A REVIEW ON SMART DRIVER MONITORING SYSTEM

Authors

  • Aaditya Aradhye UG Student, Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering, Pandharpur, India. Author
  • Sanket Badave UG Student, Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering, Pandharpur, India. Author
  • Vishant Bagewadikar UG Student, Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering, Pandharpur, India. Author
  • Dr. A. O. Mulani Associate Professor, Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering, Pandharpur, India. Author
  • Ms. T. B. Kadam Technical Assistant, Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering, Pandharpur, India. Author

Keywords:

Driver Monitoring System, Drowsiness Detection, Raspberry Pi, OpenCV, IoT, Real Time Monitoring.

Abstract

Road accidents caused by driver drowsiness and distraction are a serious safety issue. Existing systems mainly use basic eye detection, which is often inaccurate and cannot detect behaviors like yawning, head movement, or mobile usage. They also lack real-time monitoring and smart alert features. This project proposes a Smart Driver Monitoring System using Raspberry Pi, computer vision, and IoT. A USB webcam captures real-time video of the driver, and techniques using OpenCV and MediaPipe/Dlib analyze facial features such as eyes, mouth, and head position to detect drowsiness and distraction. When unsafe behavior is detected, the system generates alerts and can slow down or stop the vehicle for safety. It also provides live monitoring through a web based dashboard.

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Published

08-10-2026

How to Cite

A REVIEW ON SMART DRIVER MONITORING SYSTEM. (2026). International Journal of Mechanical Engineering Research and Technology , 18(4), 346-380. https://ijmert.com/index.php/ijmert/article/view/308