## 4 Conclusions and Corrective Actions  
This study showed that IRT is a valid assessment method for envelopes and, in particular, for the wine cellar studied, where thermal stability is even more critical. Wine ageing is strongly affected by environmental factors; therefore, the detection of thermal insulation failures, heat leakage through joineries, and the presence of humidity must be identified and avoided. The use of a UAS with an on-board camera has proven to be effective, especially in difficult-to-access areas such as the basement and roofs, reducing the risks related to performing an inspection. The two cameras used showed excellent performance in detecting thermal anomalies, although they were somewhat more inaccurate when performing a radiometric assessment of the surface temperature; the measured temperature was particularly sensitive to the emissivity of the materials and to disturbances caused by specular reflections. During the study, it could be observed that for angles of more than 45\({}^{\circ}\), the measurement deviation could exceed the sensitivity indicated by the camera manufacturer. Radiometry therefore requires further study and the use of more sophisticated cameras, but the qualitative assessment of defects was really effective. As a result of the study, the following corrective measures were proposed:  
1. Installation of systems for thermal bridge rupture in the joineries. 2. Double-glazing windows. 3. Reinforcement of the insulation layer in the subfloor. 4. Cladding the concrete columns. A key issue for the interpretation of the results of a thermal audit of buildings would be the use of photogrammetric products such as ortho-thermograms and/or 3D thermographic models. These products would provide a more holistic view than individual thermograms, yielding an interesting viewpoint to analyse the thermal performance of the building envelope as a whole. In fact, 3D-IRT provides a more useful product for evaluating the thermal performance of the winery and understanding its energy efficiency, as the building can be analysed from all directions. Although the accuracy, analysed in terms of temperature values at the envelope walls cannot be assessed using the 3D-IRT model, it was shown in Section 3.1 that there is a more than acceptable level of error between the values measured by probes in contact with the walls and those obtained from thermal imaging at the same points. Furthermore, the comparison of the 3D RGB and thermal image models shows an excellent agreement in pinpointing the areas affected by moisture. Therefore, it can be stated that, although the exclusive use of 3D-IRT only allows the precise identification of the sensitive areas in a  
Figure 18: Side view, even the most hidden wall is almost reconstructed. qualitative way, its accuracy is the same, in quantitative terms, as that demonstrated in the comparison referred to above. Pre-processing the thermal images not only increases the visual quality of the model, but also introduces a quantitative improvement in the number of thermograms that are aligned. In fact, 23.1% more images were aligned than by using the software directly. The pre-processing techniques (histogram balancing, Gaussian filtering, etc.) therefore allow for a more exhaustive and simple exploitation of the images collected by any UAS, thus facilitating a global and direct review of the areas in which the defects to be corrected are potentially found. Some IRT cameras also include an RGB sensor that is capable of capturing simultaneous images with a geometry equivalent to or very close to that of the thermogram [60]. Optical image processing allows the camera positions to be determined and the scene geometry to be reconstructed and the temperature values to be superimposed or projected onto the 3D model [61]. However, this process also involves losing some of the radiometric temperature information at the pixel level.