Over the past 2 decades, the use of artificial intelligence (AI) has exponentially increased toward complete automation of structural inspection and assessment tasks. This trend will continue to rise in image processing as unmanned aerial systems (UAS) and the internet of things (IoT) markets are expected to expand at a compound annual growth rate of 57.5% and 26%, respectively, from 2021 to 2028. This paper aims to catalog the milestone development work, summarize the current research trends, and envision a few future research directions in the innovative application of AI in civil infrastructure health monitoring. A blow-by-blow account of the major technology progression in this research field is provided in a chronological order. Detailed applications, key contributions, and performance measures of each milestone publication are presented. Representative technologies are detailed to demonstrate current research trends. A road map for future research is outlined to address contemporary issues such as explainable and physics-informed AI. This paper will provide readers with a lucid memoir of the historical progress, a good sense of the current trends, and a clear vision for future research.
T. G. Mondal and G. Chen, "Artificial Intelligence in Civil Infrastructure Health Monitoring—historical Perspectives, Current Trends, and Future Visions," Frontiers in Built Environment, vol. 8, article no. 1007886, Frontiers Media, Sep 2022.
The definitive version is available at https://doi.org/10.3389/fbuil.2022.1007886
Civil, Architectural and Environmental Engineering
Keywords and Phrases
artificial intelligence; autonomous inspection; big data analytics; deep learning; machine learning; smart maintenance and monitoring; structural health monitoring
International Standard Serial Number (ISSN)
Article - Journal
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23 Sep 2022