Drowsiness Detection and Alertness Using Eye Motion Monitoring

The driver felt sleepy when they don’t take proper rest while driving on long routes. The restless driving careless mistake could be fatal to driver as well as others’ lives. This issue has been increased to such a level that a system required to avoid accidents and save life. The driver alertness...

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Main Authors: Rabia Asghar, Ahmad Hassan, Naveed Ur Rehman Junejo, Farwa Ikram, Abeera Mahfooz Cheema
Format: Article
Language:English
Published: Sir Syed University of Engineering and Technology, Karachi. 2023-06-01
Series:Sir Syed University Research Journal of Engineering and Technology
Subjects:
Online Access:http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/573
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author Rabia Asghar
Ahmad Hassan
Naveed Ur Rehman Junejo
Farwa Ikram
Abeera Mahfooz Cheema
author_facet Rabia Asghar
Ahmad Hassan
Naveed Ur Rehman Junejo
Farwa Ikram
Abeera Mahfooz Cheema
author_sort Rabia Asghar
collection DOAJ
description The driver felt sleepy when they don’t take proper rest while driving on long routes. The restless driving careless mistake could be fatal to driver as well as others’ lives. This issue has been increased to such a level that a system required to avoid accidents and save life. The driver alertness detection can play a significant role to avoid such hazards. The system can identify the drowsiness on the face of driver and can generate an alarm for them to stop or take necessary actions. Eye state analysis is a key step for alertness detection that helps to identify the state of the eye whether it is open or close. In this paper, the method has been proposed for eye state analysis following face and eye detection to detect driver’s alertness. This system has been integrated into a four-steps includes detection of face, detection of eye, analysis of eye state, and decision regarding driver's drowsiness. A warning signal has been buzzed on drowsiness detection to alarm the driver. Simulation results validate that our proposed idea attains high accuracy and low error rate as compared to state-of-art.
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institution Kabale University
issn 1997-0641
2415-2048
language English
publishDate 2023-06-01
publisher Sir Syed University of Engineering and Technology, Karachi.
record_format Article
series Sir Syed University Research Journal of Engineering and Technology
spelling doaj-art-bf80c307fc374b08bb12db37580d52322025-08-20T03:26:43ZengSir Syed University of Engineering and Technology, Karachi.Sir Syed University Research Journal of Engineering and Technology1997-06412415-20482023-06-01131Drowsiness Detection and Alertness Using Eye Motion MonitoringRabia Asghar0Ahmad Hassan1Naveed Ur Rehman Junejo2Farwa Ikram3Abeera Mahfooz CheemaDepartment of Computer Engineering, The University of Lahore, Lahore PakistanDepartment of Computer Engineering, The University of Lahore, Lahore, PakistanDepartment of Computer Engineering, The University of Lahore, Lahore PakistanDepartment of Computer Engineering, The University of Lahore, Lahore Pakistan The driver felt sleepy when they don’t take proper rest while driving on long routes. The restless driving careless mistake could be fatal to driver as well as others’ lives. This issue has been increased to such a level that a system required to avoid accidents and save life. The driver alertness detection can play a significant role to avoid such hazards. The system can identify the drowsiness on the face of driver and can generate an alarm for them to stop or take necessary actions. Eye state analysis is a key step for alertness detection that helps to identify the state of the eye whether it is open or close. In this paper, the method has been proposed for eye state analysis following face and eye detection to detect driver’s alertness. This system has been integrated into a four-steps includes detection of face, detection of eye, analysis of eye state, and decision regarding driver's drowsiness. A warning signal has been buzzed on drowsiness detection to alarm the driver. Simulation results validate that our proposed idea attains high accuracy and low error rate as compared to state-of-art. http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/573drowsiness detectionalertness monitoring systemEuclidean distance classifier68-facelandmarks algorithm
spellingShingle Rabia Asghar
Ahmad Hassan
Naveed Ur Rehman Junejo
Farwa Ikram
Abeera Mahfooz Cheema
Drowsiness Detection and Alertness Using Eye Motion Monitoring
Sir Syed University Research Journal of Engineering and Technology
drowsiness detection
alertness monitoring system
Euclidean distance classifier
68-facelandmarks algorithm
title Drowsiness Detection and Alertness Using Eye Motion Monitoring
title_full Drowsiness Detection and Alertness Using Eye Motion Monitoring
title_fullStr Drowsiness Detection and Alertness Using Eye Motion Monitoring
title_full_unstemmed Drowsiness Detection and Alertness Using Eye Motion Monitoring
title_short Drowsiness Detection and Alertness Using Eye Motion Monitoring
title_sort drowsiness detection and alertness using eye motion monitoring
topic drowsiness detection
alertness monitoring system
Euclidean distance classifier
68-facelandmarks algorithm
url http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/573
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AT naveedurrehmanjunejo drowsinessdetectionandalertnessusingeyemotionmonitoring
AT farwaikram drowsinessdetectionandalertnessusingeyemotionmonitoring
AT abeeramahfoozcheema drowsinessdetectionandalertnessusingeyemotionmonitoring