Wildfire early warning system based on wireless sensors and unmanned aerial vehicle

Abstract

Wildfires erupt annually around the world causing serious loss of life and property damage. Despite the rapid progress of science and technology, there are no effective means to forecast wildfires. Various wildfire monitoring systems are deployed in different countries, most depend on photos or videos to identify features of wildfire after the first outbreak, while the delay of confirmation varies with technology. An autonomous forest wildfire early warning system is presented in this paper, which employs a state-of-the-art unmanned aerial vehicle (UAV) to fly around a forest regularly according to established routes and strict procedures, to collect environmental data from sensors installed on trees, to monitor and predict wildfire, then provide early warning before eruption if a danger emerges. Bluetooth Low Energy (BLE) is employed to exchange data between UAV and the host of sensors. The collected monitoring data, such as temperature and humidity, is effective to reflect the real condition of the forest, which could result in early warning of wildfires. The application of this system in the environment will enhance the ability of wildfire prediction for the community.