Automatic generation of building information models from digitized plans

Doukari, Omar and Greenwood, David (2020) Automatic generation of building information models from digitized plans. Automation in Construction, 113. p. 103129. ISSN 0926-5805

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Doukari and Greenwood 2020 20191226_AUTCON paper - AAM.pdf - Accepted Version
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Official URL: https://doi.org/10.1016/j.autcon.2020.103129

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.

Item Type: Article
Uncontrolled Keywords: Artificial intelligence, Automation, Digitized plans, Expert system, Knowledge base
Subjects: G700 Artificial Intelligence
H300 Mechanical Engineering
H700 Production and Manufacturing Engineering
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
Depositing User: Elena Carlaw
Date Deposited: 09 Mar 2020 15:12
Last Modified: 31 Jul 2021 15:05
URI: http://nrl.northumbria.ac.uk/id/eprint/42424

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