Artificial Intelligence in Cloud Computing technology in the Construction industry: a bibliometric and systematic review

Wang, Jian; Antwi-Afari, Maxwell; Tezel, Algan; Antwi-Afari, Prince; Kasim, Tala

Abstract

The integration and impact of artificial intelligence (AI) and cloud computing (CC) technology in the construction industry (CI) would support their implementation process and adoption. However, there is a lack of research in the extant literature, and recent advances in this field have not been explored. As such, the key research question focuses on the extent of existing literature, main research hotspots, and recent advances (i.e., research gaps and future directions) in AI in CC in the CI. To address this research question, this study aims to conduct a state-of-the-art review of AI in CC in the CI by providing a qualitative discussion of the main research hotspots, research gaps, and future research directions. This review study used a four-step bibliometric-systematic review approach consisting of literature search, literature screening, science mapping analysis, and qualitative discussion. The results found four main research hotspots, namely (1) construction project performance indicators, (2) data analysis and visualization, (3) construction quality control and safety, and (4) construction energy efficiency. These findings would provide valuable insights for scholars and practitioners seeking to understand and integrate AI and CC technology applications in the CI. This review study will lay a better foundation for future developments in construction project management processes, data-sharing protocols, real-time safety monitoring, and ethical implications of AI and CC technologies.

Citation

Wang, J., Antwi-Afari, M., Tezel, A., Antwi-Afari, P., & Kasim, T. (2024). Artificial Intelligence in Cloud Computing technology in the Construction industry: a bibliometric and systematic review. Journal of Information Technology in Construction, 29, 480-502. https://doi.org/10.36680/j.itcon.2024.022

• Journal Article Type: Article
• Acceptance Date: May 30, 2024
• Online Publication Date: Jul 26, 2024
• Publication Date: Jul 26, 2024
• Deposit Date: Jun 7, 2024
• Publicly Available Date: Jul 26, 2024
• Journal: Journal of Information Technology in Construction
• Electronic ISSN: 1874-4753
• Peer Reviewed: Peer Reviewed
• Volume: 29
• Pages: 480-502
• DOI: https://doi.org/10.36680/j.itcon.2024.022
• Keywords: Artificial Intelligence, Cloud Computing, Construction, Science Mapping, Literature Review
• Public URL: https://nottingham-repository.worktribe.com/output/35734250