Abstract
This paper presents the problem of model comparison in platform-neutral collaboration of Building Information Models. The paper describes that model matching and comparison strategies for platform-neutral models (i.e. IFC models) are the keys to solve the problem of iterative change management during BIM collaboration workflows. It is highlighted that the current model comparison strategies are centric towards using GUIDS which may not lead to accurate results due to the complexity of modelling operations and internal data structures of modelling tools. The paper proposes a signature-based model matching approach for IFC models that use model object characteristics to define object signatures for object recognition and comparison. Examples of creating signatures from IFC object characteristics are presented. The proposed methodologies for creating IFC object signatures are implemented in a custom-built tool, XBIM Signatures exporter, which then demonstrates a successful export of object signatures on a test case. The paper concludes that the proposed object signatures can be useful to establish accurate candidates for comparison and can reduce the workload of the overall model comparison process. However, a robust solution for IFC model comparison would require a weighting formula for various object characteristics to formulate an object recognition and comparison strategy.
Original language | English |
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DOIs | |
Publication status | Published - 2018 |
Event | 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018 - Berlin, Germany Duration: Jul 20 2018 → Jul 25 2018 |
Conference
Conference | 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018 |
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Country/Territory | Germany |
City | Berlin |
Period | 7/20/18 → 7/25/18 |
Keywords
- BIM
- IFC
- Model comparison
- Model server
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Artificial Intelligence
- Building and Construction