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Parametric Digital Twins for Preserving Historic Buildings: A Case Study at Löfstad Castle in Östergötland, Sweden
Linköping Univ, Dept Sci & TECHNOL, Campus Norrköping, S-60174 Norrköping, Sweden..ORCID iD: 0000-0003-0931-7584
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Arts, Department of Art History, Conservation.ORCID iD: 0009-0005-8810-3956
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Arts, Department of Art History, Conservation.ORCID iD: 0000-0002-1614-5365
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Arts, Department of Art History, Conservation.ORCID iD: 0000-0002-2546-0981
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2025 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 13, p. 3371-3389Article in journal (Refereed) Published
Abstract [en]

This study showcases the digitalization of L & ouml;stad Castle in Sweden to contribute to preserving its heritage values. The castle and its collections are deteriorating due to an inappropriate indoor climate. To address this, thirteen cloud-connected sensor boxes, equipped with 84 sensors, were installed throughout the main building, from the basement to the attic, to continuously monitor various indoor environmental parameters. The collected extensive multi-parametric data form the basis for creating a parametric digital twin of the building. The digital twin and detailed data analytics offer a deeper understanding of indoor climate and guide the adoption of appropriate heating and ventilation strategies. The results revealed the need to address high humidity problems in the basement and on the ground floor, such as installing vapor barriers. Opportunities for adopting energy-efficient heating and ventilation strategies on the upper floors were also highlighted. The digitalization solution and findings are not only applicable to L & ouml;fstad Castle but also provide valuable guidance for the conservation of other historic buildings facing similar challenges.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2025. Vol. 13, p. 3371-3389
Keywords [en]
Buildings, Digital twins, Cloud computing, Data models, Internet of Things, Environmental management, Computational modeling, Atmospheric modeling, Ventilation, Ontologies, Digital twin, heritage conservation, historic building, indoor climate
National Category
Building Technologies
Identifiers
URN: urn:nbn:se:uu:diva-549597DOI: 10.1109/ACCESS.2024.3525442ISI: 001394723100039Scopus ID: 2-s2.0-85214989379OAI: oai:DiVA.org:uu-549597DiVA, id: diva2:1935233
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VinnovaSwedish Energy AgencyAvailable from: 2025-02-06 Created: 2025-02-06 Last updated: 2025-02-06Bibliographically approved

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Ni, ZhongjunHupkes, JelrikEriksson, PetraLeijonhufvud, GustafKarlsson, MagnusGong, Shaofang
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