Drowsy Driver Detection System

Abstract

Driver weariness is one of the key causes of road mishaps in the world. Detecting the drowsiness of the driver can be one of the surest ways of quantifying driver fatigue. In this project we aim to develop an archetype drowsiness detection system. This mechanism works by monitoring the eyes of the driver and sounding an alarm when he/she feels heavy eyed. The system so constructed is a non-intrusive real-time observing system. The primacy is on improving the safety of the driver. In this mechanism the eye blink of the driver is detected. If the driver’s eyes remain closed for more than a certain span of time, the driver is believed to be tired and an alarm is sounded. The programming for this is carried out in OpenCV using the Haar cascade library for the detection of facial features.