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Sleep Detection for Drivers

This project is designed to help prevent road accidents caused by driver drowsiness, especially for Lagos drivers who often spend long hours in traffic and risk feeling sleepy behind the wheel.

The system continuously monitors the driver’s eyes using a webcam feed. By applying computer vision techniques, it can detect when the driver starts to close their eyes for too long , a key sign of drowsiness and then triggers an alarm to alert the driver before an accident happens.


How it Works

  • OpenCV → captures and processes real-time video from the webcam
  • MediaPipe Face Mesh → detects facial landmarks with high accuracy
  • Eye Aspect Ratio (EAR) logic → calculates the ratio between eye landmarks to determine if the eyes are closing
  • Alarm System → sounds an alert when EAR values suggest drowsiness

Why this Matters

Road safety is a huge concern, especially in places like Lagos where drivers endure long commutes. This project aims to reduce accidents caused by fatigue and promote safer driving by providing a simple yet effective early warning system.

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