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
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;
Conference_Titel :
Power Electronics Systems and Applications (PESA), 2013 5th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4799-3276-4
DOI :
10.1109/PESA.2013.6828247