Real time violence detection system

The Real-Time Violence Detection System is an AI-powered web application designed for real-time security monitoring. Using advanced deep learning models, it continuously analyzes video feeds to detect violent activities and immediately sends alerts to the recent contacts for personal usage (like in mobiles) and nearest authorities. This system can be deployed in correctional facilities to enhance security and safety and in public spaces, workplaces, and homes also. It can monitor surveillance cameras to detect violent incidents among inmates and alert prison staff in real time. Additionally, by autometic survailance it aids in maintaining compliance with safety regulations and reducing risks for both inmates and guards.

The real-time violence detection system was built from scratch using Deep Learning, OpenCV, Flask, and the Twilio API to ensure fast and accurate detection of violent activities. A deep learning model was trained on video datasets to recognize patterns of violence, and OpenCV was used to process live video feeds from surveillance cameras. The Flask framework was implemented to create a web-based interface for real-time monitoring, while Twilio was integrated to send instant SMS alerts to emergency contacts and law enforcement when violence is detected. This system is particularly effective in high-risk areas such as prisons, where it can automatically identify violent incidents among inmates and notify authorities for immediate intervention, enhancing security and preventing escalation.

Real time violence detection system

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