# A Collaborative UAV-WSN Network for Monitoring Large Areas
## 3 Results
### Method Validation on Real Test-Bed  
In order to further evaluate the proposed solution for UAV and ground WSN interlinking, some real implementations were developed. Lately we have paid a particular attention to this topic, involving significant efforts to create a real test-bed for validating the proposed strategies. This section showcases some of our experimental results drawn from test-beds simulations. Our test-bed experiments are based on TelosB/Tmote Sky platforms compatible with Contiki OS. Regarding WSN discovery mechanism for estimating positions of sensor nodes, we created a test-bed comprising of five sensor nodes, CM3300, which is an IEEE 802.15.4 compliant wireless sensor node, designed by Advanctsys, based on the original open-source TelosB platform. The main specifications of the CM3300 note are available in Table 2.  
Outdoor communication range values are specified in ideal conditions using a power amplifier and a high gain omnidirectional antenna. In a real environmental monitoring application, due to obstructions and vegetations, the expectation is for this to decrease by a factor between 4\(\times\) and 10\(\times\). Four sensor nodes were configured to act as ground sensor nodes according to the described algorithms. To make it easier to spot them, they were placed over yellow colored boards (Figure 12a). The fifth one was configured to act as the UAV node and it was included in the UAV's payload (Figure 12b). Specifications regarding the UAV used--DJI MATRICE 600 PRO \begin{table}
\begin{tabular}{c} **Standard** \\ **Deviation** \\ \end{tabular} \\ \hline
40 & 18 & 31.5 & 12.2 & 30 & 30.7 & 22.7 \\ \hline
80 & 55 & 61.6 & 12.7 & 25 & 24.1 & 16.3 \\ \hline
100 & 52 & 57.8 & 13.1 & 20 & 21.9 & 13.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Statistic simulation results. For this experiment, a flight plan was defined, with an elevation of 35 m above the ground, designed to explore an area of interest of 3 ha. The average cruise speed was 3 m/s, and the flight time was 10:47 min. Using the available flight record we generated the following flying path illustrated in Figure 13.  
After processing the logged data from the UAV's node, the following representations for WSN's response positions could be generated (Figure 14). In each representation, the currently referred sensory node is marked with a large black dot. The red dots represent UAV positions at which packets from the current sensor are received. To simplify the representation, only responses with a signal strength indicator above a sensitivity limit were retained. Sensor nodes are uniquely identified inside the network by means of their RIME communication stack addresses. For this particular example we observe that better placed nodes inside the area described by the flying path (24.125 and 112.104) can be accurately estimated, while nodes located at the border get the worst estimates. This was previously highlighted in Section 3.1.1. Figure 12: Equipment used in the experimental run. (**a**) Ground sensor node; (**b**) UAV. Figure 13: Flying path for the experimental run. Sensors' estimated location over-approximated by ellipsoidal shapes are illustrated in Figure 15. For node 4.130 which is located at the edge of the monitored area, it was not possible to define an estimated position. For the rest of the nodes we consider the identification procedure to be precise enough (the uncertain radius \(r_{j}^{\prime}\) is significantly smaller than the communication radius \(r_{j}\)). Variability of vegetation density during the year, weather conditions, and antenna orientation after uncontrolled aerial deployment are known as critical factors impacting node communication performance [15; 16]. In our scenario through the experimental deployment we observe such phenomena for sensor node 4.130, graphically illustrated in Figure 16, which has been deployed  
Figure 14: Sensor nodes response positions. Figure 15: Sensors’ estimated location as the result of succesive UAV mesurements. at the edge of the field with surrounding vegetation.