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

Auteur(s): ORCID
ORCID
ORCID
ORCID
ORCID
Médium: article de revue
Langue(s): anglais
Publié dans: Journal of Information Technology in Construction, , v. 29
Page(s): 480-502
DOI: 10.36680/j.itcon.2024.022
Abstrait:

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 dis-cussion. 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.

Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.36680/j.itcon.2024.022.
  • Informations
    sur cette fiche
  • Reference-ID
    10798141
  • Publié(e) le:
    01.09.2024
  • Modifié(e) le:
    01.09.2024
 
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