- We are developing a driver detection system that alerts when it detects drowsiness signs to prevent drowsiness-related accidents.
- The system uses a camera and a real-time face and eye tracking algorithm (MediaPipe) running on a Raspberry Pi 5 to monitor the driver’s face activity.
- The main goal behind our project is to enhance road safety by offering an affordable, offline solution that reduces accidents caused by drowsy driving.
- Unlike detection systems in expensive high-end cars, our solution is
affordable,standalone, worksoffline, and can be installed in any vehicle, making it more accessible to a broader audience.
Implementation Details
Our solution uses a camera connected to a Raspberry Pi 5 to monitor the driver’s facial features in real-time. We utilize MediaPipe to detect three key signs of drowsiness: closed eyes, yawning, and looking away, by analyzing facial landmarks. OpenCV is used for image processing and frame handling. A GPS module is integrated to enable Auto mode, where detection activates automatically when the vehicle speed reaches 20 km/h or higher. When signs of drowsiness are detected, the system plays a progressive audio alert through a speaker to immediately warn the driver.
What Makes Our Solution Unique
Unlike existing systems in luxury vehicles, our approach is affordable, works offline, and can be installed in any vehicle. This makes it more accessible to everyday drivers.
Target Audience
We aim to serve drivers looking for a cost-effective way to improve road safety without needing high-end features found in premium cars.
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