Detection of Criminal Activity Using Deep Learning

The surge in criminal activities presents a formidable challenge for global law enforcement agencies. Traditional crime detection methods often struggle to address the intricate and varied nature of criminal behaviors. Many businesses deploy CCTV systems for continuous observation of people and their activities. The developed system exhibits significant potential for applications in public safety, surveillance, and law enforcement, serving as an intelligent and automated tool for early detection and prevention of criminal activities. Continuous human monitoring of data is nearly impossible due to the workforce and attention required. Automation becomes essential. The project proposed utilizes the deep learning technology, a CNN model is designed to identify harmful behaviour in the videos. To expedite the identification of abnormal events, it is crucial to automate this process, indicating which frame and segment contain the unusual activity. This involves dividing the video into frames and scrutinizing the people and activities in each processed frame. When it detects criminal activity, it can trigger alerts or notifications to the personnel, allowing them to respond promptly.