TY - JOUR
T1 - Environmental Monitoring using Embedded Systems on UAVs
AU - Vazquez-Carmona, Esther Viridiana
AU - Vasquez-Gomez, Juan Irving
AU - Herrera-Lozada, Juan Carlos
N1 - Publisher Copyright:
© 2003-2012 IEEE.
PY - 2020/2
Y1 - 2020/2
N2 - Nowadays, Earth is being affected by the greenhouse effect. A first step to improve the current situation is to track the involved variables under temporal and spatial sampling. In this paper, we propose an integrated system for monitoring the related greenhouse effect gasses and several environmental variables. The system has been designed to be mounted on an unmanned aerial vehicle to overcome the spatial constraints and it also has been designed to work under the Internet of Things paradigm to overcome the temporal constraints. Unlike previous approaches, we have integrated an optimal filtering step with Kalman Filter, improving the reliability and precision of the measurements. Our experiments show that the proposed system can provide the information to the final user in near real-time. In addition, the use of the Kalman filter decreases the mean square error of our system with respect to a reference sensor.
AB - Nowadays, Earth is being affected by the greenhouse effect. A first step to improve the current situation is to track the involved variables under temporal and spatial sampling. In this paper, we propose an integrated system for monitoring the related greenhouse effect gasses and several environmental variables. The system has been designed to be mounted on an unmanned aerial vehicle to overcome the spatial constraints and it also has been designed to work under the Internet of Things paradigm to overcome the temporal constraints. Unlike previous approaches, we have integrated an optimal filtering step with Kalman Filter, improving the reliability and precision of the measurements. Our experiments show that the proposed system can provide the information to the final user in near real-time. In addition, the use of the Kalman filter decreases the mean square error of our system with respect to a reference sensor.
KW - Embedded System
KW - Environmental Monitoring
KW - Greenhouse Effect
KW - Internet of Things
KW - Kalman Filter
KW - Micro Air Vehicle
KW - UAV
UR - http://www.scopus.com/inward/record.url?scp=85084532317&partnerID=8YFLogxK
U2 - 10.1109/TLA.2020.9085284
DO - 10.1109/TLA.2020.9085284
M3 - Artículo
AN - SCOPUS:85084532317
SN - 1548-0992
VL - 18
SP - 303
EP - 310
JO - IEEE Latin America Transactions
JF - IEEE Latin America Transactions
IS - 2
M1 - 9085284
ER -