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Ani-sha23 / repository
AI-powered Driver Drowsiness & Distraction Detection System leveraging Computer Vision and Deep Learning to intelligently monitor eye movement, yawning, fatigue, and driver attention in real time for smarter and safer roads.
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A real-time AI-based system that detects driver drowsiness and distraction using computer vision and deep learning.
This system helps prevent road accidents by monitoring eye movement, blinking rate, yawning, and head orientation.
Driver fatigue and distraction are among the leading causes of road accidents worldwide.
This project uses a webcam and deep learning models to continuously monitor the driver and trigger alerts when signs of fatigue or distraction are detected.
The system works in real-time and can be deployed in cars, simulators, or monitoring systems.
✔ Real-time face detection
✔ Eye blink detection
✔ Yawning detection
✔ Head pose tracking
✔ Drowsiness scoring system
✔ Distraction detection (looking away)
✔ Alarm alert system
✔ Lightweight and fast
| Technology | Purpose |
|---|---|
| Python | Core programming |
| OpenCV | Video processing |
| Dlib | Face & landmark detection |
| TensorFlow / Keras | Deep learning |
| NumPy | Numerical operations |
| SciPy | Eye aspect ratio |
| PyGame | Alarm sound |