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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM9243

DROWSINESS DETECTION SYSTEM USING MACHINE LEARNING

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM9243

Volume:

5 |

6 |

Jun 2021

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

NJ

Naman Jain

MAM

Mr. Arpit Mishra

KV

Khushi Verma

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Abstract

The Drowsiness Detection System (DDS) is an innovative solution designed to detect and prevent accidents caused by drowsy driving. By combining computer vision and machine learning techniques, the DDS continuously monitors the driver’s eyes in real-time. The system captures video frames, detects faces, and analyzes the eye regions to determine if the eyes are open or closed. Using a scoring mechanism, the DDS assesses the driver’s level of drowsiness, and when it exceeds a threshold, an alarm is triggered to alert the driver. With its ability to detect early signs of drowsiness, the DDS enhances road safety by providing timely warnings to drivers, mitigating the risks associated with drowsy driving.

KEYWORDS

Machine learning Deep learning Convolutional Neural Network

Cite This Article

Naman Jain, Mr. Arpit Mishra, Khushi Verma, "DROWSINESS DETECTION SYSTEM USING MACHINE LEARNING," International Journal of Scientific Research in Engineering and Management, vol. 5, no. 6, Jun 2021.

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Publication Date

6/6/2023

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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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