Bridge Damage Classification and Detection Using Fully Convolutional Neural Network Based on Images from UAVs

Shi, Jiyuan; Zuo, Rongzhi; Dang, Ji

doi:10.1201/9781003090564-26

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Computer Vision for Bridge Inspection and Monitoring

Wu,

Chen,

Dang

2024

Springer Tracts in Civil Engineering

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Computer Vision for Bridge Inspection and Monitoring

Wu,

Chen,

Dang

2024

Springer Tracts in Civil Engineering

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Utilization of Unmanned Aerial Vehicle, Artificial Intelligence, and Remote Measurement Technology for Bridge Inspections

Chun¹,

Dang²,

Hamasaki³

et al. 2020

JRM

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In recent years, aging of bridges has become a growing concern, and the danger of bridge collapse is increasing. To appropriately maintain bridges, it is necessary to perform inspections to accurately understand their current state. Until now, bridge inspections have involved a visual inspection in which inspection personnel come close to the bridges to perform inspection and hammering tests to investigate abnormal noises by hammering the bridges with an inspection hammer. Meanwhile, as there are a large number of bridges (for example, 730,000 bridges in Japan), and many of these are constructed at elevated spots; the issue is that the visual inspections are laborious and require huge cost. Another issue is the wide disparity in the quality of visual inspections due to the experience, knowledge, and competence of inspectors. Accordingly, the authors are trying to resolve or ameliorate these issues using unmanned aerial vehicle (UAV) technology, artificial intelligence (AI) technology, and telecommunications technology. This is discussed first in this paper. Next, the authors discuss the future prospects of bridge inspection using robot technology such as a 3-D model of bridges. The goal of this paper is to show the areas in which deployment of the UAV, robots, telecommunications, and AI is beneficial and the requirements of these technologies.

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Bridge Damage Classification and Detection Using Fully Convolutional Neural Network Based on Images from UAVs

Cited by 2 publications

References 1 publication

Computer Vision for Bridge Inspection and Monitoring

Computer Vision for Bridge Inspection and Monitoring

Utilization of Unmanned Aerial Vehicle, Artificial Intelligence, and Remote Measurement Technology for Bridge Inspections

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