A Semantic Web-Based Approach for Generating Parametric Models Using RDF

Farhad Sadeghineko, Bimal Kumar, Warren Chan

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

5 Citations (Scopus)

Abstract

Semantic-rich 3D parametric models, like Building Information Models (BIMs) are becoming the main information source during the entire lifespan of an asset. The use of BIM in existing buildings has been hampered by the challenges surrounding the limitations of existing technologies for developing retrofit models. Some progress has been recently made in generating non-parametric models from the Point Cloud Data (PCD). However, a proper fully developed parametric model is still some way away. In this paper, challenges are addressed by reviewing the state-of-the-art before presenting our approach. The aim of our approach is to apply the Semantic Web Technologies for generating parametric models using PCD as primary data. The Semantic Web as a set of standards and technologies is used for providing an appropriate framework for storing, sharing, and reusing the semantics of information on the web. Building elements are recognized in PCD, and the concept of Resource Description Framework (RDF) as a Semantic Web technology and a standard model for interchanging the data on the web is then used to markup detected elements. The RDF data is then standardized to Industry Foundation Classes (IFC) as an open standard building data model to generate the parametric model of the asset utilizing BIM software that supports IFC. Some parts of this ongoing research are performed manually, and the future work is to implement the process automatically. Primary results are quite promising and should be of interest to the modeling of all kinds of assets, in particular, Historical Building Information Modelling (HBIM).
Original languageEnglish
Title of host publicationAdvanced Computing Strategies for Engineering. EG-ICE 2018.
PublisherSpringer
Chapter20
Pages361-377
ISBN (Electronic)978-3-319-91638-5
ISBN (Print)978-3-319-91637-8
DOIs
Publication statusPublished - 19 May 2018

Publication series

NameAdvanced Computing Strategies for Engineering
Volume10864
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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