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@article{176399,
        author = {Mohd Rahamath and Raghu Ram Vara and Bhojeshwar Jamre and Veer Kumar},
        title = {Automated Entry Management with Suspicious Person Tracking},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {7111-7118},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176399},
        abstract = {This paper describes an adaptive and smart face recognition system for entry control and real-time suspicious individual tracking. The system classifies individuals as authorized users, unfamiliar visitors, or blacklisted individuals based on ArcFace with cosine similarity for secure facial verification, with 93% real-time precision. Coupled with FastAPI and a Streamlit dashboard, the solution provides SHA-256 encrypted admin authentication, UUID-based email/SMS notification, and real-time behavioral anomaly detection. Tests show 90% unauthorized entry prevention. The system is suitable for high-traffic environments like residential compounds and commercial spaces, enhancing operational efficiency and minimizing manual intervention.},
        keywords = {Facial Recognition, ArcFace, Anomaly Detection, FastAPI, Entry Management, Streamlit, Real-Time Security.},
        month = {April},
        }