Drowsiness detection system using eye aspect ratio technique

• Main Authors: Sathasivam, Saravanaraj, Mahamad, Abd Kadir, Saon, Sharifah, Sidek, Azmi, Md Som, Mohamad, Ameen, Hussein Ali
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General)
• Online Access: http://eprints.uthm.edu.my/6213/1/P12435_2620b964aaacf2ca87e9e354da02cbcc.pdf; http://eprints.uthm.edu.my/6213/

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.