A Digital Twin City Model for Age-Friendly Communities: Capturing Environmental Distress from Multimodal Sensory Data

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dc.contributor.authorAhn, Changbum
dc.contributor.authorHam, Youngjib
dc.contributor.authorKim, Jinwoo
dc.contributor.authorKim, Jaeyoon
dc.date.accessioned2020-01-04T07:29:38Z
dc.date.available2020-01-04T07:29:38Z
dc.date.issued2020-01-07
dc.description.abstractAs the worldwide population is aging, the demands of aging-in-place are also increasing and require smarter and more connected cities to keep mobility independence of older adults. However, today’s aging built environment often poses great environmental demands to older adults’ mobility and causes their distresses. To better understand and help mitigating older adults’ distress in their daily trips, this paper proposes constructing the digital twin city (DTC) model that integrates multimodal data (i.e., physiological sensing, visual sensing) on environmental demands in urban communities, so that such environmental demands can be considered in mobility planning of older adults. Specifically, this paper examines how data acquired from various modalities (i.e., electrodermal activity, gait patterns, visual sensing) can portray environmental demands associated with older adults’ mobility. In addition, it discusses the challenges and opportunities of multimodal data fusion in capturing environmental distresses in urban communities.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2020.206
dc.identifier.isbn978-0-9981331-3-3
dc.identifier.urihttp://hdl.handle.net/10125/63945
dc.language.isoeng
dc.relation.ispartofProceedings of the 53rd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSmart City Digital Twins
dc.subjectaging-in-place
dc.subjectbuilt environment assessment
dc.subjectdigital twin city
dc.subjectphysiological signals
dc.subjectvisual sensing
dc.titleA Digital Twin City Model for Age-Friendly Communities: Capturing Environmental Distress from Multimodal Sensory Data
dc.typeConference Paper
dc.type.dcmiText

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