Abstract: 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.

Raz Amzar Fahimi Rozali, Suzi Iryanti Fadilah, Azizul Rahman Mohd Shariff, Khuzairi Mohd Zaini, Fatima Karim, Mohd Helmy Abd Wahab, Rajan Thangaveloo and Abdul Samad Bin Shibghatullah, “Driver Drowsiness Detection and Monitoring System (DDDMS)” International Journal of Advanced Computer Science and Applications(IJACSA), 13(6), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130691

@article{Rozali2022,
title = {Driver Drowsiness Detection and Monitoring System (DDDMS)},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130691},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130691},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {6},
author = {Raz Amzar Fahimi Rozali and Suzi Iryanti Fadilah and Azizul Rahman Mohd Shariff and Khuzairi Mohd Zaini and Fatima Karim and Mohd Helmy Abd Wahab and Rajan Thangaveloo and Abdul Samad Bin Shibghatullah}
}