Revolutionizing Fire Detection: Unleashing the Power of YOLOv8 Algorithm for Accurate Image Recognition

Fire incidents present a significant threat to human safety and property, emphasizing the need for highly effective detection methods. This study introduces a cutting-edge fire image recognition algorithm, leveraging the capabilities of YOLOv8 renowned for its swift and precise target detection. Through rigorous evaluation, YOLOv8 demonstrated an exceptional accuracy rate exceeding 90%, accompanied by remarkable recall and F1 score values. Additionally, the model's performance was thoroughly assessed using mean Average Precision (mAP) at an Intersection over Union (IoU) threshold of 0.5, outperforming other models across all metrics. This research underscores the immense potential of YOLOv8 in the realm of fire image recognition, showcasing its practicality in real-time fire detection systems to fortify public safety and safeguard property.