Soroush Motayyeb; Farhad Samadzadegan; Farzaneh Dadrasjavan
Abstract
Extended AbstractIntroduction, MaterialsImproving energy efficiency in buildings has become a major topic of interest in recent studies. Modern technologies have improved energy performance in new buildings. However, there is a growing demand for inspecting old buildings and enhancing their energy efficiency. ...
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Extended AbstractIntroduction, MaterialsImproving energy efficiency in buildings has become a major topic of interest in recent studies. Modern technologies have improved energy performance in new buildings. However, there is a growing demand for inspecting old buildings and enhancing their energy efficiency. Areas of heat dissipation are the most significant faults in insulation occurring as a result of thermal bridge, excessive heat loss, air leakage, or defective thermal insulation in building components. Heat dissipation mainly occurs on the facade. Lack of sufficient information on the energy performance and associated costs of retrofitting buildings have made visualization and determination of the heat dissipation areas crucial for improving energy efficiency. The present study primarily seeks to determine areas of heat dissipation on building facades in order to optimize energy efficiency and energy storage in buildings. A vertical flight Unmanned Aerial Vehicle (UAVs) with low altitude flight, equipped with Post-Processing Kinematic (PPK) module and MC1-640s thermal infrared camera made by KeiiElectro Optics Technology at a rate of 30 frames per second have been utilized in the present study to gather the needed data. Also, thermal infrared images of the building facade were collected from PedarSalar palace in Aliabad village, Aradan-Garmsar city with a longitude of 52.3034 and a latitude of 35.1600 in order to assess the proposed method. Methods, ResultsThe present study seeks to propose a method for visualizing and determining the heat dissipation areas in facades with the aim of increasing energy efficiency. The proposed research method was divided into two parts. The first stage involved the generation of a dense point cloud and related orthophotomosaics utilizing thermal infrared images collected by UAVs, bundles adjustment, Structure from Motion (SfM) and Multi View Stereo (MVS) algorithms. The second stage involved converting the thermal infrared orthophotomosaic to HSV color space in order to choose the seed pixels for the Region-Growing-based segmentation algorithm. Since Hue-Saturation-Value (HSV) color space performs better when visualizing the concept of light, seed pixels were chosen from the HSV color space pixels with the highest degrees of grayscale to enter the segmentation algorithm. Then, introducing the seed pixels as input to the Region-Growing algorithm, areas of heat dissipation were automatically determined in the facade.A dense thermal infrared point cloud was produced with a density of 1779067 points per square meter, Reprojection error of 0.41 pixels and Ground Sample Distance (GSD) of 0.75 cm using 45 thermal infrared images captured by UAVs flying perpendicular to the facade of the building at a distance of 11 meters and a flight altitude of 1.70 meters. The Precision and Recall evaluation criteria have been employed to analyze detected areas of heat dissipation. Precision and recall evaluation criteria equaled 90 percent and 87 percent, respectively. Results indicated that the proposed method has improved precision and recall evaluation criteria and determined areas of heat dissipation with higher accuracy. Discussion, ConclusionGiven the critical importance of improving energy efficiency, and potential energy storage and reducing energy consumption in buildings and costs of production, obtaining related data to find optimization solutions is critical especially in older buildings. Since heat dissipation mainly occurs on the facade, the present study seeks to identify and determine areas of heat dissipation on the facade to visualize and improve energy efficiency applying the Region-Growing segmentation algorithm on the thermal infrared orthophotomosaic generated by photogrammetry UAVs. Since the HSV color space shows higher resolution in distribution of pixels used to extract areas of high temperature, seed pixels were introduced to the Region-Growing segmentation algorithm. Finally, precision and recall evaluation criteria were used to determine the accuracy of heat dissipation areas automatically detected on orthophotomosaics. Thus, the accuracy of the proposed method has been evaluated using the precision and recall criteria resulting in 90% and 87 %, respectively. Results indicated increased accuracy of the proposed heat dissipation detection method as compared to previous studies.
