Record link: 
http://hdl.handle.net/20.500.12708/188981
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Title: 
From Sketching to BIM – Workflow for the generation of IFC-based BIM models from 4D semantic sketches
en
Citation: 
Stauß, P., Rasoulzadeh, S., Reisinger, J., & Kovacic, I. (2023). From Sketching to BIM – Workflow for the generation of IFC-based BIM models from 4D semantic sketches. In W. Dokonal, U. Hirschberg, & G. Wurzer (Eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) (pp. 241–250). https://doi.org/10.52842/conf.ecaade.2023.1.241
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Publisher DOI: 
10.52842/conf.ecaade.2023.1.241
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Publication Type: 
Inproceedings - Full-Paper Contribution
en
 
Konferenzbeitrag - Full-Paper Contribution
de
Language: 
English
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Authors: 
Stauß, Philipp 
Rasoulzadeh, Shervin 
Reisinger, Julia 
Kovacic, Iva 
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Organisational Unit: 
E210-01 - Forschungsbereich Integrale Planung und Industriebau 
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Published in: 
Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) 
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ISBN: 
978-9-49120-734-1
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Volume: 
1
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Date (published): 
2023
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Event name: 
41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) 
en
Event date: 
20-Sep-2023 - 22-Sep-2023
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Event place: 
Graz, Austria
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Number of Pages: 
10
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Keywords: 
Conceptual Design; Sketch-based Modelling; Building Information Modelling (BIM); Industry Foundation Classes (IFC)
en
Abstract: 
The preliminary development of highly detailed BIM models lacks eligible design methods in the conceptual design stage. Initial design solutions cannot be shared among collaborative and consecutive design parties without relying on error-prone briefings and data exchanges. As advances in Artificial Intelligence are increasingly being used for BIM’s big data challenges, this paper presents a workflow based on a small scope of IFC definitions for the generation of conceptual BIM models from 4D semantic sketches, using a machine learning based pipeline. The workflow offers a user-friendly architectural design perspective, while preserving information more reliably throughout the entire life cycle of a BIM model.
en
Research Areas: 
Development and Advancement of the Architectural Arts: 25%
Computer Science Foundations: 25%
Modeling and Simulation: 50%
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Science Branch: 
2011 - Bauingenieurwesen: 50%
2012 - Architektur: 50%
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Appears in Collections:
Conference Paper

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