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Influence of Artificial Intelligence in Civil Engineering toward Sustainable Development—A Systematic Literature Review

Authors :
Bilal Manzoor
Idris Othman
Serdar Durdyev
Syuhaida Ismail
Mohammad Hussaini Wahab
Source :
Applied System Innovation, Vol 4, Iss 3, p 52 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

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 scholars.

Details

Language :
English
ISSN :
25715577
Volume :
4
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Applied System Innovation
Publication Type :
Academic Journal
Accession number :
edsdoj.9d788aefd6a44f2da734fb0deb333aea
Document Type :
article
Full Text :
https://doi.org/10.3390/asi4030052