Application of Unmanned Aerial Vehicles for Autonomous Fire Detection

This paper describes the development and implementation of an autonomous system for fire detection using Unmanned Aerial Vehicles (UAVs). This project aims to explore new technologies for quick and effective responses, thereby reducing the damage caused by natural disasters. The approach utilizes computer vision techniques, with the UAV equipped with a camera to identify signs of fire and smoke. Using UAVs in fire detection presents a promising alternative to conventional methods, offering the potential to cover vast areas quickly and transmit real-time data to command centers. The methodology includes designing and implementing a UAV equipped with computer vision technology. The YOLO object detection model was used, configured to identify signs of fire and smoke in images captured during flight. The UAV was programmed to navigate autonomously following predefined routes, with the capability to adjust its trajectory based on real-time data collected. Results indicate that the UAV could correctly identify signs of fire and smoke with significant accuracy. The system’s capabilities were validated under controlled conditions, where the UAV demonstrated effectiveness in detecting and sending alerts to a base station. This study concludes that the use of UAVs for fire detection is feasible and effective, providing a valuable tool for firefighting efforts.