Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/88256
Title: Artificial intelligence in the AEC industry : scientometric analysis and visualization of research activities
Authors: Darko, A 
Chan, APC 
Adabre, MA 
Edwards, DJ
Hosseini, MR
Ameyaw, EE
Issue Date: Apr-2020
Source: Automation in construction, Apr. 2020, v. 112, 103081, p. 1-19, https://doi.org/10.1016/j.autcon.2020.103081
Abstract: The Architecture, Engineering and Construction (AEC) industry is fraught with complex and difficult problems. Artificial intelligence (AI) represents a powerful tool to assist in addressing these problems. Therefore, over the years, researchers have been conducting research on AI in the AEC industry (AI-in-the-AECI). In this paper, the first comprehensive scientometric study appraising the state-of-the-art of research on AI-in-the-AECI is presented. The science mapping method was used to systematically and quantitatively analyze 41,827 related bibliographic records retrieved from Scopus. The results indicated that genetic algorithms, neural networks, fuzzy logic, fuzzy sets, and machine learning have been the most widely used AI methods in AEC. Optimization, simulation, uncertainty, project management, and bridges have been the most commonly addressed topics/issues using AI methods/concepts. The primary value and uniqueness of this study lies in it being the first in providing an up-to-date inclusive, big picture of the literature on AI-in-the-AECI. This study adds value to the AEC literature through visualizing and understanding trends and patterns, identifying main research interests, journals, institutions, and countries, and how these are linked within now-available studies on AI-in-the-AECI. The findings bring to light the deficiencies in the current research and provide paths for future research, where they indicated that future research opportunities lie in applying robotic automation and convolutional neural networks to AEC problems. For the world of practice, the study offers a readily-available point of reference for practitioners, policy makers, and research and development (R&D) bodies. This study therefore raises the level of awareness of AI and facilitates building the intellectual wealth of the AI area in the AEC industry.
Keywords: Architecture-engineering-construction
Artificial intelligence
Machine intelligence
Industry 4.0
Automation
Digital transformation
Scientometric
Review
Publisher: Elsevier
Journal: Automation in construction 
ISSN: 0926-5805
EISSN: 1872-7891
DOI: 10.1016/j.autcon.2020.103081
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

WEB OF SCIENCETM
Citations

4
Citations as of Oct 17, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.