LoRaWAN Network for Fire Monitoring in Rural Environments

Electronics

Roberto Vega-Rodríguez¹  Sandra Sendra¹  Ignacio Bosch²  Laura García³  Jaime Lloret³ 

[1] Department of Teoría de la Señal, Telemática y Comunicaciones (TSTC), Universidad de Granada, Periodista Daniel Saucedo Aranda s/n, 18014 Granada, Spain;Institute of Telecommunications and Multimedia Applications (iTEAM), Universitat Politècnica de València, Camino Vera s/n, 46022 Valencia, Spain;Instituto de Investigación para la Gestión Integrada de zonas Costeras (IGIC), Universitat Politècnica de València, Paraninf 1, 46730 Valencia, Spain;

关键词: long range (lora);    lorawan;    fire detection;    low-cost;    arduino;    monitoring;    sensors;    wireless sensor networks (wsn), dragino;    the things network (ttn);   

DOI  :  10.3390/electronics9030531

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown