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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREMWP8032

Efficient Roadway Management through AI-Powered Damage Detection and Lane Detection

Stream/Area:

-

Subject:

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Paper ID:

IJSREMWP8032

Volume:

8 |

7 |

Jul 2024

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

JHS

Jagadeesha H S

MVP

Mr. Vinay Patel

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Abstract

The objective of this project is to improve roadway management for autonomous vehicles by implementing AI-powered damage detection and lane detection systems. The primary focus is to develop algorithms that can accurately identify road damage and detect lane markings in real-time. By leveraging machine learning and computer vision techniques, this system aims to enhance safety and efficiency on roadways. The damage detection component will help self-driving cars navigate around obstacles and hazards effectively, while the lane detection feature ensures precise vehicle positioning within designated lanes. Overall, this integrated approach aims to improve the capabilities of autonomous vehicles, contributing to safer and more reliable transportation systems.

KEYWORDS

YOLOv8 Canny edge detection roadway management AI-powered damage detection lane detection self-drivingcars machine learning computer vision real-time detection transportation safety.

Cite This Article

Jagadeesha H S, Mr. Vinay Patel, "Efficient Roadway Management through AI-Powered Damage Detection and Lane Detection," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 7, Jul 2024.

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12/31/45492

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

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