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@article{178733,
        author = {Matheshwaran M and Matheshwaran M and Makeshwar K and Sahul hameed muhammed S and Dr.A.Vinvent Antony Kuma},
        title = {AI-INTEGRATED BIOMETRIC ATTENDANCE AND HEALTH MONITORING SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {5887-5892},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178733},
        abstract = {This AI-powered biometric system seamlessly integrates fingerprint recognition for attendance management with infrared temperature monitoring and pressure-based stress detection to provide a comprehensive view of individual wellness. The system utilizes machine learning to analyze health data patterns, including temperature fluctuations, pressure levels, and stress indicators, to deliver personalized insights into each user's health status. It not only simplifies attendance tracking but also enhances proactive health monitoring by detecting potential issues like stress and fever early on. The system is particularly valuable in environments such as schools, corporate offices, and hospitals, ensuring continuous and accurate monitoring of both attendance and health. By providing real-time alerts for abnormal temperature or stress levels, the system fosters a safer and more supportive environment for everyone. Its ability to offer both attendance tracking and health assessments makes it an ideal solution for creating a healthier, more efficient workplace or institution.},
        keywords = {Attendance management, Biometric, Temperature prediction, Stress prediction and health monitoring},
        month = {May},
        }