• DocumentCode
    686568
  • Title

    Intelligent BVAC information capturing system for smart building information modelling

  • Author

    Tang, L.C.M. ; Cho, Seong ; Xia, Li

  • Author_Institution
    Dept. of Archit. & Built Environ. Eng., Univ. of Nottingham Ningbo China, Ningbo, China
  • fYear
    2013
  • fDate
    11-13 Dec. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Building Information Modelling (BIM) has implications for all processes and activities related to construction supply chain and can, thus, make significant contributions to lean construction process. The existing dimensions of BIM not only attend to most aspects of the construction work and processes, but the technology also has the potential to add further dimensions responding to other existing or future challenges. This paper will look into ways in which Artificial Neural Network (ANN)-COBie can help architects and engineers to perform HVAC analysis with the support of a BIM platform. Other applications e.g. HVAC load analysis and life-cycle cost analysis for any system or component associated with a building may be conducted using the ANN-COBie system that can be stored in the BIM authoring application and exported using IFC or gbXML to any analytic software. These applications´ associated future challenges will be briefly discussed.
  • Keywords
    HVAC; building management systems; buildings (structures); home automation; lean production; neural nets; power engineering computing; supply chains; ANN-COBie system; BIM authoring application; IFC; artificial neural network; construction supply chain; gbXML; intelligent HVAC information capturing system; lean construction process; smart building information modelling; Artificial neural networks; Buildings; Cooling; Data models; Heating; Humidity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics Systems and Applications (PESA), 2013 5th International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4799-3276-4
  • Type

    conf

  • DOI
    10.1109/PESA.2013.6828247
  • Filename
    6828247