Evaluation of IFC for the Augmentation of Intelligent Transportation Systems (ITS) into Bridge Information Models (BrIM)

ABSTRACTIntelligent transportation systems (ITS) produce valuable data by using various sensors incorporated with transportation infrastructure. The use of ITS has transformed infrastructure management by making it easier and more efficient. Quality and comprehensiveness of the ITS data have direct impact on the effectiveness of planning, design, and maintenance activities. Previous research suggested that the fusion of ITS data with bridge information modeling (BrIM) can provide a reliable visual database that can satisfy design and maintenance needs while enhances the integration and management of databases. However, one major challenge identified is the lack of interoperability between the various software and systems required for the fusion. The industry foundation classes (IFC) is an international data exchange standard for building information modeling (BIM) that has been developed for the exchange of data within the building industry. Recently, IFC has been developed to include the required elements for modeling transportation infrastructure including bridges, highways, and tunnels. This research investigates the use of IFC to include the data that have been produced through ITS and are needed for the full exchange of information between transportation stakeholders. The scope of this paper is to provide a high-level evaluation of IFC to determine the feasibility and applicability of the augmentation of BrIM and ITS fusion data. The result of this research will help in the improvement of communication and collaboration between designers and stakeholders that can eventually help the management of transportation infrastructure.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 177-184
  • Monograph Title: Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation

Subject/Index Terms

Filing Info

  • Accession Number: 01708130
  • Record Type: Publication
  • ISBN: 9780784482421
  • Files: TRIS, ASCE
  • Created Date: Jun 20 2019 5:19PM