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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM36644

VEHICLE GRIEVANCE HANDLING

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM36644

Volume:

8 |

7 |

Jul 2024

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

MN

Manu N

MRR

Mrs. Roopa R

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Abstract

In this vehicle grievance handling our cutting-edge traffic safety monitoring system uses object detection, machine learning, and YOLOv3 to improve road safety. It can distinguish between motorbikes and non-helmet riders, recognize triple riding, and keep an eye out for fast-moving scars. This technique greatly lessens the need for physical enforcement by emphasizing the usage of helmets, speed compliance, and safe riding habits. It helps law enforcement encourage safer driving practices and lessen accident-related injuries, especially brain injuries, by offering real-time insights and actions, so increasing overall traffic safety.

KEYWORDS

Object detection Machine learning YOLOv3 Traffic surveillance Helmet detection.

Cite This Article

Manu N, Mrs. Roopa R, "VEHICLE GRIEVANCE HANDLING," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 7, Jul 2024.

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Publication Date

7/20/2024

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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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