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The persistent concern of road safety is to be addressed by introducing a cost-effective and robust model for the detection of drowsiness and yawning while driving on the road. Utilizing the ArduCam camera modules, the system constantly records facial benchmarks to analyze the eye aspect ratio (EAR). In the event of calculated EAR values falling below or exceeding the defined threshold range, indicating driver drowsiness or wakefulness, the system issues timely alerts through a speaker. The scope of this work extends to capturing drivers’ images in challenging conditions, optimizing emergency response by sending messages to authorities, and implementing a personalized alert system. The ultimate goal is to significantly reduce road accidents and contribute to enhance road safety.

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Design and Implementation of a Framework for the Detection and Prevention of Drowsiness and Yawning During Driving

  • 会议论文

  • 发表日期：

    2025年

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  • Parth Thakkar,
  • Mohammed Kaif Shaikh,
  • Harsh Sanghavi,
  • Dhruv Shah,
  • Vinodray Thumar,
  • Jaimin Shroff

摘要

The persistent concern of road safety is to be addressed by introducing a cost-effective and robust model for the detection of drowsiness and yawning while driving on the road. Utilizing the ArduCam camera modules, the system constantly records facial benchmarks to analyze the eye aspect ratio (EAR). In the event of calculated EAR values falling below or exceeding the defined threshold range, indicating driver drowsiness or wakefulness, the system issues timely alerts through a speaker. The scope of this work extends to capturing drivers’ images in challenging conditions, optimizing emergency response by sending messages to authorities, and implementing a personalized alert system. The ultimate goal is to significantly reduce road accidents and contribute to enhance road safety.