## 4 Results and Discussion  
The most important aspect of drones and the IoPST is the ability of these two technologies to form an effective and efficient communication network for public safety. Drones offer many benefits such as rapid deployment, LoS, reprogrammability, etc. Therefore, the network performance of the collaboration of drones and IoPST before, during, and after a disaster should improve greatly. The simulation network is made using OPNET 14.5. The scenario consists of three drones and three SAR responders. A mobile ad hoc network (MANET) is proposed to connect the drones and responders to perform tasks efficiently. Also, the AODV routing protocol is considered for unicast and multicast routing services. Furthermore, the simulation time is 500 s. One drone is moving around closer to the events, as shown in Figure 2. This drone will capture an image of the event and share it with other drones and SAR on the ground for performing relevant actions according to the available data given by drone-2. Drone-1 and drone-3 are used to guide and deliver the supplies required by the SAR or people in a particular area. SAR-1, SAR-2, and SAR-3 are performing their duty by the guiding of drones and their wearable devices help drones to identify the location where they are needed. QoS parameters such as delay and throughput are considered for measuring the performance of the drones and SARs in particular events. The throughput and delay are measured for each device connected in a network, for testing joint performance during a disaster. Furthermore, the loss probabilities are calculated and simulated by a Matlab code. The throughput increased with the increase of the packet size through all number of nodes. Thus, the difference between each number of nodes also increases during the increasing packet size in the different time, as shown in Figure 9. Throughput decreases when some wireless node increases. Throughput is the total data traffic in bits per second successfully received then forwarded to the drone. Each node has different throughput and Table 2 shows the minimum, maximum, average, and standard deviation (Std Dev). The maximum throughput is changed from 2814.4 bit/second in the case of drone-1 to 7908.8 bit/second in the case of SAR-1. Also, the average throughput is changed from a maximum of 4016.3 in the case of SAR-1 to 1827.2 in the case of drone-1. Figure 9: Throughput vs. time. The time delay will be affected by an increasing number of wireless nodes, and will decrease with an increase in packet size through all different number of nodes, as shown in Figure 10. In the case of minimum delay, SAR-2 is the lowest, but drone-2 has the highest minimum delay, which is 0.8 ms. However, drone-1 has no delay. Also, it is the same in the case of maximum and average delay for each node, as shown in Table 3. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Object** & **Minimum** & **Maximum** & **Average** & **Std Dev** \\ \hline SAR-1 & 0 & 7908.8 & 4016.3 & 1368.3 \\ \hline Drone-3 & 0 & 6648.0 & 3496.3 & 1243.9 \\ \hline SAR-2 & 0 & 5624.0 & 2788.6 & 782.0 \\ \hline Drone-2 & 0 & 5395.2 & 2722.4 & 963.7 \\ \hline SAR-3 & 0 & 5180.8 & 2620.0 & 926.9 \\ \hline Drone-1 & 0 & 2814.4 & 1827.2 & 330.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Throughput for different nodes. Figure 10: Delay for different nodes vs. time. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Object** & **Minimum** & **Maximum** & **Average** & **Std Dev** \\ \hline Drone-2 & 0.0008937 & 0.014345 & 0.0017257 & 0.0018513 \\ \hline Drone-3 & 0.0010700 & 0.005018 & 0.0015526 & 0.0007544 \\ \hline SAR-3 & 0.0010346 & 0.007813 & 0.0014888 & 0.0009098 \\ \hline SAR-1 & 0.0010634 & 0.007173 & 0.0014134 & 0.0006074 \\ \hline SAR-2 & 0.0002425 & 0.011812 & 0.0005631 & 0.0012831 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Delay for different node. The LoS probability vs. elevation angle is depicted in Figure 11 for urban and suburban areas and dense urban area.