A Social IoT-Based Solution for Real-Time Forest Fire Detection

Conservation of the natural ecosystem is a hot topic that is receiving increasing attention not only from the scientific community, but from the entire world population. Forests and woodlands are major contributors to climate change mitigation, able to absorb significant amounts of carbon dioxide. This paper proposes a novel real-time fire monitoring and detection system based on Digital Mobile Radio (DMR) nodes and a Social Internet of Things (SIoT) platform on which fire detection decision making algorithms have been implemented. The results obtained by employing a K-Nearest Neighbors (KNN) algorithm and a Recurrent Neural Network (RNN) show the ability to detect the slightest variation in the observed parameters, determining the direction and speed of fire propagation with an accuracy of more than 98%.