Advancing Crowd Management through Innovative Surveillance using YOLOv8 and ByteTrack

Crowd management is a cumbersome task that requires broad analysis and grasp of various constraints. The main hurdles include security issues, unexpected crowd dynamics over which there is typically minimal or no control, limited infrastructure to accommodate. This paper suggests a model that is custom trained to enhance people detection in crowd and monitor crowd density as well as tracking people in a video frame. The paper proposes using YOLOv8 which is known for its capabilities as a fast single shot detector and for being extremely customizable combined with ByteTrack, an advanced model that specializes in tracking people in crowded or congested areas. Together, the models help create a powerful system that can accurately locate and follow people in dense groups, therefore revolutionizes traditional approaches to crowd management. The people counting system also helps with crowd control by indicating how many people are in a certain area. In addition to addressing the issues associated with congested areas, this system provides trustworthy means of tracking people in a variety of scenarios, hence enhancing public safety and security. ByteTrack, CrowdHuman, Crowd Management, YOLOv8