Driver Drowsiness Detection and Accident Preventition

EasyChair Preprint 8563

Abstract

Due to tiredness, many accidents happen. It is currently one of the major causes of traffic accidents. According to recent statistics, intoxication plays a major role in many accidents. Numerous people are killed each year in sleepy driving-related car accidents. Drunk driving is a factor in more than 30 percent  of accidents. There is need for a technology that can identify tiredness and alert the life-saving driver to prevent this. The proposed system introduces a driver drowsiness programme in this project. In this instance, a webcam is continually watching the driver. The driver's face and eyes are the main subjects of this model's image processing methods. The algorithm isolates the driver's face and forecasts an eyeblink in the eye region. To check if driver is drowsy the system tracks and analyses the faces and eyes of drivers using an algorithm. The device sounds an alert to the driver when the blinking intensity is high.

Keyphrases: Accident Detection, Drowsiness Detection, Eye Aspect Ratio, SMS alert, face detection

@booklet{EasyChair:8563,
  author    = {C M Bhuvaneshwari and M V Pragna},
  title     = {Driver Drowsiness Detection and Accident Preventition},
  howpublished = {EasyChair Preprint 8563},
  year      = {EasyChair, 2022}}