A UAV with Autonomy, Pattern Recognition for Forest Fire Prevention, and AI for Providing Advice to Firefighters Fighting Forest Fires

Evangelos A. Yfantis, University of Nevada, Las Vegas


The design of a long endurance UAV powered by solar energy, with autonomy flying over a pre specified forest area equipped with LiDAR which includes R, G, B and Infrared or near infrared bands to take clear and detail video of every part of the forest in order to recognize legal or illegal camp fires, dry areas providing hazardous conditions, upload temperature, humidity and other ground sensor data, helping to characterize the degree of forest fire vulnerability using pattern recognition, and communicating this information to firefighters either upon request, or as alarm events. The airplane electronic hardware software uses computational photography and virtual reality to create a detail 3-D forest video real time. It communicates all this information to a ground station real time. Although the aircraft has autonomy, trained pilots in the ground station can override the autonomy and fly the aircraft. In case of forest fire the aircraft electronic hardware software system can compute the exact area affected, the fire velocity and speed, the wind direction, and provide advice to the firefighters regarding the optimal way of fighting the fire. Often time forest fires destroy the communication infrastructure, so the airplane has a router to enable firefighters to exchange, text and voice information.