Drowsy driver detection system - via facial recognition and driving data / Nur Iman Kamila Azharudin, Hafizah Mansor and Shaila Sharmin

According to the National Highway Traffic Safety Administration, an estimated 17.6% of all fatal crashes in the years 2017–2021 involved a drowsy driver. This study proposes a drowsy driver detection system that uses both facial recognition and vehicular data to detect if a driver is feeling sleepy...

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Bibliographic Details
Main Authors: Azharudin, Nur Iman Kamila, Mansor, Hafizah, Sharmin, Shaila
Format: Article
Language:English
Published: Universiti Teknologi MARA Press (Penerbit UiTM) 2024
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/105182/1/105182.pdf
https://ir.uitm.edu.my/id/eprint/105182/
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