Driver Drowsiness Alert System with Effective Feature Extraction

Authors

  • Ashlesha Singh
  • Chandrakant Chandewar
  • Pranav Pattarkine

Keywords:

Drowsiness Detection, Eye Detection, Face Detection, Facial Landmarks, OpenCv

Abstract

Driver drowsiness is one of the major factor for road accidents. Around 20% of accidents are caused due to drowsy drivers. That’s why a driver alert system is the need of the hour. The prime purpose of this system is to detect the driver fatigue and alert the driver. This is done by obtaining frames of the driver's face, captured by the camera attached in the car. The eyes and mouth of the driver are detected and the closure of the eyes and wide opening of the mouth, after the threshold value is surpassed the driver is alert Raspberry pi is the CPU of the system with all the programming in python. A manual ON/OFF is also provided in case the car is in stationery position. The system works irrespective of the color or shape of the face. The ignition of the car doesn’t go off when the system alerts to avoid further accidents on highways, etc. Thus this system will definitely reduce the number of accidents caused due to driver drowsiness alerting the driver in real time.

Author Biographies

Ashlesha Singh

Electronics and Communication, RCOEM, Maharashtra, India

Chandrakant Chandewar

Electronics and Communication, RCOEM, Maharashtra, India

Pranav Pattarkine

Electronics and Communication, RCOEM, Maharashtra, India

Downloads

Published

30.04.2018

How to Cite

[1]
Ashlesha Singh, Chandrakant Chandewar, and Pranav Pattarkine, “Driver Drowsiness Alert System with Effective Feature Extraction”, IJREST, vol. 5, no. 4, Apr. 2018.

Issue

Section

Articles