## 5 Conclusions  
This study proposes a method for observing the inside of a temporary structure with a construction safety net using image processing, unmanned aerial vehicles (UAVs), and 3D modeling. The applicability and effectiveness of the proposed method were verified by experimentally testing a small-scale temporary structure covered with a safety net and a field test for a climbing formwork; the following conclusions were drawn. Two image processing techniques, including the histogram equalization and grayscale stretching techniques, were applied to observe the internal objects in temporary structures covered with construction safety nets, to ensure the safety of workers and prevent falling from significant heights. The installed construction safety net was composed of a single material, and when the captured image was analyzed, it was composed of a certain pixel value. The pixel values constituting the image of the construction safety net were believed to be biased, and the resolution was improved by equalizing this bias. A grayscale stretching technique was applied to prevent excessive equalization, which is a disadvantage of this technique. Moreover, 3D modeling can be used to observe a wide area from various angles. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Values** & **Figure 11** & **Figure 12** & **Figure 13** & **Figure 14** & **Figure 15** \\ \hline PSNR (dB) & 29.46 dB & 27.90 dB & 27.85 dB & 28.04 dB & 27.84 dB \\ \hline SSIM & 0.0423 & 0.2808 & 0.1715 & 0.3119 & 0.2732 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of quantitative values of image processing performance using PSNR and SSIM. Therefore, the possibility of using it to check the structural deformation of a temporary structure was identified. The applicability of the internal observation technology for a temporary structure at a construction site was estimated by selecting a target object in a climbing formwork that was temporarily installed and used at a high-rise building construction site. The improved images obtained by the proposed method clearly identified the four test objects (safety signs, PPE, etc.) whereas the original image did not. Therefore, implementing the proposed technology in temporary structures with construction safety nets can help prevent safety incidents for workers operating in areas that pose challenges to safety managers in terms of accessibility and oversight. The efficiency of the proposed method may vary depending on the colors, materials, and denier values. The limitation of this study is that the colors of the applied construction safety net are blue and gray, and only one denier value was applied. This limitation makes it difficult to expect consistent performance depending on the field conditions. However, this study verified the possibility of observing the internal objects of a temporary structure covered with a safety net at a construction site using an UAV. Future research will be performed on various variables of construction safety nets, such as the color and denier values. Additionally, research will be conducted to evaluate the impact of external factors such as weather, illumination, backlighting, and the hardware capacity of UAVs on the performance of the proposed method. Conceptualization, M.-G.K. and J.-H.W. ; methodology, M.-G.K.; software, M.-G.K. and H.-J.J.; validation, M.-G.K., S.-H.S. and H.-J.J.; formal analysis, M.-G.K.; investigation, S.-H.S. ; writing--original draft preparation, M.-G.K.; writing--review and editing, J.-H.W. ; visualization, S.-H.S. ; supervision, J.-H.W. All authors have read and agreed to the published version of the manuscript. This research was supported by the \"Leaders in Industry-University Cooperation 3.0\" Project, funded by the Ministry of Education and National Research Foundation of Korea. This research was partially supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. RS-2024-00407154).