Toward More Rigorous and Automated Energy Oriented Retrofitting in Buildings

Abstract

The majority of the energy consumed by buildings in the US is used for cooling and heating. Therefore, energy-oriented retrofitting is essential for reducing overall energy usage. Infrared thermal imaging cameras can be utilized to indicate buildings' surface temperatures. In a building with good insulation, a thermal camera scan should show a how surface on a hot day; cooler areas would indicate possible points for retrofitting. Therefore, infrared thermal imaging cameras facilitate locating possible points of heat loss in buildings. However, identifying and analyzing deficiencies in the buildings using this method is labor intensive, and time consuming because it requires numerous exterior and interior scans. In addition, finding potential deficiency points is not an automated task. This paper, presents a framework-integrating image processing algorithm to ensure rapid identification of major external isolation deficiencies of the buildings by analyzing the exterior scans. The proposed method identifies major deficiencies using thermal scanning and maps them to the actual scale of the building.