Progress and obstacles in the use of artificial intelligence in civil engineering: An in-depth review

Ruchit Parekh 1, * and Olivia Mitchell 2

1 Department of Engineering Management, Hofstra University, New York, USA.
2 Department of Civil Engineering, University of California, Berkeley, USA.
 
Review
International Journal of Science and Research Archive, 2024, 13(01), 1059–1080.
Article DOI: 10.30574/ijsra.2024.13.1.1777
Publication history: 
Received on 11 August 2024; revised on 17 September 2024; accepted on 18 October 2024
 
Abstract: 
Artificial Intelligence (AI) has emerged as a transformative force across various domains, with its potential to revolutionize urban architecture gaining increasing recognition. This paper offers a detailed examination of AI's application in the construction of public buildings, emphasizing its achievements, challenges, and future outlook. The review spans all facets of civil engineering, including review processes, analysis, design, construction management, geotechnical engineering, transportation planning, and construction oversight. AI methods, such as machine learning and genetic algorithms, are employed in analysis and design to enhance processes, forecast material behavior, and advance healthcare applications. In construction management, AI is utilized for project scheduling, resource distribution, risk evaluation, and safety management. Geotechnical applications of AI provide precise soil property estimation, soil damage assessment, and foundation construction improvements. Advanced technologies aid in transportation planning, traffic prediction, intelligent transportation systems, and infrastructure enhancements. Additionally, AI plays a crucial role in monitoring and maintaining public infrastructure, including bridge inspections, pipeline integrity evaluations, and early defect detection through image processing and data analysis. Despite significant advancements, challenges persist regarding AI's widespread adoption in civil engineering, including data availability, AI model definitions, ethical issues, and the necessity for collaborative efforts. Addressing these challenges will require the joint efforts of researchers, practitioners, and policymakers. Ultimately, AI's integration into civil engineering demonstrates its potential to enhance the efficiency, safety, and sustainability of infrastructure systems. This review summarizes the current knowledge, highlights challenges, and proposes directions for future research to advance AI integration in civil engineering.
 
Keywords: 
Artificial Intelligence; AI Applications; Structural Analysis; Structural Design; Machine Learning
 
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0