## 3 Implementation of X-IoCA for SAR Missions: SAR-IoCA  
The case study offered in this work focuses on SAR missions. For this purpose, the presented X-IoCA architecture was implemented in this particular use case, being able to test the whole system with 5G communications, suitable for SAR missions since it supports real-time requirements, high bandwidth, and low latencies [47]. Because of that, this use case was included in a 5G pilot network developed by Vodafone and Huawei. SAR-IoCA (Figure 2) aims to support SAR teams in emergency situations, providing relevant information to MEC centers, and enabling tasks for the different SAR agents, which can be human (first responders, firefighters, military units, and police), robotic (UGVs and UAVs), or canine rescue team (K9 and handler). For the sake of clarity, the elements presented in the SAR-IoCA implementation (Figure 2) respect the shapes and colors adopted in the X-IoCA architecture (Figure 1). SAR-IoCA is composed of sensing and computing elements, divided into two fundamental entities: an IoRT, where the greatest location awareness resides, and an FIS to attend the needs of the different agents, as well as for data monitoring and processing. The fog includes all the local edges and cloud edges, depicted as ground rounded rectangles and green ellipsoids in Figure 2, as well as switches and 5G CPEs (depicted as incoming red arrowheads) to route the 5G data traffic. For this particular case, the MEC centers are made up of a forward control center (FCC) and a base control center (BCC). The FCC acts as a local edge due to it belonging to the operation area, while the BCC acts as a cloud edge, since it is in a remote MEC located in a distant laboratory (less location awareness). Moreover, the BCC includes a replica of the FCC to provide redundancy. In addition, there are other MECs inside the operation area; that is to say, they are local edges with different purposes. Figure 2 shows these five local edges more, apart from the FCC. They consist of embedded computer devices (several PCs or smartphones) carried by some of the agents: three UGVs, a UAV, and a human agent. The human agent is a military who wore a 5G smartphone with which he could see (by means of ROS subscriber nodes) the images published from ROS nodes hosted in other smartphones, using the ROS-Mobile and the UMA-ROS-Android applications, respectively. Moreover, the embedded computational hosts on board the UGVs and the UAV were used for data processing. Without the loss of generality, our heterogeneous robotic team is composed of three UGVs and one UAV, shown in Figure 2. The UGVs Cuadriga and Rambler, developed by our group, are four-wheeled brushless-motors skid-steering mobile robots, while the UGV Rover J8, developed by Argo (Kitchener, Ontario, Canada), has the same locomotion system but based on eight wheels with rubber tires. Rover J8 is a large platform vehicle of 1077 kg weight with dimensions 3.48 m (length) \(\times\) 1.537 m (width) \(\times\) 1.448 m (height), capable of holding a significant payload (513 kg), which is ideal for evacuating victims. A double stretcher is available for this purpose. Rambler weighs 460 kg with dimensions 1.6 m (I) \(\times\) 1.2 m (w) \(\times\) 0.66 m (h) and has a payload of 300 kg, while Cuadriga weighs 83.1 kg with dimensions 0.82 m (length) \(\times\) 0.64 m (width) \(\times\) 0.81 m (height) and has a payload of 120 kg. Rambler has independent pneumatic active suspension provided by double-acting cylinders and pressure controllers, two for each cylinder. Moreover, a pneumatic compressor supplies the required pressure. This UGV (and all its elements) is powered by 64 lithium iron Li-Fe batteries forming 16 cells with their corresponding charge, discharge, and temperature monitoring controller. Figure 2: System architecture for search and rescue missions (SAR-IcCA).