본문 바로가기
  • Home

An Automated Road Surface Defect Detection System based on Machine Learning

  • Journal of Software Assessment and Valuation
  • Abbr : JSAV
  • 2024, 20(4), pp.117-123
  • Publisher : Korea Software Assessment and Valuation Society
  • Research Area : Engineering > Computer Science
  • Received : November 9, 2024
  • Accepted : December 20, 2024
  • Published : December 31, 2024

Lee Bong Kyu 1

1제주대학교

Accredited

ABSTRACT

Due to recent climate changes, natural disasters such as localized heavy rain in the summer and heavy snow in the winter have become more frequent, leading to increased road damage. This significantly impacts the malfunction and safety of vehicles, thereby increasing the risk of major accidents. Current road management systems primarily rely on visual inspections and manual labor to collect and analyze data, making it difficult to effectively monitor rapidly changing road conditions in real-time. Therefore, there is a need for new technology that utilizes artificial intelligence to detect and monitor road defects in real-time. This paper proposes an AI-based pavement defect detection system that automatically identifies various defects that can occur on road surfaces. The proposed system has been validated using real-world data to detect and recognize 18 types of road surface defects in real-time.

Citation status

* References for papers published after 2023 are currently being built.