
بإشراف: Dr. Syed Sohail Ahmed
Our project explores the development of an AI-powered suspicious activity tracking camera system, designed to enhance physical access control in high-security environments. Leveraging facial recognition technology, the system integrates AI algorithms and edge computing on a Raspberry Pi platform. It captures facial images via a surveillance camera, processes them using TensorFlow Lite, and compares the data with a pre-existing database of authorized individuals. Access is granted or denied based on the identification results, automating security operations and reducing reliance on manual processes.