Driver Drowsiness Detection Using Facial Landmarks: A Comprehensive Survey on Techniques, Algorithms, and Applications

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Sarita Kumari, Harsha K, Kehkeshan Jallal S, Kusumika Krori Dutta, Mohammad Hashim

Abstract

Driver fatigue and drowsiness are one of the leading causes of traffic accidents worldwide, which emphasises the importance of developing reliable and non-intrusive sleepiness detection technologies. To maintain safety, transport vehicle drivers need to be aware of the warning symptoms of fatigue, particularly while driving long distances at night. Detecting drowsiness is a simple task for human observers, but it remains a challenging task for computers. This paper examines several methods for detecting driver fatigue using facial landmarks, emphasizing the latest technological developments. The suggested system combines Python, SASS, Golang, and other technologies to offer a platform-neutral, device-independent solution. The technology can identify indicators of tiredness and notify the driver by letting the camera operate in the background, possibly averting deadly collisions with an accuracy of 97.3%.

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