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Automated Vision-Based Building Inspection Using Drone Thermography
Building energy retrofit has a significant role in achieving clean energy goals in the United States, creating a vast construction market. The initial step to improving energy efficiency is a detailed building inspection. However, building inspections are often time-consuming and not scalable. Therefore, the application of drone thermography, which can be used to create digital geometry, is explored for an automated building inspection. This application has the advantages of reducing time, labor, and safety concerns for inspection activities while solving problems of inaccessible building envelope components. Consequently, we used Infrared Thermal cameras installed on an Unmanned Aerial System to collect thermal images from building sites. The proposed workflow was started with designing a drone flight path for data collection, followed by implementing computer vision algorithms to analyze the data to identify thermal anomalies of building envelope. The paper examined a campus building in Syracuse, New York. Thermal anomalies related to cases of beam to wall thermal bridge, material degradation, and air leakage were successfully detected for the case study. Additionally, the proposed approach may be integrated with building simulation toward enriching building energy assessment. This study contributes to solve problems associated with productivity in the construction sector and to improve commercial inspection efficiency.
Automated Vision-Based Building Inspection Using Drone Thermography
Building energy retrofit has a significant role in achieving clean energy goals in the United States, creating a vast construction market. The initial step to improving energy efficiency is a detailed building inspection. However, building inspections are often time-consuming and not scalable. Therefore, the application of drone thermography, which can be used to create digital geometry, is explored for an automated building inspection. This application has the advantages of reducing time, labor, and safety concerns for inspection activities while solving problems of inaccessible building envelope components. Consequently, we used Infrared Thermal cameras installed on an Unmanned Aerial System to collect thermal images from building sites. The proposed workflow was started with designing a drone flight path for data collection, followed by implementing computer vision algorithms to analyze the data to identify thermal anomalies of building envelope. The paper examined a campus building in Syracuse, New York. Thermal anomalies related to cases of beam to wall thermal bridge, material degradation, and air leakage were successfully detected for the case study. Additionally, the proposed approach may be integrated with building simulation toward enriching building energy assessment. This study contributes to solve problems associated with productivity in the construction sector and to improve commercial inspection efficiency.
Automated Vision-Based Building Inspection Using Drone Thermography
Mirzabeigi, Shayan (author) / Razkenari, Mohamad (author)
Construction Research Congress 2022 ; 2022 ; Arlington, Virginia
Construction Research Congress 2022 ; 737-746
2022-03-07
Conference paper
Electronic Resource
English