# Coverage Path Planning with Semantic Segmentation for UAV in PV Plants
## 3 Results and Discussion
### Results of the CPP Method
#### 3.2.1 The Three First Experiments with a Typhoon UAV  
The three first CPP experiments were conducted with a Typhoon UAV, varying the CPP width between 0 and 20 m, depending on the PV plant being covered. For example, in the first and second PV plants, Unioeste 1, and Arak, respectively, the CPP widths were varied between 5 and 20 m. In the third CSUSL PV plant, the width was varied between 1 and 8 m, due to the method's restrictions on running in small areas with a large width. Then, in each of these experiments, the resulting metrics were annotated in Tables, as shown in Appendix B. The logged metrics were utilized to draw a clustered columns and lines chart for experiments 1, 2 and 3, performed with the Typhoon UAV, to highlight the most important information and to determine their correlations with each other. In these graphs the vertical axis was scaled logarithmically and the horizontal axis was labeled with the type of CPP method in use; in this way, it is possible to visualize the correlation of flight time, number of maneuvers, and path length covered with the energy consumption by each CPP method, as shown in Figures 9-11. In addition, the relationship between the redundancy metric and the CPP width is identified, showing that this metric is higher in BECD, but does not affect energy consumption, which is the primary metric of interest. The UAVs' energy consumption, in conjunction with the CPP widths, were obtained from the energy consumption results logs, then a new Table 1 was composed of three large columns, corresponding to all the assessed PV plants, and each PV plant column is made up of three CPPs with their respective values of consumed energy. The rows of the table contain the CPP widths in increasing order from top to bottom, as shown in Table 1. Where it can be observed, some parameters, such as the energy consumption with regard to CPP width, were due to the size of the RoI. Additionally, it can be observed that the greater the CPP width, the lower the energy consumption, as seen in the columns of Table 1. For example, for the BECD CPP in Unioeste 1, with a width of 5 m, the percentage of energy consumed was 98%, while, for a width of 20, the energy consumed was 29%. It is also observed that the larger the PV plant, the UAV consumed all its energy in CPPs with narrow widths; on the other hand, if the plant is small, with the same width, the UAV does not have energy consumption problems. As can be seen in the row with a width of 8, where, for the Unioeste 1 and Arak PV plants, a lot of energy was consumed, between 88% and 52%, unlike the CSUSL plant, in which where the energy consumed was very little, between 7% and 5%. In the experiments for which energy consumption, with respect to CPP width, cannot be observed, \((N/A)\) was used to annotate these results, which happened when the CPP width was very large with respect to the RoI, as this does not allow the generation of the route, or when the CPP width was very small with regard to the RoI causing a flight path in which the UAV consumes all its energy. In short, the UAV used can be undersized or oversized with respect to its intended PV plant. The graphs in Figure 12 were constructed from Table 1 by quintic polynomial interpolations, which requires six data points to form a curve that passes through all given data points [99], where the abscissa axis is the CPP width and the ordinate axis is energy consumption.