Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115761
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dc.contributorDepartment of Building Environment and Energy Engineeringen_US
dc.creatorWong, PYLen_US
dc.creatorLo, KCCen_US
dc.creatorLong, Hen_US
dc.creatorLai, JHKen_US
dc.date.accessioned2025-10-28T02:30:30Z-
dc.date.available2025-10-28T02:30:30Z-
dc.identifier.urihttp://hdl.handle.net/10397/115761-
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.rightsCopyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Wong, P. Y. L., Lo, K. C. C., Long, H., & Lai, J. H. K. (2025). Towards Digital Transformation in Building Maintenance and Renovation: Integrating BIM and AI in Practice. Applied Sciences, 15(21), 11389 is available at https://doi.org/10.3390/app152111389.en_US
dc.subjectAIen_US
dc.subjectBIMen_US
dc.subjectDigital transformationen_US
dc.subjectRenovationen_US
dc.subjectSustainable building practicesen_US
dc.titleTowards digital transformation in building maintenance and renovation : integrating BIM and AI in practiceen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume15en_US
dc.identifier.issue21en_US
dc.identifier.doi10.3390/app152111389en_US
dcterms.abstractDigital transformation powered by Building Information Modeling (BIM) and Artificial Intelligence (AI) is reshaping renovation practices by addressing persistent challenges such as fragmented records, scheduling disruptions, regulatory delays, and inefficiencies in stakeholder coordination. This study explores the integration of these technologies through a case study of a Catholic church renovation (2022–2023) in Hong Kong, supplemented by insights from 10 comparable projects. The research proposes a practical framework for incorporating digital tools into renovation workflows that focuses on diagnosing challenges, defining objectives, selecting appropriate BIM/AI tools, designing an integrated system, and combining implementation, monitoring, and scaling into a cohesive iterative process. Key technologies include centralized BIM repositories, machine learning-based predictive analytics, Internet of Things (IoT) sensors, and robotic process automation (RPA). The findings show that these tools significantly improve data organization, proactive planning, regulatory compliance, stakeholder collaboration, and overall project efficiency. While qualitative in nature, this study offers globally relevant insights and actionable strategies for advancing digital transformation in renovation practices, with a focus on scalability, continuous improvement, and alignment with regulatory frameworks.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationApplied sciences, Nov. 2025, v. 15, no. 21, 11389en_US
dcterms.isPartOfApplied sciencesen_US
dcterms.issued2025-11-
dc.identifier.eissn2076-3417en_US
dc.identifier.artn11389en_US
dc.description.validate202510 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera4143-n01-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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