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Dynamically loading IFC models on a web browser based on spatial semantic partitioning

Industry foundation classes (IFC) is an open and neutral data format specification for building information modeling (BIM) that plays a crucial role in facilitating interoperability. With increases in web-based BIM applications, there is an urgent need for fast loading large IFC models on a web brow...

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Detalles Bibliográficos
Autores principales: Lu, Hong-Lei, Wu, Jia-Xing, Liu, Yu-Shen, Wang, Wan-Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099568/
https://www.ncbi.nlm.nih.gov/pubmed/32240404
http://dx.doi.org/10.1186/s42492-019-0011-z
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author Lu, Hong-Lei
Wu, Jia-Xing
Liu, Yu-Shen
Wang, Wan-Qi
author_facet Lu, Hong-Lei
Wu, Jia-Xing
Liu, Yu-Shen
Wang, Wan-Qi
author_sort Lu, Hong-Lei
collection PubMed
description Industry foundation classes (IFC) is an open and neutral data format specification for building information modeling (BIM) that plays a crucial role in facilitating interoperability. With increases in web-based BIM applications, there is an urgent need for fast loading large IFC models on a web browser. However, the task of fully loading large IFC models typically consumes a large amount of memory of a web browser or even crashes the browser, and this significantly limits further BIM applications. In order to address the issue, a method is proposed for dynamically loading IFC models based on spatial semantic partitioning (SSP). First, the spatial semantic structure of an input IFC model is partitioned via the extraction of story information and establishing a component space index table on the server. Subsequently, based on user interaction, only the model data that a user is interested in is transmitted, loaded, and displayed on the client. The presented method is implemented via Web Graphics Library, and this enables large IFC models to be fast loaded on the web browser without requiring any plug-ins. When compared with conventional methods that load all IFC model data for display purposes, the proposed method significantly reduces memory consumption in a web browser, thereby allowing the loading of large IFC models. When compared with the existing method of spatial partitioning for 3D data, the proposed SSP entirely uses semantic information in the IFC file itself, and thereby provides a better interactive experience for users.
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spelling pubmed-70995682020-03-31 Dynamically loading IFC models on a web browser based on spatial semantic partitioning Lu, Hong-Lei Wu, Jia-Xing Liu, Yu-Shen Wang, Wan-Qi Vis Comput Ind Biomed Art Original Article Industry foundation classes (IFC) is an open and neutral data format specification for building information modeling (BIM) that plays a crucial role in facilitating interoperability. With increases in web-based BIM applications, there is an urgent need for fast loading large IFC models on a web browser. However, the task of fully loading large IFC models typically consumes a large amount of memory of a web browser or even crashes the browser, and this significantly limits further BIM applications. In order to address the issue, a method is proposed for dynamically loading IFC models based on spatial semantic partitioning (SSP). First, the spatial semantic structure of an input IFC model is partitioned via the extraction of story information and establishing a component space index table on the server. Subsequently, based on user interaction, only the model data that a user is interested in is transmitted, loaded, and displayed on the client. The presented method is implemented via Web Graphics Library, and this enables large IFC models to be fast loaded on the web browser without requiring any plug-ins. When compared with conventional methods that load all IFC model data for display purposes, the proposed method significantly reduces memory consumption in a web browser, thereby allowing the loading of large IFC models. When compared with the existing method of spatial partitioning for 3D data, the proposed SSP entirely uses semantic information in the IFC file itself, and thereby provides a better interactive experience for users. Springer Singapore 2019-06-03 /pmc/articles/PMC7099568/ /pubmed/32240404 http://dx.doi.org/10.1186/s42492-019-0011-z Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Lu, Hong-Lei
Wu, Jia-Xing
Liu, Yu-Shen
Wang, Wan-Qi
Dynamically loading IFC models on a web browser based on spatial semantic partitioning
title Dynamically loading IFC models on a web browser based on spatial semantic partitioning
title_full Dynamically loading IFC models on a web browser based on spatial semantic partitioning
title_fullStr Dynamically loading IFC models on a web browser based on spatial semantic partitioning
title_full_unstemmed Dynamically loading IFC models on a web browser based on spatial semantic partitioning
title_short Dynamically loading IFC models on a web browser based on spatial semantic partitioning
title_sort dynamically loading ifc models on a web browser based on spatial semantic partitioning
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099568/
https://www.ncbi.nlm.nih.gov/pubmed/32240404
http://dx.doi.org/10.1186/s42492-019-0011-z
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