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The use of artificial intelligence in BIM and user preferences data: A framework for design sustainability evaluation and improved decision making
Jönköping University, School of Engineering, JTH, Civil Engineeering and Lighting Science.
Jönköping University, School of Engineering, JTH, Civil Engineeering and Lighting Science.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Användning av artificiell intelligens i BIM och användarpreferenser data: Ett ramverk för designens hållbarhet utvärdering och för förbättrat beslutsfattande (Swedish)
Abstract [en]

Sustainability evaluation in building designs needs to consider the three aspects of sustainability, social, environmental and economic, simultaneously. The social aspect is less focused on the existing sustainability assessment methodologies and should be more incorporated in the assessment. The aim of this paper is to contribute a new method to sustainability evaluation that incorporates user preferences and important factors from the three aspects of sustainability and investigates Artificial intelligence (AI) for finding the best design that fits the user needs. Therefore, a framework in which a metric to compute the design quality of life (QoL) and an algorithm for evaluating design sustainability is proposed for best decision making. Building users, experts, and data from Building Information Modelling (BIM) simulation results were incorporated into the process. The study involves a literature review, a survey for collecting user preferences as methods and an experiment for testing the framework. Artificial data from designs and user is used in the experiment as inputs. The results demonstrate the feasibility of this framework to evaluate design sustainability and approximate the design that fits best the user’s requirements based on the three aspects of sustainability simultaneously. User preferences are incorporated into the framework to improve evaluating the social aspect of sustainability. More comprehensive design sustainability evaluation can be developed based on the proposed framework.

Place, publisher, year, edition, pages
2019. , p. 26
Keywords [en]
Sustainability evaluation, Social sustainability, Artificial intelligence, user preferences
National Category
Environmental Analysis and Construction Information Technology
Identifiers
URN: urn:nbn:se:hj:diva-45583ISRN: JU-JTH-PRU-2-20190146OAI: oai:DiVA.org:hj-45583DiVA, id: diva2:1343636
Subject / course
JTH, Civil Engineering
Supervisors
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Available from: 2019-08-20 Created: 2019-08-18 Last updated: 2019-08-23Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf