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@article{177851,
        author = {Kamalakar L and Maheswaran T and Dinesh M and Guhan S and Mohammed Abdulla},
        title = {Real Time Face Recognition Security System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {3330-3333},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177851},
        abstract = {This project presents a real-time smart door unlocking system using facial recognition and keypad-based authentication, powered by a Raspberry Pi 3B. The system integrates a USB camera, solenoid lock, 4x4 keypad, and PIR motion sensor to enhance security and usability. Facial recognition is implemented using OpenCV and pre-trained models, allowing contactless user verification. A secure passcode serves as a backup authentication method. A web-based interface built with Ruby on Rails enables remote access monitoring and logging of entry attempts. The system ensures minimal response delay, reliable performance under various lighting conditions, and low power consumption. Designed for small-scale environments, it offers a scalable and efficient alternative to commercial smart locks by combining machine learning, IoT, and embedded systems.},
        keywords = {Facial Recognition, Raspberry pi, Keypad Authentication, IoT Monitoring.},
        month = {May},
        }