A NEW INTELLIGENT DRIVER VIGILANCE SYSTEM DESIGN USING TILT SENSORS

A significant number of causes for people killed by automobile accidents on both public and interior roads are the driver's failure to pay attention to the roadway, as well as other factors such as tiredness, sleep during driving, using the phone, or even the driver being intoxicated, etc. This work aims to identify sleepy status, pinpoint the onset of sleep, and alert the driver when their level of alertness drops below a level that does not improve productivity or the vehicle's overall safety protocols to prevent drowsiness-related crashes. In this article, we present a new method for implementing drowsiness detection inexpensively, using a Raspberry Pi as a central processor board that connects all practical measurement components. In addition, the proposed method includes the following activities: tracking the driver's head vibration while driving using tilt sensors. Moreover, a camera was mounted in front of the driver to take photos and record videos of the driver's health. As a result, the results were entirely satisfactory, and if the driver was operating the vehicle while fatigued, the response was 95% reliable and fast.

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Publication Details

Journal
Kufa Journal of Engineering
Published
2025-02-04
DOI
https://doi.org/10.30572/2018/kje/160103
Citations
1
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.68
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article

A NEW INTELLIGENT DRIVER VIGILANCE SYSTEM DESIGN USING TILT SENSORS

Mahmood F. Mosleh, Abbas Ali Diwan, Hazeem B. Taher, Faiz Arith et al.
1 citations
Kufa Journal of Engineering
Autonomous Vehicle Technology and Safety
0.68
article

A NEW INTELLIGENT DRIVER VIGILANCE SYSTEM DESIGN USING TILT SENSORS

Mahmood F. Mosleh, Abbas Ali Diwan, Hazeem B. Taher, Faiz Arith, Karrar Shakir Muttair, Ali Z. Ghazi Zahid, Oras Ahmed Shareef, Ahmed Mahmood Farhan, Raed Hameed Chyad Alfilh
article en
1 citations

Abstract

A significant number of causes for people killed by automobile accidents on both public and interior roads are the driver's failure to pay attention to the roadway, as well as other factors such as tiredness, sleep during driving, using the phone, or even the driver being intoxicated, etc. This work aims to identify sleepy status, pinpoint the onset of sleep, and alert the driver when their level of alertness drops below a level that does not improve productivity or the vehicle's overall safety protocols to prevent drowsiness-related crashes. In this article, we present a new method for implementing drowsiness detection inexpensively, using a Raspberry Pi as a central processor board that connects all practical measurement components. In addition, the proposed method includes the following activities: tracking the driver's head vibration while driving using tilt sensors. Moreover, a camera was mounted in front of the driver to take photos and record videos of the driver's health. As a result, the results were entirely satisfactory, and if the driver was operating the vehicle while fatigued, the response was 95% reliable and fast.

Kufa Journal of EngineeringVol. 16(1)
Thi Qar University (IQ), Alsalam University College (IQ), Iraqi University (IQ), Technical University of Malaysia Malacca (MY), Middle Technical University (IQ), University of Kufa (IQ)
Openalex Percentile: Top 34%
Autonomous Vehicle Technology and Safety
0.68
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A NEW INTELLIGENT DRIVER VIGILANCE SYSTEM DESIGN USING TILT SENSORS — Mahmood F. Mosleh, Abbas Ali Diwan, et al. · Kufa Journal of Engineering (2025) | TGRS Research Map | TGRS