As–built Residential Building Information Collection and Modeling Methods for Energyanalysis

Existing buildings represent the greatest opportunity to improve building energy efficiency and reduce environmental impacts. However, millions of decision makers of the buildings usually lack sufficient information or tools for measuring their building’s energy performance. The goal of this project is to develop and evaluate rapid low-cost measurement and modeling approaches that will allow “virtual” representations for the energy and environmental performance of existing houses to be created for retrofit decision-support tools for the decision makers. To conduct an energy analysis or simulation, obtaining accurate geometric information of the house is critical. As an on-going research project, a digital image processing technique has been developed to extract digitized and vectorized house information with a high confidence and accuracy level (95%) from floor plan images available in a large local online database containing more than 150,000 houses. In addition, the elevation-view images of several houses have been tested to extract vertical view information. The algorithm can correctly recognize and extract basic geometric information of house envelops required for the energy analysis including windows, doors, walls, and a roof.