DEVELOPMENT OF A REAL-TIME DROWSINESS DETECTION SYSTEM FOR ENHANCED VEHICLE SAFETY

In recent years, enhancing driver safety has become a critical focus in the automotive industry to reduce the risk of accidents caused by driver fatigue or inattention. This project aims to develop a real-time driver safety system by monitoring eye blinks to assess driver alertness. The system detects the frequency and duration of eye closures to estimate the driver's state—whether alert, drowsy, or asleep. Based on the detected status, the system can initiate control actions to ensure safety, such as triggering alarms or reducing vehicle speed. This intelligent monitoring approach enhances situational awareness and contributes to accident prevention, especially during long or monotonous drives

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-22
DOI
https://doi.org/10.5281/zenodo.15488784
Primary Topic
Sleep and Work-Related Fatigue
Type
article
Field-Weighted Citation Impact
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article

DEVELOPMENT OF A REAL-TIME DROWSINESS DETECTION SYSTEM FOR ENHANCED VEHICLE SAFETY

Zenodo (CERN European Organization for Nuclear Research)
Sleep and Work-Related Fatigue
article

DEVELOPMENT OF A REAL-TIME DROWSINESS DETECTION SYSTEM FOR ENHANCED VEHICLE SAFETY

article en

Abstract

In recent years, enhancing driver safety has become a critical focus in the automotive industry to reduce the risk of accidents caused by driver fatigue or inattention. This project aims to develop a real-time driver safety system by monitoring eye blinks to assess driver alertness. The system detects the frequency and duration of eye closures to estimate the driver's state—whether alert, drowsy, or asleep. Based on the detected status, the system can initiate control actions to ensure safety, such as triggering alarms or reducing vehicle speed. This intelligent monitoring approach enhances situational awareness and contributes to accident prevention, especially during long or monotonous drives

Zenodo (CERN European Organization for Nuclear Research)
University of Al-Qadisiyah (IQ)
Openalex Percentile: Top 52%
Sleep and Work-Related Fatigue
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