UNCANNY ACTIVITY DETECTION USING CCTV MONITORING

“Uncanny Activity Detection Using CCTV Monitoring” introduces an innovative approach to support public safety through the integration of Machine Learning (ML) in real-time monitoring. In the contemporary world, Closed-Circuit Television (CCTV) surveillance stands as a fundamental and highly effective security measure for various premises, including hospitals, malls, and universities. It serves as a widely recognized tool for preventing and detecting unwanted activities. However, envisioning an public space equipped with several CCTV cameras across multiple buildings presents a logistical challenge. The manual monitoring of events across this expansive network is practically impossible. Furthermore, searching for a specific event in recorded video footage, even after it has occurred, proves to be a time-consuming endeavor. This project addresses the need for an efficient solution to manage and analyze extensive CCTV footage in complex environments, optimizing security practices and response times.