A scientometric-content analysis of integration of BIM and IoT

Y. Jia, M. R. Hosseini, B. Zhang, I. Martek, B. Nikmehr, J. Wang

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

1 Citation (Scopus)

Abstract

![CDATA[As two essential components of Industry 4.0 in the construction industry, building information modelling (BIM) and the Internet of things (IoT) tend to be integrated. Research in the field has increased significantly in recent years, yet previous reviews on this field are limited, and a review study with both quantitative and qualitative analysis of BIM-IoT integration remains wanting. Thus, this review paper investigates 107 peer-reviewed journal articles in the field of BIM-IoT integration using mixed scientometric-content analysis. The findings reveal that the research in this field is promising, and collaboration has achieved well-recognised outcomes, while more collaborations are expected. Besides, the analysis reveals that the research is evolving from traditional construction themes, such as safety, energy efficiency and thermal comfort, to evolutionary concepts, such as digitalisation, Industry 4.0, digital twin, and smart cities. Finally, five research opportunities are outlined, including reliability and robustness, interoperability, integration with other emerging technologies, security and privacy, and reluctance from the construction industry. This review is the first attempt to conduct a scientometric analysis of the research of BIM-IoT integration. The findings provide directions for future research.]]
Original languageEnglish
Title of host publicationIOP Conference Series: Earth and Environmental Science. Volume 1101, World Building Congress 2022, 26/06/2022 - 30/06/2022, Melbourne, Australia
PublisherInstitute of Physics Publishing
Number of pages11
DOIs
Publication statusPublished - 2022
EventWorld Building Congress -
Duration: 26 Jun 2022 → …

Conference

ConferenceWorld Building Congress
Period26/06/22 → …

Open Access - Access Right Statement

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence (https://creativecommons.org/licenses/by/3.0/). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by IOP Publishing Ltd.

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