A Real-Time AI-Powered Security System with Enhanced Security Monitoring

We all know that a face is a distinctive and essential component of their body that helps them be recognized. The suggested system detects and recognizes faces in pictures and video streams using the Face API. By training the model with a single or numerous photos of suspects, the system can accurately identify individuals in real time. The system's key features are face detection, feature extraction, and recognition, followed by an automated alert mechanism. Captured photos or video frames are examined, and the retrieved facial traits are compared to a pre-stored dataset. If a match is discovered that exceeds a predetermined accuracy threshold, authorities are contacted. Built with HTML, CSS, and JavaScript, the system has a user-friendly interface and integrates seamlessly with surveillance infrastructure. The modular architecture improves performance and enables scalability. Real-time processing and cloud-based support enhance detection efficiency and computing power. This paper gives a full implementation of the system, including its architecture and operating principles. This approach's effectiveness stems from its capacity to immediately identify possible threats and reduce crime rates by supporting law enforcement authorities with suspect identification.