# Improving Response Time for Crowd Management in Hajj
## 5 Results  
The following (Figure 6) shows the packet delivery ratios for high-priority and low-priority packets sent using PRoFFAN and all packets sent with PRoFFAN disabled. At UAV speeds less than 5 m/s (18 km/h), more than 90 percent of packets were received for all three packet types. The reason is that the UAV speed is less enough than the sink received most packets. As UAV speed increased from 5 m/s (18 km/h) to 11 m/s (40 km/h), approximately 60 percent of packets made it to the sink when PRoFFAN was disabled. When PRoFFAN was enabled, the delivery ratio of high-priority packets was above 90 percent. The delivery ratio of low priority packets was reduced to 30 percent to compensate for this. At UAV speeds higher than 11 m/s (40 km/h), it can be seen that the base station receives twice the amount of high-priority packet compared to packets sent with PRoFFAN disabled. Whatever the speed, at any time, the information that the base station receives is of more use to the FANET application than information received with PRoFFAN disabled. The benefit of using PRoFFAN is more evident when we look at the PSNR and SSIM of received images. Figure 7a,b show the PSNR and SSIM of received images. Both figures show that as the speed of the UAVs increase, the PSNR and SSIM decrease. However, with PRoFFAN enabled, the quality of images received at the base station is much higher. The curve of PSNR and SSIM for PRoFFAN is analogous with the number of high-priority packets received at the base station. With a higher delivery ratio of high-priority packets, the base station's image information is more beneficial for the FANET application because its PSNR and SSIM are better. Hence, PRoFFAN assists FANET applications in improving their response time by providing them with better quality images than networks without PRoFFAN under the same conditions. Figure 8a,b show the PSNR and SSIM calculated after every one second at the base station for packets received from a UAV traveling at 10 km/h. Without PRoFFAN, the UAV's entire journey in the base station's range could transmit packets that contributed to PSNR, reaching a max value of 6 and SSIM of 0.28, respectively, in 120 s (represented by marker 4). However, the same quality of PSNR = 6 reached the base station in almost one-third of the time using PRoFFAN at 34 s (represented by marker 3). Assuming that the FANET  
Figure 6: Packet Delivery Ratio for PRoFFAN compared to Zigbee. application required a PSNR = 6 for processing the incoming image, without PRoFFAN, the image of PSNR = 6 was received in 120 s, whereas, with PRoFFAN enabled, the same quality of image reached the base station in 34 s. Hence, PRoFFAN saved 86 s.  
The vertical line at the 60 s mark in Figure 8a depicts the deadline of 60 s. Without PRoFFAN, the image of PSNR = 4 reached the base station (represented by marker 2). On the other hand, with PRoFFAN enabled, an image of PSNR = 14 reached the base station in 60 s (represented by marker 1). In fact, at 65 s (represented by mark 5), an image with a PSNR of 17.5 had reached the base station. This improvement in the quality of the image was achieved by enabling PRoFFAN. Hence, the application can use images of much better quality for processing. This is how PRoFFAN assists in improving response time and response efficiency in FANET applications with UAVs traveling at low speeds. Figure 8: Comparison of PRoFFAN and Zigbee based on PSNR/SSIM vs. Deadline for UAV at 10 km/h. (**a**) Deadline based PSNR at 10 km/h, (**b**) Deadline based SSIM at 10 km/h. Figure 7: Comparison of PRoFFAN and Zigbee based on PSNR/SSIM vs. Speed. (**a**) PSNR vs. Speed Comparison, (**b**) SSIM vs. Speed Comparison. Figure 9 shows the image received at Marker 4 in Figure 8a. The image was received in 120 s with a PSNR of 6 without PRoFFAN. Figure 9 also shows the image received at Marker 3 in Figure 8a. This image was received in 34 s with PRoFFAN enabled with the same PSNR of 6. Hence, PRoFFAN saved 86 s of the FANET application.