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dc.contributor.authorSaeed, Zaid Osama
dc.contributor.authorMancini, Francesco
dc.contributor.authorGlusac, Tanja
dc.contributor.authorIzadpanahi, Parisa
dc.date.accessioned2022-05-24T12:43:28Z
dc.date.available2022-05-24T12:43:28Z
dc.date.issued2022
dc.identifier.citationSaeed, Z.O. and Mancini, F. and Glusac, T. and Izadpanahi, P. 2022. Artificial Intelligence and Optimization Methods in Construction Industry. Buildings. 12(5): Article No. 685.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/88569
dc.identifier.doi10.3390/buildings12050685
dc.description.abstract

Digitalisation and the future city paradigm are becoming a trend in recent research and practices. The literature discusses digitalisation and its applications as the main gear in the transformation to the ideal future city vision. Yet, the concept of digitalisation is articulated in many interpretations and presented in different applications in the built environment. One emerging application is digital twinning. Literature envisions the potential of digital twinning applications in the urban realm and discusses the cognitive city model and its implications on the future of our cities, its urban realm and the built environment in general. With the evolving themes on the ideal future city model, this systematic review tackles the following questions: what are the key motives and drivers of the future city paradigm; what is a city digital twin; and what are their expected applications. Additionally, how literature envisions the definition of the city users and their experience in the urban realm of the city of the future. This review article explores related literature on the themes of the future city model, digital urban realm, digital twinning and city users. The main findings are: identifying key gears of the future city model in literature, exploring city digital twin conceptualization and applications and discussing concepts on the definition of city user and user experience in the city of the future.

dc.languageEnglish
dc.publisherMDPI AG
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject3301 - Architecture
dc.subject3304 - Urban and regional planning
dc.titleArtificial Intelligence and Optimization Methods in Construction Industry
dc.typeJournal Article
dcterms.source.volume12(5)
dcterms.source.number685
dcterms.source.issn2075-5309
dcterms.source.titleBuildings
dc.date.updated2022-05-24T12:43:24Z
curtin.departmentSchool of Design and the Built Environment
curtin.accessStatusOpen access
curtin.facultyFaculty of Humanities
curtin.contributor.orcidMancini, Francesco [0000-0001-7119-7056]


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