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

Yunchao Tang; Yunfan Lin; Xueyu Huang; Minghui Yao; Zhaofeng Huang; Xiangjun Zou

doi:10.37256/aie.112020250

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

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 Oct. 4];1(1):8-16. Available from: https://ojs.wiserpub.com/index.php/AIE/article/view/250

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Issue

Artificial Intelligence Evolution, Volume 1 Issue 1 (2020), 1-62

Section

Research Article