Automated Reconstruction of 3d As-built Building Information Model for Building Energy Performance Assessment

The integration of three-dimensional (3D) data with infrared thermography has received much attention for its potential use as input data for building energy simulations. Therefore, researchers have proposed methods to integrate 3D data with infrared thermography obtained by different sensors. These studies show the potential of the integration of 3D data and infrared thermography using various systems. However, these studies have ignored property aspects of infrared thermography, such as the low resolution of infrared thermography and external environmental influences. Thus, their proposed methods to integrate 3D data and infrared thermography are inadequate because these problems can affect the resulting building energy simulation. This research proposes a framework that integrates infrared thermography and 3D data while accounting for the resolution and shadow effect of infrared thermography. The proposed framework consists of three steps. In the resolution enhancement step, bi-cubic interpolation is proposed. In thermal data correction from the shadow effect, the shadow area is detected from the visible image, and then the shadow effect is removed from the registered infrared thermography. Finally, enhanced infrared thermography is mapped to the 3D data obtained by a laser scanner. The performance of the proposed framework was evaluated using test images obtained from a building in operation. The experimental results show that the proposed framework provides a 3D thermal model that is useful and accurate in simulating building energy. It is expected that the 3D thermal model can be used for accurate energy simulation of existing buildings. In addition, the proposed framework can be applied in defect detection for buildings. Furthermore, this novel approach enhances infrared thermography using visible images.