@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 = {2f7cd772-faaf-3bc5-ba89-3147aaa9321f},
 created = {2022-01-26T03:00:35.700Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {b9022d50-068c-31b4-9174-ebfaaf9ee57b},
 last_modified = {2022-01-26T03:00:35.700Z},
 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)}
}

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