## 4 Experiment Setup and Results
### Experiment Results and Discussions
In general, the optimized Hata-Davidson model showed improvement in comparison to the non-optimized model in terms of connectivity, footprint, and RSS, which in turn led to the enhancement of communication links between the drone on one hand, and the GCS and rescue teams on the other hand. Notably, 15 m was found to be the optimum drone altitude based on the characteristics of the experimental area. Therefore, the altitude parameter can be changed based on the features of the covered area. Unsurprisingly, the modified Hata-Davidson model displayed a good-level of improvement when using the proposed algorithm of least squares tuning. Another observation is that the measured data showed similar characteristics using modified Hata-Davidson model, which is a good performance indicator of the proposed least squares tuning algorithm. More details are presented on Table 3, which shows the two Hata-Davidson model coefficients before and after the tuning process. Once again, the table emphasizes the performance of the modified Hata-Davidson model against the non-modified model. Figure 7: Weather conditions dashboard using Blynk application. At the 15 m drone altitude determined previously, the drone was able to send the video from the FLIR lepton camera using the TCP/IP protocol. This TCP/IP protocol package was used to perform basic wireless network communication protocol between the drone and the ground station, as well as locating the positions of missing persons using the GPS sensor. The results of the vertical view using t the thermal camera to detect persons at different altitudes are shown on Figure 9. The figure shows a person labeled with a red circle from heights of 5, 10, and 15 m, respectively. Clearly, reasonable thermal visuals were observed from these altitudes; however, as the altitude increased above 15 m both low image quality and transmission delay became noticeable. Despite the high cost, a powerful thermal camera would enhance the thermal imaging quality of these results. Figure 10 demonstrates how the ThingSpeak website was used to provide channels for MATLAB users to help convert the NMEA data of the GPS module into an understandable format, before it was stored and presented as a satellite view on a specific web page. Further, these channels in ThingSpeak stored the latitude and longitude values, which helped track the drone's movement and live location during the trial at Taif university. The figure shows the GUI of the longitude and latitude from the GPS sensor, along with a satellite map view of the detected person using the thermal camera. These results show the applicability of coupling a drone with IoT devices to carrying out intelligent search, rescue, and disaster-recovery missions. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Hata-Davidson Model** & **Before** & **After** \\
**Coefficients** & **Least Squares Tuning** & **Least Squares Tuning** \\  & **Algorithm** & **Algorithm** \\ \hline K\({}_{1}\) & 10.41 & 6.53 \\ K\({}_{2}\) & 13.75 & 8.92 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Two Hata-Davidson model coefficients. Figure 8: GUI of link budget plots of modified Hata-Davidson empirical model at 15 m altitude. To validate the proposed modified Hata-Davidson model against other well-known propagation models, the root mean square error (RMSE) is used. This study concludes with a comparison between the modified Hata-Davidson model and the GUI, Cost-231 Hata, and Okumura empirical propagation models for validation, presented in Table 4[48; 49]. The propagation models were selected as representatives of their empirical types along with their main parameters of coverage distance, transmitter antenna heights, receiver antenna heights, and high range of frequency bands. Additionally, these models exhibit better performance across different terrains in relation to other models. Furthermore, the Hata-Davidson model has the advantage of featuring some correction factors that yield high prediction accuracy. The complexity of the Hata-Davidson model is its only downside.