BIM, IoT, and GIS integration in construction resource monitoring

Abstract

In recent years, the advancement of digital technologies such as building information modeling (BIM), internet of things (IoT), and geographic information system (GIS) has had many impacts on the construction industry. However, limited research has been conducted on the integration of BIM, IoT, and GIS technologies, especially in construction resource monitoring. Therefore, this paper presents a state-of-the-art review of BIM, IoT, and GIS integration by focusing on their applications, challenges, research gaps, and future research directions. A systematic literature review and science mapping analysis were adopted in this study. The results identified the gaps in BIM, IoT, and GIS integration in construction resource monitoring, which include interoperability, data security, real-time dynamic monitoring, complex environmental data processing, environmental sustainability studies, prediction models, and convenience for the users. Moreover, challenges and future research directions were proposed. This paper contributes to extending the integrated applications of digital technologies in construction resource monitoring.

Publication DOI: https://doi.org/10.1016/j.autcon.2025.106149
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Civil Engineering
College of Engineering & Physical Sciences
Funding Information: The authors acknowledged support from National Natural Science Foundation of China, Grant Number: 71901104; Project of Social Science Foundation of Jiangsu Province, Grant Number: 21GLC017; and Jiangsu Provincial Qinglan Project of China. The authors are
Additional Information: Copyright © 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).
Uncontrolled Keywords: Building information modeling (BIM),Construction resource monitoring,Geographic information systems (GIS),Internet of things (IoT),Systematic literature review
Publication ISSN: 0926-5805
Last Modified: 02 Apr 2025 07:26
Date Deposited: 31 Mar 2025 16:26
Full Text Link:
Related URLs: https://linking ... 92658052500189X (Publisher URL)
PURE Output Type: Review article
Published Date: 2025-06
Published Online Date: 2025-03-28
Accepted Date: 2025-03-22
Authors: Liu, Xiang
Antwi-Afari, Maxwell Fordjour (ORCID Profile 0000-0002-6812-7839)
Li, Jue
Zhang, Yongcheng
Manu, Patrick

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