Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/119092
DC FieldValueLanguage
dc.contributorDepartment of Building Environment and Energy Engineeringen_US
dc.contributorResearch Institute for Smart Energyen_US
dc.creatorMa, Ten_US
dc.creatorXiao, Fen_US
dc.creatorZhang, Cen_US
dc.creatorZhang, Jen_US
dc.creatorZhang, Hen_US
dc.creatorXu, Ken_US
dc.creatorLuo, Xen_US
dc.date.accessioned2026-06-02T06:18:56Z-
dc.date.available2026-06-02T06:18:56Z-
dc.identifier.issn0926-5805en_US
dc.identifier.urihttp://hdl.handle.net/10397/119092-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectArtificial intelligenceen_US
dc.subjectBuilding information modelling (BIM)en_US
dc.subjectBuilding operation managementen_US
dc.subjectDigital twin (DT)en_US
dc.subjectMixed reality (MR)en_US
dc.titleDigital twin for 3D interactive building operations : integrating BIM, IoT-enabled building automation systems, AI, and mixed realityen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume176en_US
dc.identifier.doi10.1016/j.autcon.2025.106277en_US
dcterms.abstractDigital Twin (DT) technology has emerged as a next-generation smart building management solution, seamlessly bridging traditional Building Automation Systems (BAS) with Industry 4.0 innovations such as Building Information Modelling (BIM), artificial intelligence (AI), big data, Internet of Things (IoT), and Extended Reality (XR). However, current DT applications in building operations remain nascent, challenged by multi-source data integration, technology interoperability, and visualization interface development. This study proposes a five-layer DT architecture integrating BIM, BAS, IoT, AI, and MR for 3D interactive building operations, implemented on a typical floor of a high-rise office building incorporating its central air conditioning system. The DT demonstrated both on-site and remote capabilities, including BIM visualization, mapping and navigation, indoor environment monitoring, portable HVAC system monitoring and control, and AI-empowered optimization. These capabilities represent significant advantages in terms of operation management, work efficiency, operator experience and response speed.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationAutomation in construction, Aug. 2025, v. 176, 106277en_US
dcterms.isPartOfAutomation in constructionen_US
dcterms.issued2025-08-
dc.identifier.scopus2-s2.0-105004878363-
dc.identifier.eissn1872-7891en_US
dc.identifier.artn106277en_US
dc.description.validate202606 bchyen_US
dc.description.oaNot applicableen_US
dc.identifier.SubFormIDG001755/2026-02-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe authors gratefully acknowledge the support of this research by the National Key R&D Program of China (2021YFE0107400) and Innovation and Technology Fund (ITP/002/22LP) of the Hong Kong SAR, China.en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2027-08-31en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2027-08-31
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