A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Automatic generation of building information models from digitized plans
Abstract This paper proposes a new approach to creating Building Information (BIM) models of existing buildings from digitized images. This automatic approach is based on three main steps. The first involves extracting the useful information automatically from rasterized plans by using image processing techniques that include segmentation, filtering, dilation, erosion, and contour detection. This information feeds the knowledge base of an expert system for BIM model generation. In the second step, using the knowledge base of the expert system, the information required to inform the BIM model can be deduced. The range of information thus obtainable can be extended beyond the examples given. The paper concludes with a discussion of the final stage: the automatic generation of an Industry Foundation Classes (IFC) information model with all the desired geometric, physical and technical information. This can be accomplished by using one of the available open-source application program interfaces (APIs). This stage is currently work-in-progress and will be the subject of a future publication.
Highlights Proposes a new approach to the automatic creation of IFC BIM models of existing buildings from digitized images The approach includes a Building Expert System to encode, represent and reproduce human expertise in order to help enriching BIM model with new information. An image-processing based algorithm to automatically calculate housing density is presented. A case study approach is utilized to comprehensively test, evaluate and validate the developed method. The paper concludes with a discussion of the next stages in the work.
Automatic generation of building information models from digitized plans
Abstract This paper proposes a new approach to creating Building Information (BIM) models of existing buildings from digitized images. This automatic approach is based on three main steps. The first involves extracting the useful information automatically from rasterized plans by using image processing techniques that include segmentation, filtering, dilation, erosion, and contour detection. This information feeds the knowledge base of an expert system for BIM model generation. In the second step, using the knowledge base of the expert system, the information required to inform the BIM model can be deduced. The range of information thus obtainable can be extended beyond the examples given. The paper concludes with a discussion of the final stage: the automatic generation of an Industry Foundation Classes (IFC) information model with all the desired geometric, physical and technical information. This can be accomplished by using one of the available open-source application program interfaces (APIs). This stage is currently work-in-progress and will be the subject of a future publication.
Highlights Proposes a new approach to the automatic creation of IFC BIM models of existing buildings from digitized images The approach includes a Building Expert System to encode, represent and reproduce human expertise in order to help enriching BIM model with new information. An image-processing based algorithm to automatically calculate housing density is presented. A case study approach is utilized to comprehensively test, evaluate and validate the developed method. The paper concludes with a discussion of the next stages in the work.
Automatic generation of building information models from digitized plans
Doukari, Omar (author) / Greenwood, David (author)
2020-02-07
Article (Journal)
Electronic Resource
English
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