Driver Drowsiness and Fatigue Detection System : A Review


Authors : Asmita Manna; Aniket Mhalungekar; Sainath Pattewar; Pushpak Kaloge; Ruturaj Patil

Volume/Issue : Volume 7 - 2022, Issue 3 - March

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3tHdxSd

DOI : https://doi.org/10.5281/zenodo.6386614

Abstract : Driver drowsiness and fatigue detection is very important in today’s day. This systems reduces the road accident and ensures the vehicles as well as driver safety. In this paper, we reviewed various researches that help in drowsiness and fatigue detection. We used four categories of approach i.e researches involving machine learning, deep learning, computer vision technology and EEG. These researches have high accuracy and can be implemented in real time. The Experiments involve simulated driving environment and healthy subjects. Theyare monitored throughout the period of driving and thus drowsiness and fatigue is detected.

Driver drowsiness and fatigue detection is very important in today’s day. This systems reduces the road accident and ensures the vehicles as well as driver safety. In this paper, we reviewed various researches that help in drowsiness and fatigue detection. We used four categories of approach i.e researches involving machine learning, deep learning, computer vision technology and EEG. These researches have high accuracy and can be implemented in real time. The Experiments involve simulated driving environment and healthy subjects. Theyare monitored throughout the period of driving and thus drowsiness and fatigue is detected.

Video Explanation for Published paper

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