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Driver Drowsiness Detection System

Author(s):

Paritosh Fuse , Shri Ramdeobaba College of Engineering and Management; B. V. Rohit, Shri Ramdeobaba College of Engineering and Management; Manoj Pothuri, Shri Ramdeobaba College of Engineering and Management; Ashok Sharma, Shri Ramdeobaba College of Engineering and Management

Keywords:

Driver Drowsiness Detection, Road Accidents, OpenCV, Facial landmarks, Raspberry Pi

Abstract

Injuries in road accidents are globally recognized as a major public health problem. Road accidents are one of the largest causes of deaths, disabilities and hospitalization. Distracted drivers are prone to severe car accidents. Distraction can be caused by driving under the influence of alcohol, exhaustion due to continuous driving etc. This paper proposes a vision-based system to monitor drivers eyes and to detect driver drowsiness in real-time. If the driver appears to be heavy-eyed, an alarm is played to alert the driver. As an additional feature when the driver is found to be drowsy, the system will send a message to the IoT server informing about drivers status. Our system attained above 85% accuracy for all tested scenarios.

Other Details

Paper ID: IJSRDV7I10917
Published in: Volume : 7, Issue : 1
Publication Date: 01/04/2019
Page(s): 1457-1461

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