SENTINEL GUARD: A FATIGUE DETECTION SYSTEM WITH MULTI-CHANNEL ALERT INTEGRATION
Dr.P.D.R.Vijayakumar,M.E.,Ph.D., A.ArockiaSelvaraj,M.E., A.Shivani, S.SilversterStalin, R.VishnuPriya.
Dr.P.D.R.Vijayakumar HOD-CSE & INFO INSTITUTE OF ENGINEERING, COIMBATORE
A.Arockiaselvaraj AP- IT & INFO INSTITUTE OF ENGINEERING, COIMBATORE
A.Shivani BE CSE & INFO INSTITUTE OF ENGINEERING, COIMBATORE
S.Silversterstalin BE CSE & INFO INSTITUTE OF ENGINEERING, COIMBATORE
R.Vishnupriya BE CSE & INFO INSTITUTE OF ENGINEERING, COIMBATORE
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Abstract - The fatigue detection system is a critical application aimed at enhancing safety in various domains by addressing the risks associated with drowsiness related incidents. Leveraging advanced technologies such as machine learning, computer vision, and real-time communication, the system offers a comprehensive solution for monitoring and alerting users to signs of fatigue in real-time. Through the integration of pre-trained models, such as the shape_predictor_68_face_landmarks.dat, the system accurately detects facial landmarks and tracks eye movements, enabling the identification of drowsiness indicators. Upon detection, the system generates alerts via email and WhatsApp, accompanied by audible alarm buzzers to prompt immediate user intervention. The inclusion of live location information in alerts provides additional context, facilitating timely assistance and support. Furthermore, the system's architecture allows for future enhancements, including the integration of multi-sensor data fusion techniques and collaboration with industry stakeholders to promote standardized protocols and widespread adoption. Overall, the fatigue detection system represents a significant step towards mitigating the risks of drowsinessrelated accidents and improving safety across various applications
Key Words: Fatigue detection, Machine learning, CNN, Real time alerts, Facial Expression analysis, Open CV
