Student Mobile Usage Detection and Fine Notification System in Restricted Areas Using Deep Learning Techniques
D.N.V.S.L.S. Indira, Abdul Yaseen, Choppara Sai Venkat, Dasari Supriya, Chaluvadi Udayini · 2024
The Student Mobile Usage Detection and Fine Notification System in Restricted areas using Deep Learning Techniques is an innovative project that harnesses the capabilities of deep learning to enforce security and compliance within restricted zones. In an era where mobile devices are ubiquitous, ensuring the sanctity of secure areas is of paramount importance, and this system provides an intelligent and proactive solution. Utilizing cutting-edge deep learning algorithms, neural networks, and computer vision technologies, this project actively monitors and detects unauthorized mobile device usage within designated restricted areas. Beyond mere detection, it captures real-time images of individuals and employs facial recognition to ascertain their identity. Upon successful identification of an individual using a mobile device in violation of the restricted zone, the system automatically sends a notification to the respective Hod or academic coordinator. This notification includes the individual's name (or) id with the fine of 1000 rupees and proof of an image. Key features of this system include adaptability to diverse environments, robustness against false alarms, and seamless integration with existing security infrastructure. By implementing deep learning technology, this project offers a forward-thinking approach to security enforcement. It not only deters unauthorized mobile device usage but also ensures swift accountability through the imposition of a fine.