A driver drowsiness detection system is a technology that monitors a driver's state and alerts them when signs of drowsiness or fatigue are detected. The system typically uses sensors or cameras to track the driver's facial movements, eye blinks, and head position, and applies machine learning or deep learning algorithms to analyze the data and classify the driver's state as awake or drowsy.
The system's main objective is to enhance road safety and prevent accidents caused by driver fatigue. The technology has applications in a range of settings, including commercial vehicles, public transportation, and personal vehicles.
The tech stack used in this project includes:
- Python as the programming language
- OpenCV for image and video processing tasks
- Dlib for face detection and facial landmark recognition
- imutils for image processing
- NumPy for numerical operations on arrays
- pygame for playing the alert sounds
- threading for multi-threading in the alarm function
- scipy for calculating the distance between points
Some Outputs:
