Advancements in Fire Detection: A Review of Computer Vision and Deep Learning Approaches

This paper reviews existing research and effort on an important contemporary topic in the field of computer vision. Specifically, it examines current methodologies and algorithms for the fire and smoke detection. As fires are becoming more frequent and spread rapidly, causing substantial material damage andpotentiallyendangeringhumanlives,itisnecessaryto develop technology that can detect fires promptly and notify the relevant authorities. This paper specifically emphasizes the work conducted in the domain of computer vision and deep learning. Additionally, the paper highlights the advantages of using unmanned aerial vehicles equipped with RGB and IR cameras for operations in hard-to-reach fire areas. The implementation of IoT technology enhances the fire detection system since it improves the accuracy of early and real-time fire detection, while also supplying valuable data for subsequent analysis and fire preventive efforts. Despite the many advantages offered by the current technology, due to the unpredictable fire nature and specific machine learning characteristics, there is still room for further progress in this research domain.