An Early Forest Fire Detection System Based on DJI M300 Drone and H20T Camera

Abstract

This paper presents a drone-based early forest fire detection system. Using multiple on-board aerial sensors, thermal images, RGB images, and distance between forest fire points and drones can be captured and determined from the air. To take advantage of data from different sources for forest fire detection and confirmation, both deep learning-based and traditional computer vision algorithms are developed and employed. The on-board computer and ground station computer are designed to work collaboratively according to the different complexity and computational demands of sub-modules in this system. By integrating different sensor data with a two-phase strategy for potential early forest fire detection and confirmation, the proposed system achieves a relatively low false alarm rate and has good robustness in the outdoor real-time early forest fire detection experiments with an on-board computer installed on a DJI M300 drone.