## 5 Discussion
### Performance  
The presented experiments were used to test and validate the SAR-IoCA architecture. The use of the architecture allowed the coordinated operation of three UGVs and one UAV in a joint mission of search and rescue with first responders. The FCC decided how and when to send the UGVs in accordance with the data received from the field, through the H2 WTN and the streamed video from the UAV, and later from the UGVs themselves. The mission was completed successfully, finding and evacuating the victims in the designated area as a result of the joint operation of a fire brigade team, a military emergency team, and our systems (comprising the UGVs, UAV, FCC, and BCC). The experiments  
Figure 9: Cooperative robots. lasted one hour and fourteen minutes. They started at 12:02 with the take off of the UAV to perform the aerial exploration and mapping, and finished at 13:16 with the return of [PERSON] to the FCC, although the applications were running until 13:52. Previously to the experiment, the FCC was deployed in the designated area for command posts, next to the field of operations. The deployment of the FCC took two hours and was performed the previous day to avoid interferences with the deployment of other command posts from other responders. However, it could have been performed immediately before the experiments. The exercise included experiments and tests performed by the rest of the teams of first responders, within a limited time frame. Thus, to speed up our experiments and facilitate the coordination with the rest of teams, a DEM was obtained previously, instead of creating it out of the first flight of the UAV. Nevertheless, a short demo of the process was included in the sequence. The static sensor-nodes of the LoRa H-WSN were deployed in advance, the same day of the exercise. The sensor-nodes were placed manually in locations determined out of the geographical features of the operation area, available through the DEM. The zone near the tunnels was avoided in this first deployment to emulate the discovery of a new area of operations after the initial set up. Although having the static sensor-nodes deployed in advance is not realistic, it was not considered to affect the fidelity of the experiments, since the ultimate goal of the exercise was to perform a mission in an area outside an original plan. Besides the LoRa static sensor-nodes, BLE transceiver nodes were deployed in the vicinity of the tunnels to play the role of hidden victims, who may wear BLE-based devices. The sequence of the experiment started with the request from the coordinators of the exercise for an operation in a new area, not planned before, at 11:30. A first flight of the UAV started at 12:02 for the demonstration of the mapping. The UAV landed at 12:09. A second flight took place from 12:15 to 12:27 (Figure 10). The aim of this flight was to explore the new zone, streaming 4K video to the FCC. In relation to TC1, the UAV was equipped with a 5G smartphone (Figure 11), running the UMA-ROS-Android app [39], and transmitting the video through the ROS network, in real time, using the 5G network. During the first flight, the video was transmitted through ROS and processed in the cloud to obtain a tessellation of a limited zone in the operation area (TC3). The ROS master node, or roscore, was hosted in the cloud. The video was received and displayed at the FCC with good quality and fluidity during both flights (TC2). At 12:30, the set of physiological sensors (EDA, ECG, and lung capacity) were placed on a firefighter of the team designated to participate in the mission. These BLE-based sensors started transmitting data from this point until all applications were closed. They were linked to a 5G smartphone via Bluetooth, as external sensors (TC7). The data acquired were sent via 5G to the MEC centers, which was performed to monitor the firefighter's health, in real time, as the firefighter performed his tasks. This data could be used to assess the level of stress of the firefighter.