Autonomous Drones for Forest Fire Detection and Early Response Systems

Abstract

The research looks into developing and deploying autonomous drone systems for automated detection and enhanced fire surveillance of active fire incidents occurring in forests. The goal is to utilize novel sensing and artificial intelligence (AI) technologies, or advanced AI algorithms, to achieve rapid, precise, and real-time identification of early fire outbreaks so response time can be minimized to lessen the consequential damage on the environment and economy. Our methodology employs thermal and visual cameras along with UAVs equipped with AI-powered imaging systems for real-time anomaly detection, autonomous navigation, and active surveillance. Findings show that autonomous systems allow early detection and autonomous drones allow for faster speeds as compared to traditional methods which provide critical early warnings. This effort aims to pioneer new frontiers of research in intelligent forest fire management while improving the management of natural disasters.