Project Description

The Drowsiness Detection System is an innovative machine learning project designed to enhance road safety by monitoring and detecting driver fatigue in real time. Utilizing a camera to capture high-resolution images of the driver's face, the system employs advanced computer vision techniques to identify and analyze facial landmarks, focusing on eye movements and blink duration.

By evaluating key indicators such as prolonged eye closure, slow blink rates, and head tilting, the system can accurately assess the driver's level of alertness. When signs of drowsiness are detected, it triggers immediate alerts—such as visual notifications or audible alarms—to warn the driver, helping to prevent potential accidents caused by fatigue.

Implemented with tools like OpenCV and Python, this system not only showcases the power of machine learning but also represents a crucial step toward improving safety on our roads by addressing the significant risks associated with drowsy driving.