Application of machine learning in the civil engineering sector -a review

Artificial Intelligence (AI) and machine learning have a diverse array of applications within the civil engineering sector. These technologies are revolutionising structural engineering by enhancing the ability to predict and monitor structural integrity and potential failures. Machine learning improves construction management by optimizing project planning, resource allocation, cost prediction, and risk mitigation, while AI-driven technologies enhance safety, efficiency, and decision-making. In geotechnical engineering, machine learning algorithms are being used to analyse soil properties, predict landslides, and design more stable foundations. AI models optimise traffic management systems, improve the efficiency and safety of transportation networks, and aid the development of autonomous vehicles. Additionally, AI is finding applications in environmental engineering, where it helps in assessing environmental impacts promoting sustainable practices and many more.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/nigercon62786.2024.10926968
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Application of machine learning in the civil engineering sector -a review

Bernard Chukwuemeka Finbarrs-Ezema, Stephen Aderomose, Rachael Folorunso, Precious Belema et al.
Data Mining and Machine Learning Applications
article

Application of machine learning in the civil engineering sector -a review

Bernard Chukwuemeka Finbarrs-Ezema, Stephen Aderomose, Rachael Folorunso, Precious Belema, Emmanuel Fagbuyi
article en

Abstract

Artificial Intelligence (AI) and machine learning have a diverse array of applications within the civil engineering sector. These technologies are revolutionising structural engineering by enhancing the ability to predict and monitor structural integrity and potential failures. Machine learning improves construction management by optimizing project planning, resource allocation, cost prediction, and risk mitigation, while AI-driven technologies enhance safety, efficiency, and decision-making. In geotechnical engineering, machine learning algorithms are being used to analyse soil properties, predict landslides, and design more stable foundations. AI models optimise traffic management systems, improve the efficiency and safety of transportation networks, and aid the development of autonomous vehicles. Additionally, AI is finding applications in environmental engineering, where it helps in assessing environmental impacts promoting sustainable practices and many more.

Afe Babalola University (NG)
Openalex Percentile: Top 55%
Data Mining and Machine Learning Applications
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Application of machine learning in the civil engineering sector -a review — Bernard Chukwuemeka Finbarrs-Ezema, Stephen Aderomose, et al. · (2024) | TGRS Research Map | TGRS