The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.
Technologies for digital twin applications in construction
Open accessAbstract
The construction industry is facing enormous pressure to adopt digital solutions to solve the industry's inherent problems. The digital twin has emerged as a solution that can update a BIM model with real-time data to achieve cyber-physical integration, enabling real-time monitoring of assets and activities and improving decision-making. The application of digital twins in the construction industry is still in its nascent stages but has been steadily growing over the past few years. A wide variety of emerging technologies are being used in the development of digital twins in diverse applications in construction but it is not immediately clear from the literature which ones are key to the successful development of digital twins, necessitating a systematic literature review with a focus on technologies. This paper aims to identify the key technologies used in the development of digital twins in construction in the existing literature, the research gaps and the potential areas for future research. This is achieved by conducting a systematic review of studies with demonstrative case studies and experimental setups in construction. Based on the observed research gaps, prominent future research directions are suggested, focusing on technologies in data transmission, interoperability and data integration and data processing and visualisation.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Wireless sensor networks: a survey
Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002) · Computer Networks · doi:10.1016/s1389-1286(01)00302-4 · Cited by 17,418
The Internet of Things: A survey
Atzori, L., Iera, A., & Morabito, G. (2010) · Computer Networks · doi:10.1016/j.comnet.2010.05.010 · Cited by 15,613
A translation approach to portable ontology specifications
Gruber, T. R. (1993) · Knowledge Acquisition · doi:10.1006/knac.1993.1008 · Cited by 12,752
Artificial intelligence: A modern approach
Nilsson, N. J. (1996) · Artificial Intelligence · doi:10.1016/0004-3702(96)00007-0 · Cited by 10,583
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2009.06.006 · Cited by 10,578
Azuma, R. T. (1997) · Presence: Teleoperators and Virtual Environments · doi:10.1162/pres.1997.6.4.355 · Cited by 10,121
Intelligence without representation
Brooks, R. A. (1991) · Artificial Intelligence · doi:10.1016/0004-3702(91)90053-m · Cited by 4,853
Systematic Literature Reviews in Software Engineering—A Systematic Literature Review
Kitchenham, B., Pearl Brereton, O., Budgen, D., Turner, M., Bailey, J., & Linkman, S. (2009) · Information and Software Technology · doi:10.1016/j.infsof.2008.09.009 · Cited by 4,537
Characterising the Digital Twin: A systematic literature review
Jones, D., Snider, C., Nassehi, A., Yon, J., & Hicks, B. (2020) · CIRP Journal of Manufacturing Science and Technology · doi:10.1016/j.cirpj.2020.02.002 · Cited by 2,422
Gusenbauer, M., & Haddaway, N. R. (2020) · Research Synthesis Methods · doi:10.1002/jrsm.1378 · Cited by 2,379
Cited by
Analysis of Digital Twin Applications in Energy Efficiency: A Systematic Review
Ba, L., Tangour, F., El Abbassi, I., & Absi, R. (2025) · Sustainability · doi:10.3390/su17083560 · Cited by 96
A review of drivers and barriers of Digital Twin adoption in building project development processes
Jahangir, M. F., Schultz, C. P. L., & Kamari, A. (2024) · Journal of Information Technology in Construction · doi:10.36680/j.itcon.2024.008 · Cited by 34
DIGITAL TWIN APPLICATION IN CONSTRUCTION COST MANAGEMENT
Che Haron, R., & Muhd Zafir, N. B. (2025) · PLANNING MALAYSIA · doi:10.21837/pm.v23i35.1665 · Cited by 6
Metadata
- Authors
- Tuhaise, V. V., Tah, J. H. M., & Abanda, F. H.
- Venue
- Automation in Construction
- Publisher
- Elsevier BV
- Published
- 2023-08
- Volume
- 152
- Pages
- 104931
- ISSN
- 0926-5805 (ISSN-L)
- OpenAlex
- W4381789065
- Cited by
- 308
- References
- 90
- FWCI
- 36.89
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Technologies for digital twin applications in construction. https://app.cochat.ai/papers/10.1016/j.autcon.2023.104931
- The paper
- Tuhaise, V. V., Tah, J. H. M., & Abanda, F. H. (2023). Technologies for digital twin applications in construction. Automation in Construction. https://doi.org/10.1016/j.autcon.2023.104931
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.