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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM19669

POTHOLES AND TRAFFIC SIGNAL VIOLATION DETECTOR SYSTEM

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM19669

Volume:

7 |

4 |

Apr 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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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

SP

Swaraj Patil

KP

Krutik Patil

YP

Yatish Patil

PK

Priyanka Kamble

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Abstract

This project will be a Machine Learning (ML) based application, which will be using algorithms to detect the potholes on the roads and also the vehicles violating the traffic light. Nowadays, potholes on Indian roads, is major issue for vehicle drivers. Also, the increasing number of cars in cities has caused high amount of traffic, and has given rise to traffic violations. This causes heavy destruction of government as well as private property and accidents that may endanger the lives of the people. To solve the alarming problem and prevent such unfathomable consequences, traffic violation detection systems are needed and at the same time pothole detection on roads is necessary. For which the system makes proper traffic regulations at all times, and make them to follow rules those who does not comply. A traffic violation and pothole detection system must be realized in real-time as the authorities track the roads all the time. Hence, traffic rules be followed properly and protected by everyone efficiently; as the traffic detection system detects violations of traffic faster than humans also detects potholes precisely.

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Cite This Article

Swaraj Patil, Krutik Patil, Yatish Patil, Priyanka Kamble, "POTHOLES AND TRAFFIC SIGNAL VIOLATION DETECTOR SYSTEM," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 4, Apr 2023. https://doi.org/10.55041/IJSREM19669

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Publication Date

4/27/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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

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