DEVELOPMENT OF AN ADVANCED DROWSINESS DETECTION SYSTEM TO ENHANCE AUTOMOTIVE SAFETY

Driver safety is a critical concern in modern automotive systems aimed at reducing road accidents. This project focuses on enhancing vehicle safety by monitoring the driver’s eye blinks to assess their level of alertness. By detecting and analyzing eye blink patterns, the system estimates the driver’s status—such as fatigue or distraction—and subsequently enables real-time control interventions to prevent potential accidents. The integration of this eye blink detection mechanism within the car’s safety system offers a proactive approach to accident avoidance, improving overall road safety. This study demonstrates the feasibility of using eye blink monitoring as an effective measure for driver status evaluation and underscores its importance in the development of intelligent driver assistance systems

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-23
DOI
https://doi.org/10.5281/zenodo.15496073
Primary Topic
Sleep and Work-Related Fatigue
Type
article
Field-Weighted Citation Impact
0.00
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article

DEVELOPMENT OF AN ADVANCED DROWSINESS DETECTION SYSTEM TO ENHANCE AUTOMOTIVE SAFETY

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

DEVELOPMENT OF AN ADVANCED DROWSINESS DETECTION SYSTEM TO ENHANCE AUTOMOTIVE SAFETY

article en

Abstract

Driver safety is a critical concern in modern automotive systems aimed at reducing road accidents. This project focuses on enhancing vehicle safety by monitoring the driver’s eye blinks to assess their level of alertness. By detecting and analyzing eye blink patterns, the system estimates the driver’s status—such as fatigue or distraction—and subsequently enables real-time control interventions to prevent potential accidents. The integration of this eye blink detection mechanism within the car’s safety system offers a proactive approach to accident avoidance, improving overall road safety. This study demonstrates the feasibility of using eye blink monitoring as an effective measure for driver status evaluation and underscores its importance in the development of intelligent driver assistance systems

Zenodo (CERN European Organization for Nuclear Research)
University of Al-Qadisiyah (IQ)
Openalex Percentile: Top 48%
Sleep and Work-Related Fatigue
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