# Coverage Path Planning with Semantic Segmentation for UAV in PV Plants
## 3 Results and Discussion
### Results of the CPP Method
#### 3.2.2 The Last Three Experiments with 3 DR Iris UAV
It is also observed that, for larger PV plants, the UAV consumed all its energy in a CPP with a small width, whereas, for small plants of the same width, the UAV did not have energy waste problems. As can be seen in the row corresponding to a CPP width of 8 m, at the Unioeste 1 and Arak plants a lot of energy was consumed, between 100%, and 88%, unlike at the CSUSL plant, where the energy consumed was very little, between 9%, and 8%. Similarly, in the previous experiments, wherein the UAV's energy was exhausted and the CPP width did not allow the generation of the route or when the CPP width was large with regard to the RoI, the results were scored with (\(N/A\)). To summarize, the UAV used is suitable for the last PV plant. On the other hand, the 3 DR Iris UAV, with its design, size, autonomy, and performance is suitable when the PV plant to be inspected is small, of an approximate size of 5000 square meters or less, such as the CSUSL PV plant, at 1344 square meters. Owing to such PV plant sizes, any coverage method used in this work can be used to cover an area with a CPP width of 1 meter, while minimizing the metrics of path length covered, flight time and maneuverability, to obtain lower energy consumption, as shown in the Table 2. In addition, this UAV did not perform well at large or medium-sized plants, since, to cover them using the CPP method, the width that must be provided is greater than 8 m; therefore, though the UAV's inspection of the PV plant had no high-resolution cameras on board, they were needed; without them, the inspection cannot be guaranteed. The graphs in Figure 16 were constructed from Table 2 using quintic polynomial interpolations, wherein the abscissa axis is CPP width and the ordinate axis is energy consumption. Additionally, the graph in Figure 16a shows that the BECD method had the lowest energy consumption; when the CPP width spanned the entire test range, the GBSTC and GBWC methods showed a higher energy consumption at the Unioeste 1 PV plant. The graph in Figure 16b shows that the BECD method had the lowest energy consumption when the CPP width was in the range of 8 to 10 m, whereas BECD and GBWC had similar energy consumption, leaving the GBWC method with the lowest consumption, when the \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**Energy Consumption**} & & & & & & & & & \\ \hline \multicolumn{1}{c}{**PV Plant**} & \multicolumn{3}{c}{**Unioeste 1 (35,975 m\({}^{2}\))**} & & & & & & & & \\ \hline \multicolumn{1}{c}{**Width (m)CPP**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**Width (m)CPP**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**1**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**2**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**3**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**4**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**5**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**6**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**8**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**7**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**8**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**9**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**10**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**12**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**15**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**17**} & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**20**} & & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of three CPP methods with regard to CPP width, simulated in a 3 DR Iris UAV on three PV plants. CPP width was in the range of 10 to 15 m. On the other hand, the GBWC method had the lowest energy consumption when the CPP width was in the range of 15 and 20 m; this test was conducted at the Arak PV plant.