Vision based Accident Detection System Using AI ML and Yolov8 Algorithms

Abstract

There is a real danger of accidental discovery of safety and order. In this paper, we propose the use of YOLOv8 for accident-based vision, with embedded insights and machine learning State-of-the-art Acknowledgment Question Our algorithm communicates real-time flight video from the active camera to identify them accurately Classified and Accident. We demonstrate a comprehensive approach to improve YOLOv8 performance using data sets annotated with crash images. Through comparative analysis with existing methods, we confirm the uniqueness of our vision-based algorithm in terms of speed, accuracy, and performance. Our insights help improve accident management, provide appropriate planning to improve road safety, and potentially reduce the impact of accidents on the road. Index Terms— Road Accidents, Accident Detection, Computer Vision, Machine Learning, Deep Learning, CNN Classifier, Real- time Detection, Emergency Alerting, Intelligent Transportation Systems.