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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. ; This 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).

[EN] 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. ; This work was partially supported by the "Ministerio de Ciencia, Innovacion y Universidades" through the "Ayudas para la adquisicion de equipamiento cientifico-tecnico, Subprograma estatal de infraestructuras de investigacion y equipamiento cientifico-tecnico (plan Estatal I+D+i 2017-2020)" (project EQC2018-004988-P), by Universidad de Granada through the "Programa de Proyectos de Investigacion Precompetitivos para Jovenes Investigadores. Modalidad A jovenes Doctores" of "Plan Propio de Investigacion y Transferencia 2019" (PPJIA2019.10), by the Campus de Excelencia Internacional Global del Mar (CEI.Mar) through the "Ayudas Proyectos Jovenes 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 ...

[EN] Forest fires are one of the main environmental problems in the entire Mediterranean basin. In a context where low power and long-range networks (LPWAN) are increasingly common to the rise of Internet of Things (IoT) architecture, the interest in providing solutions to monitor scenarios and fire prevention based on these technologies is huge. This paper presents a low cost Long Range (LoRa) based network able to evaluate level of fire risk and the presence of a forest fire. The system is composed by a LoRa node and a set of sensors to measure the temperature, relative humidity, wind speed and CO2. The evaluation algorithm is based on the 30- 30-30 rule. Through website the users can see the parameters measured by nodes in real time. The system has been tested in a real environment and the results show that it is possible to cover a circular area of 1.1km or radius. ; This work has been partially supported by the Ministerio de Ciencia, Innovación y Universidades through the Ayudas para la adquisición de equipamiento científicotécnico, Subprograma estatal de infraestructuras de investigación y equipamiento científico-técnico (plan Estatal I+D+i 2017-2020) (project EQC2018-004988-P) and through the Research Contracts of Youth Employment of the University of Granada, through its operative program of Youth Guarantee of the Regional Government of Andalusia and the European Social Fund. ; Vega-Rodríguez, R.; Sendra, S.; Lloret, J.; Romero-Díaz, P.; García-Navas, JL. (2019). Low Cost LoRa based Network for Forest Fire Detection. IEEE. 177-184. https://doi.org/10.1109/IOTSMS48152.2019.8939193 ; S ; 177 ; 184