The goal of the research was to create a new automated system for making 3D models of buildings to improve energy modeling accuracy. The researchers used deep learning algorithms, drones, and GIS data to collect information and generate detailed models. They found that the generated models had small errors in size and energy performance compared to actual buildings, with cooling and heating energy values being within 5-6% of the real values.