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Digital Tools for Fast Mapping of Buildings
Politecnico di Milano, Italy.
RISE Research Institutes of Sweden, Built Environment, Building and Real Estate.ORCID iD: 0000-0003-2210-3003
CGI Sverige AB, Sweden.
2022 (English)In: SpringerBriefs in Applied Sciences and Technology, Springer Science and Business Media Deutschland GmbH , 2022, p. 51-62Chapter in book (Other academic)
Abstract [en]

While the construction sector embraces digitalization, new technologies related to it are spreading benefits. The need of creating a 3D model of a building, a digital copy of something existing, is not new. Mediated by the advent of photographic and laser instrumentation, the construction of a digital model has crossed the fields of surveying with increasing accuracy and precision, imposing standards of capturing the existing first and modelling then ever higher. But while the Building Information Modelling allows a virtual representation of the existing asset enriching its geometry with precious and significant information related to its properties, advanced survey has always faced the impossibility to break the surface of the building, surveying what is inside walls, thus excluding what necessary should be contained within a BIM model. Also, BIM models do not consider the real-time component and do not report the real-time behaviour of the building. In this chapter we will investigate several technologies and instruments exploited till now for the surveying and positioning of existing buildings, plants included, and a new toolkit based on AR that, coupled with sensors and visualisation tools developed by BIM4EEB, offers many advantages when surveying the whole building. © 2022, The Author(s).

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH , 2022. p. 51-62
Keywords [en]
Advanced survey, Augmented reality, Digital, IFC, Sensors, 3D modeling, Architectural design, Construction industry, Digital devices, 3D models, 3d-modeling, Accuracy and precision, Construction sectors, Digital copy, Digital modeling, Digital tools, Surveys
National Category
Civil Engineering
Identifiers
URN: urn:nbn:se:ri:diva-59867DOI: 10.1007/978-3-031-04670-4_4Scopus ID: 2-s2.0-85133539123OAI: oai:DiVA.org:ri-59867DiVA, id: diva2:1685104
Available from: 2022-08-01 Created: 2022-08-01 Last updated: 2023-05-16Bibliographically approved

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Kurkinen, Eva-Lotta

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • Other style
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Language
  • de-DE
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  • en-US
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  • nn-NO
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Output format
  • html
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  • asciidoc
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