LoRaWAN Network for Fire Monitoring in Rural Environments
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Long RangeFire detectionWireless sensor networks (WSN)The Things NetworkLoRaWAN
Sendra, S., García, L., Lloret, J., Bosch, I., & Vega-Rodríguez, R. (2020). LoRaWAN Network for Fire Monitoring in Rural Environments. Electronics, 9(3), 531.
SponsorshipThis work was partially supported by the “Ministerio de Ciencia, Innovación y Universidades” through the “Ayudas para la adquisición de equipamiento científico-técnico, Subprograma estatal de infraestructuras de investigación y equipamiento científico-técnico (plan Estatal I+D+i 2017-2020)” (project EQC2018-004988-P), by Universidad de Granada through the “Programa de Proyectos de Investigación Precompetitivos para Jóvenes Investigadores. Modalidad A jóvenes Doctores” of “Plan Propio de Investigación y Transferencia 2019” (PPJIA2019.10), by the Campus de Excelencia Internacional Global del Mar (CEI·Mar) through the “Ayudas Proyectos Jóvenes Investigadores CEI·Mar 2019”, (Project CEIJ-020), by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) (Project ERANETMED3-227 SMARTWATIR).
The number of forest fires that occurred in recent years in different parts of the world is causing increased concern in the population, as the consequences of these fires expand beyond the destruction of the ecosystem. However, with the proliferation of the Internet of Things (IoT) industry, solutions for early fire detection should be developed. The assessment of the fire risk of an area and the communication of this fact to the population could reduce the number of fires originated by accident or due to the carelessness of the users. This paper presents a low-cost network based on Long Range (LoRa) technology to autonomously evaluate the level of fire risk and the presence of a forest fire in rural areas. The system is comprised of several LoRa nodes with sensors to measure the temperature, relative humidity, wind speed and CO2 of the environment. The data from the nodes is stored and processed in a The Things Network (TTN) server that sends the data to a website for the graphic visualization of the collected data. The system is tested in a real environment and, the results show that it is possible to cover a circular area of a radius of 4 km with a single gateway.