Sleep Sense

Abstract: There is a large number of cases of road accidents across the world out of which a significant number of accidents are caused due to driver fatigue and drowsy behavior .A system which is reliable in detection of drowsy behavior and signs of fatigue can help in preventing such road accidents by monitoring driver behavior and generating alerts to them when signs of fatigue detected. This paper presents a machine learning approach that uses real-time image and processing it by taking insights from its processing like closing eyes ,facial expressions, calculating the closing and open eye-aspect ratios using different machine learning algorithms and generating alerts if it detects driver drowsy behavior . Experimental research shows that our system is effective and reliable in detection of drowsy behavior of drivers and it generates timely alerts to drivers if it is found drowsy and makes the driver safe.

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-03-28
DOI
https://doi.org/10.22214/ijraset.2025.67918
Primary Topic
Sleep and Wakefulness Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Sleep Sense

Thipendra P. Singh, Shiv Bhardwaj, Swati Pandit, Yash Kaundinya et al.
International Journal for Research in Applied Science and Engineering Technology
Sleep and Wakefulness Research
article

Sleep Sense

Thipendra P. Singh, Shiv Bhardwaj, Swati Pandit, Yash Kaundinya, Gauri, Shruti Varshney
article en

Abstract

Abstract: There is a large number of cases of road accidents across the world out of which a significant number of accidents are caused due to driver fatigue and drowsy behavior .A system which is reliable in detection of drowsy behavior and signs of fatigue can help in preventing such road accidents by monitoring driver behavior and generating alerts to them when signs of fatigue detected. This paper presents a machine learning approach that uses real-time image and processing it by taking insights from its processing like closing eyes ,facial expressions, calculating the closing and open eye-aspect ratios using different machine learning algorithms and generating alerts if it detects driver drowsy behavior . Experimental research shows that our system is effective and reliable in detection of drowsy behavior of drivers and it generates timely alerts to drivers if it is found drowsy and makes the driver safe.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(3)
Aligarh Muslim University (IN)
Openalex Percentile: Top 94%
Sleep and Wakefulness Research
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Sleep Sense — Thipendra P. Singh, Shiv Bhardwaj, et al. · International Journal for Research in Applied Science and Engineering Technology (2025) | TGRS Research Map | TGRS