Drowsiness Detection using Computer Vision

The proposed system aims to enhance transportation safety by reducing the number of accidents caused by driver fatigue and drowsiness, which have become increasingly common. The system analyzes facial and bodily gestures such as eye tiredness and yawning to identify signs of drowsiness and fatigue. Eye aspect ratio (EAR) is used to detect drowsiness by measuring the ratio of distances between horizontal and vertical eye landmarks. Yawn detection is performed by calculating a YAWN value based on the distance between the upper and lower lips and comparing it to a threshold value. The system incorporates an eSpeak module, a text-to-speech synthesizer, to provide appropriate voice alerts when drowsiness or yawning is detected. The ultimate goal of the proposed system is to reduce the number of fatalities resulting from road accidents and contribute to technology advancements.