Automated Driver Drowsiness Monitoring System

Authors

  • Dr. B. Saroja Ph. D Professor& Head of Department, Siddartha Institute of Science and Technology, India Author
  • Addula Madhukar Reddy Department of ECE, Siddartha Institute of Science and Technology, India Author
  • S. Jyoshna Department of ECE, Siddartha Institute of Science and Technology, India Author
  • D. Jaya Sree Department of ECE, Siddartha Institute of Science and Technology, India Author
  • K.A. Mohamed Farook Department of ECE, Siddartha Institute of Science and Technology, India Author
  • J. Madhu Teja Department of ECE, Siddartha Institute of Science and Technology, India Author

DOI:

https://doi.org/10.47392/IRJAEM.2024.0199

Keywords:

Web Camera, Accident Alert, Raspberry Pi

Abstract

This presentation introduces an innovative end-to-end non-intrusive IoT-based automated frame work designed for logistic and public transport applications, aiming to address the exponential growth in road accidents. Leveraging behaviour analysis-based approaches and computer vision techniques, the framework detects and monitors driver behaviours such as drowsiness, sleeping, yawning, and distractions. Comprising embedded systems, edge computing, cloud modules, and a mobile app, the solution ensures real-time monitoring and evaluation. With a focus on minimizing latency and enhancing accuracy, the framework achieves a remarkable 96% overall accuracy in experimental testing. This comprehensive solution offers heightened road safety through its robust, portable, and user-friendly design, making it a valuable tool for proactive driver behaviour management.

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Published

2024-05-18