BIM Integration Across Engineering Disciplines: A Systematic
Review of Methodological Advances, Interoperability
Challenges, and Emerging Digital Frameworks
Ann Wolter1,* Paul Bailey2 Raja Ahmed Hassan2 Wipitha Mazungwi3
1HAN University of Applied Sciences, Arnhem, The Netherlands
2School of Science, Engineering and Environment, University of Salford, UK
3The School of Science, Engineering and Environment, University of Salford, Manchester, UK
Emails: Ann.Wolter@han.nl; pj_bailey@outlook.com; rahmedh@gmail.com; tracymwipitha@gmail.com
Received: December 12, 2025 Revised: January 19, 2026 Accepted: February 27, 2026 ⋆ Corresponding author
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 prioritising
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: Building information modeling Digital twin Machine learning Interoperability IFC Systematic
review BIM–GIS Facility management Smart construction Digital workflow