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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM20453

DETECTING DRIVER DROWSINESS USING FACIAL RECOGNITION

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM20453

Volume:

7 |

5 |

May 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

CR

Chilumula Rajkumar

AP

Amaragani Pranav

BA

Boga Abhinav

AA

Adla Akashvardhan

S

S.R.Shailaja

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Abstract

Driver’s fatigue and its indication is an active research area. Most of the conventional methods are either Drowsy driving is one of the major causes of road accidents and death. Hence, detection of vehicle based, or behavioural based or physiological based. Few methods are intrusive and distract the driver, some require expensive sensors and data handling. Therefore, in this study, a low-cost, real-time driver’s drowsiness detection system is developed with acceptable accuracy. In the developed system, a webcam records the video and driver’s face is detected in each frame employing image processing techniques. Facial landmarks on the detected face are pointed and subsequently the eye aspect ratio, mouth opening ratio and nose length ratio are computed and depending on their values, drowsiness is detected based on developed adaptive thresholding. Machine learning algorithms have been implemented as well in an offline manner.

KEYWORDS

Face Detection Eye Detection Eye Tracking Feature Extraction Machine Learning Real time Processing OpenCV Drowsiness Detection

Cite This Article

Chilumula Rajkumar, Amaragani Pranav, Boga Abhinav, Adla Akashvardhan, S.R.Shailaja, "DETECTING DRIVER DROWSINESS USING FACIAL RECOGNITION," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 5, May 2023. https://doi.org/10.55041/IJSREM20453

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Publication Date

7/4/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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