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dc.contributor.authorBalogun, Habeeb
dc.contributor.authorAlaka, Hafiz
dc.contributor.authorDemir, Eren
dc.contributor.authorEgwim, Christian Nnaemeka
dc.contributor.authorSulaimon, Ismail
dc.contributor.authorOlu-Ajayi, Razak
dc.contributor.authorOseghale, Raphael
dc.date.accessioned2024-09-03T16:30:05Z
dc.date.available2024-09-03T16:30:05Z
dc.date.issued2024-10
dc.identifier.citationBalogun , H , Alaka , H , Demir , E , Egwim , C N , Sulaimon , I , Olu-Ajayi , R & Oseghale , R 2024 , ' Artificial intelligence for deconstruction: Current state, challenges, and opportunities ' , Automation in Construction , vol. 166 , 105641 , pp. 1-15 . https://doi.org/10.1016/j.autcon.2024.105641
dc.identifier.issn0926-5805
dc.identifier.urihttp://hdl.handle.net/2299/28121
dc.description© 2024 The Authors. Published by Elsevier B.V. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/
dc.description.abstractArtificial intelligence and its subfields, such as machine learning, robotics, optimisation, knowledge-based systems, reality capture and extended reality, have brought remarkable advancements and transformative changes to various industries, including the building deconstruction industry. Acknowledging AI's benefits for deconstruction, this paper aims to investigate AI applications within this domain. A systematic review of existing literature focused on AI applications for planning, implementation and post-implementation activities within the context of deconstruction was carried out. Furthermore, the challenges and opportunities of AI for deconstruction activities were identified and presented in this paper. By offering insights into AI's application for key deconstruction activities, this paper paves the way for realising AI's potential benefits for this sector.en
dc.format.extent15
dc.format.extent4852973
dc.language.isoeng
dc.relation.ispartofAutomation in Construction
dc.subjectArtificial intelligence
dc.subjectChallenges
dc.subjectDeconstruction
dc.subjectOpportunities
dc.subjectSustainability
dc.subjectControl and Systems Engineering
dc.subjectCivil and Structural Engineering
dc.subjectBuilding and Construction
dc.titleArtificial intelligence for deconstruction: Current state, challenges, and opportunitiesen
dc.contributor.institutionCentre for Future Societies Research
dc.contributor.institutionCentre for Climate Change Research (C3R)
dc.contributor.institutionHertfordshire Business School
dc.contributor.institutionStatistical Services Consulting Unit
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85199928678&partnerID=8YFLogxK
rioxxterms.versionofrecord10.1016/j.autcon.2024.105641
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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