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@article{193375,
        author = {Bishwa Ranjan Behera},
        title = {Face Recognition Based Smart Attendance System for Classroom Monitoring},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {150-154},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=193375},
        abstract = {This paper presents a real-time face recognition-based attendance system designed for classroom environments. The proposed system uses a standard USB webcam or IP-based CCTV camera to capture live video of students, and employs OpenCV for face detection together with a facial-embedding based face recognition library to identify individual students in the frame. A small dataset of registered students is collected in advance, from which facial encodings are extracted and stored locally. During a session, the system detects faces in each frame, compares them with the known encodings, and automatically marks attendance for recognized students in a CSV file along with timestamp information, ensuring that each student is logged only once per session. The implementation is prototyped on a low-cost platform using Python and Raspberry Pi / personal computer hardware, making it suitable for resource-constrained educational settings. Experimental tests in a single-classroom scenario demonstrate that the system can operate in real time and achieve reliable recognition under reasonable lighting and camera placement. Limitations under poor lighting, occlusions, and increased class size are discussed, along with future integration using RTSP streams from CCTV cameras and central database connectivity.},
        keywords = {Attendance system, Face recognition, Raspberry Pi, OpenCV, Computer vision, Classroom automation.},
        month = {March},
        }