Accident Detection in Surveillance Camera

Road accidents are a major cause of death, and many victims die as a result of not reporting such events to the appropriate authorities. Because the event was not reported, there is a lack of emergency medical assistance, which leads to deaths. A computer vision-based traffic observing and revealing strategy can help with giving health related crises continuously, perhaps saving many individuals. Conventional traffic systems, which are outfitted with IP cameras and sensors, are currently set up all around the city to supervise and control traffic. In this paper, we present a better traffic checking framework that perceives and distinguishes moving items like vehicles, cruisers, etc. in live camera, takes care of, identifies accidents of these moving articles, and promptly sends crisis admonitions to the fitting authorities. An innovative architecture for detecting road accidents is given in this paper. The suggested framework uses YOLO to locate accurate objects, followed by accident detection for surveillance data. The nearest police station is notified of the observed accident. On commonplace street traffic CCTV reconnaissance film, the proposed framework gives a reliable procedure to accomplish a high Detection Rate and a low False Alarm Rate.