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Integrating GIS and BIM for community building energy design

University of British Columbia

Increasing urbanization has caused a corresponding increase in energy consumption from the design, construction and operation of the built environment. To achieve energy-efficient design in urban communities, the design phase needs to adopt reliable energy modeling approaches. However, current urban modeling approaches often use abstract and low level information to describe buildings because of the difficulties of collecting and managing building data on the large scale required of such urban communities. This abstraction of building data creates large uncertainties in the modeling and simulation of energy scenarios at the community level. An additional consequence is a general separation between community energy design (with low level building information) and building energy design (with high level building information). An important part of the solution to this challenge relies on the integration of information systems at the scale of both urban communities and individual buildings, which are based on Geographic Information System (GIS) and Building Information Modeling (BIM) respectively. Since current technologies do not sufficiently address the interoperability between GIS and BIM, the existing conversion between GIS and BIM does not satisfy the data requirements for community energy design. This thesis investigates this challenge and presents an approach that uses Semantic Web technologies, including OWL (Web Ontology Language) and RDF (Resource Description Framework), to integrate GIS and BIM data. In this approach, we first develop relevant design scenarios for energy consumption in buildings of the University of British Columbia (UBC) campus. Based on the scenarios and required information for the energy simulation, we create a suitable ontology to transform the data into a Semantic Web model. Then we conduct relevant queries on the transformed data to provide the required information for energy simulation of a UBC campus neighborhood that contains richer and more detailed building information that is extracted from the campus building information models. Finally, we visualize the simulation results in a three-dimensional environment and discuss how it supports designers and decision makers engaged in community planning and design.

Text

2017-01-06

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/60287

Civil Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/