Drowsiness detection system using eye aspect ratio technique

Sathasivam, Saravanaraj and Mahamad, Abd Kadir and Saon, Sharifah and Sidek, Azmi and Md Som, Mohamad and Ameen, Hussein Ali (2020) Drowsiness detection system using eye aspect ratio technique. In: 2020 IEEE Student Conference on Research and Development (SCOReD), 27-28 September 2020, Johor, Malaysia.

[img] Text
Restricted to Registered users only

Download (254kB) | Request a copy


Transportation is widely used to allow user travel conveniently from place to place, for a personal of official purpose. Travel during peak hour or holiday, expose the driver to traffic jam for several hour, thus cause the drive to feel drowsy easily due to high concentration and lack of rest. This situation contributes the increasing of the percentage of car incident due to car driver fatigue is the primary origin of the car accident. In this paper, image detection drowsiness system is proposed to detect the state of the car driver using Eye Aspect Ratio (EAR) technique. A developed system that occupied with the Pi camera, Raspberry Pi 4 and GPS module are used to detect and analyse continuously the state of eye closure in real time. This system able to recognize whether the driver is drowsy or not, with the initial, wearing spectacles, dim light and microsleep condition experimental conducted successfully give 90% of accuracy. This situation can increase the vigilant of drivers significantly.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Drowsy; car accident; eye aspect ratio; raspberry Pi 4; transportation
Subjects: T Technology > TJ Mechanical engineering and machinery > TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General)
Depositing User: Mr. Abdul Rahim Mat Radzuan
Date Deposited: 31 Jan 2022 06:52
Last Modified: 31 Jan 2022 06:52
URI: http://eprints.uthm.edu.my/id/eprint/6213

Actions (login required)

View Item View Item