Fatigue Detection System Based on Eye Blinks of Drivers
A.Aravind1, Aditya Agarwal2, Ayush Jaiswal3, Ayush Panjiyara4, Mallikarjun Shastry P M5
1AAravind, School of C&IT REVA University, Bangalore (Karnataka), India.
2Aditya Agarwal, School of C&IT REVA University, Bangalore, India.
3Ayush Jaiswal, School of C&IT REVA University, Bangalore (Karnataka), India.
4Ayush Panjiyara, School of C&IT REVA University, Bangalore (Karnataka), India.
5Mallikarjun Shastry PM, School of C&IT REVA University, Bangalore (Karnataka), India.
Manuscript received on 04 June 2019 | Revised Manuscript received on 12 June 2019 | Manuscript Published on 29 June 2019 | PP: 72-75 | Volume-8 Issue-5S, May 2019 | Retrieval Number: E10150585S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In recent years, road accidents have increased significantly. One of the major reasons for the accidents as reported is driver fatigue. Therefore, there is a need for a system to measure the fatigue level of the driver and alert the driver when he/she feels drowsy to avoid accidents. So, in this paper we propose a system which comprises of a camera installed in the car dashboard. It will continuously monitor the blink pattern of driver and detect whether he is feeling drowsy or not. If the system finds the driver is feeling drowsy then an alert will be generated to avoid accident. This project attempts to contribute towards the exercise of analyzing driver behavior-based Eye Aspect Ratio (EAR) in order to reduce preventable road accidents.
Keywords: Blink Pattern, Camera, Car Dashboard, Driver Fatigue, Drowsy, Eye Aspect Ratio (EAR).
Scope of the Article: Software & System Security