Environment monitoring of rose crops greenhouse based on autonomous vehicles with a wsn and data analysis. Rosero-Montalvo, P., D., Erazo-Chamorro, V., C., López-Batista, V., F., Moreno-García, M., N., & Peluffo-Ordóñez, D., H. Sensors (Switzerland), 2020. Website doi abstract bibtex 11 downloads 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.
@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},
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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)}
}
Downloads: 11
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