A real-time driver safety monitoring system designed to detect driver drowsiness and inattentiveness using live camera input.
The system helps prevent road accidents by identifying signs of fatigue and triggering alerts when unsafe conditions are detected.
Driver fatigue is one of the leading causes of road accidents worldwide.
This project focuses on improving road safety by continuously monitoring the driver’s facial features through a camera feed and detecting alertness levels in real time.
When signs of drowsiness or inattention are detected, the system immediately raises alerts to warn the driver.
This solution is suitable for:
- Road safety systems
- Smart vehicle monitoring
- Fleet & transport safety
- Driver assistance applications
- 🎥 Live Camera Monitoring
- 👁️ Eye Blink & Facial Feature Detection
- 😴 Drowsiness Detection
- 🚨 Real-Time Alert System (Beep / Warning)
- 📊 Continuous Monitoring & Analysis
- ⚡ Lightweight & Real-Time Performance
- Python
- OpenCV (Computer Vision)
- NumPy
- Dlib / Haar Cascade (Facial Detection)
- Webcam / Camera Integration
- Alert & Logic Handling
- The system captures live video from the camera.
- Facial landmarks (eyes, face) are detected frame by frame.
- Eye movement and blinking patterns are analyzed.
- If prolonged eye closure or inattentiveness is detected:
- A warning alert is triggered
- The driver is notified immediately
- Monitoring continues in real time.
- Smart vehicle safety systems
- Accident prevention solutions
- Transport & logistics monitoring
- Research & academic projects
- AI-based driver assistance systems
- Mobile notification support
- AI-based behavior analysis
- Integration with vehicle systems
- Cloud-based monitoring dashboard
Gowtham K
Cyber Security & AI Project Developer
Focused on real-world problem solving using AI, automation, and data-driven systems.
📬 Feel free to connect or explore my other projects!