Volume 12 • Issue 2 • PP: 39–47 • 2026
BIM Integration Across Engineering Disciplines: A Systematic Review of Methodological Advances, Interoperability Challenges, and Emerging Digital Frameworks
View PDF Abstract
This paper provides a comprehensive systematic review of Building Information Modeling (BIM) integration across ten engineering disciplines, synthesising publications from January 2020 to January 2026. It identifies convergent trends, persistent knowledge gaps, and translational barriers that separate research prototypes from scalable industry practice. A PRISMA-guided systematic review was conducted across Scopus, Web of Science, ASCE Library, and ScienceDirect. An initial corpus of 4,712 records was screened and quality-assessed, yielding 63 papers for quantitative synthesis and a broader qualitative corpus of 293 studies spanning ten sub-domains: BIM–digital twin integration, BIM and artificial intelligence/machine learning, interoperability and IFC, structural engineering, MEP and building services, facility management and operations, BIM–GIS for smart cities, off-site and modular construction, adoption barriers, and energy and sustainability analysis. Annual BIM publications grew by approximately 256% between 2019 and 2024. BIM–AI/ML and BIM–digital twin integration are the two fastest-growing sub-domains, yet both remain constrained by data standardisation deficiencies and a shortage of domain-specific training datasets. IFC-based interoperability has matured significantly, but real-time bidirectional exchange across disciplines remains nascent. Structural engineering applications exhibit the highest technology readiness, while BIM–GIS integration for smart-city applications shows the widest gap between published prototypes and commercial deployment. The review delivers a thematic roadmap and a consolidated evidence base for prioritizing investment in digital workflows, standards development, and workforce training. An original four-layer integrated framework is proposed that connects engineering code provisions, AI/ML analytics, digital twin synchronisation, and automated quantity extraction within a single traceable workflow.
Keywords
References
[1] R. Sacks, C. Eastman, G. Lee, and P. Teicholz, BIM Handbook: A Guide to Building Information Modeling for Owners, Designers, Engineers, Contractors, and Facility Managers 3rd ed. Hoboken, NJ, USA: John Wiley & Sons, 2018.
[2] S. Azhar, “Building information modeling (BIM): Trends, benefits, risks, and challenges for the AEC industry,” Leadership and Management in Engineering, vol. 11, no. 3, pp. 241–252, 2011, doi: 10.1061/(ASCE)LM.1943-5630.0000127.
[3] D. Bryde, M. Broquetas, and J. M. Volm, “The project benefits of building information modelling (BIM),” International Journal of Project Management, vol. 31, no. 7, pp. 971–980, 2013, doi: 10.1016/j.ijproman.2012.12.001.
[4] International Organization for Standardization, ISO 19650- 1:2018 Organization and Digitization of Information about Buildings and Civil Engineering Works — Part 1: Concepts and Principles. Geneva, Switzerland: ISO, 2018.
[5] International Organization for Standardization, ISO 19650- 3:2020 Organization and Digitization of Information about Buildings and Civil Engineering Works— Part 3: Operational Phase of the Assets. Geneva, Switzerland: ISO, 2020.
[6] A. Zabin, V. A. Gonzalez, Y. Zou, and R. Amor, “Applications of machine learning to BIM: A systematic literature review,” Advanced Engineering Informatics, vol. 51, p. 101474, 2022, doi: 10.1016/j.aei.2021.101474.
[7] B. Abbasnejad, M. P. Nepal, A. Ahankoob, A. Nasirian, and R. Drogemuller, “BIM adoption and implementation enablers in AEC firms: A systematic literature review,” Architectural Engineering and Design Management, vol. 17, no. 5–6, pp. 411–433, 2020, doi: 10.1080/17452007.2020.1793894.
[8] M. Baghalzadeh Shishehgarkhaneh, A. Keivani, R. C. Moehler, N. Jelodari, and S. Roshdi Laleh, “Internet of Things (IoT), Building Information Modeling (BIM), and Digital Twin (DT) in construction industry: A review, bibliometric, and network analysis,” Buildings, vol. 12, no. 10, p. 1503, 2022, doi: 10.3390/buildings12101503.
[9] R. Sacks, I. Brilakis, E. Pikas, H. S. Xie, and M. Girolami, “Construction with digital twin information systems,” Data-Centric Engineering, vol. 1, p. e14, 2020, doi: 10.1017/dce.2020.16.
[10] Y. Cao, S. N. Kamaruzzaman, and N. M. Aziz, “Building information modeling (BIM) capabilities in the operation and maintenance phase of green buildings: A systematic review,” Buildings, vol. 12, no. 6, p. 830, 2022, doi: 10.3390/buildings12060830.
[11] D. K. Abideen, A. Yunusa-Kaltungo, P. Manu, and C. Cheung, “A systematic review of the extent to which BIM is integrated into operation and maintenance,” Sustainability, vol. 14, no. 14, p. 8692, 2022, doi: 10.3390/su14148692.
[12] Y. Yu, S. Kim, H. Jeon, and B. Koo, “A systematic review of the trends and advances in IFC schema extensions for BIM interoperability,” Applied Sciences, vol. 13, no. 23, p. 12560, 2023, doi: 10.3390/app132312560.
[13] H. Kim, J. Park, and S. Kwon, “BIM and digital twin for developing convergence technologies as future of digital construction,” Buildings, vol. 13, no. 2, p. 441, 2023, doi: 10.3390/buildings13020441.
[14] I. I. Shoheb, M. Metwally, and I. R. Endut, “Parametric sensitivity of axial–flexural interaction in reinforced concrete shear walls for optimized design and structural efficiency,” International Journal of BIM and Engineering Science (IJBES), vol. 12, no. 1, pp. 75–96, 2026, doi: 10.54216/IJBES.120105.
[15] N. Moretti, L. Giannini, and M. Cardinali, “BIM methodology in bridge construction management and structural assessment,” Applied Sciences, vol. 10, no. 20, p. 7284, 2020, doi: 10.3390/app10207284.
[16] E. Alreshidi, “Towards BIM-based sustainable structural design optimization: A systematic review and industry perspective,” Sustainability, vol. 15, no. 20, p. 15117, 2023, doi: 10.3390/su152015117.
[17] R. Volk, J. Stengel, and F. Schultmann, “Building information modeling (BIM) for existing buildings — Literature review and future needs,” Automation in Construction, vol. 38, pp. 109–127, 2014, doi: 10.1016/j.autcon.2013.10.023.
[18] Q. Lu, A. K. Parlikad, P. Woodall, G. D. Xie, X. Xie, Z. Liang, and J. M. Schooling, “Developing a digital twin at building and city levels: Case study of West Cambridge campus,” Journal of Management in Engineering, vol. 36, no. 3, p. 05020004, 2020, doi: 10.1061/(ASCE)ME.1943- 5479.0000763.
[19] T. Wang, V. J. L. Gan, D. Hu, and H. Liu, “Digital twinenabled built environment sensing and monitoring through semantic enrichment of BIM with SensorML,” Automation in Construction, vol. 144, p. 104625, 2022, doi: 10.1016/j.autcon.2022.104625.
[20] Y. Pan and L. Zhang, “A BIM-data mining integrated digital twin framework for advanced project management,” Automation in Construction, vol. 124, p. 103564, 2021, doi: 10.1016/j.autcon.2021.103564.
[21] X. Wang, H. Yu, W. McGee, C. C. Menassa, and V. R. Kamat, “Enabling BIM-driven human-robot collaborative construction workflows with closed-loop digital twins,” Automation in Construction, vol. 157, p. 104295, 2023, doi: 10.1016/j.autcon.2023.104295.
[22] A. A. Akanmu, C. J. Anumba, and O. R. Ogunseiju, “Towards next generation cyber-physical systems and digital twins for construction,” Journal of Information Technology in Construction, vol. 26, pp. 505–525, 2021, doi: 10.36680/j.itcon.2021.027.
[23] C. Malaga-Chuquitaype, “Machine learning in structural design: An opinionated review,” Frontiers in Built Environment, vol. 8, p. 815717, 2022, doi: 10.3389/fbuil.2022.815717.
[24] Y. Shen and Y. Pan, “BIM-supported automatic energy performance analysis for green building design using explainable machine learning and multi-objective optimization,” Applied Energy, vol. 333, p. 120575, 2023, doi: 10.1016/j.apenergy.2022.120575.
[25] Y. Pan and L. Zhang, “Integrating BIM and AI for smart construction management: Current status and future directions,” Archives of Computational Methods in Engineering, vol. 30, no. 2, pp. 1081–1110, 2023, doi: 10.1007/s11831-022-09830- 8.
[26] S. Tang, D. R. Shelden, C. M. Eastman, P. Pishdad- Bozorgi, and X. Gao, “A review of building information modeling (BIM) and the Internet of Things (IoT) devices integration: Present status and future trends,” Automation in Construction, vol. 101, pp. 127–139, 2019, doi: 10.1016/j.autcon.2019.01.020.
[27] W. Solihin and C. Eastman, “Classification of rule-based BIM checking processes,” Automation in Construction, vol. 53, pp. 69–82, 2015, doi: 10.1016/j.autcon.2015.03.003.
[28] J. Zhang and N. M. El-Gohary, “Automated extraction of construction regulatory requirements from textual documents,” Automation in Construction, vol. 69, pp. 1–14, 2016, doi: 10.1016/j.autcon.2016.05.006.
[29] M.-K. Kim, J. P. P. Thedja, and Q. Wang, “On BIM interoperability via the IFC standard: An assessment from the structural engineering and design viewpoint,” Applied Sciences, vol. 11, no. 23, p. 11430, 2021, doi: 10.3390/app112311430.
[30] J. C. P. Cheng, W. Chen, K. Chen, and Q. Wang, “Datadriven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms,” Automation in Construction, vol. 112, p. 103087, 2020, doi: 10.1016/j.autcon.2020.103087.
[31] M. R. Hosseini, M. Maghrebi, A. Akbarnezhad, I. Martek, and M. Arashpour, “BIM enabler for facilities management: A review of 33 cases,” International Journal of Construction Management, vol. 23, no. 9, pp. 1647–1659, 2023, doi: 10.1080/15623599.2023.2222962.
[32] W. Jiang, L. Liu, H. Cai, Z. Ni, and H. Wu, “Study on city digital twin technologies for sustainable smart city design: A review and bibliometric analysis of GIS and BIM integration,” Sustainable Cities and Society, vol. 100, p. 105050, 2023, doi: 10.1016/j.scs.2023.105050.
[33] S. Zhang, D. Hou, C. Wang, F. Pan, and L. Yan, “Integrating and managing BIM in 3D web-based GIS for hydraulic and hydropower engineering projects,” Automation in Construction, vol. 112, p. 103114, 2020, doi: 10.1016/j.autcon.2020.103114.
[34] L. L. Zhao, J. Mbachu, and Z. Liu, “Developing an integrated BIM and GIS web-based platform for a mega construction project,” KSCE Journal of Civil Engineering, vol. 26, no. 4, pp. 1505–1521, 2022, doi: 10.1007/s12205-022-2028-5.
[35] A. Justo, M. Soilan, A. Sanchez-Rodriguez, and B. Riveiro, “Scan-to-BIM for the infrastructure domain: Generation of IFC-compliant models of road infrastructure assets using 3D point cloud data,” Automation in Construction, vol. 127, p. 103703, 2021, doi: 10.1016/j.autcon.2021.103703.
[36] M. Wang, C.-C. Wang, S. Sepasgozar, and S. Zlatanova, “A systematic review of digital technology adoption in off-site construction: Current status and future direction towards Industry 4.0,” Buildings, vol. 10, no. 11, p. 204, 2020, doi: 10.3390/buildings10110204.
[37] Z. Wu, R. Zhao, S. Bi, and W. Lu, “Barriers to modular integrated construction: A literature review and future research directions,” Engineering, Construction and Architectural Management, vol. 29, no. 9, pp. 3595–3616, 2022, doi:10.1108/ECAM-07-2021-0625.
[38] Y. E. Jang, J. W. Son, and J.-S. Yi, “BIM-based management system for off-site construction projects,” Applied Sciences, vol. 12, no. 19, p. 9878, 2022, doi: 10.3390/app12199878.
[39] H. Xu, W. Feng, Z. Li, L. Kong, S. Tang, and X. Lu, “Interaction mechanism of BIM application barriers in prefabricated construction and driving strategies from stakeholders’ perspectives,” Ain Shams Engineering Journal, vol. 14, no. 1, p. 101821, 2023, doi: 10.1016/j.asej.2022.101821.
[40] S. Siebelink, H. Voordijk, M. Endedijk, and A. Adriaanse, “Understanding barriers to BIM implementation: Their impact across organizational levels in relation to BIM maturity,” Frontiers of Engineering Management, vol. 8, no. 2, pp. 236–257, 2021, doi: 10.1007/s42524-020-0107-3.
[41] A. Darko, A. P. C. Chan, Y. Yang, M. O. Tetteh, and G. Nani, “Building information modelling (BIM) adoption in developing countries: An assessment of the profession of engineering,” Engineering, Construction and Architectural Management, vol. 27, no. 9, pp. 2255–2275, 2020, doi: 10.1108/ECAM-01- 2020-0032.
[42] S. Durdyev, J. Mbachu, D. Thurnell, L. Zhao, and M. R. Hosseini, “BIM adoption in the Cambodian construction industry: Key drivers and barriers,” ISPRS International Journal of Geo-Information, vol. 10, no. 4, p. 215, 2021, doi: 10.3390/ijgi10040215.
[43] N. Dong, Z. Liu, Z. Luo, and H. Li, “BIM application in the whole life cycle of green building: A systematic review,” Sustainability, vol. 13, no. 14, p. 7866, 2021, doi: 10.3390/su13147866.
[44] F. Pour Rahimian, S. Seyedzadeh, S. Oliver, S. Rodriguez, and N. Dawood, “On-demand monitoring of construction projects through a game-like hybrid application of BIM and machine learning,” Automation in Construction, vol. 110, p. 103012, 2020, doi: 10.1016/j.autcon.2019.103012.
[45] F. Xue, L. Wu, W. Lu, W. G. C. K. Wong, and Z. Zhao, “Semantic enrichment of building and city information models: A ten-year review,” Advanced Engineering Informatics, vol. 47, p. 101241, 2021, doi: 10.1016/j.aei.2021.101241.
[46] S. Alizadehsalehi, A. Hadavi, and J. C. Huang, “From BIM to extended reality in AEC industry,” Automation in Construction, vol. 116, p. 103254, 2020, doi: 10.1016/j.autcon.2020.103254.
[47] I. Yitmen, S. Alizadehsalehi, I. Akiner, and M. E. Akiner, “An adapted model of cognitive digital twins for building lifecycle management: Combined BIM, semantic web, and machine learning,” Applied Sciences, vol. 11, no. 6, p. 2909, 2021, doi: 10.3390/app11062909.
[48] G. B. Ozturk, “Digital twin research in the AECO-FM industry: Trends, costs, and challenges,” Journal of Building Engineering, vol. 48, p. 103704, 2022, doi: 10.1016/j.jobe.2021.103704.
[49] H. Mohammed, S. Hadleigh-Dunn, D. Hamish, and A. Omran, “Building information modeling and Internet of Things integration in the construction industry: A scoping study,” Advances in Civil Engineering, vol. 2022, p. 7886497, 2022, doi: 10.1155/2022/7886497.
Cite This Article
Choose your preferred format