded system to control it using an XBee andATMega328p microcontrollers to remotely activate and deactivate aerators to maintain the quality of each pool in neat conditions.},\\n bibtype = {inproceedings},\\n author = {Capelo, Jesús and Ruiz, Erick and Asanza, Víctor and Toscano-quiroga, Tonny and Sánchez-pozo, Nadia N and Lorente-leyva, Leandro L and Peluffo-ordóñez, Diego Hernan},\\n booktitle = {2021 International Conference on Applied Electronics, AE}\\n}\",\"author_short\":[\"Capelo,  J.\",\"Ruiz,  E.\",\"Asanza,  V.\",\"Toscano-quiroga,  T.\",\"Sánchez-pozo,  N., N.\",\"Lorente-leyva,  L., L.\",\"Peluffo-ordóñez,  D., H.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/9542907\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"capelo-ruiz-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-raspberrypibasediotforshrimpfarmsrealtimeremotemonitoringwithautomatedsystem-2021\",\"role\":\"author\",\"keyword\":[\"atmega328p\",\"cyberphysical system\",\"dissolved oxygen\",\"ecuador\",\"salinity\",\"shrimp farming\",\"temperature\",\"xbee\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Monitoring a turkey hatchery based on a cyber-physical system\",\"type\":\"inproceedings\",\"year\":\"2021\",\"keywords\":\"internet of things,meleagriculture,pid tunner toolbox,sensor,system identification toolbox\",\"websites\":\"https://ieeexplore.ieee.org/document/9542899\",\"id\":\"f1527520-fe07-3126-80c3-7186ffde656e\",\"created\":\"2022-02-02T03:56:09.861Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:09.861Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The implementation of a turkey farm brings with it severe environmental problems due to the deficient study of the physical space where the animals are placed. To counteract this situation and improve the quality of life in the hatchery, it is necessary to monitor and control the following variables: Temperature, Humidity, Ammonia Emission and Lux. The solution is based on a cyber-physical system which is composed of a network of sensors, controller and actuator. The sensors will provide information from the physical environment, the con- troller evaluates these parameters to execute an action to the actuator. Proportional, Integral and Derivative (PID) control defines the setpoint for temperature while Pulse- Width Modulation (PWM) adjusts the light intensity in a spotlight. The End Device executes these actions and its parameters will be sent to ThingSpeak which monitors system behavior the Internet of Things.\",\"bibtype\":\"inproceedings\",\"author\":\"Maisincho-Jivaja, Anthony and Alejandro-Sanjines, Ulbio and Asanza, Víctor and Toscano-Quiroga, Tonny and Sánchez-Pozo, Nadia N. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego Hernan\",\"booktitle\":\"2021 International Conference on Applied Electronics, AE\",\"bibtex\":\"@inproceedings{\\n title = {Monitoring a turkey hatchery based on a cyber-physical system},\\n type = {inproceedings},\\n year = {2021},\\n keywords = {internet of things,meleagriculture,pid tunner toolbox,sensor,system identification toolbox},\\n websites = {https://ieeexplore.ieee.org/document/9542899},\\n id = {f1527520-fe07-3126-80c3-7186ffde656e},\\n created = {2022-02-02T03:56:09.861Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:09.861Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The implementation of a turkey farm brings with it severe environmental problems due to the deficient study of the physical space where the animals are placed. To counteract this situation and improve the quality of life in the hatchery, it is necessary to monitor and control the following variables: Temperature, Humidity, Ammonia Emission and Lux. The solution is based on a cyber-physical system which is composed of a network of sensors, controller and actuator. The sensors will provide information from the physical environment, the con- troller evaluates these parameters to execute an action to the actuator. Proportional, Integral and Derivative (PID) control defines the setpoint for temperature while Pulse- Width Modulation (PWM) adjusts the light intensity in a spotlight. The End Device executes these actions and its parameters will be sent to ThingSpeak which monitors system behavior the Internet of Things.},\\n bibtype = {inproceedings},\\n author = {Maisincho-Jivaja, Anthony and Alejandro-Sanjines, Ulbio and Asanza, Víctor and Toscano-Quiroga, Tonny and Sánchez-Pozo, Nadia N. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego Hernan},\\n booktitle = {2021 International Conference on Applied Electronics, AE}\\n}\",\"author_short\":[\"Maisincho-Jivaja,  A.\",\"Alejandro-Sanjines,  U.\",\"Asanza,  V.\",\"Toscano-Quiroga,  T.\",\"Sánchez-Pozo,  N., N.\",\"Lorente-Leyva,  L., L.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/9542899\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"maisinchojivaja-alejandrosanjines-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-monitoringaturkeyhatcherybasedonacyberphysicalsystem-2021\",\"role\":\"author\",\"keyword\":[\"internet of things\",\"meleagriculture\",\"pid tunner toolbox\",\"sensor\",\"system identification toolbox\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Intelligent WSN system for water quality analysis using machine learning algorithms: A case study (Tahuando river from Ecuador)\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Prototype selection,River pollution,Supervised classification,WSN\",\"websites\":\"https://www.mdpi.com/2072-4292/12/12/1988\",\"id\":\"b68f8492-fa74-3b81-8b98-9a464dc94e39\",\"created\":\"2022-02-02T03:56:10.104Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:10.104Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2020b\",\"private_publication\":false,\"abstract\":\"This work presents a wireless sensor network (WSN) system able to determine the water quality of rivers. Particularly, we consider the Tahuando River from Ibarra, Ecuador, as a case study. The main goal of this research is to determine the river's status throughout its route, by generating data reports into an interactive user interface. To this end, we use an array of sensors collecting several measures such as: turbidity, temperature, water quality, pH, and temperature. Subsequently, from the information collected on an Internet-of-Things (IoT) server, we develop a data analysis scheme with both data representation and supervised classification. As an important result, our system outputs a map that shows the contamination levels of the river at different regions. Furthermore, in terms of data analysis performance, the proposed system reduces the data matrix by 97% from its original size, while it reaches a classification performance over 90%. Furthermore, as an additional remarkable result, we here introduce the so-called quantitative metric of balance (QMB), which measures the balance or ratio between performance and power consumption.\",\"bibtype\":\"article\",\"author\":\"Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Riascos, Jaime A. and Peluffo-Ordóñez, Diego H.\",\"doi\":\"10.3390/rs12121988\",\"journal\":\"Remote Sensing\",\"bibtex\":\"@article{\\n title = {Intelligent WSN system for water quality analysis using machine learning algorithms: A case study (Tahuando river from Ecuador)},\\n type = {article},\\n year = {2020},\\n keywords = {Prototype selection,River pollution,Supervised classification,WSN},\\n websites = {https://www.mdpi.com/2072-4292/12/12/1988},\\n id = {b68f8492-fa74-3b81-8b98-9a464dc94e39},\\n created = {2022-02-02T03:56:10.104Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:10.104Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2020b},\\n private_publication = {false},\\n abstract = {This work presents a wireless sensor network (WSN) system able to determine the water quality of rivers. Particularly, we consider the Tahuando River from Ibarra, Ecuador, as a case study. The main goal of this research is to determine the river's status throughout its route, by generating data reports into an interactive user interface. To this end, we use an array of sensors collecting several measures such as: turbidity, temperature, water quality, pH, and temperature. Subsequently, from the information collected on an Internet-of-Things (IoT) server, we develop a data analysis scheme with both data representation and supervised classification. As an important result, our system outputs a map that shows the contamination levels of the river at different regions. Furthermore, in terms of data analysis performance, the proposed system reduces the data matrix by 97% from its original size, while it reaches a classification performance over 90%. Furthermore, as an additional remarkable result, we here introduce the so-called quantitative metric of balance (QMB), which measures the balance or ratio between performance and power consumption.},\\n bibtype = {article},\\n author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Riascos, Jaime A. and Peluffo-Ordóñez, Diego H.},\\n doi = {10.3390/rs12121988},\\n journal = {Remote Sensing}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"López-Batista,  V., F.\",\"Riascos,  J., A.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"https://www.mdpi.com/2072-4292/12/12/1988\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-lpezbatista-riascos-peluffoordez-intelligentwsnsystemforwaterqualityanalysisusingmachinelearningalgorithmsacasestudytahuandoriverfromecuador-2020\",\"role\":\"author\",\"keyword\":[\"Prototype selection\",\"River pollution\",\"Supervised classification\",\"WSN\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":14,\"html\":\"\"},{\"title\":\"Hybrid Embedded-Systems-based Approach to in-Driver Drunk Status Detection using Image Processing and Sensor Networks\",\"type\":\"article\",\"year\":\"2020\",\"websites\":\"https://ieeexplore.ieee.org/document/9258992\",\"id\":\"1527f9d0-0222-32fe-af6c-76c2bf9af830\",\"created\":\"2022-02-02T03:56:10.365Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:10.365Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2020a\",\"private_publication\":false,\"abstract\":\"Car drivers under the influence of alcohol is one of the most common causes of road traffic accidents. To tackle this issue, an emerging, suitable alternative is the use of intelligent systems -traditionally based on either sensor networks or artificial vision- that are aimed to prevent starting the car when drunk status on the car driver is detected. In such vein, this paper introduces a system whose main objective is identifying a person having alcohol in the blood through supervised classification of sensor-generated and computer-vision-based data. To do so, some drunk-status criteria are considered, namely: the concentration of alcohol in the car environment, the facial temperature of the driver and the pupil width. Specifically, for data acquisition purposes, the proposed system incorporates a gas sensor, temperature sensor and a digital camera. Acquired data are analyzed into a two-stages machine learning system consisting of feature selection and supervised classification algorithms. Both acquisition and analysis stages are to be performed into a embedded system, and therefore all procedures and algorithms are designed to work at low-computational resources. As a remarkable outcome, due mainly to the incorporation of feature selection and relevance analysis stages, proposed approach reaches a classification performance of 98% while ensures adequate operation conditions for the embedded system.\",\"bibtype\":\"article\",\"author\":\"Rosero-Montalvo, Paul D. and Lopez-Batista, Vivian F. and Peluffo-Ordonez, Diego H.\",\"doi\":\"10.1109/jsen.2020.3038143\",\"journal\":\"IEEE Sensors Journal\",\"bibtex\":\"@article{\\n title = {Hybrid Embedded-Systems-based Approach to in-Driver Drunk Status Detection using Image Processing and Sensor Networks},\\n type = {article},\\n year = {2020},\\n websites = {https://ieeexplore.ieee.org/document/9258992},\\n id = {1527f9d0-0222-32fe-af6c-76c2bf9af830},\\n created = {2022-02-02T03:56:10.365Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:10.365Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2020a},\\n private_publication = {false},\\n abstract = {Car drivers under the influence of alcohol is one of the most common causes of road traffic accidents. To tackle this issue, an emerging, suitable alternative is the use of intelligent systems -traditionally based on either sensor networks or artificial vision- that are aimed to prevent starting the car when drunk status on the car driver is detected. In such vein, this paper introduces a system whose main objective is identifying a person having alcohol in the blood through supervised classification of sensor-generated and computer-vision-based data. To do so, some drunk-status criteria are considered, namely: the concentration of alcohol in the car environment, the facial temperature of the driver and the pupil width. Specifically, for data acquisition purposes, the proposed system incorporates a gas sensor, temperature sensor and a digital camera. Acquired data are analyzed into a two-stages machine learning system consisting of feature selection and supervised classification algorithms. Both acquisition and analysis stages are to be performed into a embedded system, and therefore all procedures and algorithms are designed to work at low-computational resources. As a remarkable outcome, due mainly to the incorporation of feature selection and relevance analysis stages, proposed approach reaches a classification performance of 98% while ensures adequate operation conditions for the embedded system.},\\n bibtype = {article},\\n author = {Rosero-Montalvo, Paul D. and Lopez-Batista, Vivian F. and Peluffo-Ordonez, Diego H.},\\n doi = {10.1109/jsen.2020.3038143},\\n journal = {IEEE Sensors Journal}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"Lopez-Batista,  V., F.\",\"Peluffo-Ordonez,  D., H.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/9258992\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-lopezbatista-peluffoordonez-hybridembeddedsystemsbasedapproachtoindriverdrunkstatusdetectionusingimageprocessingandsensornetworks-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":6,\"html\":\"\"},{\"title\":\"Environment monitoring of rose crops greenhouse based on autonomous vehicles with a wsn and data analysis\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Ambient intelligence,Autonomous vehicles,Monitoring systems,Roses crops,Wireless sensor networks\",\"websites\":\"https://www.mdpi.com/1424-8220/20/20/5905\",\"id\":\"d5724f9a-59e2-3c94-9c14-4a64cb13b2f7\",\"created\":\"2022-02-02T03:56:10.605Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:10.605Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2020\",\"private_publication\":false,\"abstract\":\"This work presents a monitoring system for the environmental conditions of rose flower-cultivation in greenhouses. Its main objective is to improve the quality of the crops while regulating the production time. To this end, a system consisting of autonomous quadruped vehicles connected with a wireless sensor network (WSN) is developed, which supports the decision-making on type of action to be carried out in a greenhouse to maintain the appropriate environmental conditions for rose cultivation. A data analysis process was carried out, aimed at designing an in-situ intelligent system able to make proper decisions regarding the cultivation process. This process involves stages for balancing data, prototype selection, and supervised classification. The proposed system produces a significant reduction of data in the training set obtained by the WSN while reaching a high classification performance in real conditions—amounting to 90 % and 97.5%, respectively. As a remarkable outcome, it is also provided an approach to ensure correct planning and selection of routes for the autonomous vehicle through the global positioning system.\",\"bibtype\":\"article\",\"author\":\"Rosero-Montalvo, Paul D. and Erazo-Chamorro, Vanessa C. and López-Batista, Vivian F. and Moreno-García, María N. and Peluffo-Ordóñez, Diego H.\",\"doi\":\"10.3390/s20205905\",\"journal\":\"Sensors (Switzerland)\",\"bibtex\":\"@article{\\n title = {Environment monitoring of rose crops greenhouse based on autonomous vehicles with a wsn and data analysis},\\n type = {article},\\n year = {2020},\\n keywords = {Ambient intelligence,Autonomous vehicles,Monitoring systems,Roses crops,Wireless sensor networks},\\n websites = {https://www.mdpi.com/1424-8220/20/20/5905},\\n id = {d5724f9a-59e2-3c94-9c14-4a64cb13b2f7},\\n created = {2022-02-02T03:56:10.605Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:10.605Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2020},\\n private_publication = {false},\\n abstract = {This work presents a monitoring system for the environmental conditions of rose flower-cultivation in greenhouses. Its main objective is to improve the quality of the crops while regulating the production time. To this end, a system consisting of autonomous quadruped vehicles connected with a wireless sensor network (WSN) is developed, which supports the decision-making on type of action to be carried out in a greenhouse to maintain the appropriate environmental conditions for rose cultivation. A data analysis process was carried out, aimed at designing an in-situ intelligent system able to make proper decisions regarding the cultivation process. This process involves stages for balancing data, prototype selection, and supervised classification. The proposed system produces a significant reduction of data in the training set obtained by the WSN while reaching a high classification performance in real conditions—amounting to 90 % and 97.5%, respectively. As a remarkable outcome, it is also provided an approach to ensure correct planning and selection of routes for the autonomous vehicle through the global positioning system.},\\n bibtype = {article},\\n author = {Rosero-Montalvo, Paul D. and Erazo-Chamorro, Vanessa C. and López-Batista, Vivian F. and Moreno-García, María N. and Peluffo-Ordóñez, Diego H.},\\n doi = {10.3390/s20205905},\\n journal = {Sensors (Switzerland)}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"Erazo-Chamorro,  V., C.\",\"López-Batista,  V., F.\",\"Moreno-García,  M., N.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"https://www.mdpi.com/1424-8220/20/20/5905\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-erazochamorro-lpezbatista-morenogarca-peluffoordez-environmentmonitoringofrosecropsgreenhousebasedonautonomousvehicleswithawsnanddataanalysis-2020\",\"role\":\"author\",\"keyword\":[\"Ambient intelligence\",\"Autonomous vehicles\",\"Monitoring systems\",\"Roses crops\",\"Wireless sensor networks\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"A New Approach to Supervised Data Analysis in Embedded Systems Environments: A Case Study\",\"type\":\"inproceedings\",\"year\":\"2020\",\"keywords\":\"Data analysis,Embedded systems,Sensor data\",\"websites\":\"https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29\",\"id\":\"eaeec4d3-8777-39cd-a984-8ce24e9a4eed\",\"created\":\"2022-02-02T03:56:10.960Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:10.960Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Godoy-Trujillo2020\",\"private_publication\":false,\"abstract\":\"Nowadays, the implementation of embedded systems with sensors for massive data collection has become widely used for their flexibility and improvement in decision making. However, this process can be affected by errors in reading, attrition of systems, among others. For this, a selection approach of supervised algorithms with a prototypes selection criterion is presented, which allows an adequate embedded system performance. To do that a quality measure was established which compromises between the data reduction of the training set, algorithm processing time and the classification performance. As a result, it was determined that the algorithm for the data selection is Condensed Nearest Neighbors (CNN) and the classification algorithm is k-Nearest Neighbour (k-NN).\",\"bibtype\":\"inproceedings\",\"author\":\"Godoy-Trujillo, Pamela E. and Rosero-Montalvo, Paul D. and Suárez-Zambrano, Luis E. and Peluffo-Ordoñez, Diego H. and Revelo-Fuelagán, E. J.\",\"doi\":\"10.1007/978-3-030-52249-0_29\",\"booktitle\":\"Advances in Intelligent Systems and Computing\",\"bibtex\":\"@inproceedings{\\n title = {A New Approach to Supervised Data Analysis in Embedded Systems Environments: A Case Study},\\n type = {inproceedings},\\n year = {2020},\\n keywords = {Data analysis,Embedded systems,Sensor data},\\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29},\\n id = {eaeec4d3-8777-39cd-a984-8ce24e9a4eed},\\n created = {2022-02-02T03:56:10.960Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:10.960Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Godoy-Trujillo2020},\\n private_publication = {false},\\n abstract = {Nowadays, the implementation of embedded systems with sensors for massive data collection has become widely used for their flexibility and improvement in decision making. However, this process can be affected by errors in reading, attrition of systems, among others. For this, a selection approach of supervised algorithms with a prototypes selection criterion is presented, which allows an adequate embedded system performance. To do that a quality measure was established which compromises between the data reduction of the training set, algorithm processing time and the classification performance. As a result, it was determined that the algorithm for the data selection is Condensed Nearest Neighbors (CNN) and the classification algorithm is k-Nearest Neighbour (k-NN).},\\n bibtype = {inproceedings},\\n author = {Godoy-Trujillo, Pamela E. and Rosero-Montalvo, Paul D. and Suárez-Zambrano, Luis E. and Peluffo-Ordoñez, Diego H. and Revelo-Fuelagán, E. J.},\\n doi = {10.1007/978-3-030-52249-0_29},\\n booktitle = {Advances in Intelligent Systems and Computing}\\n}\",\"author_short\":[\"Godoy-Trujillo,  P., E.\",\"Rosero-Montalvo,  P., D.\",\"Suárez-Zambrano,  L., E.\",\"Peluffo-Ordoñez,  D., H.\",\"Revelo-Fuelagán,  E., J.\"],\"urls\":{\"Website\":\"https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"godoytrujillo-roseromontalvo-surezzambrano-peluffoordoez-revelofuelagn-anewapproachtosuperviseddataanalysisinembeddedsystemsenvironmentsacasestudy-2020\",\"role\":\"author\",\"keyword\":[\"Data analysis\",\"Embedded systems\",\"Sensor data\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":1,\"html\":\"\"},{\"type\":\"inbook\",\"year\":\"2019\",\"keywords\":\"Alcohol detection,Drunk detection,Prototype selection,Sensors,Supervised classification\",\"pages\":\"234-243\",\"websites\":\"http://link.springer.com/10.1007/978-3-030-19651-6_23\",\"id\":\"61a2d993-1376-3922-93b3-c2a39cc24c28\",\"created\":\"2022-02-02T03:56:11.204Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:11.204Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2019a\",\"private_publication\":false,\"abstract\":\"This work presents a system for detecting excess alcohol in drivers to reduce road traffic accidents. To do so, criteria such as alcohol concentration the environment, a facial temperature of the driver and width of the pupil are considered. To measure the corresponding variables, the data acquisition procedure uses sensors and artificial vision. Subsequently, data analysis is performed into stages for prototype selection and supervised classification algorithms. Accordingly, the acquired data can be stored and processed in a system with low-computational resources. As a remarkable result, the amount of training samples is significantly reduced, while an admissible classification performance is achieved - reaching then suitable settings regarding the given device’s conditions.\",\"bibtype\":\"inbook\",\"author\":\"Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Erazo-Chamorro, Vanessa C. and Arciniega-Rocha, Ricardo P.\",\"doi\":\"10.1007/978-3-030-19651-6_23\",\"chapter\":\"Multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision\",\"title\":\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2019},\\n keywords = {Alcohol detection,Drunk detection,Prototype selection,Sensors,Supervised classification},\\n pages = {234-243},\\n websites = {http://link.springer.com/10.1007/978-3-030-19651-6_23},\\n id = {61a2d993-1376-3922-93b3-c2a39cc24c28},\\n created = {2022-02-02T03:56:11.204Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:11.204Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2019a},\\n private_publication = {false},\\n abstract = {This work presents a system for detecting excess alcohol in drivers to reduce road traffic accidents. To do so, criteria such as alcohol concentration the environment, a facial temperature of the driver and width of the pupil are considered. To measure the corresponding variables, the data acquisition procedure uses sensors and artificial vision. Subsequently, data analysis is performed into stages for prototype selection and supervised classification algorithms. Accordingly, the acquired data can be stored and processed in a system with low-computational resources. As a remarkable result, the amount of training samples is significantly reduced, while an admissible classification performance is achieved - reaching then suitable settings regarding the given device’s conditions.},\\n bibtype = {inbook},\\n author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Erazo-Chamorro, Vanessa C. and Arciniega-Rocha, Ricardo P.},\\n doi = {10.1007/978-3-030-19651-6_23},\\n chapter = {Multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision},\\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"López-Batista,  V., F.\",\"Peluffo-Ordóñez,  D., H.\",\"Erazo-Chamorro,  V., C.\",\"Arciniega-Rocha,  R., P.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-030-19651-6_23\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-lpezbatista-peluffoordez-erazochamorro-arciniegarocha-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\",\"role\":\"author\",\"keyword\":[\"Alcohol detection\",\"Drunk detection\",\"Prototype selection\",\"Sensors\",\"Supervised classification\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"type\":\"inbook\",\"year\":\"2019\",\"keywords\":\"Data analysis,Environmental monitoring,Environmental science computing,Intelligent system\",\"pages\":\"686-696\",\"websites\":\"http://link.springer.com/10.1007/978-3-030-29859-3_58\",\"id\":\"3b30a58f-f1ff-3ac1-ab36-65d2d7c81020\",\"created\":\"2022-02-02T03:56:11.479Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:11.479Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2019b\",\"private_publication\":false,\"abstract\":\"This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.\",\"bibtype\":\"inbook\",\"author\":\"Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Lorente-Leyva, Leandro L. and Blanco-Valencia, X. P.\",\"doi\":\"10.1007/978-3-030-29859-3_58\",\"chapter\":\"Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study\",\"title\":\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2019},\\n keywords = {Data analysis,Environmental monitoring,Environmental science computing,Intelligent system},\\n pages = {686-696},\\n websites = {http://link.springer.com/10.1007/978-3-030-29859-3_58},\\n id = {3b30a58f-f1ff-3ac1-ab36-65d2d7c81020},\\n created = {2022-02-02T03:56:11.479Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:11.479Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2019b},\\n private_publication = {false},\\n abstract = {This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.},\\n bibtype = {inbook},\\n author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Lorente-Leyva, Leandro L. and Blanco-Valencia, X. P.},\\n doi = {10.1007/978-3-030-29859-3_58},\\n chapter = {Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study},\\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"López-Batista,  V., F.\",\"Peluffo-Ordóñez,  D., H.\",\"Lorente-Leyva,  L., L.\",\"Blanco-Valencia,  X., P.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-030-29859-3_58\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\",\"role\":\"author\",\"keyword\":[\"Data analysis\",\"Environmental monitoring\",\"Environmental science computing\",\"Intelligent system\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Intelligent system for identification of wheelchair user's posture using machine learning techniques\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"Embedded system,K-nearest neighbors,Kennard-stone,posture detection,principal component analysis\",\"websites\":\"https://ieeexplore.ieee.org/document/8565996\",\"id\":\"a2ac7492-b9ff-39bf-aa8e-4cd246d9b449\",\"created\":\"2022-02-02T03:56:11.729Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:11.729Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2019c\",\"private_publication\":false,\"abstract\":\"This paper presents an intelligent system aimed at detecting a person's posture when sitting in a wheelchair. The main use of the proposed system is to warn an improper posture to prevent major health issues. A network of sensors is used to collect data that are analyzed through a scheme involving the following stages: Selection of prototypes using condensed nearest neighborhood rule (CNN), data balancing with the Kennard-Stone algorithm, and reduction of dimensionality through principal component analysis. In doing so, acquired data can be both stored and processed into a micro controller. Finally, to carry out the posture classification over balanced, pre-processed data, and the K-nearest neighbors algorithm is used. It turns to be an intelligent system reaching a good tradeoff between the necessary amount of data and performance is accomplished. As a remarkable result, the amount of required data for training is significantly reduced while an admissible classification performance is achieved being a suitable trade given the device conditions.\",\"bibtype\":\"article\",\"author\":\"Rosero-Montalvo, Paul D. and Peluffo-Ordonez, Diego Hernn and Lopez Batista, Vivian Felix and Serrano, Jorge and Rosero, Edwin A.\",\"doi\":\"10.1109/JSEN.2018.2885323\",\"journal\":\"IEEE Sensors Journal\",\"bibtex\":\"@article{\\n title = {Intelligent system for identification of wheelchair user's posture using machine learning techniques},\\n type = {article},\\n year = {2019},\\n keywords = {Embedded system,K-nearest neighbors,Kennard-stone,posture detection,principal component analysis},\\n websites = {https://ieeexplore.ieee.org/document/8565996},\\n id = {a2ac7492-b9ff-39bf-aa8e-4cd246d9b449},\\n created = {2022-02-02T03:56:11.729Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:11.729Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2019c},\\n private_publication = {false},\\n abstract = {This paper presents an intelligent system aimed at detecting a person's posture when sitting in a wheelchair. The main use of the proposed system is to warn an improper posture to prevent major health issues. A network of sensors is used to collect data that are analyzed through a scheme involving the following stages: Selection of prototypes using condensed nearest neighborhood rule (CNN), data balancing with the Kennard-Stone algorithm, and reduction of dimensionality through principal component analysis. In doing so, acquired data can be both stored and processed into a micro controller. Finally, to carry out the posture classification over balanced, pre-processed data, and the K-nearest neighbors algorithm is used. It turns to be an intelligent system reaching a good tradeoff between the necessary amount of data and performance is accomplished. As a remarkable result, the amount of required data for training is significantly reduced while an admissible classification performance is achieved being a suitable trade given the device conditions.},\\n bibtype = {article},\\n author = {Rosero-Montalvo, Paul D. and Peluffo-Ordonez, Diego Hernn and Lopez Batista, Vivian Felix and Serrano, Jorge and Rosero, Edwin A.},\\n doi = {10.1109/JSEN.2018.2885323},\\n journal = {IEEE Sensors Journal}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"Peluffo-Ordonez,  D., H.\",\"Lopez Batista,  V., F.\",\"Serrano,  J.\",\"Rosero,  E., A.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/8565996\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-peluffoordonez-lopezbatista-serrano-rosero-intelligentsystemforidentificationofwheelchairuserspostureusingmachinelearningtechniques-2019\",\"role\":\"author\",\"keyword\":[\"Embedded system\",\"K-nearest neighbors\",\"Kennard-stone\",\"posture detection\",\"principal component analysis\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":9,\"html\":\"\"},{\"type\":\"inbook\",\"year\":\"2019\",\"keywords\":\"Decision making,Embedded systems,Internet of things,Machine learning\",\"pages\":\"874-883\",\"websites\":\"http://link.springer.com/10.1007/978-3-030-02686-8_65\",\"id\":\"29c5309a-6424-3c66-9305-c30fdaec508f\",\"created\":\"2022-02-02T03:56:11.971Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:11.971Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2019\",\"private_publication\":false,\"abstract\":\"The use of electronic systems and devices has become widely spread and is reaching several fields as well as indispensable for many daily activities. Such systems and devices (here termed embedded systems) are aiming at improving human beings’ quality of life. To do so, they typically acquire users’ data to adjust themselves to different needs and environments in an adequate fashion. Consequently, they are connected to data networks to share this information and find elements that allow them to make the appropriate decisions. Then, for practical usage, their computational capabilities should be optimized to avoid issues such as: resources saturation (mainly memory and battery). In this line, machine learning offers a wide range of techniques and tools to incorporate “intelligence” into embedded systems, enabling them to make decisions by themselves. This paper reviews different data storage techniques along with machine learning algorithms for embedded systems. Its main focus is on techniques and applications (with special interest in Internet of Things) reported in literature about data analysis criteria to make decisions.\",\"bibtype\":\"inbook\",\"author\":\"Rosero-Montalvo, Paul D. and Batista, Vivian F. López and Rosero, Edwin A. and Jaramillo, Edgar D. and Caraguay, Jorge A. and Pijal-Rojas, José and Peluffo-Ordóñez, D. H.\",\"doi\":\"10.1007/978-3-030-02686-8_65\",\"chapter\":\"Intelligence in Embedded Systems: Overview and Applications\",\"title\":\"Advances in Intelligent Systems and Computing\",\"bibtex\":\"@inbook{\\n type = {inbook},\\n year = {2019},\\n keywords = {Decision making,Embedded systems,Internet of things,Machine learning},\\n pages = {874-883},\\n websites = {http://link.springer.com/10.1007/978-3-030-02686-8_65},\\n id = {29c5309a-6424-3c66-9305-c30fdaec508f},\\n created = {2022-02-02T03:56:11.971Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:11.971Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2019},\\n private_publication = {false},\\n abstract = {The use of electronic systems and devices has become widely spread and is reaching several fields as well as indispensable for many daily activities. Such systems and devices (here termed embedded systems) are aiming at improving human beings’ quality of life. To do so, they typically acquire users’ data to adjust themselves to different needs and environments in an adequate fashion. Consequently, they are connected to data networks to share this information and find elements that allow them to make the appropriate decisions. Then, for practical usage, their computational capabilities should be optimized to avoid issues such as: resources saturation (mainly memory and battery). In this line, machine learning offers a wide range of techniques and tools to incorporate “intelligence” into embedded systems, enabling them to make decisions by themselves. This paper reviews different data storage techniques along with machine learning algorithms for embedded systems. Its main focus is on techniques and applications (with special interest in Internet of Things) reported in literature about data analysis criteria to make decisions.},\\n bibtype = {inbook},\\n author = {Rosero-Montalvo, Paul D. and Batista, Vivian F. López and Rosero, Edwin A. and Jaramillo, Edgar D. and Caraguay, Jorge A. and Pijal-Rojas, José and Peluffo-Ordóñez, D. H.},\\n doi = {10.1007/978-3-030-02686-8_65},\\n chapter = {Intelligence in Embedded Systems: Overview and Applications},\\n title = {Advances in Intelligent Systems and Computing}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"Batista,  V., F., L.\",\"Rosero,  E., A.\",\"Jaramillo,  E., D.\",\"Caraguay,  J., A.\",\"Pijal-Rojas,  J.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-030-02686-8_65\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-batista-rosero-jaramillo-caraguay-pijalrojas-peluffoordez-advancesinintelligentsystemsandcomputing-2019\",\"role\":\"author\",\"keyword\":[\"Decision making\",\"Embedded systems\",\"Internet of things\",\"Machine learning\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Wireless Sensor Networks for Irrigation in Crops Using Multivariate Regression Models\",\"type\":\"inproceedings\",\"year\":\"2018\",\"keywords\":\"WSN,crops analysis,regression model\",\"pages\":\"1-6\",\"websites\":\"https://ieeexplore.ieee.org/document/8580322/\",\"month\":\"10\",\"publisher\":\"IEEE\",\"id\":\"56cfb072-a7ab-3c59-b930-9796b44f87e8\",\"created\":\"2022-02-02T03:56:12.308Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:12.308Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2018b\",\"private_publication\":false,\"abstract\":\"The present wireless sensor network system shows a data analysis approach within greenhouses in short cycle crops. This research, on the one hand, is carried out to reduce water consumption and improve the product by predicting the right moment of the irrigation cycle through the evapotranspiration criterion. On the other hand, an efficient electronic system is designed under the electronic standard. To define the best model to define the next irrigation in the crops in base to ground humidity, the algorithms are compared for continuous and discontinuous multivariate regressions. The results are evaluated with different criteria of prediction errors. As a result, the linear regression with Support Vector Machine model is chosen for counting an average deviation error of 7.89% and an error variability of 4.48%. In addition, water consumption is reduced by 20%, achieving better quality products.\",\"bibtype\":\"inproceedings\",\"author\":\"Rosero-Montalvo, Paul D. and Pijal-Rojas, Jose and Vasquez-Ayala, Carlos and Maya, Edgar and Pupiales, Carlos and Suarez, Luis and Benitez-Pereira, Henry and Peluffo-Ordonez, D.H.\",\"doi\":\"10.1109/ETCM.2018.8580322\",\"booktitle\":\"2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)\",\"bibtex\":\"@inproceedings{\\n title = {Wireless Sensor Networks for Irrigation in Crops Using Multivariate Regression Models},\\n type = {inproceedings},\\n year = {2018},\\n keywords = {WSN,crops analysis,regression model},\\n pages = {1-6},\\n websites = {https://ieeexplore.ieee.org/document/8580322/},\\n month = {10},\\n publisher = {IEEE},\\n id = {56cfb072-a7ab-3c59-b930-9796b44f87e8},\\n created = {2022-02-02T03:56:12.308Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:12.308Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2018b},\\n private_publication = {false},\\n abstract = {The present wireless sensor network system shows a data analysis approach within greenhouses in short cycle crops. This research, on the one hand, is carried out to reduce water consumption and improve the product by predicting the right moment of the irrigation cycle through the evapotranspiration criterion. On the other hand, an efficient electronic system is designed under the electronic standard. To define the best model to define the next irrigation in the crops in base to ground humidity, the algorithms are compared for continuous and discontinuous multivariate regressions. The results are evaluated with different criteria of prediction errors. As a result, the linear regression with Support Vector Machine model is chosen for counting an average deviation error of 7.89% and an error variability of 4.48%. In addition, water consumption is reduced by 20%, achieving better quality products.},\\n bibtype = {inproceedings},\\n author = {Rosero-Montalvo, Paul D. and Pijal-Rojas, Jose and Vasquez-Ayala, Carlos and Maya, Edgar and Pupiales, Carlos and Suarez, Luis and Benitez-Pereira, Henry and Peluffo-Ordonez, D.H.},\\n doi = {10.1109/ETCM.2018.8580322},\\n booktitle = {2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"Pijal-Rojas,  J.\",\"Vasquez-Ayala,  C.\",\"Maya,  E.\",\"Pupiales,  C.\",\"Suarez,  L.\",\"Benitez-Pereira,  H.\",\"Peluffo-Ordonez,  D.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/8580322/\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-pijalrojas-vasquezayala-maya-pupiales-suarez-benitezpereira-peluffoordonez-wirelesssensornetworksforirrigationincropsusingmultivariateregressionmodels-2018\",\"role\":\"author\",\"keyword\":[\"WSN\",\"crops analysis\",\"regression model\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"},{\"title\":\"Sign Language Recognition Based on Intelligent Glove Using Machine Learning Techniques\",\"type\":\"inproceedings\",\"year\":\"2018\",\"keywords\":\"intelligent glove,knn,prototype selection,sign language\",\"pages\":\"1-5\",\"websites\":\"https://ieeexplore.ieee.org/document/8580268/\",\"month\":\"10\",\"publisher\":\"IEEE\",\"id\":\"05ea9057-f763-3ffa-bd0e-32df0c7eca27\",\"created\":\"2022-02-02T03:56:12.553Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:12.553Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2018a\",\"private_publication\":false,\"abstract\":\"We present an intelligent electronic glove system able to detect numbers of sign language in order to automate the process of communication between a deaf-mute person and others. This is done by translating the hands move sign language into an oral language. The system is inside to a glove with flex sensors in each finger that we are used to collect data that are analyzed through a methodology involving the following stages: (i) Data balancing with the Kennard-Stone (KS), (ii) Comparison of prototypes selection between CHC evolutionary Algorithm and Decremental Reduction Optimization Procedure 3 (DROP3) to define the best one. Subsequently, the K-Nearest Neighbors (kNN) as classifier (iii) is implemented. As a result, the amount of data reduced from stage (i) from storage within the system is 98%. Also, a classification performance of 85% is achieved with CHC evolutionary algorithm.\",\"bibtype\":\"inproceedings\",\"author\":\"Rosero-Montalvo, Paul D. and Godoy-Trujillo, Pamela and Flores-Bosmediano, Edison and Carrascal-Garcia, Jorge and Otero-Potosi, Santiago and Benitez-Pereira, Henry and Peluffo-Ordonez, Diego H.\",\"doi\":\"10.1109/ETCM.2018.8580268\",\"booktitle\":\"2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)\",\"bibtex\":\"@inproceedings{\\n title = {Sign Language Recognition Based on Intelligent Glove Using Machine Learning Techniques},\\n type = {inproceedings},\\n year = {2018},\\n keywords = {intelligent glove,knn,prototype selection,sign language},\\n pages = {1-5},\\n websites = {https://ieeexplore.ieee.org/document/8580268/},\\n month = {10},\\n publisher = {IEEE},\\n id = {05ea9057-f763-3ffa-bd0e-32df0c7eca27},\\n created = {2022-02-02T03:56:12.553Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:12.553Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2018a},\\n private_publication = {false},\\n abstract = {We present an intelligent electronic glove system able to detect numbers of sign language in order to automate the process of communication between a deaf-mute person and others. This is done by translating the hands move sign language into an oral language. The system is inside to a glove with flex sensors in each finger that we are used to collect data that are analyzed through a methodology involving the following stages: (i) Data balancing with the Kennard-Stone (KS), (ii) Comparison of prototypes selection between CHC evolutionary Algorithm and Decremental Reduction Optimization Procedure 3 (DROP3) to define the best one. Subsequently, the K-Nearest Neighbors (kNN) as classifier (iii) is implemented. As a result, the amount of data reduced from stage (i) from storage within the system is 98%. Also, a classification performance of 85% is achieved with CHC evolutionary algorithm.},\\n bibtype = {inproceedings},\\n author = {Rosero-Montalvo, Paul D. and Godoy-Trujillo, Pamela and Flores-Bosmediano, Edison and Carrascal-Garcia, Jorge and Otero-Potosi, Santiago and Benitez-Pereira, Henry and Peluffo-Ordonez, Diego H.},\\n doi = {10.1109/ETCM.2018.8580268},\\n booktitle = {2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"Godoy-Trujillo,  P.\",\"Flores-Bosmediano,  E.\",\"Carrascal-Garcia,  J.\",\"Otero-Potosi,  S.\",\"Benitez-Pereira,  H.\",\"Peluffo-Ordonez,  D., H.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/8580268/\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-godoytrujillo-floresbosmediano-carrascalgarcia-oteropotosi-benitezpereira-peluffoordonez-signlanguagerecognitionbasedonintelligentgloveusingmachinelearningtechniques-2018\",\"role\":\"author\",\"keyword\":[\"intelligent glove\",\"knn\",\"prototype selection\",\"sign language\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":1,\"html\":\"\"},{\"title\":\"Air Quality Monitoring Intelligent System Using Machine Learning Techniques\",\"type\":\"inproceedings\",\"year\":\"2018\",\"keywords\":\"Air quality,Intelligent system,Monitoring system\",\"pages\":\"75-80\",\"websites\":\"https://ieeexplore.ieee.org/document/8564511/\",\"month\":\"11\",\"publisher\":\"IEEE\",\"id\":\"60a4cac5-3c46-3533-8f32-3e56289992ae\",\"created\":\"2022-02-02T03:56:12.803Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-02-02T03:56:12.803Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Rosero-Montalvo2018\",\"private_publication\":false,\"abstract\":\"Environment monitoring is so important because it is based on the first right of people, life and health. For this reason, this system monitoring air quality with different sensor nodes in the Ibarra that evaluate the parameters of CO2, NOx, UV Light, Temperature and Humidity. The data analysis through machine learning algorithms allow the system to classify autonomously if a certain geographical location is exceeding the established emission limits of gases. As a result, the k-Nearest Neighbor algorithm presented a great classification performance when selecting the most contaminated sectors.\",\"bibtype\":\"inproceedings\",\"author\":\"Rosero-Montalvo, Paul D. and Caraguay-Procel, Jorge A. and Jaramillo, Edgar D. and Michilena-Calderon, Jaime M. and Umaquinga-Criollo, Ana C. and Mediavilla-Valverde, Mario and Ruiz, Miguel A. and Beltran, Luis A. and Peluffo, Diego H.\",\"doi\":\"10.1109/INCISCOS.2018.00019\",\"booktitle\":\"2018 International Conference on Information Systems and Computer Science (INCISCOS)\",\"bibtex\":\"@inproceedings{\\n title = {Air Quality Monitoring Intelligent System Using Machine Learning Techniques},\\n type = {inproceedings},\\n year = {2018},\\n keywords = {Air quality,Intelligent system,Monitoring system},\\n pages = {75-80},\\n websites = {https://ieeexplore.ieee.org/document/8564511/},\\n month = {11},\\n publisher = {IEEE},\\n id = {60a4cac5-3c46-3533-8f32-3e56289992ae},\\n created = {2022-02-02T03:56:12.803Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-02-02T03:56:12.803Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Rosero-Montalvo2018},\\n private_publication = {false},\\n abstract = {Environment monitoring is so important because it is based on the first right of people, life and health. For this reason, this system monitoring air quality with different sensor nodes in the Ibarra that evaluate the parameters of CO2, NOx, UV Light, Temperature and Humidity. The data analysis through machine learning algorithms allow the system to classify autonomously if a certain geographical location is exceeding the established emission limits of gases. As a result, the k-Nearest Neighbor algorithm presented a great classification performance when selecting the most contaminated sectors.},\\n bibtype = {inproceedings},\\n author = {Rosero-Montalvo, Paul D. and Caraguay-Procel, Jorge A. and Jaramillo, Edgar D. and Michilena-Calderon, Jaime M. and Umaquinga-Criollo, Ana C. and Mediavilla-Valverde, Mario and Ruiz, Miguel A. and Beltran, Luis A. and Peluffo, Diego H.},\\n doi = {10.1109/INCISCOS.2018.00019},\\n booktitle = {2018 International Conference on Information Systems and Computer Science (INCISCOS)}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"Caraguay-Procel,  J., A.\",\"Jaramillo,  E., D.\",\"Michilena-Calderon,  J., M.\",\"Umaquinga-Criollo,  A., C.\",\"Mediavilla-Valverde,  M.\",\"Ruiz,  M., A.\",\"Beltran,  L., A.\",\"Peluffo,  D., H.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/8564511/\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-caraguayprocel-jaramillo-michilenacalderon-umaquingacriollo-mediavillavalverde-ruiz-beltran-etal-airqualitymonitoringintelligentsystemusingmachinelearningtechniques-2018\",\"role\":\"author\",\"keyword\":[\"Air quality\",\"Intelligent system\",\"Monitoring system\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A New Data-Preprocessing-Related Taxonomy of Sensors for IoT Applications\",\"type\":\"article\",\"year\":\"2022\",\"volume\":\"13\",\"websites\":\"https://www.mdpi.com/2078-2489/13/5/241\",\"id\":\"6e919451-d4ca-33fa-97ea-476c100c1d53\",\"created\":\"2022-05-09T15:28:56.810Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-05-09T15:28:56.810Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"info13050241\",\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"IoT devices play a fundamental role in the machine learning (ML) application pipeline, as they collect rich data for model training using sensors. However, this process can be affected by uncontrollable variables that introduce errors into the data, resulting in a higher computational cost to eliminate them. Thus, selecting the most suitable algorithm for this pre-processing step on-device can reduce ML model complexity and unnecessary bandwidth usage for cloud processing. Therefore, this work presents a new sensor taxonomy with which to deploy data pre-processing on an IoT device by using a specific filter for each data type that the system handles. We define statistical and functional performance metrics to perform filter selection. Experimental results show that the Butterworth filter is a suitable solution for invariant sampling rates, while the Savi&ndash;Golay and medium filters are appropriate choices for variable sampling rates.\",\"bibtype\":\"article\",\"author\":\"Rosero-Montalvo, Paul D and López-Batista, Vivian F and Peluffo-Ordóñez, Diego H\",\"doi\":\"10.3390/info13050241\",\"journal\":\"Information\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {A New Data-Preprocessing-Related Taxonomy of Sensors for IoT Applications},\\n type = {article},\\n year = {2022},\\n volume = {13},\\n websites = {https://www.mdpi.com/2078-2489/13/5/241},\\n id = {6e919451-d4ca-33fa-97ea-476c100c1d53},\\n created = {2022-05-09T15:28:56.810Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-05-09T15:28:56.810Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {info13050241},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {IoT devices play a fundamental role in the machine learning (ML) application pipeline, as they collect rich data for model training using sensors. However, this process can be affected by uncontrollable variables that introduce errors into the data, resulting in a higher computational cost to eliminate them. Thus, selecting the most suitable algorithm for this pre-processing step on-device can reduce ML model complexity and unnecessary bandwidth usage for cloud processing. Therefore, this work presents a new sensor taxonomy with which to deploy data pre-processing on an IoT device by using a specific filter for each data type that the system handles. We define statistical and functional performance metrics to perform filter selection. Experimental results show that the Butterworth filter is a suitable solution for invariant sampling rates, while the Savi&ndash;Golay and medium filters are appropriate choices for variable sampling rates.},\\n bibtype = {article},\\n author = {Rosero-Montalvo, Paul D and López-Batista, Vivian F and Peluffo-Ordóñez, Diego H},\\n doi = {10.3390/info13050241},\\n journal = {Information},\\n number = {5}\\n}\",\"author_short\":[\"Rosero-Montalvo,  P., D.\",\"López-Batista,  V., F.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"https://www.mdpi.com/2078-2489/13/5/241\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"roseromontalvo-lpezbatista-peluffoordez-anewdatapreprocessingrelatedtaxonomyofsensorsforiotapplications-2022\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Electromiographic Signal Processing Using Embedded Artificial Intelligence: An Adaptive Filtering Approach\",\"type\":\"article\",\"year\":\"2022\",\"volume\":\"7\",\"websites\":\"https://www.ijimai.org/journal/bibcite/reference/3162\",\"id\":\"dbf8fb76-8137-39b9-96c9-e599a483de7a\",\"created\":\"2022-08-27T03:33:14.152Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-08-27T03:33:14.152Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"ijmai2022\",\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Proaño-Guevara, Daniel and Blanco-Valencia, Xiomara and Rosero-Montalvo, Paul D and Peluffo-Ordóñez, Diego H\",\"doi\":\"10.9781/ijimai.2022.08.009\",\"journal\":\"International Journal of Interactive Multimedia and Artificial Intelligence\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Electromiographic Signal Processing Using Embedded Artificial Intelligence: An Adaptive Filtering Approach},\\n type = {article},\\n year = {2022},\\n volume = {7},\\n websites = {https://www.ijimai.org/journal/bibcite/reference/3162},\\n id = {dbf8fb76-8137-39b9-96c9-e599a483de7a},\\n created = {2022-08-27T03:33:14.152Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-08-27T03:33:14.152Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {ijmai2022},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Proaño-Guevara, Daniel and Blanco-Valencia, Xiomara and Rosero-Montalvo, Paul D and Peluffo-Ordóñez, Diego H},\\n doi = {10.9781/ijimai.2022.08.009},\\n journal = {International Journal of Interactive Multimedia and Artificial Intelligence},\\n number = {5}\\n}\",\"author_short\":[\"Proaño-Guevara,  D.\",\"Blanco-Valencia,  X.\",\"Rosero-Montalvo,  P., D.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"https://www.ijimai.org/journal/bibcite/reference/3162\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"proaoguevara-blancovalencia-roseromontalvo-peluffoordez-electromiographicsignalprocessingusingembeddedartificialintelligenceanadaptivefilteringapproach-2022\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":4,\"html\":\"\"},{\"title\":\"Analysis of Sorting Algorithms Using a WSN and Environmental Pollution Data based on FPGA\",\"type\":\"inproceedings\",\"year\":\"2022\",\"pages\":\"1-4\",\"websites\":\"https://ieeexplore.ieee.org/document/9920090\",\"id\":\"7aa2d8ec-2350-3657-b8cd-f012a3b86d27\",\"created\":\"2022-10-20T14:01:02.564Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-10-20T14:01:02.564Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"9920090\",\"source_type\":\"inproceedings\",\"private_publication\":false,\"abstract\":\"Wireless Snesor Network (WSN) based systems with a focus on Internet of Things (IoT) applications generate a large amount of data. Many applications that need to process data in real time make use of microcontroller-based architectures with sequential programming. Systems based on sequential programming can emulate parallelism up to a certain number of instructions, which is not the case with Field Programmable Gate Array (FPGA). The main objective of this work is to monitor a network of 40 CO2 sensors and to perform real-time sorting of all data. In addition, the run time analysis of two sorting algorithms is performed: bubble sort and insertion sort. For this purpose, an FPGA-based architecture is implemented, controlled by a finite state machine(FSM), which executes each of the sorting algorithms. The results show that the insertion sort algorithm is faster than the burbble sort, but consumes more hardware resources in the FPGA.\",\"bibtype\":\"inproceedings\",\"author\":\"Montesdeoca, Guillermo and Asanza, Víctor and Chica, Kevin and Peluffo-Ordóñez, Diego H.\",\"doi\":\"10.1109/AE54730.2022.9920090\",\"booktitle\":\"2022 International Conference on Applied Electronics (AE)\",\"bibtex\":\"@inproceedings{\\n title = {Analysis of Sorting Algorithms Using a WSN and Environmental Pollution Data based on FPGA},\\n type = {inproceedings},\\n year = {2022},\\n pages = {1-4},\\n websites = {https://ieeexplore.ieee.org/document/9920090},\\n id = {7aa2d8ec-2350-3657-b8cd-f012a3b86d27},\\n created = {2022-10-20T14:01:02.564Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-10-20T14:01:02.564Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {9920090},\\n source_type = {inproceedings},\\n private_publication = {false},\\n abstract = {Wireless Snesor Network (WSN) based systems with a focus on Internet of Things (IoT) applications generate a large amount of data. Many applications that need to process data in real time make use of microcontroller-based architectures with sequential programming. Systems based on sequential programming can emulate parallelism up to a certain number of instructions, which is not the case with Field Programmable Gate Array (FPGA). The main objective of this work is to monitor a network of 40 CO2 sensors and to perform real-time sorting of all data. In addition, the run time analysis of two sorting algorithms is performed: bubble sort and insertion sort. For this purpose, an FPGA-based architecture is implemented, controlled by a finite state machine(FSM), which executes each of the sorting algorithms. The results show that the insertion sort algorithm is faster than the burbble sort, but consumes more hardware resources in the FPGA.},\\n bibtype = {inproceedings},\\n author = {Montesdeoca, Guillermo and Asanza, Víctor and Chica, Kevin and Peluffo-Ordóñez, Diego H.},\\n doi = {10.1109/AE54730.2022.9920090},\\n booktitle = {2022 International Conference on Applied Electronics (AE)}\\n}\",\"author_short\":[\"Montesdeoca,  G.\",\"Asanza,  V.\",\"Chica,  K.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/9920090\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"montesdeoca-asanza-chica-peluffoordez-analysisofsortingalgorithmsusingawsnandenvironmentalpollutiondatabasedonfpga-2022\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Electrooculography Signals Classification for FPGA-based Human-Computer Interaction\",\"type\":\"inproceedings\",\"year\":\"2022\",\"pages\":\"1-7\",\"websites\":\"https://ieeexplore.ieee.org/document/9989664\",\"id\":\"c535033c-395b-3611-a3e0-9c99cfb876ce\",\"created\":\"2022-12-28T23:00:00.128Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2022-12-28T23:00:00.128Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"9989664\",\"source_type\":\"inproceedings\",\"private_publication\":false,\"abstract\":\"Electrooculographic techniques are applied in the development of new technologies that compensate for the limitations of people with motor disabilities. The algorithms in charge of classifying these signals play a fundamental role, mainly for Human Computer Interfaces (HCI), specially when the machine learning algorithms are implemented in customized hardware like FPGA. In this work, electrooculography data were collected from 10 healthy subjects during six eye movement tasks. Then, the data were filtered and introduced into supervised and unsupervised learning algorithms with six classification labels. The results obtained showed that the SVM algorithm had 93.5% of accuracy, thus being considered the most efficient of the classification algorithms proposed in this work. Then, we develop a custom hardware architecture for real-time implementation of EOG classification model in al FPGA card. We demonstrate the effectiveness of the proposed framework for EOG data classification.\",\"bibtype\":\"inproceedings\",\"author\":\"Asanza, Víctor and Miranda, Jesús and Miranda, Jocelyn and Rivas, Leiber and Hernan Peluffo-Ordóñez, Diego and Pelaez, Enrique and Loayza, Francis and Alejandro, Otilia\",\"doi\":\"10.1109/ANDESCON56260.2022.9989664\",\"booktitle\":\"2022 IEEE ANDESCON\",\"bibtex\":\"@inproceedings{\\n title = {Electrooculography Signals Classification for FPGA-based Human-Computer Interaction},\\n type = {inproceedings},\\n year = {2022},\\n pages = {1-7},\\n websites = {https://ieeexplore.ieee.org/document/9989664},\\n id = {c535033c-395b-3611-a3e0-9c99cfb876ce},\\n created = {2022-12-28T23:00:00.128Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2022-12-28T23:00:00.128Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {9989664},\\n source_type = {inproceedings},\\n private_publication = {false},\\n abstract = {Electrooculographic techniques are applied in the development of new technologies that compensate for the limitations of people with motor disabilities. The algorithms in charge of classifying these signals play a fundamental role, mainly for Human Computer Interfaces (HCI), specially when the machine learning algorithms are implemented in customized hardware like FPGA. In this work, electrooculography data were collected from 10 healthy subjects during six eye movement tasks. Then, the data were filtered and introduced into supervised and unsupervised learning algorithms with six classification labels. The results obtained showed that the SVM algorithm had 93.5% of accuracy, thus being considered the most efficient of the classification algorithms proposed in this work. Then, we develop a custom hardware architecture for real-time implementation of EOG classification model in al FPGA card. We demonstrate the effectiveness of the proposed framework for EOG data classification.},\\n bibtype = {inproceedings},\\n author = {Asanza, Víctor and Miranda, Jesús and Miranda, Jocelyn and Rivas, Leiber and Hernan Peluffo-Ordóñez, Diego and Pelaez, Enrique and Loayza, Francis and Alejandro, Otilia},\\n doi = {10.1109/ANDESCON56260.2022.9989664},\\n booktitle = {2022 IEEE ANDESCON}\\n}\",\"author_short\":[\"Asanza,  V.\",\"Miranda,  J.\",\"Miranda,  J.\",\"Rivas,  L.\",\"Hernan Peluffo-Ordóñez,  D.\",\"Pelaez,  E.\",\"Loayza,  F.\",\"Alejandro,  O.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/9989664\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"asanza-miranda-miranda-rivas-hernanpeluffoordez-pelaez-loayza-alejandro-electrooculographysignalsclassificationforfpgabasedhumancomputerinteraction-2022\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network\",\"type\":\"article\",\"year\":\"2023\",\"volume\":\"8\",\"websites\":\"https://www.mdpi.com/2313-7673/8/2/255\",\"id\":\"3572ed3a-0e95-3efe-99b7-e64737b51518\",\"created\":\"2023-06-17T22:40:04.517Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2023-06-17T22:40:04.517Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"biomimetics8020255\",\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15.\",\"bibtype\":\"article\",\"author\":\"Avilés-Mendoza, Karla and Gaibor-León, Neil George and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H\",\"doi\":\"10.3390/biomimetics8020255\",\"journal\":\"Biomimetics\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network},\\n type = {article},\\n year = {2023},\\n volume = {8},\\n websites = {https://www.mdpi.com/2313-7673/8/2/255},\\n id = {3572ed3a-0e95-3efe-99b7-e64737b51518},\\n created = {2023-06-17T22:40:04.517Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2023-06-17T22:40:04.517Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {biomimetics8020255},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15.},\\n bibtype = {article},\\n author = {Avilés-Mendoza, Karla and Gaibor-León, Neil George and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\\n doi = {10.3390/biomimetics8020255},\\n journal = {Biomimetics},\\n number = {2}\\n}\",\"author_short\":[\"Avilés-Mendoza,  K.\",\"Gaibor-León,  N., G.\",\"Asanza,  V.\",\"Lorente-Leyva,  L., L.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"https://www.mdpi.com/2313-7673/8/2/255\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"avilsmendoza-gaiborlen-asanza-lorenteleyva-peluffoordez-a3dprintedbionichandpoweredbyemgsignalsandcontrolledbyanonlineneuralnetwork-2023\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology\",\"type\":\"article\",\"year\":\"2023\",\"volume\":\"14\",\"websites\":\"http://dx.doi.org/10.14569/IJACSA.2023.0140829\",\"publisher\":\"The Science and Information Organization\",\"id\":\"b5f6f478-e071-3552-b06c-143bb6986f0e\",\"created\":\"2023-08-30T20:19:32.593Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2023-08-30T20:19:32.593Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"Pontón2023\",\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The shrimp farming industry in Ecuador, renowned for its shrimp breeding and exportation, faces challenges due to diseases related to variations in abiotic factors during the maturation stage. This is partly attributed to the traditional methods employed in shrimp farms. Consequently, a prototype has been developed for monitoring and controlling abiotic factors using IoT technology. The proposed system consists of three nodes communicating through the LoRa interface. For control purposes, a fuzzy logic system has been implemented that evaluates temperature and dissolved oxygen abiotic factors to determine the state of the aerator, updating the information in the ThingSpeak application. A detailed analysis of equipment energy consumption and the maximum communication range for message transmission and reception was conducted. Subsequently, the monitoring and control system underwent comprehensive testing, including communication with the visualization platform. The results demonstrated significant improvements in system performance. By modifying parameters in the microcontroller, a 2.55-fold increase in battery durability was achieved. The implemented fuzzy logic system enabled effective on/off control of the aerators, showing a corrective trend in response to variations in the analyzed abiotic parameters. The robustness of the LoRa communication interface was evident in urban environments, achieving a distance of up to 1 km without line of sight.\",\"bibtype\":\"article\",\"author\":\"Pontón, José M Pereira and Ojeda, Verónica and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H\",\"doi\":\"10.14569/IJACSA.2023.0140829\",\"journal\":\"International Journal of Advanced Computer Science and Applications\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology},\\n type = {article},\\n year = {2023},\\n volume = {14},\\n websites = {http://dx.doi.org/10.14569/IJACSA.2023.0140829},\\n publisher = {The Science and Information Organization},\\n id = {b5f6f478-e071-3552-b06c-143bb6986f0e},\\n created = {2023-08-30T20:19:32.593Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2023-08-30T20:19:32.593Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {Pontón2023},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The shrimp farming industry in Ecuador, renowned for its shrimp breeding and exportation, faces challenges due to diseases related to variations in abiotic factors during the maturation stage. This is partly attributed to the traditional methods employed in shrimp farms. Consequently, a prototype has been developed for monitoring and controlling abiotic factors using IoT technology. The proposed system consists of three nodes communicating through the LoRa interface. For control purposes, a fuzzy logic system has been implemented that evaluates temperature and dissolved oxygen abiotic factors to determine the state of the aerator, updating the information in the ThingSpeak application. A detailed analysis of equipment energy consumption and the maximum communication range for message transmission and reception was conducted. Subsequently, the monitoring and control system underwent comprehensive testing, including communication with the visualization platform. The results demonstrated significant improvements in system performance. By modifying parameters in the microcontroller, a 2.55-fold increase in battery durability was achieved. The implemented fuzzy logic system enabled effective on/off control of the aerators, showing a corrective trend in response to variations in the analyzed abiotic parameters. The robustness of the LoRa communication interface was evident in urban environments, achieving a distance of up to 1 km without line of sight.},\\n bibtype = {article},\\n author = {Pontón, José M Pereira and Ojeda, Verónica and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\\n doi = {10.14569/IJACSA.2023.0140829},\\n journal = {International Journal of Advanced Computer Science and Applications},\\n number = {8}\\n}\",\"author_short\":[\"Pontón,  J., M., P.\",\"Ojeda,  V.\",\"Asanza,  V.\",\"Lorente-Leyva,  L., L.\",\"Peluffo-Ordóñez,  D., H.\"],\"urls\":{\"Website\":\"http://dx.doi.org/10.14569/IJACSA.2023.0140829\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"pontn-ojeda-asanza-lorenteleyva-peluffoordez-designandimplementationofaniotcontrolandmonitoringsystemfortheoptimizationofshrimppoolsusingloratechnology-2023\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Myoelectric Prosthesis Using Sensor Fusion Between Electromyography and Pulse Oximetry Signals\",\"type\":\"article\",\"year\":\"2023\",\"keywords\":\"artificial,bioelectric signal,electromyography,intelligence,myoelectric prosthesis,neural network,sensor fusion\",\"pages\":\"641-649\",\"volume\":\"56\",\"websites\":\"https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413\",\"id\":\"9082a1fb-63b8-326c-b8f2-83190391caef\",\"created\":\"2023-10-02T16:15:28.275Z\",\"file_attached\":false,\"profile_id\":\"aba9653c-d139-3f95-aad8-969c487ed2f3\",\"group_id\":\"1e7ab630-581a-3aa0-aaa7-d77ad12b77fe\",\"last_modified\":\"2023-10-02T16:39:16.649Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"citation_key\":\"TorresK.EspinozaJ.AsanzaV.Lorente-LeyvaL.L.Peluffo-Ordonez2023\",\"private_publication\":false,\"abstract\":\"Approximately 215,156 people in Ecuador grapple with physical disabilities, of whom nearly half fall within the 30 to 49% disability range, and a considerable number lack limbs. Moreover, there's been a surge in amputation cases, a trend linked to the increasing diabetes prevalence estimated at around 537 million cases by 2021 as per the International Diabetes Federation (IDF). While prosthetic solutions exist, they might incur high costs or offer constrained movement, even when more affordable. Thus, an alternative is proposed: a myoelectric upper limb prosthesis. This prosthesis would be maneuvered through electromyography and pulse oximetry signals, leveraging artificial intelligence methods. Employing a multi-layer neural network model, a structure comprising an input layer, four hidden layers, and an output layer, yields an impressive 93% prediction accuracy for user movement intentions. For AI model training, data from EMG and PPG sensors were recorded and scrutinized, leading to the condensation of classes from four to three. The model was embedded within an ESP32 C3 DevKit-M1 development board, and open-source blueprints facilitated the prosthesis's creation, complemented by supplementary components for electronics integration. The model attains a 93% precision in predicting classes, while the prosthesis's endurance spans approximately three hours and costs $295, equipped to handle diverse lightweight objects.\",\"bibtype\":\"article\",\"author\":\"Torres, K., Espinoza, J., Asanza, V., Lorente-Leyva, L.L., Peluffo-Ordóñez, D.H.\",\"journal\":\"Journal Européen des Systèmes Automatisés\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Myoelectric Prosthesis Using Sensor Fusion Between Electromyography and Pulse Oximetry Signals},\\n type = {article},\\n year = {2023},\\n keywords = {artificial,bioelectric signal,electromyography,intelligence,myoelectric prosthesis,neural network,sensor fusion},\\n pages = {641-649},\\n volume = {56},\\n websites = {https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413},\\n id = {9082a1fb-63b8-326c-b8f2-83190391caef},\\n created = {2023-10-02T16:15:28.275Z},\\n file_attached = {false},\\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\\n last_modified = {2023-10-02T16:39:16.649Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n citation_key = {TorresK.EspinozaJ.AsanzaV.Lorente-LeyvaL.L.Peluffo-Ordonez2023},\\n private_publication = {false},\\n abstract = {Approximately 215,156 people in Ecuador grapple with physical disabilities, of whom nearly half fall within the 30 to 49% disability range, and a considerable number lack limbs. Moreover, there's been a surge in amputation cases, a trend linked to the increasing diabetes prevalence estimated at around 537 million cases by 2021 as per the International Diabetes Federation (IDF). While prosthetic solutions exist, they might incur high costs or offer constrained movement, even when more affordable. Thus, an alternative is proposed: a myoelectric upper limb prosthesis. This prosthesis would be maneuvered through electromyography and pulse oximetry signals, leveraging artificial intelligence methods. Employing a multi-layer neural network model, a structure comprising an input layer, four hidden layers, and an output layer, yields an impressive 93% prediction accuracy for user movement intentions. For AI model training, data from EMG and PPG sensors were recorded and scrutinized, leading to the condensation of classes from four to three. The model was embedded within an ESP32 C3 DevKit-M1 development board, and open-source blueprints facilitated the prosthesis's creation, complemented by supplementary components for electronics integration. The model attains a 93% precision in predicting classes, while the prosthesis's endurance spans approximately three hours and costs $295, equipped to handle diverse lightweight objects.},\\n bibtype = {article},\\n author = {Torres, K., Espinoza, J., Asanza, V., Lorente-Leyva, L.L., Peluffo-Ordóñez, D.H.},\\n journal = {Journal Européen des Systèmes Automatisés},\\n number = {4}\\n}\",\"author_short\":[\"Torres, K., Espinoza, J., Asanza, V., Lorente-Leyva, L.L., Peluffo-Ordóñez,  D.\"],\"urls\":{\"Website\":\"https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413\"},\"biburl\":\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3\",\"bibbaseid\":\"torres-myoelectricprosthesisusingsensorfusionbetweenelectromyographyandpulseoximetrysignals-2023\",\"role\":\"author\",\"keyword\":[\"artificial\",\"bioelectric signal\",\"electromyography\",\"intelligence\",\"myoelectric prosthesis\",\"neural network\",\"sensor fusion\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"}],\n      metadata: {\"authorlinks\":{}},\n      ownerID: undefined\n    };\n  </script>\n\n  <script type=\"text/javascript\">\n  var site$;\n  if (typeof $ != 'undefined') {\n    console.log('existing jquery: storing and then restoring');\n    site$ = $;\n    $ = null;\n  }\n  </script>\n\n  <script src=\"https://ajax.googleapis.com/ajax/libs/jquery/2.2.4/jquery.min.js\">\n  </script>\n  <script type=\"text/javascript\">\n  if (site$) {\n    console.log('existing jquery: avoiding conflict and restoring');\n    bb$ = $.noConflict(true);\n    $ = site$;\n  } else {\n    bb$ = $;\n  }\n  </script>\n\n  <script src=\"//bibbase.org/js/bibbase.min.js\"\n          type=\"text/javascript\">\n  </script>\n\n  <script type=\"text/javascript\"\n          src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML\">\n  </script>\n  <script type=\"text/x-mathjax-config\">\n    MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\\\(','\\\\)']]},\n                        skipTags: [\"body\"],\n                        processClass: \"bibbase_paper\"});\n  </script>\n\n  <style>\n  @media print {\n    .dontprint {\n        display: none !important;\n    }\n\n  .bibbase_group {\n    background-color: #E0E0E0;\n    font-style: italic;\n    font-size: larger;\n    text-shadow: 0px 0px 3px #FFFFFF;\n    border-radius: 4px 4px 4px 4px;\n    -moz-border-radius: 4px 4px 4px 4px;\n    -webkit-border-radius: 4px;\n    padding: 5px 40px 5px;\n    margin-top: 10px;\n    margin-bottom: 5px;\n    cursor: pointer;\n  }\n\n  .bibbase_paper {\n    margin-bottom: 5px;\n  }\n\n  }\n  </style>\n\n  \n  <div style=\"float: right; margin-right: 10px; margin-top: 10px; text-align: right; font-size: 12px\">\n    generated by\n    <a href=\"//bibbase.org\"\n       onclick=\"trackOutboundLink('bibbase', 'logo clicked', window.location.href, '//bibbase.org'); return false;\">\n      <img src=\"//bibbase.org/img/logo.svg\"\n           style=\"vertical-align: middle; margin-left: 3px; height: 16px;\"/\n           alt=\"bibbase.org\"\n           title=\"BibBase – The easiest way to maintain your publications page.\"\n        ></a>\n    \n  </div>\n  \n\n  <div id=\"bibbase_header\" class=\"dontprint\" style=\"\">\n\n    <ul class=\"nav nav-pills\" style=\"margin: 0px;\">\n\n      <li class=\"dropdown\" id=\"groupby_dropdown\">\n      <a class=\"dropdown-toggle\"\n         data-toggle=\"dropdown\"\n         href=\"#\">\n          Group by\n          <b class=\"caret\"></b>\n      </a>\n      <ul class=\"dropdown-menu\">\n        <li class=\"groupby year\"><a onclick=\"groupby('year')\">\n            Year</a>\n        </li>\n        <li class=\"groupby author\"><a onclick=\"groupby('author_short')\">\n            Author</a>\n        </li>\n        <li class=\"groupby type\"><a onclick=\"groupby('type')\">\n            Type</a>\n        </li>\n        <li class=\"groupby keyword\"><a onclick=\"groupby('keyword')\">\n            Keyword</a>\n        </li>\n        <li class=\"groupby downloads\"><a onclick=\"groupby('downloads')\">\n            Downloads</a>\n        </li>\n      </ul>\n      </li>\n\n\n      <li class=\"dropdown\" id=\"menu_dropdown\">\n      <a class=\"dropdown-toggle\"\n         data-toggle=\"dropdown\"\n         href=\"#\" alt=\"controls\">\n          <i class=\"fa fa-reorder\" alt=\"controls\"></i>\n          <b class=\"caret\"></b>\n      </a>\n      <ul class=\"dropdown-menu\">\n        <li>\n          <a onclick=\"toggleAll()\">\n            <i class=\"fa fa-chevron-down fa-fw\"></i> Expand/Collapse All\n          </a>\n        </li>\n        <li>\n          <a download=\"all.bib\" href=\"data:text/bibtex;base64,@article{
 title = {Air Pollution Monitoring Using WSN Nodes with Machine Learning Techniques: A Case Study},
 type = {article},
 year = {2021},
 websites = {https://academic.oup.com/jigpal/advance-article/doi/10.1093/jigpal/jzab005/6133990},
 month = {2},
 day = {13},
 id = {1aeb55bd-ea97-3fe8-a1e4-f9a523616cae},
 created = {2022-02-02T03:56:08.786Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:08.786Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2021},
 private_publication = {false},
 abstract = {Air pollution is a current concern of people and government entities. Therefore, in urban scenarios, its monitoring and subsequent analysis is a remarkable and challenging issue due mainly to the variability of polluting-related factors. For this reason, the present work shows the development of a wireless sensor network that, through machine learning techniques, can be classified into three different types of environments: high pollution levels, medium pollution and no noticeable contamination into the Ibarra City. To achieve this goal, signal smoothing stages, prototype selection, feature analysis and a comparison of classification algorithms are performed. As relevant results, there is a classification performance of 95% with a significant noisy data reduction.},
 bibtype = {article},
 author = {Rosero-Montalvo, Paul D and López-Batista, Vivian F and Arciniega-Rocha, Ricardo and Peluffo-Ordóñez, Diego H},
 doi = {10.1093/jigpal/jzab005},
 journal = {Logic Journal of the IGPL}
}

@article{
 title = {Design of a low computational cost prototype for cardiac arrhythmia detection [Diseño de un prototipo de bajo coste computacional para detección de arritmias cardiacas]},
 type = {article},
 year = {2021},
 pages = {470-479},
 volume = {2021},
 websites = {https://search.proquest.com/openview/d9dffd8a726c99f54a47adaf372e13b8/1?pq-origsite=gscholar&cbl=1006393},
 id = {2688dd89-0c9d-3427-a6d6-27db7812bf80},
 created = {2022-02-02T03:56:09.036Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:09.036Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Vargas-Muñoz2021470},
 source_type = {article},
 private_publication = {false},
 abstract = {This research presents the design of a prototype for the detection of cardiac arrhythmias that incorporates an embedded low-cost computational system in an environment of limited computational resources capable of analyzing characteristics of the QRS complexes. To do this, a strategy for classifying normal and pathological heart beats is developed in long-term electrocardiographic recordings (Holter), which are representative waves of the beat and their analysis allows identifying ventricular arrhythmias. For the development of this initial prototype, it is found that the use of the k nearest neighbors (k-NN) algorithm together with a stage of selection of variables from the training set is a good alternative and represents an important contribution of this work to experimental level. The experiments were carried out on the basis of cardiac arrhythmia data from the Massachusetts Institute of Technology (MIT). The results are satisfactory and promising. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.},
 bibtype = {article},
 author = {Vargas-Muñoz, A M and Chamorro-Sangoquiza, D C and Umaquinga-Criollo, A C and Rosero-Montalvo, P D and Becerra, M A and Peluffo-Ordóñez, D H and Revelo-Fuelagán, E J},
 journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao},
 number = {E40}
}

@article{
 title = {Addressing the Data Acquisition Paradigm in the Early Detection of Pediatric Foot Deformities},
 type = {article},
 year = {2021},
 keywords = {academic editor,children,data analysis,embedded systems,emmanouil,machine learning,plantar pressure},
 pages = {1-17},
 websites = {https://www.mdpi.com/1424-8220/21/13/4422},
 id = {e3698b0d-af9d-3acd-980b-72b08352f328},
 created = {2022-02-02T03:56:09.307Z},
 file_attached = {true},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:13.096Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The analysis of plantar pressure through podometry has allowed analyzing and detecting different types of disorders and treatments in child patients. Early detection of an inadequate distribution of the patient’s weight can prevent serious injuries to the knees and lower spine. In this paper, an embedded system capable of detecting the presence of normal, flat, or arched footprints using resistive pressure sensors was proposed. For this purpose, both hardware- and software-related criteria were studied for an improved data acquisition through signal coupling and filtering processes. Subsequently, learning algorithms allowed us to estimate the type of footprint biomechanics in preschool and school children volunteers. As a result, the proposed algorithm achieved an overall classification accuracy of 97.2%. A flat feet share of 60% was encountered in a sample of 1000 preschool children. Similarly, flat feet were observed in 52% of a sample of 600 school children.},
 bibtype = {article},
 author = {Rosero-montalvo, Paul D and Fuentes-hernández, Edison A and Morocho-cayamcela, Manuel E},
 journal = {Sensors}
}

@inproceedings{
 title = {Raspberry Pi-based IoT for shrimp farms Real-time remote monitoring with automated system},
 type = {inproceedings},
 year = {2021},
 keywords = {atmega328p,cyberphysical system,dissolved oxygen,ecuador,salinity,shrimp farming,temperature,xbee},
 pages = {7-10},
 websites = {https://ieeexplore.ieee.org/document/9542907},
 id = {c403ae99-57f9-3597-802a-a0981d13b1a3},
 created = {2022-02-02T03:56:09.567Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:09.567Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This project analyses the optimal parameters for the shrimp farming, trying to help the aquaculture of Ecuador, using a cyberphysical system, which includes temperature, salinity, dissolved oxygen, and pH sensors to monitor the water conditions and an embedded system to control it using an XBee andATMega328p microcontrollers to remotely activate and deactivate aerators to maintain the quality of each pool in neat conditions.},
 bibtype = {inproceedings},
 author = {Capelo, Jesús and Ruiz, Erick and Asanza, Víctor and Toscano-quiroga, Tonny and Sánchez-pozo, Nadia N and Lorente-leyva, Leandro L and Peluffo-ordóñez, Diego Hernan},
 booktitle = {2021 International Conference on Applied Electronics, AE}
}

@inproceedings{
 title = {Monitoring a turkey hatchery based on a cyber-physical system},
 type = {inproceedings},
 year = {2021},
 keywords = {internet of things,meleagriculture,pid tunner toolbox,sensor,system identification toolbox},
 websites = {https://ieeexplore.ieee.org/document/9542899},
 id = {f1527520-fe07-3126-80c3-7186ffde656e},
 created = {2022-02-02T03:56:09.861Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:09.861Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The implementation of a turkey farm brings with it severe environmental problems due to the deficient study of the physical space where the animals are placed. To counteract this situation and improve the quality of life in the hatchery, it is necessary to monitor and control the following variables: Temperature, Humidity, Ammonia Emission and Lux. The solution is based on a cyber-physical system which is composed of a network of sensors, controller and actuator. The sensors will provide information from the physical environment, the con- troller evaluates these parameters to execute an action to the actuator. Proportional, Integral and Derivative (PID) control defines the setpoint for temperature while Pulse- Width Modulation (PWM) adjusts the light intensity in a spotlight. The End Device executes these actions and its parameters will be sent to ThingSpeak which monitors system behavior the Internet of Things.},
 bibtype = {inproceedings},
 author = {Maisincho-Jivaja, Anthony and Alejandro-Sanjines, Ulbio and Asanza, Víctor and Toscano-Quiroga, Tonny and Sánchez-Pozo, Nadia N. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego Hernan},
 booktitle = {2021 International Conference on Applied Electronics, AE}
}

@article{
 title = {Intelligent WSN system for water quality analysis using machine learning algorithms: A case study (Tahuando river from Ecuador)},
 type = {article},
 year = {2020},
 keywords = {Prototype selection,River pollution,Supervised classification,WSN},
 websites = {https://www.mdpi.com/2072-4292/12/12/1988},
 id = {b68f8492-fa74-3b81-8b98-9a464dc94e39},
 created = {2022-02-02T03:56:10.104Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:10.104Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2020b},
 private_publication = {false},
 abstract = {This work presents a wireless sensor network (WSN) system able to determine the water quality of rivers. Particularly, we consider the Tahuando River from Ibarra, Ecuador, as a case study. The main goal of this research is to determine the river's status throughout its route, by generating data reports into an interactive user interface. To this end, we use an array of sensors collecting several measures such as: turbidity, temperature, water quality, pH, and temperature. Subsequently, from the information collected on an Internet-of-Things (IoT) server, we develop a data analysis scheme with both data representation and supervised classification. As an important result, our system outputs a map that shows the contamination levels of the river at different regions. Furthermore, in terms of data analysis performance, the proposed system reduces the data matrix by 97% from its original size, while it reaches a classification performance over 90%. Furthermore, as an additional remarkable result, we here introduce the so-called quantitative metric of balance (QMB), which measures the balance or ratio between performance and power consumption.},
 bibtype = {article},
 author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Riascos, Jaime A. and Peluffo-Ordóñez, Diego H.},
 doi = {10.3390/rs12121988},
 journal = {Remote Sensing}
}

@article{
 title = {Hybrid Embedded-Systems-based Approach to in-Driver Drunk Status Detection using Image Processing and Sensor Networks},
 type = {article},
 year = {2020},
 websites = {https://ieeexplore.ieee.org/document/9258992},
 id = {1527f9d0-0222-32fe-af6c-76c2bf9af830},
 created = {2022-02-02T03:56:10.365Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:10.365Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2020a},
 private_publication = {false},
 abstract = {Car drivers under the influence of alcohol is one of the most common causes of road traffic accidents. To tackle this issue, an emerging, suitable alternative is the use of intelligent systems -traditionally based on either sensor networks or artificial vision- that are aimed to prevent starting the car when drunk status on the car driver is detected. In such vein, this paper introduces a system whose main objective is identifying a person having alcohol in the blood through supervised classification of sensor-generated and computer-vision-based data. To do so, some drunk-status criteria are considered, namely: the concentration of alcohol in the car environment, the facial temperature of the driver and the pupil width. Specifically, for data acquisition purposes, the proposed system incorporates a gas sensor, temperature sensor and a digital camera. Acquired data are analyzed into a two-stages machine learning system consisting of feature selection and supervised classification algorithms. Both acquisition and analysis stages are to be performed into a embedded system, and therefore all procedures and algorithms are designed to work at low-computational resources. As a remarkable outcome, due mainly to the incorporation of feature selection and relevance analysis stages, proposed approach reaches a classification performance of 98% while ensures adequate operation conditions for the embedded system.},
 bibtype = {article},
 author = {Rosero-Montalvo, Paul D. and Lopez-Batista, Vivian F. and Peluffo-Ordonez, Diego H.},
 doi = {10.1109/jsen.2020.3038143},
 journal = {IEEE Sensors Journal}
}

@article{
 title = {Environment monitoring of rose crops greenhouse based on autonomous vehicles with a wsn and data analysis},
 type = {article},
 year = {2020},
 keywords = {Ambient intelligence,Autonomous vehicles,Monitoring systems,Roses crops,Wireless sensor networks},
 websites = {https://www.mdpi.com/1424-8220/20/20/5905},
 id = {d5724f9a-59e2-3c94-9c14-4a64cb13b2f7},
 created = {2022-02-02T03:56:10.605Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:10.605Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2020},
 private_publication = {false},
 abstract = {This work presents a monitoring system for the environmental conditions of rose flower-cultivation in greenhouses. Its main objective is to improve the quality of the crops while regulating the production time. To this end, a system consisting of autonomous quadruped vehicles connected with a wireless sensor network (WSN) is developed, which supports the decision-making on type of action to be carried out in a greenhouse to maintain the appropriate environmental conditions for rose cultivation. A data analysis process was carried out, aimed at designing an in-situ intelligent system able to make proper decisions regarding the cultivation process. This process involves stages for balancing data, prototype selection, and supervised classification. The proposed system produces a significant reduction of data in the training set obtained by the WSN while reaching a high classification performance in real conditions—amounting to 90 % and 97.5%, respectively. As a remarkable outcome, it is also provided an approach to ensure correct planning and selection of routes for the autonomous vehicle through the global positioning system.},
 bibtype = {article},
 author = {Rosero-Montalvo, Paul D. and Erazo-Chamorro, Vanessa C. and López-Batista, Vivian F. and Moreno-García, María N. and Peluffo-Ordóñez, Diego H.},
 doi = {10.3390/s20205905},
 journal = {Sensors (Switzerland)}
}

@inproceedings{
 title = {A New Approach to Supervised Data Analysis in Embedded Systems Environments: A Case Study},
 type = {inproceedings},
 year = {2020},
 keywords = {Data analysis,Embedded systems,Sensor data},
 websites = {https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29},
 id = {eaeec4d3-8777-39cd-a984-8ce24e9a4eed},
 created = {2022-02-02T03:56:10.960Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:10.960Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Godoy-Trujillo2020},
 private_publication = {false},
 abstract = {Nowadays, the implementation of embedded systems with sensors for massive data collection has become widely used for their flexibility and improvement in decision making. However, this process can be affected by errors in reading, attrition of systems, among others. For this, a selection approach of supervised algorithms with a prototypes selection criterion is presented, which allows an adequate embedded system performance. To do that a quality measure was established which compromises between the data reduction of the training set, algorithm processing time and the classification performance. As a result, it was determined that the algorithm for the data selection is Condensed Nearest Neighbors (CNN) and the classification algorithm is k-Nearest Neighbour (k-NN).},
 bibtype = {inproceedings},
 author = {Godoy-Trujillo, Pamela E. and Rosero-Montalvo, Paul D. and Suárez-Zambrano, Luis E. and Peluffo-Ordoñez, Diego H. and Revelo-Fuelagán, E. J.},
 doi = {10.1007/978-3-030-52249-0_29},
 booktitle = {Advances in Intelligent Systems and Computing}
}

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Alcohol detection,Drunk detection,Prototype selection,Sensors,Supervised classification},
 pages = {234-243},
 websites = {http://link.springer.com/10.1007/978-3-030-19651-6_23},
 id = {61a2d993-1376-3922-93b3-c2a39cc24c28},
 created = {2022-02-02T03:56:11.204Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:11.204Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2019a},
 private_publication = {false},
 abstract = {This work presents a system for detecting excess alcohol in drivers to reduce road traffic accidents. To do so, criteria such as alcohol concentration the environment, a facial temperature of the driver and width of the pupil are considered. To measure the corresponding variables, the data acquisition procedure uses sensors and artificial vision. Subsequently, data analysis is performed into stages for prototype selection and supervised classification algorithms. Accordingly, the acquired data can be stored and processed in a system with low-computational resources. As a remarkable result, the amount of training samples is significantly reduced, while an admissible classification performance is achieved - reaching then suitable settings regarding the given device’s conditions.},
 bibtype = {inbook},
 author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Erazo-Chamorro, Vanessa C. and Arciniega-Rocha, Ricardo P.},
 doi = {10.1007/978-3-030-19651-6_23},
 chapter = {Multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Data analysis,Environmental monitoring,Environmental science computing,Intelligent system},
 pages = {686-696},
 websites = {http://link.springer.com/10.1007/978-3-030-29859-3_58},
 id = {3b30a58f-f1ff-3ac1-ab36-65d2d7c81020},
 created = {2022-02-02T03:56:11.479Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:11.479Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2019b},
 private_publication = {false},
 abstract = {This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.},
 bibtype = {inbook},
 author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Lorente-Leyva, Leandro L. and Blanco-Valencia, X. P.},
 doi = {10.1007/978-3-030-29859-3_58},
 chapter = {Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

@article{
 title = {Intelligent system for identification of wheelchair user's posture using machine learning techniques},
 type = {article},
 year = {2019},
 keywords = {Embedded system,K-nearest neighbors,Kennard-stone,posture detection,principal component analysis},
 websites = {https://ieeexplore.ieee.org/document/8565996},
 id = {a2ac7492-b9ff-39bf-aa8e-4cd246d9b449},
 created = {2022-02-02T03:56:11.729Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:11.729Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2019c},
 private_publication = {false},
 abstract = {This paper presents an intelligent system aimed at detecting a person's posture when sitting in a wheelchair. The main use of the proposed system is to warn an improper posture to prevent major health issues. A network of sensors is used to collect data that are analyzed through a scheme involving the following stages: Selection of prototypes using condensed nearest neighborhood rule (CNN), data balancing with the Kennard-Stone algorithm, and reduction of dimensionality through principal component analysis. In doing so, acquired data can be both stored and processed into a micro controller. Finally, to carry out the posture classification over balanced, pre-processed data, and the K-nearest neighbors algorithm is used. It turns to be an intelligent system reaching a good tradeoff between the necessary amount of data and performance is accomplished. As a remarkable result, the amount of required data for training is significantly reduced while an admissible classification performance is achieved being a suitable trade given the device conditions.},
 bibtype = {article},
 author = {Rosero-Montalvo, Paul D. and Peluffo-Ordonez, Diego Hernn and Lopez Batista, Vivian Felix and Serrano, Jorge and Rosero, Edwin A.},
 doi = {10.1109/JSEN.2018.2885323},
 journal = {IEEE Sensors Journal}
}

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Decision making,Embedded systems,Internet of things,Machine learning},
 pages = {874-883},
 websites = {http://link.springer.com/10.1007/978-3-030-02686-8_65},
 id = {29c5309a-6424-3c66-9305-c30fdaec508f},
 created = {2022-02-02T03:56:11.971Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:11.971Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2019},
 private_publication = {false},
 abstract = {The use of electronic systems and devices has become widely spread and is reaching several fields as well as indispensable for many daily activities. Such systems and devices (here termed embedded systems) are aiming at improving human beings’ quality of life. To do so, they typically acquire users’ data to adjust themselves to different needs and environments in an adequate fashion. Consequently, they are connected to data networks to share this information and find elements that allow them to make the appropriate decisions. Then, for practical usage, their computational capabilities should be optimized to avoid issues such as: resources saturation (mainly memory and battery). In this line, machine learning offers a wide range of techniques and tools to incorporate “intelligence” into embedded systems, enabling them to make decisions by themselves. This paper reviews different data storage techniques along with machine learning algorithms for embedded systems. Its main focus is on techniques and applications (with special interest in Internet of Things) reported in literature about data analysis criteria to make decisions.},
 bibtype = {inbook},
 author = {Rosero-Montalvo, Paul D. and Batista, Vivian F. López and Rosero, Edwin A. and Jaramillo, Edgar D. and Caraguay, Jorge A. and Pijal-Rojas, José and Peluffo-Ordóñez, D. H.},
 doi = {10.1007/978-3-030-02686-8_65},
 chapter = {Intelligence in Embedded Systems: Overview and Applications},
 title = {Advances in Intelligent Systems and Computing}
}

@inproceedings{
 title = {Wireless Sensor Networks for Irrigation in Crops Using Multivariate Regression Models},
 type = {inproceedings},
 year = {2018},
 keywords = {WSN,crops analysis,regression model},
 pages = {1-6},
 websites = {https://ieeexplore.ieee.org/document/8580322/},
 month = {10},
 publisher = {IEEE},
 id = {56cfb072-a7ab-3c59-b930-9796b44f87e8},
 created = {2022-02-02T03:56:12.308Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:12.308Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2018b},
 private_publication = {false},
 abstract = {The present wireless sensor network system shows a data analysis approach within greenhouses in short cycle crops. This research, on the one hand, is carried out to reduce water consumption and improve the product by predicting the right moment of the irrigation cycle through the evapotranspiration criterion. On the other hand, an efficient electronic system is designed under the electronic standard. To define the best model to define the next irrigation in the crops in base to ground humidity, the algorithms are compared for continuous and discontinuous multivariate regressions. The results are evaluated with different criteria of prediction errors. As a result, the linear regression with Support Vector Machine model is chosen for counting an average deviation error of 7.89% and an error variability of 4.48%. In addition, water consumption is reduced by 20%, achieving better quality products.},
 bibtype = {inproceedings},
 author = {Rosero-Montalvo, Paul D. and Pijal-Rojas, Jose and Vasquez-Ayala, Carlos and Maya, Edgar and Pupiales, Carlos and Suarez, Luis and Benitez-Pereira, Henry and Peluffo-Ordonez, D.H.},
 doi = {10.1109/ETCM.2018.8580322},
 booktitle = {2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)}
}

@inproceedings{
 title = {Sign Language Recognition Based on Intelligent Glove Using Machine Learning Techniques},
 type = {inproceedings},
 year = {2018},
 keywords = {intelligent glove,knn,prototype selection,sign language},
 pages = {1-5},
 websites = {https://ieeexplore.ieee.org/document/8580268/},
 month = {10},
 publisher = {IEEE},
 id = {05ea9057-f763-3ffa-bd0e-32df0c7eca27},
 created = {2022-02-02T03:56:12.553Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:12.553Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2018a},
 private_publication = {false},
 abstract = {We present an intelligent electronic glove system able to detect numbers of sign language in order to automate the process of communication between a deaf-mute person and others. This is done by translating the hands move sign language into an oral language. The system is inside to a glove with flex sensors in each finger that we are used to collect data that are analyzed through a methodology involving the following stages: (i) Data balancing with the Kennard-Stone (KS), (ii) Comparison of prototypes selection between CHC evolutionary Algorithm and Decremental Reduction Optimization Procedure 3 (DROP3) to define the best one. Subsequently, the K-Nearest Neighbors (kNN) as classifier (iii) is implemented. As a result, the amount of data reduced from stage (i) from storage within the system is 98%. Also, a classification performance of 85% is achieved with CHC evolutionary algorithm.},
 bibtype = {inproceedings},
 author = {Rosero-Montalvo, Paul D. and Godoy-Trujillo, Pamela and Flores-Bosmediano, Edison and Carrascal-Garcia, Jorge and Otero-Potosi, Santiago and Benitez-Pereira, Henry and Peluffo-Ordonez, Diego H.},
 doi = {10.1109/ETCM.2018.8580268},
 booktitle = {2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)}
}

@inproceedings{
 title = {Air Quality Monitoring Intelligent System Using Machine Learning Techniques},
 type = {inproceedings},
 year = {2018},
 keywords = {Air quality,Intelligent system,Monitoring system},
 pages = {75-80},
 websites = {https://ieeexplore.ieee.org/document/8564511/},
 month = {11},
 publisher = {IEEE},
 id = {60a4cac5-3c46-3533-8f32-3e56289992ae},
 created = {2022-02-02T03:56:12.803Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-02-02T03:56:12.803Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Rosero-Montalvo2018},
 private_publication = {false},
 abstract = {Environment monitoring is so important because it is based on the first right of people, life and health. For this reason, this system monitoring air quality with different sensor nodes in the Ibarra that evaluate the parameters of CO2, NOx, UV Light, Temperature and Humidity. The data analysis through machine learning algorithms allow the system to classify autonomously if a certain geographical location is exceeding the established emission limits of gases. As a result, the k-Nearest Neighbor algorithm presented a great classification performance when selecting the most contaminated sectors.},
 bibtype = {inproceedings},
 author = {Rosero-Montalvo, Paul D. and Caraguay-Procel, Jorge A. and Jaramillo, Edgar D. and Michilena-Calderon, Jaime M. and Umaquinga-Criollo, Ana C. and Mediavilla-Valverde, Mario and Ruiz, Miguel A. and Beltran, Luis A. and Peluffo, Diego H.},
 doi = {10.1109/INCISCOS.2018.00019},
 booktitle = {2018 International Conference on Information Systems and Computer Science (INCISCOS)}
}

@article{
 title = {A New Data-Preprocessing-Related Taxonomy of Sensors for IoT Applications},
 type = {article},
 year = {2022},
 volume = {13},
 websites = {https://www.mdpi.com/2078-2489/13/5/241},
 id = {6e919451-d4ca-33fa-97ea-476c100c1d53},
 created = {2022-05-09T15:28:56.810Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-05-09T15:28:56.810Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {info13050241},
 source_type = {article},
 private_publication = {false},
 abstract = {IoT devices play a fundamental role in the machine learning (ML) application pipeline, as they collect rich data for model training using sensors. However, this process can be affected by uncontrollable variables that introduce errors into the data, resulting in a higher computational cost to eliminate them. Thus, selecting the most suitable algorithm for this pre-processing step on-device can reduce ML model complexity and unnecessary bandwidth usage for cloud processing. Therefore, this work presents a new sensor taxonomy with which to deploy data pre-processing on an IoT device by using a specific filter for each data type that the system handles. We define statistical and functional performance metrics to perform filter selection. Experimental results show that the Butterworth filter is a suitable solution for invariant sampling rates, while the Savi&ndash;Golay and medium filters are appropriate choices for variable sampling rates.},
 bibtype = {article},
 author = {Rosero-Montalvo, Paul D and López-Batista, Vivian F and Peluffo-Ordóñez, Diego H},
 doi = {10.3390/info13050241},
 journal = {Information},
 number = {5}
}

@article{
 title = {Electromiographic Signal Processing Using Embedded Artificial Intelligence: An Adaptive Filtering Approach},
 type = {article},
 year = {2022},
 volume = {7},
 websites = {https://www.ijimai.org/journal/bibcite/reference/3162},
 id = {dbf8fb76-8137-39b9-96c9-e599a483de7a},
 created = {2022-08-27T03:33:14.152Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-08-27T03:33:14.152Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {ijmai2022},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Proaño-Guevara, Daniel and Blanco-Valencia, Xiomara and Rosero-Montalvo, Paul D and Peluffo-Ordóñez, Diego H},
 doi = {10.9781/ijimai.2022.08.009},
 journal = {International Journal of Interactive Multimedia and Artificial Intelligence},
 number = {5}
}

@inproceedings{
 title = {Analysis of Sorting Algorithms Using a WSN and Environmental Pollution Data based on FPGA},
 type = {inproceedings},
 year = {2022},
 pages = {1-4},
 websites = {https://ieeexplore.ieee.org/document/9920090},
 id = {7aa2d8ec-2350-3657-b8cd-f012a3b86d27},
 created = {2022-10-20T14:01:02.564Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-10-20T14:01:02.564Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {9920090},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Wireless Snesor Network (WSN) based systems with a focus on Internet of Things (IoT) applications generate a large amount of data. Many applications that need to process data in real time make use of microcontroller-based architectures with sequential programming. Systems based on sequential programming can emulate parallelism up to a certain number of instructions, which is not the case with Field Programmable Gate Array (FPGA). The main objective of this work is to monitor a network of 40 CO2 sensors and to perform real-time sorting of all data. In addition, the run time analysis of two sorting algorithms is performed: bubble sort and insertion sort. For this purpose, an FPGA-based architecture is implemented, controlled by a finite state machine(FSM), which executes each of the sorting algorithms. The results show that the insertion sort algorithm is faster than the burbble sort, but consumes more hardware resources in the FPGA.},
 bibtype = {inproceedings},
 author = {Montesdeoca, Guillermo and Asanza, Víctor and Chica, Kevin and Peluffo-Ordóñez, Diego H.},
 doi = {10.1109/AE54730.2022.9920090},
 booktitle = {2022 International Conference on Applied Electronics (AE)}
}

@inproceedings{
 title = {Electrooculography Signals Classification for FPGA-based Human-Computer Interaction},
 type = {inproceedings},
 year = {2022},
 pages = {1-7},
 websites = {https://ieeexplore.ieee.org/document/9989664},
 id = {c535033c-395b-3611-a3e0-9c99cfb876ce},
 created = {2022-12-28T23:00:00.128Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2022-12-28T23:00:00.128Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {9989664},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Electrooculographic techniques are applied in the development of new technologies that compensate for the limitations of people with motor disabilities. The algorithms in charge of classifying these signals play a fundamental role, mainly for Human Computer Interfaces (HCI), specially when the machine learning algorithms are implemented in customized hardware like FPGA. In this work, electrooculography data were collected from 10 healthy subjects during six eye movement tasks. Then, the data were filtered and introduced into supervised and unsupervised learning algorithms with six classification labels. The results obtained showed that the SVM algorithm had 93.5% of accuracy, thus being considered the most efficient of the classification algorithms proposed in this work. Then, we develop a custom hardware architecture for real-time implementation of EOG classification model in al FPGA card. We demonstrate the effectiveness of the proposed framework for EOG data classification.},
 bibtype = {inproceedings},
 author = {Asanza, Víctor and Miranda, Jesús and Miranda, Jocelyn and Rivas, Leiber and Hernan Peluffo-Ordóñez, Diego and Pelaez, Enrique and Loayza, Francis and Alejandro, Otilia},
 doi = {10.1109/ANDESCON56260.2022.9989664},
 booktitle = {2022 IEEE ANDESCON}
}

@article{
 title = {A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network},
 type = {article},
 year = {2023},
 volume = {8},
 websites = {https://www.mdpi.com/2313-7673/8/2/255},
 id = {3572ed3a-0e95-3efe-99b7-e64737b51518},
 created = {2023-06-17T22:40:04.517Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2023-06-17T22:40:04.517Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {biomimetics8020255},
 source_type = {article},
 private_publication = {false},
 abstract = {About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15.},
 bibtype = {article},
 author = {Avilés-Mendoza, Karla and Gaibor-León, Neil George and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},
 doi = {10.3390/biomimetics8020255},
 journal = {Biomimetics},
 number = {2}
}

@article{
 title = {Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology},
 type = {article},
 year = {2023},
 volume = {14},
 websites = {http://dx.doi.org/10.14569/IJACSA.2023.0140829},
 publisher = {The Science and Information Organization},
 id = {b5f6f478-e071-3552-b06c-143bb6986f0e},
 created = {2023-08-30T20:19:32.593Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2023-08-30T20:19:32.593Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Pontón2023},
 source_type = {article},
 private_publication = {false},
 abstract = {The shrimp farming industry in Ecuador, renowned for its shrimp breeding and exportation, faces challenges due to diseases related to variations in abiotic factors during the maturation stage. This is partly attributed to the traditional methods employed in shrimp farms. Consequently, a prototype has been developed for monitoring and controlling abiotic factors using IoT technology. The proposed system consists of three nodes communicating through the LoRa interface. For control purposes, a fuzzy logic system has been implemented that evaluates temperature and dissolved oxygen abiotic factors to determine the state of the aerator, updating the information in the ThingSpeak application. A detailed analysis of equipment energy consumption and the maximum communication range for message transmission and reception was conducted. Subsequently, the monitoring and control system underwent comprehensive testing, including communication with the visualization platform. The results demonstrated significant improvements in system performance. By modifying parameters in the microcontroller, a 2.55-fold increase in battery durability was achieved. The implemented fuzzy logic system enabled effective on/off control of the aerators, showing a corrective trend in response to variations in the analyzed abiotic parameters. The robustness of the LoRa communication interface was evident in urban environments, achieving a distance of up to 1 km without line of sight.},
 bibtype = {article},
 author = {Pontón, José M Pereira and Ojeda, Verónica and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},
 doi = {10.14569/IJACSA.2023.0140829},
 journal = {International Journal of Advanced Computer Science and Applications},
 number = {8}
}

@article{
 title = {Myoelectric Prosthesis Using Sensor Fusion Between Electromyography and Pulse Oximetry Signals},
 type = {article},
 year = {2023},
 keywords = {artificial,bioelectric signal,electromyography,intelligence,myoelectric prosthesis,neural network,sensor fusion},
 pages = {641-649},
 volume = {56},
 websites = {https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413},
 id = {9082a1fb-63b8-326c-b8f2-83190391caef},
 created = {2023-10-02T16:15:28.275Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},
 last_modified = {2023-10-02T16:39:16.649Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {TorresK.EspinozaJ.AsanzaV.Lorente-LeyvaL.L.Peluffo-Ordonez2023},
 private_publication = {false},
 abstract = {Approximately 215,156 people in Ecuador grapple with physical disabilities, of whom nearly half fall within the 30 to 49% disability range, and a considerable number lack limbs. Moreover, there's been a surge in amputation cases, a trend linked to the increasing diabetes prevalence estimated at around 537 million cases by 2021 as per the International Diabetes Federation (IDF). While prosthetic solutions exist, they might incur high costs or offer constrained movement, even when more affordable. Thus, an alternative is proposed: a myoelectric upper limb prosthesis. This prosthesis would be maneuvered through electromyography and pulse oximetry signals, leveraging artificial intelligence methods. Employing a multi-layer neural network model, a structure comprising an input layer, four hidden layers, and an output layer, yields an impressive 93% prediction accuracy for user movement intentions. For AI model training, data from EMG and PPG sensors were recorded and scrutinized, leading to the condensation of classes from four to three. The model was embedded within an ESP32 C3 DevKit-M1 development board, and open-source blueprints facilitated the prosthesis's creation, complemented by supplementary components for electronics integration. The model attains a 93% precision in predicting classes, while the prosthesis's endurance spans approximately three hours and costs $295, equipped to handle diverse lightweight objects.},
 bibtype = {article},
 author = {Torres, K., Espinoza, J., Asanza, V., Lorente-Leyva, L.L., Peluffo-Ordóñez, D.H.},
 journal = {Journal Européen des Systèmes Automatisés},
 number = {4}
}\">\n            <i class=\"fa fa-download fa-fw\"></i> Download BibTeX\n          </a>\n        </li>\n        <li>\n          <a href=\"//bibbase.org/rss?bib=\">\n            <i class=\"fa fa-rss fa-fw\"></i> RSS Feed\n          </a>\n          </li>\n      </ul>\n      </li>\n\n      \n\n\n      \n    </ul>\n\n\n    <div class=\"alert alert-success bibbase_msg\" id=\"bibbase_msg_embed\"\n         style=\"display: none;\">\n\n      Excellent! Next you can\n      <a href=\"/network/register?next=/network/newSiteFromTemplate%3Fbiburl=\"\n      >create a new website with this list</a>, or\n      embed it in an existing web page by copying &amp; pasting\n      any of the following snippets.\n\n      <div style=\"text-align: left; margin-top: 1em;\">\n        <strong>JavaScript</strong>\n        <span class=\"comment recommended\">(easiest)</span>\n        <div class=\"well well-small\">\n          <code>\n            &lt;script src=\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3/group/1e7ab630-581a-3aa0-aaa7-d77ad12b77fe?jsonp=1&amp;jsonp=1\"&gt;&lt;/script&gt;\n          </code>\n        </div>\n\n        <strong>PHP</strong>\n        <div class=\"well well-small\">\n          <code>\n            &lt;?php\n            $contents = file_get_contents(\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3/group/1e7ab630-581a-3aa0-aaa7-d77ad12b77fe?jsonp=1\");\n            print_r($contents);\n            ?&gt;\n          </code>\n        </div>\n\n        <strong>iFrame</strong>\n        <span class=\"comment\">(not recommended)</span>\n        <div class=\"well well-small\">\n          <code>\n            &lt;iframe src=\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3/group/1e7ab630-581a-3aa0-aaa7-d77ad12b77fe?jsonp=1\"&gt;&lt;/iframe&gt;\n          </code>\n        </div>\n\n        <p>\n          For more details see the <a href=\"//bibbase.org/help\">documention</a>.\n        </p>\n      </div>\n    </div>\n\n    <div class=\"alert alert-success bibbase_msg\" id=\"bibbase_msg_preview\"\n         style=\"display: none;\">\n\n      This is a preview! To use this list on your own web site\n      or create a new web site from it,\n      <a href=\"/network/register?next=/network/newAccountWithFile%3FfileId=\"\n      >create a free account</a>. The file will be added\n      and you will be able to edit it in the File Manager.\n      We will show you instructions once you've created your account.\n    </div>\n\n    <div class=\"alert alert-warning bibbase_msg\" id=\"bibbase_msg_mendeley1\"\n         style=\"display: none;\">\n\n      <p>To the site owner:</p>\n\n      <p><strong>Action required!</strong> Mendeley is changing its\n        API. In order to keep using Mendeley with BibBase past April\n        14th, you need to:\n        <ol>\n          <li>renew the authorization for BibBase on Mendeley, and</li>\n          <li>update the BibBase URL\n            in your page the same way you did when you initially set up\n            this page.\n          </li>\n        </ol>\n      </p>\n\n      <p>\n        <a href=\"http://bibbase.org/cgi-bin/mendeley2/get.py\">\n          <i class=\"fa fa-angle-double-right\"></i>\n          Fix it now</a>\n      </p>\n    </div>\n\n  </div>\n\n\n  <div id=\"bibbase_body\">\n    \n  \n  <div class=\"bibbase_group_whole\" id=\"group_2023\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2023')\"\n      onkeypress=\"toggleGroup('group_2023')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2023</span>\n      <span class=\"bibbase_group_count\">\n        \n        (3)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"avilsmendoza-gaiborlen-asanza-lorenteleyva-peluffoordez-a3dprintedbionichandpoweredbyemgsignalsandcontrolledbyanonlineneuralnetwork-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.mdpi.com/2313-7673/8/2/255\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'avilsmendoza-gaiborlen-asanza-lorenteleyva-peluffoordez-a3dprintedbionichandpoweredbyemgsignalsandcontrolledbyanonlineneuralnetwork-2023', 'https://www.mdpi.com/2313-7673/8/2/255', event);\">\n    A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Avilés-Mendoza,  K.; Gaibor-León,  N., G.; Asanza,  V.; Lorente-Leyva,  L., L.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  <i>Biomimetics</i>, 8(2).  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.mdpi.com/2313-7673/8/2/255\"\n     onclick=\"log_download('avilsmendoza-gaiborlen-asanza-lorenteleyva-peluffoordez-a3dprintedbionichandpoweredbyemgsignalsandcontrolledbyanonlineneuralnetwork-2023', 'https://www.mdpi.com/2313-7673/8/2/255', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.3390/biomimetics8020255\"\n     onclick=\"log_download('avilsmendoza-gaiborlen-asanza-lorenteleyva-peluffoordez-a3dprintedbionichandpoweredbyemgsignalsandcontrolledbyanonlineneuralnetwork-2023', 'http://doi.org/10.3390/biomimetics8020255', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/avilsmendoza-gaiborlen-asanza-lorenteleyva-peluffoordez-a3dprintedbionichandpoweredbyemgsignalsandcontrolledbyanonlineneuralnetwork-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('avilsmendoza-gaiborlen-asanza-lorenteleyva-peluffoordez-a3dprintedbionichandpoweredbyemgsignalsandcontrolledbyanonlineneuralnetwork-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network},\n type = {article},\n year = {2023},\n volume = {8},\n websites = {https://www.mdpi.com/2313-7673/8/2/255},\n id = {3572ed3a-0e95-3efe-99b7-e64737b51518},\n created = {2023-06-17T22:40:04.517Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2023-06-17T22:40:04.517Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {biomimetics8020255},\n source_type = {article},\n private_publication = {false},\n abstract = {About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15.},\n bibtype = {article},\n author = {Avilés-Mendoza, Karla and Gaibor-León, Neil George and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/biomimetics8020255},\n journal = {Biomimetics},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pontn-ojeda-asanza-lorenteleyva-peluffoordez-designandimplementationofaniotcontrolandmonitoringsystemfortheoptimizationofshrimppoolsusingloratechnology-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://dx.doi.org/10.14569/IJACSA.2023.0140829\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pontn-ojeda-asanza-lorenteleyva-peluffoordez-designandimplementationofaniotcontrolandmonitoringsystemfortheoptimizationofshrimppoolsusingloratechnology-2023', 'http://dx.doi.org/10.14569/IJACSA.2023.0140829', event);\">\n    Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pontón,  J., M., P.; Ojeda,  V.; Asanza,  V.; Lorente-Leyva,  L., L.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Advanced Computer Science and Applications</i>, 14(8).  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://dx.doi.org/10.14569/IJACSA.2023.0140829\"\n     onclick=\"log_download('pontn-ojeda-asanza-lorenteleyva-peluffoordez-designandimplementationofaniotcontrolandmonitoringsystemfortheoptimizationofshrimppoolsusingloratechnology-2023', 'http://dx.doi.org/10.14569/IJACSA.2023.0140829', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.14569/IJACSA.2023.0140829\"\n     onclick=\"log_download('pontn-ojeda-asanza-lorenteleyva-peluffoordez-designandimplementationofaniotcontrolandmonitoringsystemfortheoptimizationofshrimppoolsusingloratechnology-2023', 'http://doi.org/10.14569/IJACSA.2023.0140829', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pontn-ojeda-asanza-lorenteleyva-peluffoordez-designandimplementationofaniotcontrolandmonitoringsystemfortheoptimizationofshrimppoolsusingloratechnology-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pontn-ojeda-asanza-lorenteleyva-peluffoordez-designandimplementationofaniotcontrolandmonitoringsystemfortheoptimizationofshrimppoolsusingloratechnology-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology},\n type = {article},\n year = {2023},\n volume = {14},\n websites = {http://dx.doi.org/10.14569/IJACSA.2023.0140829},\n publisher = {The Science and Information Organization},\n id = {b5f6f478-e071-3552-b06c-143bb6986f0e},\n created = {2023-08-30T20:19:32.593Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2023-08-30T20:19:32.593Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Pontón2023},\n source_type = {article},\n private_publication = {false},\n abstract = {The shrimp farming industry in Ecuador, renowned for its shrimp breeding and exportation, faces challenges due to diseases related to variations in abiotic factors during the maturation stage. This is partly attributed to the traditional methods employed in shrimp farms. Consequently, a prototype has been developed for monitoring and controlling abiotic factors using IoT technology. The proposed system consists of three nodes communicating through the LoRa interface. For control purposes, a fuzzy logic system has been implemented that evaluates temperature and dissolved oxygen abiotic factors to determine the state of the aerator, updating the information in the ThingSpeak application. A detailed analysis of equipment energy consumption and the maximum communication range for message transmission and reception was conducted. Subsequently, the monitoring and control system underwent comprehensive testing, including communication with the visualization platform. The results demonstrated significant improvements in system performance. By modifying parameters in the microcontroller, a 2.55-fold increase in battery durability was achieved. The implemented fuzzy logic system enabled effective on/off control of the aerators, showing a corrective trend in response to variations in the analyzed abiotic parameters. The robustness of the LoRa communication interface was evident in urban environments, achieving a distance of up to 1 km without line of sight.},\n bibtype = {article},\n author = {Pontón, José M Pereira and Ojeda, Verónica and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\n doi = {10.14569/IJACSA.2023.0140829},\n journal = {International Journal of Advanced Computer Science and Applications},\n number = {8}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The shrimp farming industry in Ecuador, renowned for its shrimp breeding and exportation, faces challenges due to diseases related to variations in abiotic factors during the maturation stage. This is partly attributed to the traditional methods employed in shrimp farms. Consequently, a prototype has been developed for monitoring and controlling abiotic factors using IoT technology. The proposed system consists of three nodes communicating through the LoRa interface. For control purposes, a fuzzy logic system has been implemented that evaluates temperature and dissolved oxygen abiotic factors to determine the state of the aerator, updating the information in the ThingSpeak application. A detailed analysis of equipment energy consumption and the maximum communication range for message transmission and reception was conducted. Subsequently, the monitoring and control system underwent comprehensive testing, including communication with the visualization platform. The results demonstrated significant improvements in system performance. By modifying parameters in the microcontroller, a 2.55-fold increase in battery durability was achieved. The implemented fuzzy logic system enabled effective on/off control of the aerators, showing a corrective trend in response to variations in the analyzed abiotic parameters. The robustness of the LoRa communication interface was evident in urban environments, achieving a distance of up to 1 km without line of sight.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"torres-myoelectricprosthesisusingsensorfusionbetweenelectromyographyandpulseoximetrysignals-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'torres-myoelectricprosthesisusingsensorfusionbetweenelectromyographyandpulseoximetrysignals-2023', 'https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413', event);\">\n    Myoelectric Prosthesis Using Sensor Fusion Between Electromyography and Pulse Oximetry Signals.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Torres, K., Espinoza, J., Asanza, V., Lorente-Leyva, L.L., Peluffo-Ordóñez,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Journal Européen des Systèmes Automatisés</i>, 56(4): 641-649.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413\"\n     onclick=\"log_download('torres-myoelectricprosthesisusingsensorfusionbetweenelectromyographyandpulseoximetrysignals-2023', 'https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Myoelectric Prosthesis Using Sensor Fusion Between Electromyography and Pulse Oximetry Signals [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/torres-myoelectricprosthesisusingsensorfusionbetweenelectromyographyandpulseoximetrysignals-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('torres-myoelectricprosthesisusingsensorfusionbetweenelectromyographyandpulseoximetrysignals-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Myoelectric Prosthesis Using Sensor Fusion Between Electromyography and Pulse Oximetry Signals},\n type = {article},\n year = {2023},\n keywords = {artificial,bioelectric signal,electromyography,intelligence,myoelectric prosthesis,neural network,sensor fusion},\n pages = {641-649},\n volume = {56},\n websites = {https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413},\n id = {9082a1fb-63b8-326c-b8f2-83190391caef},\n created = {2023-10-02T16:15:28.275Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2023-10-02T16:39:16.649Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {TorresK.EspinozaJ.AsanzaV.Lorente-LeyvaL.L.Peluffo-Ordonez2023},\n private_publication = {false},\n abstract = {Approximately 215,156 people in Ecuador grapple with physical disabilities, of whom nearly half fall within the 30 to 49% disability range, and a considerable number lack limbs. Moreover, there&#x27;s been a surge in amputation cases, a trend linked to the increasing diabetes prevalence estimated at around 537 million cases by 2021 as per the International Diabetes Federation (IDF). While prosthetic solutions exist, they might incur high costs or offer constrained movement, even when more affordable. Thus, an alternative is proposed: a myoelectric upper limb prosthesis. This prosthesis would be maneuvered through electromyography and pulse oximetry signals, leveraging artificial intelligence methods. Employing a multi-layer neural network model, a structure comprising an input layer, four hidden layers, and an output layer, yields an impressive 93% prediction accuracy for user movement intentions. For AI model training, data from EMG and PPG sensors were recorded and scrutinized, leading to the condensation of classes from four to three. The model was embedded within an ESP32 C3 DevKit-M1 development board, and open-source blueprints facilitated the prosthesis&#x27;s creation, complemented by supplementary components for electronics integration. The model attains a 93% precision in predicting classes, while the prosthesis&#x27;s endurance spans approximately three hours and costs $295, equipped to handle diverse lightweight objects.},\n bibtype = {article},\n author = {Torres, K., Espinoza, J., Asanza, V., Lorente-Leyva, L.L., Peluffo-Ordóñez, D.H.},\n journal = {Journal Européen des Systèmes Automatisés},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Approximately 215,156 people in Ecuador grapple with physical disabilities, of whom nearly half fall within the 30 to 49% disability range, and a considerable number lack limbs. Moreover, there's been a surge in amputation cases, a trend linked to the increasing diabetes prevalence estimated at around 537 million cases by 2021 as per the International Diabetes Federation (IDF). While prosthetic solutions exist, they might incur high costs or offer constrained movement, even when more affordable. Thus, an alternative is proposed: a myoelectric upper limb prosthesis. This prosthesis would be maneuvered through electromyography and pulse oximetry signals, leveraging artificial intelligence methods. Employing a multi-layer neural network model, a structure comprising an input layer, four hidden layers, and an output layer, yields an impressive 93% prediction accuracy for user movement intentions. For AI model training, data from EMG and PPG sensors were recorded and scrutinized, leading to the condensation of classes from four to three. The model was embedded within an ESP32 C3 DevKit-M1 development board, and open-source blueprints facilitated the prosthesis's creation, complemented by supplementary components for electronics integration. The model attains a 93% precision in predicting classes, while the prosthesis's endurance spans approximately three hours and costs $295, equipped to handle diverse lightweight objects.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2022\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2022')\"\n      onkeypress=\"toggleGroup('group_2022')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2022</span>\n      <span class=\"bibbase_group_count\">\n        \n        (4)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"roseromontalvo-lpezbatista-peluffoordez-anewdatapreprocessingrelatedtaxonomyofsensorsforiotapplications-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.mdpi.com/2078-2489/13/5/241\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-lpezbatista-peluffoordez-anewdatapreprocessingrelatedtaxonomyofsensorsforiotapplications-2022', 'https://www.mdpi.com/2078-2489/13/5/241', event);\">\n    A New Data-Preprocessing-Related Taxonomy of Sensors for IoT Applications.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; López-Batista,  V., F.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  <i>Information</i>, 13(5).  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.mdpi.com/2078-2489/13/5/241\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-peluffoordez-anewdatapreprocessingrelatedtaxonomyofsensorsforiotapplications-2022', 'https://www.mdpi.com/2078-2489/13/5/241', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A New Data-Preprocessing-Related Taxonomy of Sensors for IoT Applications [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.3390/info13050241\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-peluffoordez-anewdatapreprocessingrelatedtaxonomyofsensorsforiotapplications-2022', 'http://doi.org/10.3390/info13050241', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-lpezbatista-peluffoordez-anewdatapreprocessingrelatedtaxonomyofsensorsforiotapplications-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-lpezbatista-peluffoordez-anewdatapreprocessingrelatedtaxonomyofsensorsforiotapplications-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A New Data-Preprocessing-Related Taxonomy of Sensors for IoT Applications},\n type = {article},\n year = {2022},\n volume = {13},\n websites = {https://www.mdpi.com/2078-2489/13/5/241},\n id = {6e919451-d4ca-33fa-97ea-476c100c1d53},\n created = {2022-05-09T15:28:56.810Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-05-09T15:28:56.810Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {info13050241},\n source_type = {article},\n private_publication = {false},\n abstract = {IoT devices play a fundamental role in the machine learning (ML) application pipeline, as they collect rich data for model training using sensors. However, this process can be affected by uncontrollable variables that introduce errors into the data, resulting in a higher computational cost to eliminate them. Thus, selecting the most suitable algorithm for this pre-processing step on-device can reduce ML model complexity and unnecessary bandwidth usage for cloud processing. Therefore, this work presents a new sensor taxonomy with which to deploy data pre-processing on an IoT device by using a specific filter for each data type that the system handles. We define statistical and functional performance metrics to perform filter selection. Experimental results show that the Butterworth filter is a suitable solution for invariant sampling rates, while the Savi&amp;ndash;Golay and medium filters are appropriate choices for variable sampling rates.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D and López-Batista, Vivian F and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/info13050241},\n journal = {Information},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  IoT devices play a fundamental role in the machine learning (ML) application pipeline, as they collect rich data for model training using sensors. However, this process can be affected by uncontrollable variables that introduce errors into the data, resulting in a higher computational cost to eliminate them. Thus, selecting the most suitable algorithm for this pre-processing step on-device can reduce ML model complexity and unnecessary bandwidth usage for cloud processing. Therefore, this work presents a new sensor taxonomy with which to deploy data pre-processing on an IoT device by using a specific filter for each data type that the system handles. We define statistical and functional performance metrics to perform filter selection. Experimental results show that the Butterworth filter is a suitable solution for invariant sampling rates, while the Savi&ndash;Golay and medium filters are appropriate choices for variable sampling rates.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"proaoguevara-blancovalencia-roseromontalvo-peluffoordez-electromiographicsignalprocessingusingembeddedartificialintelligenceanadaptivefilteringapproach-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.ijimai.org/journal/bibcite/reference/3162\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'proaoguevara-blancovalencia-roseromontalvo-peluffoordez-electromiographicsignalprocessingusingembeddedartificialintelligenceanadaptivefilteringapproach-2022', 'https://www.ijimai.org/journal/bibcite/reference/3162', event);\">\n    Electromiographic Signal Processing Using Embedded Artificial Intelligence: An Adaptive Filtering Approach.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Proaño-Guevara,  D.; Blanco-Valencia,  X.; Rosero-Montalvo,  P., D.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Interactive Multimedia and Artificial Intelligence</i>, 7(5).  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.ijimai.org/journal/bibcite/reference/3162\"\n     onclick=\"log_download('proaoguevara-blancovalencia-roseromontalvo-peluffoordez-electromiographicsignalprocessingusingembeddedartificialintelligenceanadaptivefilteringapproach-2022', 'https://www.ijimai.org/journal/bibcite/reference/3162', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Electromiographic Signal Processing Using Embedded Artificial Intelligence: An Adaptive Filtering Approach [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.9781/ijimai.2022.08.009\"\n     onclick=\"log_download('proaoguevara-blancovalencia-roseromontalvo-peluffoordez-electromiographicsignalprocessingusingembeddedartificialintelligenceanadaptivefilteringapproach-2022', 'http://doi.org/10.9781/ijimai.2022.08.009', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/proaoguevara-blancovalencia-roseromontalvo-peluffoordez-electromiographicsignalprocessingusingembeddedartificialintelligenceanadaptivefilteringapproach-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>4 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('proaoguevara-blancovalencia-roseromontalvo-peluffoordez-electromiographicsignalprocessingusingembeddedartificialintelligenceanadaptivefilteringapproach-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Electromiographic Signal Processing Using Embedded Artificial Intelligence: An Adaptive Filtering Approach},\n type = {article},\n year = {2022},\n volume = {7},\n websites = {https://www.ijimai.org/journal/bibcite/reference/3162},\n id = {dbf8fb76-8137-39b9-96c9-e599a483de7a},\n created = {2022-08-27T03:33:14.152Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-08-27T03:33:14.152Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {ijmai2022},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Proaño-Guevara, Daniel and Blanco-Valencia, Xiomara and Rosero-Montalvo, Paul D and Peluffo-Ordóñez, Diego H},\n doi = {10.9781/ijimai.2022.08.009},\n journal = {International Journal of Interactive Multimedia and Artificial Intelligence},\n number = {5}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"montesdeoca-asanza-chica-peluffoordez-analysisofsortingalgorithmsusingawsnandenvironmentalpollutiondatabasedonfpga-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/9920090\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'montesdeoca-asanza-chica-peluffoordez-analysisofsortingalgorithmsusingawsnandenvironmentalpollutiondatabasedonfpga-2022', 'https://ieeexplore.ieee.org/document/9920090', event);\">\n    Analysis of Sorting Algorithms Using a WSN and Environmental Pollution Data based on FPGA.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Montesdeoca,  G.; Asanza,  V.; Chica,  K.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  In <i>2022 International Conference on Applied Electronics (AE)</i>, pages 1-4,  2022. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/9920090\"\n     onclick=\"log_download('montesdeoca-asanza-chica-peluffoordez-analysisofsortingalgorithmsusingawsnandenvironmentalpollutiondatabasedonfpga-2022', 'https://ieeexplore.ieee.org/document/9920090', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Analysis of Sorting Algorithms Using a WSN and Environmental Pollution Data based on FPGA [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/AE54730.2022.9920090\"\n     onclick=\"log_download('montesdeoca-asanza-chica-peluffoordez-analysisofsortingalgorithmsusingawsnandenvironmentalpollutiondatabasedonfpga-2022', 'http://doi.org/10.1109/AE54730.2022.9920090', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/montesdeoca-asanza-chica-peluffoordez-analysisofsortingalgorithmsusingawsnandenvironmentalpollutiondatabasedonfpga-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('montesdeoca-asanza-chica-peluffoordez-analysisofsortingalgorithmsusingawsnandenvironmentalpollutiondatabasedonfpga-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Analysis of Sorting Algorithms Using a WSN and Environmental Pollution Data based on FPGA},\n type = {inproceedings},\n year = {2022},\n pages = {1-4},\n websites = {https://ieeexplore.ieee.org/document/9920090},\n id = {7aa2d8ec-2350-3657-b8cd-f012a3b86d27},\n created = {2022-10-20T14:01:02.564Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-10-20T14:01:02.564Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {9920090},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Wireless Snesor Network (WSN) based systems with a focus on Internet of Things (IoT) applications generate a large amount of data. Many applications that need to process data in real time make use of microcontroller-based architectures with sequential programming. Systems based on sequential programming can emulate parallelism up to a certain number of instructions, which is not the case with Field Programmable Gate Array (FPGA). The main objective of this work is to monitor a network of 40 CO2 sensors and to perform real-time sorting of all data. In addition, the run time analysis of two sorting algorithms is performed: bubble sort and insertion sort. For this purpose, an FPGA-based architecture is implemented, controlled by a finite state machine(FSM), which executes each of the sorting algorithms. The results show that the insertion sort algorithm is faster than the burbble sort, but consumes more hardware resources in the FPGA.},\n bibtype = {inproceedings},\n author = {Montesdeoca, Guillermo and Asanza, Víctor and Chica, Kevin and Peluffo-Ordóñez, Diego H.},\n doi = {10.1109/AE54730.2022.9920090},\n booktitle = {2022 International Conference on Applied Electronics (AE)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Wireless Snesor Network (WSN) based systems with a focus on Internet of Things (IoT) applications generate a large amount of data. Many applications that need to process data in real time make use of microcontroller-based architectures with sequential programming. Systems based on sequential programming can emulate parallelism up to a certain number of instructions, which is not the case with Field Programmable Gate Array (FPGA). The main objective of this work is to monitor a network of 40 CO2 sensors and to perform real-time sorting of all data. In addition, the run time analysis of two sorting algorithms is performed: bubble sort and insertion sort. For this purpose, an FPGA-based architecture is implemented, controlled by a finite state machine(FSM), which executes each of the sorting algorithms. The results show that the insertion sort algorithm is faster than the burbble sort, but consumes more hardware resources in the FPGA.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"asanza-miranda-miranda-rivas-hernanpeluffoordez-pelaez-loayza-alejandro-electrooculographysignalsclassificationforfpgabasedhumancomputerinteraction-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/9989664\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'asanza-miranda-miranda-rivas-hernanpeluffoordez-pelaez-loayza-alejandro-electrooculographysignalsclassificationforfpgabasedhumancomputerinteraction-2022', 'https://ieeexplore.ieee.org/document/9989664', event);\">\n    Electrooculography Signals Classification for FPGA-based Human-Computer Interaction.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Asanza,  V.; Miranda,  J.; Miranda,  J.; Rivas,  L.; Hernan Peluffo-Ordóñez,  D.; Pelaez,  E.; Loayza,  F.;  and Alejandro,  O.\n</span>\n\n  \n\n</span>\n\n  In <i>2022 IEEE ANDESCON</i>, pages 1-7,  2022. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/9989664\"\n     onclick=\"log_download('asanza-miranda-miranda-rivas-hernanpeluffoordez-pelaez-loayza-alejandro-electrooculographysignalsclassificationforfpgabasedhumancomputerinteraction-2022', 'https://ieeexplore.ieee.org/document/9989664', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Electrooculography Signals Classification for FPGA-based Human-Computer Interaction [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/ANDESCON56260.2022.9989664\"\n     onclick=\"log_download('asanza-miranda-miranda-rivas-hernanpeluffoordez-pelaez-loayza-alejandro-electrooculographysignalsclassificationforfpgabasedhumancomputerinteraction-2022', 'http://doi.org/10.1109/ANDESCON56260.2022.9989664', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/asanza-miranda-miranda-rivas-hernanpeluffoordez-pelaez-loayza-alejandro-electrooculographysignalsclassificationforfpgabasedhumancomputerinteraction-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('asanza-miranda-miranda-rivas-hernanpeluffoordez-pelaez-loayza-alejandro-electrooculographysignalsclassificationforfpgabasedhumancomputerinteraction-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Electrooculography Signals Classification for FPGA-based Human-Computer Interaction},\n type = {inproceedings},\n year = {2022},\n pages = {1-7},\n websites = {https://ieeexplore.ieee.org/document/9989664},\n id = {c535033c-395b-3611-a3e0-9c99cfb876ce},\n created = {2022-12-28T23:00:00.128Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-12-28T23:00:00.128Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {9989664},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Electrooculographic techniques are applied in the development of new technologies that compensate for the limitations of people with motor disabilities. The algorithms in charge of classifying these signals play a fundamental role, mainly for Human Computer Interfaces (HCI), specially when the machine learning algorithms are implemented in customized hardware like FPGA. In this work, electrooculography data were collected from 10 healthy subjects during six eye movement tasks. Then, the data were filtered and introduced into supervised and unsupervised learning algorithms with six classification labels. The results obtained showed that the SVM algorithm had 93.5% of accuracy, thus being considered the most efficient of the classification algorithms proposed in this work. Then, we develop a custom hardware architecture for real-time implementation of EOG classification model in al FPGA card. We demonstrate the effectiveness of the proposed framework for EOG data classification.},\n bibtype = {inproceedings},\n author = {Asanza, Víctor and Miranda, Jesús and Miranda, Jocelyn and Rivas, Leiber and Hernan Peluffo-Ordóñez, Diego and Pelaez, Enrique and Loayza, Francis and Alejandro, Otilia},\n doi = {10.1109/ANDESCON56260.2022.9989664},\n booktitle = {2022 IEEE ANDESCON}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Electrooculographic techniques are applied in the development of new technologies that compensate for the limitations of people with motor disabilities. The algorithms in charge of classifying these signals play a fundamental role, mainly for Human Computer Interfaces (HCI), specially when the machine learning algorithms are implemented in customized hardware like FPGA. In this work, electrooculography data were collected from 10 healthy subjects during six eye movement tasks. Then, the data were filtered and introduced into supervised and unsupervised learning algorithms with six classification labels. The results obtained showed that the SVM algorithm had 93.5% of accuracy, thus being considered the most efficient of the classification algorithms proposed in this work. Then, we develop a custom hardware architecture for real-time implementation of EOG classification model in al FPGA card. We demonstrate the effectiveness of the proposed framework for EOG data classification.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2021\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2021')\"\n      onkeypress=\"toggleGroup('group_2021')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2021</span>\n      <span class=\"bibbase_group_count\">\n        \n        (5)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"roseromontalvo-lpezbatista-arciniegarocha-peluffoordez-airpollutionmonitoringusingwsnnodeswithmachinelearningtechniquesacasestudy-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://academic.oup.com/jigpal/advance-article/doi/10.1093/jigpal/jzab005/6133990\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-lpezbatista-arciniegarocha-peluffoordez-airpollutionmonitoringusingwsnnodeswithmachinelearningtechniquesacasestudy-2021', 'https://academic.oup.com/jigpal/advance-article/doi/10.1093/jigpal/jzab005/6133990', event);\">\n    Air Pollution Monitoring Using WSN Nodes with Machine Learning Techniques: A Case Study.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; López-Batista,  V., F.; Arciniega-Rocha,  R.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  <i>Logic Journal of the IGPL</i>. 2 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://academic.oup.com/jigpal/advance-article/doi/10.1093/jigpal/jzab005/6133990\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-arciniegarocha-peluffoordez-airpollutionmonitoringusingwsnnodeswithmachinelearningtechniquesacasestudy-2021', 'https://academic.oup.com/jigpal/advance-article/doi/10.1093/jigpal/jzab005/6133990', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Air Pollution Monitoring Using WSN Nodes with Machine Learning Techniques: A Case Study [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1093/jigpal/jzab005\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-arciniegarocha-peluffoordez-airpollutionmonitoringusingwsnnodeswithmachinelearningtechniquesacasestudy-2021', 'http://doi.org/10.1093/jigpal/jzab005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-lpezbatista-arciniegarocha-peluffoordez-airpollutionmonitoringusingwsnnodeswithmachinelearningtechniquesacasestudy-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>11 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-lpezbatista-arciniegarocha-peluffoordez-airpollutionmonitoringusingwsnnodeswithmachinelearningtechniquesacasestudy-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Air Pollution Monitoring Using WSN Nodes with Machine Learning Techniques: A Case Study},\n type = {article},\n year = {2021},\n websites = {https://academic.oup.com/jigpal/advance-article/doi/10.1093/jigpal/jzab005/6133990},\n month = {2},\n day = {13},\n id = {1aeb55bd-ea97-3fe8-a1e4-f9a523616cae},\n created = {2022-02-02T03:56:08.786Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:08.786Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2021},\n private_publication = {false},\n abstract = {Air pollution is a current concern of people and government entities. Therefore, in urban scenarios, its monitoring and subsequent analysis is a remarkable and challenging issue due mainly to the variability of polluting-related factors. For this reason, the present work shows the development of a wireless sensor network that, through machine learning techniques, can be classified into three different types of environments: high pollution levels, medium pollution and no noticeable contamination into the Ibarra City. To achieve this goal, signal smoothing stages, prototype selection, feature analysis and a comparison of classification algorithms are performed. As relevant results, there is a classification performance of 95% with a significant noisy data reduction.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D and López-Batista, Vivian F and Arciniega-Rocha, Ricardo and Peluffo-Ordóñez, Diego H},\n doi = {10.1093/jigpal/jzab005},\n journal = {Logic Journal of the IGPL}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Air pollution is a current concern of people and government entities. Therefore, in urban scenarios, its monitoring and subsequent analysis is a remarkable and challenging issue due mainly to the variability of polluting-related factors. For this reason, the present work shows the development of a wireless sensor network that, through machine learning techniques, can be classified into three different types of environments: high pollution levels, medium pollution and no noticeable contamination into the Ibarra City. To achieve this goal, signal smoothing stages, prototype selection, feature analysis and a comparison of classification algorithms are performed. As relevant results, there is a classification performance of 95% with a significant noisy data reduction.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"vargasmuoz-chamorrosangoquiza-umaquingacriollo-roseromontalvo-becerra-peluffoordez-revelofuelagn-designofalowcomputationalcostprototypeforcardiacarrhythmiadetectiondiseodeunprototipodebajocostecomputacionalparadeteccindearritmiascardiacas-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://search.proquest.com/openview/d9dffd8a726c99f54a47adaf372e13b8/1?pq-origsite=gscholar&amp;cbl=1006393\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'vargasmuoz-chamorrosangoquiza-umaquingacriollo-roseromontalvo-becerra-peluffoordez-revelofuelagn-designofalowcomputationalcostprototypeforcardiacarrhythmiadetectiondiseodeunprototipodebajocostecomputacionalparadeteccindearritmiascardiacas-2021', 'https://search.proquest.com/openview/d9dffd8a726c99f54a47adaf372e13b8/1?pq-origsite=gscholar&amp;cbl=1006393', event);\">\n    Design of a low computational cost prototype for cardiac arrhythmia detection [Diseño de un prototipo de bajo coste computacional para detección de arritmias cardiacas].\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Vargas-Muñoz,  A., M.; Chamorro-Sangoquiza,  D., C.; Umaquinga-Criollo,  A., C.; Rosero-Montalvo,  P., D.; Becerra,  M., A.; Peluffo-Ordóñez,  D., H.;  and Revelo-Fuelagán,  E., J.\n</span>\n\n  \n\n</span>\n\n  <i>RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao</i>, 2021(E40): 470-479.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://search.proquest.com/openview/d9dffd8a726c99f54a47adaf372e13b8/1?pq-origsite=gscholar&amp;cbl=1006393\"\n     onclick=\"log_download('vargasmuoz-chamorrosangoquiza-umaquingacriollo-roseromontalvo-becerra-peluffoordez-revelofuelagn-designofalowcomputationalcostprototypeforcardiacarrhythmiadetectiondiseodeunprototipodebajocostecomputacionalparadeteccindearritmiascardiacas-2021', 'https://search.proquest.com/openview/d9dffd8a726c99f54a47adaf372e13b8/1?pq-origsite=gscholar&amp;cbl=1006393', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Design of a low computational cost prototype for cardiac arrhythmia detection [Diseño de un prototipo de bajo coste computacional para detección de arritmias cardiacas] [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/vargasmuoz-chamorrosangoquiza-umaquingacriollo-roseromontalvo-becerra-peluffoordez-revelofuelagn-designofalowcomputationalcostprototypeforcardiacarrhythmiadetectiondiseodeunprototipodebajocostecomputacionalparadeteccindearritmiascardiacas-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('vargasmuoz-chamorrosangoquiza-umaquingacriollo-roseromontalvo-becerra-peluffoordez-revelofuelagn-designofalowcomputationalcostprototypeforcardiacarrhythmiadetectiondiseodeunprototipodebajocostecomputacionalparadeteccindearritmiascardiacas-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Design of a low computational cost prototype for cardiac arrhythmia detection [Diseño de un prototipo de bajo coste computacional para detección de arritmias cardiacas]},\n type = {article},\n year = {2021},\n pages = {470-479},\n volume = {2021},\n websites = {https://search.proquest.com/openview/d9dffd8a726c99f54a47adaf372e13b8/1?pq-origsite=gscholar&amp;cbl=1006393},\n id = {2688dd89-0c9d-3427-a6d6-27db7812bf80},\n created = {2022-02-02T03:56:09.036Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:09.036Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Vargas-Muñoz2021470},\n source_type = {article},\n private_publication = {false},\n abstract = {This research presents the design of a prototype for the detection of cardiac arrhythmias that incorporates an embedded low-cost computational system in an environment of limited computational resources capable of analyzing characteristics of the QRS complexes. To do this, a strategy for classifying normal and pathological heart beats is developed in long-term electrocardiographic recordings (Holter), which are representative waves of the beat and their analysis allows identifying ventricular arrhythmias. For the development of this initial prototype, it is found that the use of the k nearest neighbors (k-NN) algorithm together with a stage of selection of variables from the training set is a good alternative and represents an important contribution of this work to experimental level. The experiments were carried out on the basis of cardiac arrhythmia data from the Massachusetts Institute of Technology (MIT). The results are satisfactory and promising. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.},\n bibtype = {article},\n author = {Vargas-Muñoz, A M and Chamorro-Sangoquiza, D C and Umaquinga-Criollo, A C and Rosero-Montalvo, P D and Becerra, M A and Peluffo-Ordóñez, D H and Revelo-Fuelagán, E J},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao},\n number = {E40}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This research presents the design of a prototype for the detection of cardiac arrhythmias that incorporates an embedded low-cost computational system in an environment of limited computational resources capable of analyzing characteristics of the QRS complexes. To do this, a strategy for classifying normal and pathological heart beats is developed in long-term electrocardiographic recordings (Holter), which are representative waves of the beat and their analysis allows identifying ventricular arrhythmias. For the development of this initial prototype, it is found that the use of the k nearest neighbors (k-NN) algorithm together with a stage of selection of variables from the training set is a good alternative and represents an important contribution of this work to experimental level. The experiments were carried out on the basis of cardiac arrhythmia data from the Massachusetts Institute of Technology (MIT). The results are satisfactory and promising. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"roseromontalvo-fuenteshernndez-morochocayamcela-addressingthedataacquisitionparadigmintheearlydetectionofpediatricfootdeformities-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3/file/6edcd1ce-608a-db0f-48fa-413a482fbe37/2021_Sensors_AddressingtheDataAcquisition.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-fuenteshernndez-morochocayamcela-addressingthedataacquisitionparadigmintheearlydetectionofpediatricfootdeformities-2021', 'https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3/file/6edcd1ce-608a-db0f-48fa-413a482fbe37/2021_Sensors_AddressingtheDataAcquisition.pdf.pdf', event);\">\n    Addressing the Data Acquisition Paradigm in the Early Detection of Pediatric Foot Deformities.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-montalvo,  P., D.; Fuentes-hernández,  E., A.;  and Morocho-cayamcela,  M., E.\n</span>\n\n  \n\n</span>\n\n  <i>Sensors</i>,1-17.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3/file/6edcd1ce-608a-db0f-48fa-413a482fbe37/2021_Sensors_AddressingtheDataAcquisition.pdf.pdf\"\n     onclick=\"log_download('roseromontalvo-fuenteshernndez-morochocayamcela-addressingthedataacquisitionparadigmintheearlydetectionofpediatricfootdeformities-2021', 'https://bibbase.org/service/mendeley/aba9653c-d139-3f95-aad8-969c487ed2f3/file/6edcd1ce-608a-db0f-48fa-413a482fbe37/2021_Sensors_AddressingtheDataAcquisition.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Addressing the Data Acquisition Paradigm in the Early Detection of Pediatric Foot Deformities [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://www.mdpi.com/1424-8220/21/13/4422\"\n     onclick=\"log_download('roseromontalvo-fuenteshernndez-morochocayamcela-addressingthedataacquisitionparadigmintheearlydetectionofpediatricfootdeformities-2021', 'https://www.mdpi.com/1424-8220/21/13/4422', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Addressing the Data Acquisition Paradigm in the Early Detection of Pediatric Foot Deformities [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-fuenteshernndez-morochocayamcela-addressingthedataacquisitionparadigmintheearlydetectionofpediatricfootdeformities-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-fuenteshernndez-morochocayamcela-addressingthedataacquisitionparadigmintheearlydetectionofpediatricfootdeformities-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Addressing the Data Acquisition Paradigm in the Early Detection of Pediatric Foot Deformities},\n type = {article},\n year = {2021},\n keywords = {academic editor,children,data analysis,embedded systems,emmanouil,machine learning,plantar pressure},\n pages = {1-17},\n websites = {https://www.mdpi.com/1424-8220/21/13/4422},\n id = {e3698b0d-af9d-3acd-980b-72b08352f328},\n created = {2022-02-02T03:56:09.307Z},\n file_attached = {true},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:13.096Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The analysis of plantar pressure through podometry has allowed analyzing and detecting different types of disorders and treatments in child patients. Early detection of an inadequate distribution of the patient’s weight can prevent serious injuries to the knees and lower spine. In this paper, an embedded system capable of detecting the presence of normal, flat, or arched footprints using resistive pressure sensors was proposed. For this purpose, both hardware- and software-related criteria were studied for an improved data acquisition through signal coupling and filtering processes. Subsequently, learning algorithms allowed us to estimate the type of footprint biomechanics in preschool and school children volunteers. As a result, the proposed algorithm achieved an overall classification accuracy of 97.2%. A flat feet share of 60% was encountered in a sample of 1000 preschool children. Similarly, flat feet were observed in 52% of a sample of 600 school children.},\n bibtype = {article},\n author = {Rosero-montalvo, Paul D and Fuentes-hernández, Edison A and Morocho-cayamcela, Manuel E},\n journal = {Sensors}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The analysis of plantar pressure through podometry has allowed analyzing and detecting different types of disorders and treatments in child patients. Early detection of an inadequate distribution of the patient’s weight can prevent serious injuries to the knees and lower spine. In this paper, an embedded system capable of detecting the presence of normal, flat, or arched footprints using resistive pressure sensors was proposed. For this purpose, both hardware- and software-related criteria were studied for an improved data acquisition through signal coupling and filtering processes. Subsequently, learning algorithms allowed us to estimate the type of footprint biomechanics in preschool and school children volunteers. As a result, the proposed algorithm achieved an overall classification accuracy of 97.2%. A flat feet share of 60% was encountered in a sample of 1000 preschool children. Similarly, flat feet were observed in 52% of a sample of 600 school children.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"capelo-ruiz-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-raspberrypibasediotforshrimpfarmsrealtimeremotemonitoringwithautomatedsystem-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/9542907\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'capelo-ruiz-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-raspberrypibasediotforshrimpfarmsrealtimeremotemonitoringwithautomatedsystem-2021', 'https://ieeexplore.ieee.org/document/9542907', event);\">\n    Raspberry Pi-based IoT for shrimp farms Real-time remote monitoring with automated system.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Capelo,  J.; Ruiz,  E.; Asanza,  V.; Toscano-quiroga,  T.; Sánchez-pozo,  N., N.; Lorente-leyva,  L., L.;  and Peluffo-ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  In <i>2021 International Conference on Applied Electronics, AE</i>, pages 7-10,  2021. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/9542907\"\n     onclick=\"log_download('capelo-ruiz-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-raspberrypibasediotforshrimpfarmsrealtimeremotemonitoringwithautomatedsystem-2021', 'https://ieeexplore.ieee.org/document/9542907', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Raspberry Pi-based IoT for shrimp farms Real-time remote monitoring with automated system [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/capelo-ruiz-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-raspberrypibasediotforshrimpfarmsrealtimeremotemonitoringwithautomatedsystem-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('capelo-ruiz-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-raspberrypibasediotforshrimpfarmsrealtimeremotemonitoringwithautomatedsystem-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Raspberry Pi-based IoT for shrimp farms Real-time remote monitoring with automated system},\n type = {inproceedings},\n year = {2021},\n keywords = {atmega328p,cyberphysical system,dissolved oxygen,ecuador,salinity,shrimp farming,temperature,xbee},\n pages = {7-10},\n websites = {https://ieeexplore.ieee.org/document/9542907},\n id = {c403ae99-57f9-3597-802a-a0981d13b1a3},\n created = {2022-02-02T03:56:09.567Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:09.567Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {This project analyses the optimal parameters for the shrimp farming, trying to help the aquaculture of Ecuador, using a cyberphysical system, which includes temperature, salinity, dissolved oxygen, and pH sensors to monitor the water conditions and an embedded system to control it using an XBee andATMega328p microcontrollers to remotely activate and deactivate aerators to maintain the quality of each pool in neat conditions.},\n bibtype = {inproceedings},\n author = {Capelo, Jesús and Ruiz, Erick and Asanza, Víctor and Toscano-quiroga, Tonny and Sánchez-pozo, Nadia N and Lorente-leyva, Leandro L and Peluffo-ordóñez, Diego Hernan},\n booktitle = {2021 International Conference on Applied Electronics, AE}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This project analyses the optimal parameters for the shrimp farming, trying to help the aquaculture of Ecuador, using a cyberphysical system, which includes temperature, salinity, dissolved oxygen, and pH sensors to monitor the water conditions and an embedded system to control it using an XBee andATMega328p microcontrollers to remotely activate and deactivate aerators to maintain the quality of each pool in neat conditions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"maisinchojivaja-alejandrosanjines-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-monitoringaturkeyhatcherybasedonacyberphysicalsystem-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/9542899\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'maisinchojivaja-alejandrosanjines-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-monitoringaturkeyhatcherybasedonacyberphysicalsystem-2021', 'https://ieeexplore.ieee.org/document/9542899', event);\">\n    Monitoring a turkey hatchery based on a cyber-physical system.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Maisincho-Jivaja,  A.; Alejandro-Sanjines,  U.; Asanza,  V.; Toscano-Quiroga,  T.; Sánchez-Pozo,  N., N.; Lorente-Leyva,  L., L.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  In <i>2021 International Conference on Applied Electronics, AE</i>,  2021. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/9542899\"\n     onclick=\"log_download('maisinchojivaja-alejandrosanjines-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-monitoringaturkeyhatcherybasedonacyberphysicalsystem-2021', 'https://ieeexplore.ieee.org/document/9542899', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Monitoring a turkey hatchery based on a cyber-physical system [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/maisinchojivaja-alejandrosanjines-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-monitoringaturkeyhatcherybasedonacyberphysicalsystem-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('maisinchojivaja-alejandrosanjines-asanza-toscanoquiroga-snchezpozo-lorenteleyva-peluffoordez-monitoringaturkeyhatcherybasedonacyberphysicalsystem-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Monitoring a turkey hatchery based on a cyber-physical system},\n type = {inproceedings},\n year = {2021},\n keywords = {internet of things,meleagriculture,pid tunner toolbox,sensor,system identification toolbox},\n websites = {https://ieeexplore.ieee.org/document/9542899},\n id = {f1527520-fe07-3126-80c3-7186ffde656e},\n created = {2022-02-02T03:56:09.861Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:09.861Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The implementation of a turkey farm brings with it severe environmental problems due to the deficient study of the physical space where the animals are placed. To counteract this situation and improve the quality of life in the hatchery, it is necessary to monitor and control the following variables: Temperature, Humidity, Ammonia Emission and Lux. The solution is based on a cyber-physical system which is composed of a network of sensors, controller and actuator. The sensors will provide information from the physical environment, the con- troller evaluates these parameters to execute an action to the actuator. Proportional, Integral and Derivative (PID) control defines the setpoint for temperature while Pulse- Width Modulation (PWM) adjusts the light intensity in a spotlight. The End Device executes these actions and its parameters will be sent to ThingSpeak which monitors system behavior the Internet of Things.},\n bibtype = {inproceedings},\n author = {Maisincho-Jivaja, Anthony and Alejandro-Sanjines, Ulbio and Asanza, Víctor and Toscano-Quiroga, Tonny and Sánchez-Pozo, Nadia N. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego Hernan},\n booktitle = {2021 International Conference on Applied Electronics, AE}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The implementation of a turkey farm brings with it severe environmental problems due to the deficient study of the physical space where the animals are placed. To counteract this situation and improve the quality of life in the hatchery, it is necessary to monitor and control the following variables: Temperature, Humidity, Ammonia Emission and Lux. The solution is based on a cyber-physical system which is composed of a network of sensors, controller and actuator. The sensors will provide information from the physical environment, the con- troller evaluates these parameters to execute an action to the actuator. Proportional, Integral and Derivative (PID) control defines the setpoint for temperature while Pulse- Width Modulation (PWM) adjusts the light intensity in a spotlight. The End Device executes these actions and its parameters will be sent to ThingSpeak which monitors system behavior the Internet of Things.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2020\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2020')\"\n      onkeypress=\"toggleGroup('group_2020')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2020</span>\n      <span class=\"bibbase_group_count\">\n        \n        (4)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"roseromontalvo-lpezbatista-riascos-peluffoordez-intelligentwsnsystemforwaterqualityanalysisusingmachinelearningalgorithmsacasestudytahuandoriverfromecuador-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.mdpi.com/2072-4292/12/12/1988\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-lpezbatista-riascos-peluffoordez-intelligentwsnsystemforwaterqualityanalysisusingmachinelearningalgorithmsacasestudytahuandoriverfromecuador-2020', 'https://www.mdpi.com/2072-4292/12/12/1988', event);\">\n    Intelligent WSN system for water quality analysis using machine learning algorithms: A case study (Tahuando river from Ecuador).\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; López-Batista,  V., F.; Riascos,  J., A.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  <i>Remote Sensing</i>.  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.mdpi.com/2072-4292/12/12/1988\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-riascos-peluffoordez-intelligentwsnsystemforwaterqualityanalysisusingmachinelearningalgorithmsacasestudytahuandoriverfromecuador-2020', 'https://www.mdpi.com/2072-4292/12/12/1988', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Intelligent WSN system for water quality analysis using machine learning algorithms: A case study (Tahuando river from Ecuador) [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.3390/rs12121988\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-riascos-peluffoordez-intelligentwsnsystemforwaterqualityanalysisusingmachinelearningalgorithmsacasestudytahuandoriverfromecuador-2020', 'http://doi.org/10.3390/rs12121988', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-lpezbatista-riascos-peluffoordez-intelligentwsnsystemforwaterqualityanalysisusingmachinelearningalgorithmsacasestudytahuandoriverfromecuador-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>14 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-lpezbatista-riascos-peluffoordez-intelligentwsnsystemforwaterqualityanalysisusingmachinelearningalgorithmsacasestudytahuandoriverfromecuador-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Intelligent WSN system for water quality analysis using machine learning algorithms: A case study (Tahuando river from Ecuador)},\n type = {article},\n year = {2020},\n keywords = {Prototype selection,River pollution,Supervised classification,WSN},\n websites = {https://www.mdpi.com/2072-4292/12/12/1988},\n id = {b68f8492-fa74-3b81-8b98-9a464dc94e39},\n created = {2022-02-02T03:56:10.104Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:10.104Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2020b},\n private_publication = {false},\n abstract = {This work presents a wireless sensor network (WSN) system able to determine the water quality of rivers. Particularly, we consider the Tahuando River from Ibarra, Ecuador, as a case study. The main goal of this research is to determine the river&#x27;s status throughout its route, by generating data reports into an interactive user interface. To this end, we use an array of sensors collecting several measures such as: turbidity, temperature, water quality, pH, and temperature. Subsequently, from the information collected on an Internet-of-Things (IoT) server, we develop a data analysis scheme with both data representation and supervised classification. As an important result, our system outputs a map that shows the contamination levels of the river at different regions. Furthermore, in terms of data analysis performance, the proposed system reduces the data matrix by 97% from its original size, while it reaches a classification performance over 90%. Furthermore, as an additional remarkable result, we here introduce the so-called quantitative metric of balance (QMB), which measures the balance or ratio between performance and power consumption.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Riascos, Jaime A. and Peluffo-Ordóñez, Diego H.},\n doi = {10.3390/rs12121988},\n journal = {Remote Sensing}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This work presents a wireless sensor network (WSN) system able to determine the water quality of rivers. Particularly, we consider the Tahuando River from Ibarra, Ecuador, as a case study. The main goal of this research is to determine the river's status throughout its route, by generating data reports into an interactive user interface. To this end, we use an array of sensors collecting several measures such as: turbidity, temperature, water quality, pH, and temperature. Subsequently, from the information collected on an Internet-of-Things (IoT) server, we develop a data analysis scheme with both data representation and supervised classification. As an important result, our system outputs a map that shows the contamination levels of the river at different regions. Furthermore, in terms of data analysis performance, the proposed system reduces the data matrix by 97% from its original size, while it reaches a classification performance over 90%. Furthermore, as an additional remarkable result, we here introduce the so-called quantitative metric of balance (QMB), which measures the balance or ratio between performance and power consumption.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"roseromontalvo-lopezbatista-peluffoordonez-hybridembeddedsystemsbasedapproachtoindriverdrunkstatusdetectionusingimageprocessingandsensornetworks-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/9258992\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-lopezbatista-peluffoordonez-hybridembeddedsystemsbasedapproachtoindriverdrunkstatusdetectionusingimageprocessingandsensornetworks-2020', 'https://ieeexplore.ieee.org/document/9258992', event);\">\n    Hybrid Embedded-Systems-based Approach to in-Driver Drunk Status Detection using Image Processing and Sensor Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; Lopez-Batista,  V., F.;  and Peluffo-Ordonez,  D., H.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Sensors Journal</i>.  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/9258992\"\n     onclick=\"log_download('roseromontalvo-lopezbatista-peluffoordonez-hybridembeddedsystemsbasedapproachtoindriverdrunkstatusdetectionusingimageprocessingandsensornetworks-2020', 'https://ieeexplore.ieee.org/document/9258992', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Hybrid Embedded-Systems-based Approach to in-Driver Drunk Status Detection using Image Processing and Sensor Networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/jsen.2020.3038143\"\n     onclick=\"log_download('roseromontalvo-lopezbatista-peluffoordonez-hybridembeddedsystemsbasedapproachtoindriverdrunkstatusdetectionusingimageprocessingandsensornetworks-2020', 'http://doi.org/10.1109/jsen.2020.3038143', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-lopezbatista-peluffoordonez-hybridembeddedsystemsbasedapproachtoindriverdrunkstatusdetectionusingimageprocessingandsensornetworks-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>6 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-lopezbatista-peluffoordonez-hybridembeddedsystemsbasedapproachtoindriverdrunkstatusdetectionusingimageprocessingandsensornetworks-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Hybrid Embedded-Systems-based Approach to in-Driver Drunk Status Detection using Image Processing and Sensor Networks},\n type = {article},\n year = {2020},\n websites = {https://ieeexplore.ieee.org/document/9258992},\n id = {1527f9d0-0222-32fe-af6c-76c2bf9af830},\n created = {2022-02-02T03:56:10.365Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:10.365Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2020a},\n private_publication = {false},\n abstract = {Car drivers under the influence of alcohol is one of the most common causes of road traffic accidents. To tackle this issue, an emerging, suitable alternative is the use of intelligent systems -traditionally based on either sensor networks or artificial vision- that are aimed to prevent starting the car when drunk status on the car driver is detected. In such vein, this paper introduces a system whose main objective is identifying a person having alcohol in the blood through supervised classification of sensor-generated and computer-vision-based data. To do so, some drunk-status criteria are considered, namely: the concentration of alcohol in the car environment, the facial temperature of the driver and the pupil width. Specifically, for data acquisition purposes, the proposed system incorporates a gas sensor, temperature sensor and a digital camera. Acquired data are analyzed into a two-stages machine learning system consisting of feature selection and supervised classification algorithms. Both acquisition and analysis stages are to be performed into a embedded system, and therefore all procedures and algorithms are designed to work at low-computational resources. As a remarkable outcome, due mainly to the incorporation of feature selection and relevance analysis stages, proposed approach reaches a classification performance of 98% while ensures adequate operation conditions for the embedded system.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D. and Lopez-Batista, Vivian F. and Peluffo-Ordonez, Diego H.},\n doi = {10.1109/jsen.2020.3038143},\n journal = {IEEE Sensors Journal}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Car drivers under the influence of alcohol is one of the most common causes of road traffic accidents. To tackle this issue, an emerging, suitable alternative is the use of intelligent systems -traditionally based on either sensor networks or artificial vision- that are aimed to prevent starting the car when drunk status on the car driver is detected. In such vein, this paper introduces a system whose main objective is identifying a person having alcohol in the blood through supervised classification of sensor-generated and computer-vision-based data. To do so, some drunk-status criteria are considered, namely: the concentration of alcohol in the car environment, the facial temperature of the driver and the pupil width. Specifically, for data acquisition purposes, the proposed system incorporates a gas sensor, temperature sensor and a digital camera. Acquired data are analyzed into a two-stages machine learning system consisting of feature selection and supervised classification algorithms. Both acquisition and analysis stages are to be performed into a embedded system, and therefore all procedures and algorithms are designed to work at low-computational resources. As a remarkable outcome, due mainly to the incorporation of feature selection and relevance analysis stages, proposed approach reaches a classification performance of 98% while ensures adequate operation conditions for the embedded system.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"roseromontalvo-erazochamorro-lpezbatista-morenogarca-peluffoordez-environmentmonitoringofrosecropsgreenhousebasedonautonomousvehicleswithawsnanddataanalysis-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.mdpi.com/1424-8220/20/20/5905\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-erazochamorro-lpezbatista-morenogarca-peluffoordez-environmentmonitoringofrosecropsgreenhousebasedonautonomousvehicleswithawsnanddataanalysis-2020', 'https://www.mdpi.com/1424-8220/20/20/5905', event);\">\n    Environment monitoring of rose crops greenhouse based on autonomous vehicles with a wsn and data analysis.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; Erazo-Chamorro,  V., C.; López-Batista,  V., F.; Moreno-García,  M., N.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  <i>Sensors (Switzerland)</i>.  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.mdpi.com/1424-8220/20/20/5905\"\n     onclick=\"log_download('roseromontalvo-erazochamorro-lpezbatista-morenogarca-peluffoordez-environmentmonitoringofrosecropsgreenhousebasedonautonomousvehicleswithawsnanddataanalysis-2020', 'https://www.mdpi.com/1424-8220/20/20/5905', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Environment monitoring of rose crops greenhouse based on autonomous vehicles with a wsn and data analysis [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.3390/s20205905\"\n     onclick=\"log_download('roseromontalvo-erazochamorro-lpezbatista-morenogarca-peluffoordez-environmentmonitoringofrosecropsgreenhousebasedonautonomousvehicleswithawsnanddataanalysis-2020', 'http://doi.org/10.3390/s20205905', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-erazochamorro-lpezbatista-morenogarca-peluffoordez-environmentmonitoringofrosecropsgreenhousebasedonautonomousvehicleswithawsnanddataanalysis-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-erazochamorro-lpezbatista-morenogarca-peluffoordez-environmentmonitoringofrosecropsgreenhousebasedonautonomousvehicleswithawsnanddataanalysis-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Environment monitoring of rose crops greenhouse based on autonomous vehicles with a wsn and data analysis},\n type = {article},\n year = {2020},\n keywords = {Ambient intelligence,Autonomous vehicles,Monitoring systems,Roses crops,Wireless sensor networks},\n websites = {https://www.mdpi.com/1424-8220/20/20/5905},\n id = {d5724f9a-59e2-3c94-9c14-4a64cb13b2f7},\n created = {2022-02-02T03:56:10.605Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:10.605Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2020},\n private_publication = {false},\n abstract = {This work presents a monitoring system for the environmental conditions of rose flower-cultivation in greenhouses. Its main objective is to improve the quality of the crops while regulating the production time. To this end, a system consisting of autonomous quadruped vehicles connected with a wireless sensor network (WSN) is developed, which supports the decision-making on type of action to be carried out in a greenhouse to maintain the appropriate environmental conditions for rose cultivation. A data analysis process was carried out, aimed at designing an in-situ intelligent system able to make proper decisions regarding the cultivation process. This process involves stages for balancing data, prototype selection, and supervised classification. The proposed system produces a significant reduction of data in the training set obtained by the WSN while reaching a high classification performance in real conditions—amounting to 90 % and 97.5%, respectively. As a remarkable outcome, it is also provided an approach to ensure correct planning and selection of routes for the autonomous vehicle through the global positioning system.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D. and Erazo-Chamorro, Vanessa C. and López-Batista, Vivian F. and Moreno-García, María N. and Peluffo-Ordóñez, Diego H.},\n doi = {10.3390/s20205905},\n journal = {Sensors (Switzerland)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This work presents a monitoring system for the environmental conditions of rose flower-cultivation in greenhouses. Its main objective is to improve the quality of the crops while regulating the production time. To this end, a system consisting of autonomous quadruped vehicles connected with a wireless sensor network (WSN) is developed, which supports the decision-making on type of action to be carried out in a greenhouse to maintain the appropriate environmental conditions for rose cultivation. A data analysis process was carried out, aimed at designing an in-situ intelligent system able to make proper decisions regarding the cultivation process. This process involves stages for balancing data, prototype selection, and supervised classification. The proposed system produces a significant reduction of data in the training set obtained by the WSN while reaching a high classification performance in real conditions—amounting to 90 % and 97.5%, respectively. As a remarkable outcome, it is also provided an approach to ensure correct planning and selection of routes for the autonomous vehicle through the global positioning system.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"godoytrujillo-roseromontalvo-surezzambrano-peluffoordoez-revelofuelagn-anewapproachtosuperviseddataanalysisinembeddedsystemsenvironmentsacasestudy-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'godoytrujillo-roseromontalvo-surezzambrano-peluffoordoez-revelofuelagn-anewapproachtosuperviseddataanalysisinembeddedsystemsenvironmentsacasestudy-2020', 'https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29', event);\">\n    A New Approach to Supervised Data Analysis in Embedded Systems Environments: A Case Study.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Godoy-Trujillo,  P., E.; Rosero-Montalvo,  P., D.; Suárez-Zambrano,  L., E.; Peluffo-Ordoñez,  D., H.;  and Revelo-Fuelagán,  E., J.\n</span>\n\n  \n\n</span>\n\n  In <i>Advances in Intelligent Systems and Computing</i>,  2020. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29\"\n     onclick=\"log_download('godoytrujillo-roseromontalvo-surezzambrano-peluffoordoez-revelofuelagn-anewapproachtosuperviseddataanalysisinembeddedsystemsenvironmentsacasestudy-2020', 'https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A New Approach to Supervised Data Analysis in Embedded Systems Environments: A Case Study [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-030-52249-0_29\"\n     onclick=\"log_download('godoytrujillo-roseromontalvo-surezzambrano-peluffoordoez-revelofuelagn-anewapproachtosuperviseddataanalysisinembeddedsystemsenvironmentsacasestudy-2020', 'http://doi.org/10.1007/978-3-030-52249-0_29', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/godoytrujillo-roseromontalvo-surezzambrano-peluffoordoez-revelofuelagn-anewapproachtosuperviseddataanalysisinembeddedsystemsenvironmentsacasestudy-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>1 download</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('godoytrujillo-roseromontalvo-surezzambrano-peluffoordoez-revelofuelagn-anewapproachtosuperviseddataanalysisinembeddedsystemsenvironmentsacasestudy-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {A New Approach to Supervised Data Analysis in Embedded Systems Environments: A Case Study},\n type = {inproceedings},\n year = {2020},\n keywords = {Data analysis,Embedded systems,Sensor data},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29},\n id = {eaeec4d3-8777-39cd-a984-8ce24e9a4eed},\n created = {2022-02-02T03:56:10.960Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:10.960Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Godoy-Trujillo2020},\n private_publication = {false},\n abstract = {Nowadays, the implementation of embedded systems with sensors for massive data collection has become widely used for their flexibility and improvement in decision making. However, this process can be affected by errors in reading, attrition of systems, among others. For this, a selection approach of supervised algorithms with a prototypes selection criterion is presented, which allows an adequate embedded system performance. To do that a quality measure was established which compromises between the data reduction of the training set, algorithm processing time and the classification performance. As a result, it was determined that the algorithm for the data selection is Condensed Nearest Neighbors (CNN) and the classification algorithm is k-Nearest Neighbour (k-NN).},\n bibtype = {inproceedings},\n author = {Godoy-Trujillo, Pamela E. and Rosero-Montalvo, Paul D. and Suárez-Zambrano, Luis E. and Peluffo-Ordoñez, Diego H. and Revelo-Fuelagán, E. J.},\n doi = {10.1007/978-3-030-52249-0_29},\n booktitle = {Advances in Intelligent Systems and Computing}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Nowadays, the implementation of embedded systems with sensors for massive data collection has become widely used for their flexibility and improvement in decision making. However, this process can be affected by errors in reading, attrition of systems, among others. For this, a selection approach of supervised algorithms with a prototypes selection criterion is presented, which allows an adequate embedded system performance. To do that a quality measure was established which compromises between the data reduction of the training set, algorithm processing time and the classification performance. As a result, it was determined that the algorithm for the data selection is Condensed Nearest Neighbors (CNN) and the classification algorithm is k-Nearest Neighbour (k-NN).\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2019\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2019')\"\n      onkeypress=\"toggleGroup('group_2019')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2019</span>\n      <span class=\"bibbase_group_count\">\n        \n        (4)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"roseromontalvo-lpezbatista-peluffoordez-erazochamorro-arciniegarocha-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-19651-6_23\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-lpezbatista-peluffoordez-erazochamorro-arciniegarocha-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://link.springer.com/10.1007/978-3-030-19651-6_23', event);\">\n    Multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; López-Batista,  V., F.; Peluffo-Ordóñez,  D., H.; Erazo-Chamorro,  V., C.;  and Arciniega-Rocha,  R., P.\n</span>\n\n  \n\n</span>\n\n  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 234-243.  2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-19651-6_23\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-peluffoordez-erazochamorro-arciniegarocha-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://link.springer.com/10.1007/978-3-030-19651-6_23', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-030-19651-6_23\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-peluffoordez-erazochamorro-arciniegarocha-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://doi.org/10.1007/978-3-030-19651-6_23', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-lpezbatista-peluffoordez-erazochamorro-arciniegarocha-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-lpezbatista-peluffoordez-erazochamorro-arciniegarocha-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Alcohol detection,Drunk detection,Prototype selection,Sensors,Supervised classification},\n pages = {234-243},\n websites = {http://link.springer.com/10.1007/978-3-030-19651-6_23},\n id = {61a2d993-1376-3922-93b3-c2a39cc24c28},\n created = {2022-02-02T03:56:11.204Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:11.204Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2019a},\n private_publication = {false},\n abstract = {This work presents a system for detecting excess alcohol in drivers to reduce road traffic accidents. To do so, criteria such as alcohol concentration the environment, a facial temperature of the driver and width of the pupil are considered. To measure the corresponding variables, the data acquisition procedure uses sensors and artificial vision. Subsequently, data analysis is performed into stages for prototype selection and supervised classification algorithms. Accordingly, the acquired data can be stored and processed in a system with low-computational resources. As a remarkable result, the amount of training samples is significantly reduced, while an admissible classification performance is achieved - reaching then suitable settings regarding the given device’s conditions.},\n bibtype = {inbook},\n author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Erazo-Chamorro, Vanessa C. and Arciniega-Rocha, Ricardo P.},\n doi = {10.1007/978-3-030-19651-6_23},\n chapter = {Multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This work presents a system for detecting excess alcohol in drivers to reduce road traffic accidents. To do so, criteria such as alcohol concentration the environment, a facial temperature of the driver and width of the pupil are considered. To measure the corresponding variables, the data acquisition procedure uses sensors and artificial vision. Subsequently, data analysis is performed into stages for prototype selection and supervised classification algorithms. Accordingly, the acquired data can be stored and processed in a system with low-computational resources. As a remarkable result, the amount of training samples is significantly reduced, while an admissible classification performance is achieved - reaching then suitable settings regarding the given device’s conditions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-29859-3_58\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://link.springer.com/10.1007/978-3-030-29859-3_58', event);\">\n    Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; López-Batista,  V., F.; Peluffo-Ordóñez,  D., H.; Lorente-Leyva,  L., L.;  and Blanco-Valencia,  X., P.\n</span>\n\n  \n\n</span>\n\n  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 686-696.  2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-29859-3_58\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://link.springer.com/10.1007/978-3-030-29859-3_58', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-030-29859-3_58\"\n     onclick=\"log_download('roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019', 'http://doi.org/10.1007/978-3-030-29859-3_58', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-lpezbatista-peluffoordez-lorenteleyva-blancovalencia-lecturenotesincomputerscienceincludingsubserieslecturenotesinartificialintelligenceandlecturenotesinbioinformatics-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Data analysis,Environmental monitoring,Environmental science computing,Intelligent system},\n pages = {686-696},\n websites = {http://link.springer.com/10.1007/978-3-030-29859-3_58},\n id = {3b30a58f-f1ff-3ac1-ab36-65d2d7c81020},\n created = {2022-02-02T03:56:11.479Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:11.479Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2019b},\n private_publication = {false},\n abstract = {This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.},\n bibtype = {inbook},\n author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Lorente-Leyva, Leandro L. and Blanco-Valencia, X. P.},\n doi = {10.1007/978-3-030-29859-3_58},\n chapter = {Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"roseromontalvo-peluffoordonez-lopezbatista-serrano-rosero-intelligentsystemforidentificationofwheelchairuserspostureusingmachinelearningtechniques-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/8565996\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-peluffoordonez-lopezbatista-serrano-rosero-intelligentsystemforidentificationofwheelchairuserspostureusingmachinelearningtechniques-2019', 'https://ieeexplore.ieee.org/document/8565996', event);\">\n    Intelligent system for identification of wheelchair user's posture using machine learning techniques.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; Peluffo-Ordonez,  D., H.; Lopez Batista,  V., F.; Serrano,  J.;  and Rosero,  E., A.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Sensors Journal</i>.  2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/8565996\"\n     onclick=\"log_download('roseromontalvo-peluffoordonez-lopezbatista-serrano-rosero-intelligentsystemforidentificationofwheelchairuserspostureusingmachinelearningtechniques-2019', 'https://ieeexplore.ieee.org/document/8565996', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Intelligent system for identification of wheelchair user&#x27;s posture using machine learning techniques [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/JSEN.2018.2885323\"\n     onclick=\"log_download('roseromontalvo-peluffoordonez-lopezbatista-serrano-rosero-intelligentsystemforidentificationofwheelchairuserspostureusingmachinelearningtechniques-2019', 'http://doi.org/10.1109/JSEN.2018.2885323', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-peluffoordonez-lopezbatista-serrano-rosero-intelligentsystemforidentificationofwheelchairuserspostureusingmachinelearningtechniques-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>9 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-peluffoordonez-lopezbatista-serrano-rosero-intelligentsystemforidentificationofwheelchairuserspostureusingmachinelearningtechniques-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Intelligent system for identification of wheelchair user&#x27;s posture using machine learning techniques},\n type = {article},\n year = {2019},\n keywords = {Embedded system,K-nearest neighbors,Kennard-stone,posture detection,principal component analysis},\n websites = {https://ieeexplore.ieee.org/document/8565996},\n id = {a2ac7492-b9ff-39bf-aa8e-4cd246d9b449},\n created = {2022-02-02T03:56:11.729Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:11.729Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2019c},\n private_publication = {false},\n abstract = {This paper presents an intelligent system aimed at detecting a person&#x27;s posture when sitting in a wheelchair. The main use of the proposed system is to warn an improper posture to prevent major health issues. A network of sensors is used to collect data that are analyzed through a scheme involving the following stages: Selection of prototypes using condensed nearest neighborhood rule (CNN), data balancing with the Kennard-Stone algorithm, and reduction of dimensionality through principal component analysis. In doing so, acquired data can be both stored and processed into a micro controller. Finally, to carry out the posture classification over balanced, pre-processed data, and the K-nearest neighbors algorithm is used. It turns to be an intelligent system reaching a good tradeoff between the necessary amount of data and performance is accomplished. As a remarkable result, the amount of required data for training is significantly reduced while an admissible classification performance is achieved being a suitable trade given the device conditions.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D. and Peluffo-Ordonez, Diego Hernn and Lopez Batista, Vivian Felix and Serrano, Jorge and Rosero, Edwin A.},\n doi = {10.1109/JSEN.2018.2885323},\n journal = {IEEE Sensors Journal}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper presents an intelligent system aimed at detecting a person's posture when sitting in a wheelchair. The main use of the proposed system is to warn an improper posture to prevent major health issues. A network of sensors is used to collect data that are analyzed through a scheme involving the following stages: Selection of prototypes using condensed nearest neighborhood rule (CNN), data balancing with the Kennard-Stone algorithm, and reduction of dimensionality through principal component analysis. In doing so, acquired data can be both stored and processed into a micro controller. Finally, to carry out the posture classification over balanced, pre-processed data, and the K-nearest neighbors algorithm is used. It turns to be an intelligent system reaching a good tradeoff between the necessary amount of data and performance is accomplished. As a remarkable result, the amount of required data for training is significantly reduced while an admissible classification performance is achieved being a suitable trade given the device conditions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"roseromontalvo-batista-rosero-jaramillo-caraguay-pijalrojas-peluffoordez-advancesinintelligentsystemsandcomputing-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-02686-8_65\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-batista-rosero-jaramillo-caraguay-pijalrojas-peluffoordez-advancesinintelligentsystemsandcomputing-2019', 'http://link.springer.com/10.1007/978-3-030-02686-8_65', event);\">\n    Intelligence in Embedded Systems: Overview and Applications.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; Batista,  V., F., L.; Rosero,  E., A.; Jaramillo,  E., D.; Caraguay,  J., A.; Pijal-Rojas,  J.;  and Peluffo-Ordóñez,  D., H.\n</span>\n\n  \n\n</span>\n\n  Advances in Intelligent Systems and Computing, pages 874-883.  2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-02686-8_65\"\n     onclick=\"log_download('roseromontalvo-batista-rosero-jaramillo-caraguay-pijalrojas-peluffoordez-advancesinintelligentsystemsandcomputing-2019', 'http://link.springer.com/10.1007/978-3-030-02686-8_65', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Advances in Intelligent Systems and Computing [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-030-02686-8_65\"\n     onclick=\"log_download('roseromontalvo-batista-rosero-jaramillo-caraguay-pijalrojas-peluffoordez-advancesinintelligentsystemsandcomputing-2019', 'http://doi.org/10.1007/978-3-030-02686-8_65', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-batista-rosero-jaramillo-caraguay-pijalrojas-peluffoordez-advancesinintelligentsystemsandcomputing-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-batista-rosero-jaramillo-caraguay-pijalrojas-peluffoordez-advancesinintelligentsystemsandcomputing-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Decision making,Embedded systems,Internet of things,Machine learning},\n pages = {874-883},\n websites = {http://link.springer.com/10.1007/978-3-030-02686-8_65},\n id = {29c5309a-6424-3c66-9305-c30fdaec508f},\n created = {2022-02-02T03:56:11.971Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:11.971Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2019},\n private_publication = {false},\n abstract = {The use of electronic systems and devices has become widely spread and is reaching several fields as well as indispensable for many daily activities. Such systems and devices (here termed embedded systems) are aiming at improving human beings’ quality of life. To do so, they typically acquire users’ data to adjust themselves to different needs and environments in an adequate fashion. Consequently, they are connected to data networks to share this information and find elements that allow them to make the appropriate decisions. Then, for practical usage, their computational capabilities should be optimized to avoid issues such as: resources saturation (mainly memory and battery). In this line, machine learning offers a wide range of techniques and tools to incorporate “intelligence” into embedded systems, enabling them to make decisions by themselves. This paper reviews different data storage techniques along with machine learning algorithms for embedded systems. Its main focus is on techniques and applications (with special interest in Internet of Things) reported in literature about data analysis criteria to make decisions.},\n bibtype = {inbook},\n author = {Rosero-Montalvo, Paul D. and Batista, Vivian F. López and Rosero, Edwin A. and Jaramillo, Edgar D. and Caraguay, Jorge A. and Pijal-Rojas, José and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-030-02686-8_65},\n chapter = {Intelligence in Embedded Systems: Overview and Applications},\n title = {Advances in Intelligent Systems and Computing}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The use of electronic systems and devices has become widely spread and is reaching several fields as well as indispensable for many daily activities. Such systems and devices (here termed embedded systems) are aiming at improving human beings’ quality of life. To do so, they typically acquire users’ data to adjust themselves to different needs and environments in an adequate fashion. Consequently, they are connected to data networks to share this information and find elements that allow them to make the appropriate decisions. Then, for practical usage, their computational capabilities should be optimized to avoid issues such as: resources saturation (mainly memory and battery). In this line, machine learning offers a wide range of techniques and tools to incorporate “intelligence” into embedded systems, enabling them to make decisions by themselves. This paper reviews different data storage techniques along with machine learning algorithms for embedded systems. Its main focus is on techniques and applications (with special interest in Internet of Things) reported in literature about data analysis criteria to make decisions.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2018\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2018')\"\n      onkeypress=\"toggleGroup('group_2018')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2018</span>\n      <span class=\"bibbase_group_count\">\n        \n        (3)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"roseromontalvo-pijalrojas-vasquezayala-maya-pupiales-suarez-benitezpereira-peluffoordonez-wirelesssensornetworksforirrigationincropsusingmultivariateregressionmodels-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/8580322/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-pijalrojas-vasquezayala-maya-pupiales-suarez-benitezpereira-peluffoordonez-wirelesssensornetworksforirrigationincropsusingmultivariateregressionmodels-2018', 'https://ieeexplore.ieee.org/document/8580322/', event);\">\n    Wireless Sensor Networks for Irrigation in Crops Using Multivariate Regression Models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; Pijal-Rojas,  J.; Vasquez-Ayala,  C.; Maya,  E.; Pupiales,  C.; Suarez,  L.; Benitez-Pereira,  H.;  and Peluffo-Ordonez,  D.\n</span>\n\n  \n\n</span>\n\n  In <i>2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)</i>, pages 1-6, 10 2018. IEEE\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/8580322/\"\n     onclick=\"log_download('roseromontalvo-pijalrojas-vasquezayala-maya-pupiales-suarez-benitezpereira-peluffoordonez-wirelesssensornetworksforirrigationincropsusingmultivariateregressionmodels-2018', 'https://ieeexplore.ieee.org/document/8580322/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Wireless Sensor Networks for Irrigation in Crops Using Multivariate Regression Models [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/ETCM.2018.8580322\"\n     onclick=\"log_download('roseromontalvo-pijalrojas-vasquezayala-maya-pupiales-suarez-benitezpereira-peluffoordonez-wirelesssensornetworksforirrigationincropsusingmultivariateregressionmodels-2018', 'http://doi.org/10.1109/ETCM.2018.8580322', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-pijalrojas-vasquezayala-maya-pupiales-suarez-benitezpereira-peluffoordonez-wirelesssensornetworksforirrigationincropsusingmultivariateregressionmodels-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-pijalrojas-vasquezayala-maya-pupiales-suarez-benitezpereira-peluffoordonez-wirelesssensornetworksforirrigationincropsusingmultivariateregressionmodels-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Wireless Sensor Networks for Irrigation in Crops Using Multivariate Regression Models},\n type = {inproceedings},\n year = {2018},\n keywords = {WSN,crops analysis,regression model},\n pages = {1-6},\n websites = {https://ieeexplore.ieee.org/document/8580322/},\n month = {10},\n publisher = {IEEE},\n id = {56cfb072-a7ab-3c59-b930-9796b44f87e8},\n created = {2022-02-02T03:56:12.308Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:12.308Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2018b},\n private_publication = {false},\n abstract = {The present wireless sensor network system shows a data analysis approach within greenhouses in short cycle crops. This research, on the one hand, is carried out to reduce water consumption and improve the product by predicting the right moment of the irrigation cycle through the evapotranspiration criterion. On the other hand, an efficient electronic system is designed under the electronic standard. To define the best model to define the next irrigation in the crops in base to ground humidity, the algorithms are compared for continuous and discontinuous multivariate regressions. The results are evaluated with different criteria of prediction errors. As a result, the linear regression with Support Vector Machine model is chosen for counting an average deviation error of 7.89% and an error variability of 4.48%. In addition, water consumption is reduced by 20%, achieving better quality products.},\n bibtype = {inproceedings},\n author = {Rosero-Montalvo, Paul D. and Pijal-Rojas, Jose and Vasquez-Ayala, Carlos and Maya, Edgar and Pupiales, Carlos and Suarez, Luis and Benitez-Pereira, Henry and Peluffo-Ordonez, D.H.},\n doi = {10.1109/ETCM.2018.8580322},\n booktitle = {2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The present wireless sensor network system shows a data analysis approach within greenhouses in short cycle crops. This research, on the one hand, is carried out to reduce water consumption and improve the product by predicting the right moment of the irrigation cycle through the evapotranspiration criterion. On the other hand, an efficient electronic system is designed under the electronic standard. To define the best model to define the next irrigation in the crops in base to ground humidity, the algorithms are compared for continuous and discontinuous multivariate regressions. The results are evaluated with different criteria of prediction errors. As a result, the linear regression with Support Vector Machine model is chosen for counting an average deviation error of 7.89% and an error variability of 4.48%. In addition, water consumption is reduced by 20%, achieving better quality products.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"roseromontalvo-godoytrujillo-floresbosmediano-carrascalgarcia-oteropotosi-benitezpereira-peluffoordonez-signlanguagerecognitionbasedonintelligentgloveusingmachinelearningtechniques-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/8580268/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-godoytrujillo-floresbosmediano-carrascalgarcia-oteropotosi-benitezpereira-peluffoordonez-signlanguagerecognitionbasedonintelligentgloveusingmachinelearningtechniques-2018', 'https://ieeexplore.ieee.org/document/8580268/', event);\">\n    Sign Language Recognition Based on Intelligent Glove Using Machine Learning Techniques.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; Godoy-Trujillo,  P.; Flores-Bosmediano,  E.; Carrascal-Garcia,  J.; Otero-Potosi,  S.; Benitez-Pereira,  H.;  and Peluffo-Ordonez,  D., H.\n</span>\n\n  \n\n</span>\n\n  In <i>2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)</i>, pages 1-5, 10 2018. IEEE\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/8580268/\"\n     onclick=\"log_download('roseromontalvo-godoytrujillo-floresbosmediano-carrascalgarcia-oteropotosi-benitezpereira-peluffoordonez-signlanguagerecognitionbasedonintelligentgloveusingmachinelearningtechniques-2018', 'https://ieeexplore.ieee.org/document/8580268/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Sign Language Recognition Based on Intelligent Glove Using Machine Learning Techniques [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/ETCM.2018.8580268\"\n     onclick=\"log_download('roseromontalvo-godoytrujillo-floresbosmediano-carrascalgarcia-oteropotosi-benitezpereira-peluffoordonez-signlanguagerecognitionbasedonintelligentgloveusingmachinelearningtechniques-2018', 'http://doi.org/10.1109/ETCM.2018.8580268', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-godoytrujillo-floresbosmediano-carrascalgarcia-oteropotosi-benitezpereira-peluffoordonez-signlanguagerecognitionbasedonintelligentgloveusingmachinelearningtechniques-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>1 download</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-godoytrujillo-floresbosmediano-carrascalgarcia-oteropotosi-benitezpereira-peluffoordonez-signlanguagerecognitionbasedonintelligentgloveusingmachinelearningtechniques-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Sign Language Recognition Based on Intelligent Glove Using Machine Learning Techniques},\n type = {inproceedings},\n year = {2018},\n keywords = {intelligent glove,knn,prototype selection,sign language},\n pages = {1-5},\n websites = {https://ieeexplore.ieee.org/document/8580268/},\n month = {10},\n publisher = {IEEE},\n id = {05ea9057-f763-3ffa-bd0e-32df0c7eca27},\n created = {2022-02-02T03:56:12.553Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:12.553Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2018a},\n private_publication = {false},\n abstract = {We present an intelligent electronic glove system able to detect numbers of sign language in order to automate the process of communication between a deaf-mute person and others. This is done by translating the hands move sign language into an oral language. The system is inside to a glove with flex sensors in each finger that we are used to collect data that are analyzed through a methodology involving the following stages: (i) Data balancing with the Kennard-Stone (KS), (ii) Comparison of prototypes selection between CHC evolutionary Algorithm and Decremental Reduction Optimization Procedure 3 (DROP3) to define the best one. Subsequently, the K-Nearest Neighbors (kNN) as classifier (iii) is implemented. As a result, the amount of data reduced from stage (i) from storage within the system is 98%. Also, a classification performance of 85% is achieved with CHC evolutionary algorithm.},\n bibtype = {inproceedings},\n author = {Rosero-Montalvo, Paul D. and Godoy-Trujillo, Pamela and Flores-Bosmediano, Edison and Carrascal-Garcia, Jorge and Otero-Potosi, Santiago and Benitez-Pereira, Henry and Peluffo-Ordonez, Diego H.},\n doi = {10.1109/ETCM.2018.8580268},\n booktitle = {2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We present an intelligent electronic glove system able to detect numbers of sign language in order to automate the process of communication between a deaf-mute person and others. This is done by translating the hands move sign language into an oral language. The system is inside to a glove with flex sensors in each finger that we are used to collect data that are analyzed through a methodology involving the following stages: (i) Data balancing with the Kennard-Stone (KS), (ii) Comparison of prototypes selection between CHC evolutionary Algorithm and Decremental Reduction Optimization Procedure 3 (DROP3) to define the best one. Subsequently, the K-Nearest Neighbors (kNN) as classifier (iii) is implemented. As a result, the amount of data reduced from stage (i) from storage within the system is 98%. Also, a classification performance of 85% is achieved with CHC evolutionary algorithm.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"roseromontalvo-caraguayprocel-jaramillo-michilenacalderon-umaquingacriollo-mediavillavalverde-ruiz-beltran-etal-airqualitymonitoringintelligentsystemusingmachinelearningtechniques-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/8564511/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'roseromontalvo-caraguayprocel-jaramillo-michilenacalderon-umaquingacriollo-mediavillavalverde-ruiz-beltran-etal-airqualitymonitoringintelligentsystemusingmachinelearningtechniques-2018', 'https://ieeexplore.ieee.org/document/8564511/', event);\">\n    Air Quality Monitoring Intelligent System Using Machine Learning Techniques.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rosero-Montalvo,  P., D.; Caraguay-Procel,  J., A.; Jaramillo,  E., D.; Michilena-Calderon,  J., M.; Umaquinga-Criollo,  A., C.; Mediavilla-Valverde,  M.; Ruiz,  M., A.; Beltran,  L., A.;  and Peluffo,  D., H.\n</span>\n\n  \n\n</span>\n\n  In <i>2018 International Conference on Information Systems and Computer Science (INCISCOS)</i>, pages 75-80, 11 2018. IEEE\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/8564511/\"\n     onclick=\"log_download('roseromontalvo-caraguayprocel-jaramillo-michilenacalderon-umaquingacriollo-mediavillavalverde-ruiz-beltran-etal-airqualitymonitoringintelligentsystemusingmachinelearningtechniques-2018', 'https://ieeexplore.ieee.org/document/8564511/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Air Quality Monitoring Intelligent System Using Machine Learning Techniques [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/INCISCOS.2018.00019\"\n     onclick=\"log_download('roseromontalvo-caraguayprocel-jaramillo-michilenacalderon-umaquingacriollo-mediavillavalverde-ruiz-beltran-etal-airqualitymonitoringintelligentsystemusingmachinelearningtechniques-2018', 'http://doi.org/10.1109/INCISCOS.2018.00019', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/roseromontalvo-caraguayprocel-jaramillo-michilenacalderon-umaquingacriollo-mediavillavalverde-ruiz-beltran-etal-airqualitymonitoringintelligentsystemusingmachinelearningtechniques-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('roseromontalvo-caraguayprocel-jaramillo-michilenacalderon-umaquingacriollo-mediavillavalverde-ruiz-beltran-etal-airqualitymonitoringintelligentsystemusingmachinelearningtechniques-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Air Quality Monitoring Intelligent System Using Machine Learning Techniques},\n type = {inproceedings},\n year = {2018},\n keywords = {Air quality,Intelligent system,Monitoring system},\n pages = {75-80},\n websites = {https://ieeexplore.ieee.org/document/8564511/},\n month = {11},\n publisher = {IEEE},\n id = {60a4cac5-3c46-3533-8f32-3e56289992ae},\n created = {2022-02-02T03:56:12.803Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {1e7ab630-581a-3aa0-aaa7-d77ad12b77fe},\n last_modified = {2022-02-02T03:56:12.803Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2018},\n private_publication = {false},\n abstract = {Environment monitoring is so important because it is based on the first right of people, life and health. For this reason, this system monitoring air quality with different sensor nodes in the Ibarra that evaluate the parameters of CO2, NOx, UV Light, Temperature and Humidity. The data analysis through machine learning algorithms allow the system to classify autonomously if a certain geographical location is exceeding the established emission limits of gases. As a result, the k-Nearest Neighbor algorithm presented a great classification performance when selecting the most contaminated sectors.},\n bibtype = {inproceedings},\n author = {Rosero-Montalvo, Paul D. and Caraguay-Procel, Jorge A. and Jaramillo, Edgar D. and Michilena-Calderon, Jaime M. and Umaquinga-Criollo, Ana C. and Mediavilla-Valverde, Mario and Ruiz, Miguel A. and Beltran, Luis A. and Peluffo, Diego H.},\n doi = {10.1109/INCISCOS.2018.00019},\n booktitle = {2018 International Conference on Information Systems and Computer Science (INCISCOS)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Environment monitoring is so important because it is based on the first right of people, life and health. For this reason, this system monitoring air quality with different sensor nodes in the Ibarra that evaluate the parameters of CO2, NOx, UV Light, Temperature and Humidity. The data analysis through machine learning algorithms allow the system to classify autonomously if a certain geographical location is exceeding the established emission limits of gases. As a result, the k-Nearest Neighbor algorithm presented a great classification performance when selecting the most contaminated sectors.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n\n\n\n  </div>\n\n\n  <!-- Modal -->\n\n  <!-- <iframe id=\"bibbase_network_frame\" -->\n  <!--         src=\"//bibbase.org/network/control\" -->\n  <!--         style=\"display: none;\"> -->\n  <!-- </iframe> -->\n\n</div>\n"}; document.write(bibbase_data.data);