Machine Learning Software for the Detection of Violence from CCTV Live Footage

Abstract

Automated CCTV analytics have become a potent resource for boosting public safety. The software program, which has sophisticated video analytics capabilities, is introduced in this paper. The software program can instantly identify situations and notify concerned agencies such as the police and medical staff. Software processes video in three different ways: live streaming from external links, video uploaded from a computer, and real-time video from security cameras. Using past data for analysis, it scans CCTV feeds from public spaces for instances of violent crime, theft, burglary, and other crimes. The software’s key features are real-time CCTV stream analysis, alarm and report generating and database updating for prompt response by the nearest police station. This software has the potential to significantly improve public safety measures by enabling proactive incident detection and real-time response, which will improve law enforcement operations. The software Program boasts key features such as real-time CCTV stream analysis, the instantaneous generation of alarms and reports, and seamless database updates accessible to the nearest police station for immediate response. This software's potential to significantly enhance public safety measures lies in its capacity to enable proactive incident detection and real-time responses, promising to optimize law enforcement operations and overall security.