Grand Challenges of Machine-Vision Technology in Civil Structural Health Monitoring

Authors

  • Yunchao Tang College of Urban and Rural Construction, Zhongkai University of Agriculture and Engineering, Guangzhou, China https://orcid.org/0000-0002-6178-4457
  • Yunfan Lin College of Urban and Rural Construction, Zhongkai University of Agriculture and Engineering, Guangzhou, China
  • Xueyu Huang College of Urban and Rural Construction, Zhongkai University of Agriculture and Engineering, Guangzhou, China
  • Minghui Yao College of Urban and Rural Construction, Zhongkai University of Agriculture and Engineering, Guangzhou, China
  • Zhaofeng Huang College of Engineering, South China Agricultural University, Guangzhou, China
  • Xiangjun Zou College of Engineering, South China Agricultural University, Guangzhou, China

DOI:

https://doi.org/10.37256/aie.112020250

Keywords:

artificial intelligence, smart sensors, vision technology, deep learning, structural health monitoring

Abstract

Machine-vision technology has progressed remarkably in both accuracy and speed owing to advances in computer technology and artificial intelligence. In this paper, state-of-the-art research on vision-based techniques is reviewed for civil infrastructure condition assessment. The major challenges of machine vision technique in civil structural health monitoring are presented.

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Published

2020-03-23

How to Cite

1.
Tang Y, Yunfan Lin, Xueyu Huang, Minghui Yao, Zhaofeng Huang, Xiangjun Zou. Grand Challenges of Machine-Vision Technology in Civil Structural Health Monitoring. Artificial Intelligence Evolution [Internet]. 2020 Mar. 23 [cited 2024 Jul. 13];1(1):8-16. Available from: https://ojs.wiserpub.com/index.php/AIE/article/view/250