Abstract:

To solve the problems of high false alarm rate and slow response speed in traditional forest fire detection, it is proposed to use UAV as the detection platform and ground station as the fire identification system to realize the automatic detection, identification and location of forest fires. First, a six- rotor UAV platform was developed to obtain forest fire scene images through the mounted infrared camera and onboard computer and transmit them back to the ground in real time. Secondly, the ground station was used to process the received fire images to achieve forest fire online monitoring of fire sites. In terms of forest fire recognition algorithm, the O- YOLOv3 algorithm is proposed, the Darknet framework is used for network training, and the K-means method is used to automatically generate anchor points, which effectively improves the accuracy and response speed of fire recognition. Finally, the O-YOLOv3 algorithm is compared with several other algorithms to verify the effectiveness of this algorithm. Experimental results show that: OYOLOv3 fire identification algorithm can quickly and accurately identify forest fires.The developed UAV forest fire detection system based on O-YOLOv3 can be used for actual forest fire detection.  

Key words: UAV, forest fire, O-YOLOv3, fire recognition