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Influence of artificial intelligence in civil engineering toward sustainable development-a systematic literature review

Manzoor, Bilal and Othman, Idris and Durdyev, Serdar and Ismail, Syuhaida and Wahab, Mohammad Hussaini (2021) Influence of artificial intelligence in civil engineering toward sustainable development-a systematic literature review. Applied System Innovation, 4 (3). pp. 1-17. ISSN 2571-5577


Official URL: http://dx.doi.org/10.3390/asi4030052


The widespread use of artificial intelligence (AI) in civil engineering has provided civil engineers with various benefits and opportunities, including a rich data collection, sustainable assessment, and productivity. The trend of construction is diverted toward sustainability with the aid of digital technologies. In this regard, this paper presents a systematic literature review (SLR) in order to explore the influence of AI in civil engineering toward sustainable development. In addition, SLR was carried out by using academic publications from Scopus (i.e., 3478 publications). Furthermore, screening is carried out, and eventually, 105 research publications in the field of AI were selected. Keywords were searched through Boolean operation “Artificial Intelligence” OR “Machine intelligence” OR “Machine Learning” OR “Computational intelligence” OR “Computer vision” OR “Expert systems” OR “Neural networks” AND “Civil Engineering” OR “Construction Engineering” OR “Sustainable Development” OR “Sustainability”. According to the findings, it was revealed that the trend of publications received its high intention of researchers in 2020, the most important contribution of publications on AI toward sustainability by the Automation in Construction, the United States has the major influence among all the other countries, the main features of civil engineering toward sustainability are interconnectivity, functionality, unpredictability, and individuality. This research adds to the body of knowledge in civil engineering by visualizing and comprehending trends and patterns, as well as defining major research goals, journals, and countries. In addition, a theoretical framework has been proposed in light of the results for prospective researchers and cholars.

Item Type:Article
Uncontrolled Keywords:construction, construction engineering, machine learning, sustainable development
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General) > T58.5-58.64 Information technology
T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Razak School of Engineering and Advanced Technology
ID Code:95753
Deposited By: Yanti Mohd Shah
Deposited On:31 May 2022 21:18
Last Modified:31 May 2022 21:18

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