Data completion in building information management: electrical lines from range scans and photographs

Ulrich Krispel, Henrik Leander Evers, Martin Tamke, Torsten Ullrich

Research output: Contribution to journalArticleResearchpeer-review

Abstract


Background

The concept of building information management (BIM) is based on its holistic nature. This idea pays off, if all relevant information is fused into one consistent data set. As a consequence, the completeness of data is vital and the research question on how to complete data automatically remains open.
Methods

In this article we present a data completion technique based on knowledge management. We encode expert and domain knowledge in a generative system that represents norms and standards in a machine-readable manner. The implementation of this approach be used to automatically determine a hypothesis on the location of electrical lines within indoor range scans.
Results

The generative paradigm can encode domain expert knowledge in a machine-readable way. In this article we demonstrate its usage to represent norms and standards.
Conclusions

The benefit of our method is the further completion of digital building information models – a necessary step to take full advantage of building information modeling.
LanguageEnglish
Number of pages11
JournalVisualization in Engineering
Volume5
Issue number1
DOIs
StatusPublished - 21 Mar 2017

Fingerprint

Information Management
Information management
Completion
Line
Knowledge management
Range of data
Norm
Knowledge Management
Domain Knowledge
Completeness
Paradigm
Necessary
Modeling
Demonstrate
Standards
Model

Keywords

  • Data completion
  • Formal language
  • Shape grammars
  • Knowledge Management

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications

Cite this

Data completion in building information management: electrical lines from range scans and photographs. / Krispel, Ulrich; Evers, Henrik Leander; Tamke, Martin; Ullrich, Torsten.

In: Visualization in Engineering, Vol. 5, No. 1, 21.03.2017.

Research output: Contribution to journalArticleResearchpeer-review

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