## 5 Discussion
### Performance
This same 5G smartphone had the UMA-ROS-Android application running in a background mode in order to transmit the audio, via  
Figure 10: Panoramic aerial views (DJI Flight Log Viewer). ROS, from the firefighter's position. An exploration with a UGV (Cuadriga) was then planned using SAR-FIS at the FCC, defining points of interest thanks to the previous exploration of the drone. Cuadriga was teleoperated from the FCC from 12:49 to 12:52, moving from a nearby station to the zone, and then switched to a path planned with SAR-FIS. The path was completed between 12:53 and 12:54. The goal was to explore the zone and stream video but also gather data through the sensor-nodes carried onboard as a part of the LoRa H-WSN, since this area was not covered by the previously deployed static nodes (Figure 8b). Thus, Cuadriga remained in the area until the end of the mission, although static. An additional goal for Cuadriga was to test BLE detection during both its teleoperated and autonomous movements. Both a commercial scanner and a purpose-built one were installed onboard Cuadriga. In relation to TC5, Cuadriga was remotely controlled in teleoperated mode from the FCC (local edge) using 5G supported by the images captured by a onboard IP camera. The teleoperation was performed without problems, with a good feedback from the operator regarding video quality and latency. In the following stage, path planning for Cuadriga was obtained by cloud and local edges in SAR-FIS. The BLE scanners onboard Cuadriga detected successfully the hidden BLE beacons in the area (TC4). A custom-built BLE scanner was carried by the UAV to detect BLE beacons in the area. From 12:57 to 12:59, Rambler was teleoperated to a nearby static position (see Figure 11) to increase the coverage for the LoRa H-WSN, as it carried a LoRa concentrator-node. Figure 12 shows Rambler's position, together with the two UAV flights. At that point, an event of temperature level was detected by the LoRa H-WSN. SAR-FIS planned a path for Rambler to get close to the location and obtain a confirmation through its sensor-nodes onboard. Rambler reached the sensor-node location from where new images of the entrance to the tunnels were visualized (Figure 8a). In relation to the TC6, the temperature level event was triggered by setting up a threshold in a LoRa sensor-node. When the threshold was met, a LoRa packet sent from this node was received through the two LoRa concentrator-nodes located on the roof of the laboratory building (cloud edge) and on board the Rambler (local edge). Regarding TC4 and TC5, sensory event processing performed by SAR-FIS (cloud and local edges, i.e., BCC and FCC, respectively) obtained the path planning for [PERSON] displacement toward the location of the LoRa sensor-node involved in the fire detection. Figure 11: [PERSON]’s static position from the UAV. At 13:06, a request for evacuation from the main control center of the exercise was received at our FCC. Rover J8 is sent in follow me mode, arriving at 13:12 to the required location, inside one of the tunnels. A stretcher with the victim (an actor) is then secured to Rover J8. Using follow me, a member of the military unit guides Rover J8 out of the tunnel and to a nearby station to receive medical care (Figure 9c). The evacuation takes from 13:14 to 13:15. At 13:16, J8 is teleoperated back to the FCC, ending the exercise, although the applications were kept running until 13:52. During all the evacuation, video was streamed from Rover J8 thanks to an onboard 5G smartphone. The video published via ROS from this 5G smartphone was sent to the MEC centers. This is related to TC1 and TC2.