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@article{201653,
        author = {Usha k and Sindhu G and Prabhakar Reddy and Sushmita Vishwakarma},
        title = {Pravesha AI: Face-Based Bus Entry Authentication},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {5100-5106},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201653},
        abstract = {Educational institutions increasingly require secure and efficient transportation monitoring systems to improve student safety and operational management. Conventional bus entry methods based on identity cards, manual attendance, and physical verification consume time and are vulnerable to unauthorized access and human error. This paper presents Pravesha AI, a real-time facial recognition–based authentication system developed for automated student bus entry verification. The proposed system captures live facial images using a webcam, extracts facial encodings, and compares them with registered student records stored in a centralized database. The implementation uses Python, Flask, OpenCV, face_recognition, SQLAlchemy, and SQLite to achieve secure and contactless authentication without depending on expensive biometric hardware. The system also records authentication logs with timestamps for monitoring and auditing purposes. Experimental evaluation demonstrates that the proposed solution offers fast response time, improved accuracy, reduced manual effort, and enhanced transportation security for educational institutions.},
        keywords = {},
        month = {May},
        }