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Smart Multi-Sensor System for Remote Air Quality Monitoring Using Unmanned Aerial Vehicle and LoRaWAN.
Camarillo-Escobedo, Rosa; Flores, Jorge L; Marin-Montoya, Pedro; García-Torales, Guillermo; Camarillo-Escobedo, Juana M.
  • Camarillo-Escobedo R; Mechanic and Mechatronics Department, National Technological Institute La Laguna, Blvd. Revolución & Calz. Cuauhtemoc S/N, Torreon 27000, Coahuila, Mexico.
  • Flores JL; Translational Biomedical Engineering Department, University of Guadalajara, Av. Revolución #1500, Guadalajara 44430, Jalisco, Mexico.
  • Marin-Montoya P; Translational Biomedical Engineering Department, University of Guadalajara, Av. Revolución #1500, Guadalajara 44430, Jalisco, Mexico.
  • García-Torales G; Mechanic and Mechatronics Department, National Technological Institute La Laguna, Blvd. Revolución & Calz. Cuauhtemoc S/N, Torreon 27000, Coahuila, Mexico.
  • Camarillo-Escobedo JM; Translational Biomedical Engineering Department, University of Guadalajara, Av. Revolución #1500, Guadalajara 44430, Jalisco, Mexico.
Sensors (Basel) ; 22(5)2022 Feb 22.
Article en En | MEDLINE | ID: mdl-35270852
ABSTRACT
Deaths caused by respiratory and cardiovascular diseases have increased by 10%. Every year, exposure to high levels of air pollution is the cause of 7 million premature deaths and the loss of healthy years of life. Air pollution is generally caused by the presence of CO, NO2, NH3, SO2, particulate matter PM10 and PM2.5, mainly emitted by economic activities in large metropolitan areas. The problem increases considerably in the absence of national regulations and the design, installation, and maintenance of an expensive air quality monitoring network. A smart multi-sensor system to monitor air quality is proposed in this work. The system uses an unmanned aerial vehicle and LoRa communication as an alternative for remote and in-situ atmospheric measurements. The instrumentation was integrated modularly as a node sensor to measure the concentration of carbon monoxide (CO), nitrogen dioxide (NO2), ammonia (NH3), sulfur dioxide (SO2), and suspended particulate mass PM10 and PM2.5. The optimal design of the multi-sensor system has been developed under the following constraints A low weight, compact design, and low power consumption. The integration of the multi-sensor device, UAV, and LoRa communications as a single system adds aeeded flexibility to currently fixed monitoring stations.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire Idioma: En Año: 2022 Tipo del documento: Article