IR imaging presents the temperature distribution of the exterior surface of a wall and is typically assessed through visual inspection by building science experts. A specialist must review numerous images one by one which is inefficient and inaccurate. The use of Unmanned Aerial Vehicles (UAVs) with IR camera attachments has become a method of faster and more accessible on-site building envelope evaluation. The proposed research aims to develop a machine learning framework to improve the evaluation of energy loss through the envelope, using UAV and IR thermography.
Energy-efficiency upgrades of existing buildings offer substantial energy and greenhouse gas emission reductions. Infrared thermography (IRT) of the building envelope is a non-destructive test that can be used to target retrofit actions and motivate energy efficiency improvements. Recent advances in IRT technology include using drones to collect thermal imaging data from the buildings efficiently, thoroughly, and without disturbing the occupants. The goal of this project is twofold.
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