Driver Drowsiness Detection and Monitoring System (DDDMS)

• Main Authors: Raz Amzar, Fahimi Rozali, Suzi Iryanti, Fadilah, Azizul Rahman, Mohd Shariff, Khuzairi, Mohd Zaini, Fatima, Karim, Mohd Helmy, Abd Wahab, Rajan, Thangaveloo, Abdul Samad, Shibghatullah
• Format: Article
• Language: English
• Published: The Science and Information (SAI) Organization Limited 2022
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://ir.unimas.my/id/eprint/39643/1/Driver%20Drowsiness.pdf; http://ir.unimas.my/id/eprint/39643/; https://thesai.org/Publications/ViewPaper?Volume=13&Issue=6&Code=IJACSA&SerialNo=91

—The purpose of this paper is to develop a driver drowsiness and monitoring system that could act as an assistant to the driver during the driving process. The system is aimed at reducing fatal crashes caused by driver’s drowsiness and distraction. For drowsiness, the system operates by analysing eye blinks and yawn frequency of the driver while for distraction, the system works based on the head pose estimation and eye tracking. The alarm will be triggered if any of these conditions occur. Main part of the implementation of this system will be using python with computer vision, while Raspberry Pi, which is uniquely designed, for the hardware platform and the speaker for alarming. In short, this driver drowsiness monitoring system can always monitor drivers so as to avoid accidents in real time.