Editorial: Digital transformation in construction: integrating metaverse, digital twin, and BIM

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a comprehensive overview of current research trends in construction digitalization and its link to sustainability, useful for identifying research gaps.

🏢実務担当者:Highlights practical applications of BIM, digital twins, and metaverse for improving safety, efficiency, and carbon management in construction projects.

🏛政策担当者:Shows how digital transformation can support regulatory digitalization and carbon reduction in the construction sector, informing policy for smart and sustainable infrastructure.

The Research Topic "Digital Transformation in Construction: Integrating Metaverse, Digital Twin, and BIM" brings together scholarship on how data-rich, model-based, and immersive technologies are reshaping the built environment. Its aim is to examine how BIM, digital twins, and metaverse-related technologies can improve sustainability, resilience, safety, productivity, and lifecycle decision-making in construction and infrastructure. This focus is timely because immersive technology for the built world was identified among the World Economic Forum top emerging technologies of 2024 (World Economic Forum, 2024), while buildings and construction account for about 37% of global emissions in recent global reporting (UNEP and GlobalABC, 2025).The articles in this Research Topic advance the field by moving beyond isolated digital tools toward connected cyber-physical and socio-technical ecosystems. BIM provides structured object, process, and asset information; digital twins extend this information through sensing, feedback, simulation, and lifecycle updating; and metaverse environments offer immersive spaces for visualization, training, coordination, and decision support. This progression is consistent with earlier research that framed the digital twin as a bridge between physical systems and their virtual representations (Kritzinger et al., 2018), emphasized the need for semantic construction digital twins (Boje et al., 2020), and mapped the evolution from BIM to digital twins in the AEC-FM industry (Deng et al., 2021). This Research Topic contributes to knowledge by connecting research streams that are often examined separately: BIM-based information management, AI-enabled analytics, sensing and reality capture, digital twin workflows, immersive visualization, and digital transformation for sustainability. The papers operate across project, asset, enterprise, and sector scales, addressing safety communication, inspection, drawing digitization, heritage documentation, road models, procurement, carbon reduction, circularity, and regulatory digitalization. Together, they show that digital transformation is not a single technology shift, but a coordinated change in data, workflows, skills, governance, and human interaction.The broader contribution of the collection is its emphasis on implementation. The papers move beyond conceptual enthusiasm for BIM, digital twins, and metaverse technologies by showing how these tools can be evaluated through pilot studies, computational models, systematic reviews, case studies, and methods papers. They also identify persistent research needs, including interoperability, semantic enrichment, cybersecurity, data governance, ethical use, workforce adoption, and field validation. In doing so, the collection helps define an applied research agenda for a built environment that is more intelligent, resilient, sustainable, and inclusive. Figure 1 summarizes the overarching themes of this Research Topic and shows how BIM, digital twins, immersive technologies, and data-driven intelligence collectively support digital transformation in the built environment. The published contributions can be organized into five article-type categories: Original Research, Systematic Review, Review, Methods, and Opinion. The Original Research papers provide empirical, computational, and casebased evidence on digital safety, structural engineering, digital twins, heritage documentation, road modeling, carbon reduction, and circular material tracking. The Systematic Review and Review papers consolidate evidence on immersive technologies, engineering procurement, bridge maintenance, and digital twins for energy and indoor environmental quality. The Methods and Opinion papers address regulatory document digitalization and the conceptual transition from BIM to digital twins and the metaverse.The Original Research category begins with studies focused on safety, AI, and construction intelligence. Baikati et al. (2026), in "Integrating BIM and VR for enhanced safety communication and training in construction," develop BIM-enabled VR safety training for multilingual construction environments. Ying et al. (2026), in "An Efficient Deep Learning Framework for Text Detection and Recognition in Engineering Drawings," propose deep learning for extracting rebar annotations from complex drawings. Kookalani et al. (2026), in "Interpretable machine learning for predicting the bearing capacity of double shear-bolted connections," combine predictive modeling with interpretability to support data-driven steel design. Prabhu et al. (2026), in "Artificial intelligence-driven safety assessment of scaffolding using LiDAR sensing," present a cloud-based workflow for automated scaffolding inspection.A second group addresses digital twins, reality capture, heritage, infrastructure semantics, enterprise transformation, and circularity. Ramón-Constantí et al. (2026), in "Integrating thermal point clouds into BIM-GIS environments," propose a BIM-GIS workflow for multi-layer thermal digital twins. Li and Willkens (2026), in "Digital transformation through multi-device HBIM workflow," present a scan-to-HBIM workflow for adaptive reuse of the Odd Fellows Building in Atlanta. Crampen and Blankenbach (2025), in "Data enrichment for semantic segmentation of point clouds for the generation of geometric-semantic road models," enrich point-cloud segmentation with semantic information for road modeling. Zhao et al. (2025), in "Digital transformation of construction enterprises and carbon emission reduction," provide listed-company evidence on digital transformation and carbon reduction. Shehu et al. (2025), in "Opportunities for digital tracking technologies in the precast concrete sector in Sweden," examine digital tracking technologies for circular economy practices in precast concrete.The Systematic Review category is represented by Sornoza-Parrales et al. (2025), whose paper, "Evolution and research trends in virtual reality and augmented reality technologies for the architecture, engineering, and construction industry," uses systematic review and science mapping methods to clarify the development of AR and VR research in AEC. The paper helps situate immersive technologies within broader trends involving digital twins, metaverse applications, and project lifecycle integration.The Review category expands the collection from immersive environments to procurement, infrastructure maintenance, and building performance. Awodele et al. (2026), in "The Role of Digital Technologies in Engineering Procurement," synthesize literature on AI, blockchain, IoT, BIM, robotic process automation, and eprocurement, showing how engineering procurement is becoming a strategic, data-driven capability. Medrano-Sanchez and Martos (2025), in "Strategies for bridge maintenance using BIM," review BIM-based bridge maintenance methods and tools, identify gaps in interoperability and skills, and highlight the importance of preventive and data-driven asset management. Venkateswarlu and Sathiyamoorthy (2025), in "Sustainable innovations in digital twin technology," review digital twin research related to energy efficiency and indoor environmental quality, showing how digital twins can support sustainable building operation and occupant wellbeing.The Methods category is represented by Kabzhan et al. (2025), whose paper, "Semantic and ontology-based analysis of regulatory documents for construction industry digitalization," develops an automated approach for analyzing construction regulatory documents using ontology modeling and natural language processing. This contribution addresses a central barrier to digital transformation: the conversion of complex, changing, and textheavy regulatory requirements into structured knowledge that can support digital workflows. The Opinion category is represented by Noroozinejad Farsangi et al. (2024), "Transitioning from BIM to Digital Twin to Metaverse," which provides a conceptual framing for the movement from static information models to dynamic digital twins and then to immersive, interconnected metaverse environments. This opinion paper helps anchor the collection by clarifying the conceptual pathway that links many of the empirical and review contributions.Collectively, the papers in this Research Topic show that digital transformation in construction is entering a more integrated and evidence-based phase. The field is moving from stand-alone BIM models and isolated visualization tools toward interoperable digital twins, intelligent sensing, AI-enabled analytics, semantic information structures, immersive interfaces, and digitally supported sustainability strategies. The collection advances knowledge by connecting technical innovation with real problems in safety, infrastructure management, heritage conservation, procurement, carbon reduction, circularity, and regulatory modernization.Future work may extend this discussion toward generative AI, secure and ethical digital twins, metaverse-enabled collaboration, digital product passports, cyber-physical jobsites, and human-centered adoption.

• openalex https://doi.org/10.3389/fbuil.2026.1905914first seen 2026-08-02 16:43:45