## 5 Potential Use Cases
### Smart City Video Surveillance over 5G  
A critical requirement for the implementation of an autonomous video surveillance smart city solution is the capacity to capture, stream and process video with a high-quality level. To deploy such a solution across a wide area, a high amount of network and computational power is required to handle such a number of video streams. From its early stage, media handling has been one of the main concerns of 5G research activities associated with one of its pillar KPIs, namely eMBB. Figure 9 describes the potential video surveillance solution from a high-level perspective. As presented in Figure 9, the computer vision analytics for emergencies (CVAE) solution is expected to deploy network services both at the core as well as the edge of a 5G ecosystem. Taking into consideration that instantiating a service at the core or at the edge pertain different requirements and limitations, as visible in the image, two kinds of CVAE network service will be developed:  
Core CVAE service: This service will be instantiated at the core of the network taking advantage of all the computational power available there. This service is the central unit of CVAE solution and will be responsible for receiving and sending information from all edge CVAE service instances, deep processing of all the video streams broadcasted by edge CVAE service, correlating information sources from the different CVAE services and interacting directly with urban platform service to receive and broadcast emergency event information. Edge CVAE service: Multiple instances of this service are expected to be instantiated at the edge of the network. Each instance is to receive the video streams of one or more closed-circuit television (CCTV) cameras and pre-process its content with the aim of detecting a potential emergency event. Additionally, these services are also prone to retrieve UE information, such as location coordinates and UE identification, as well as allow end users to manually report an emergency event. All these services are to be linked to core  
Figure 9: CVAE High Level Overview. CVAE service to report video streams and events, as well as receive commands from it to either look for a specific object or share the video broadcast of one or more cameras connected to it. The deployment scenario is shown in Figure 10. The end-user devices, such as CCTV cameras, UEs and IoT devices will connect to the small cell (also indicated as lamp post) via 5G new radio (NR). The lamp posts will be equipped with 5G NR RAN, computing and network resources, which will be all abstracted by a virtualized infrastructure, i.e., virtual RAN (vRAN) and virtualized infrastructure manager (VIM) in order to instantiate services at the edge node. As such, the data fed from the end-user devices flow through the DU and central unit (CU), where they can be intercepted and processed by the services running at the edge NFVI. In addition, some lamp posts will have a physical button, namely a panic button, which is hardwired to an embedded device with networking capabilities which will be linked to a particular service running at the edge. At the 5G Core a VIM will also be available to ensure the instantiation of NFV services. To be noted that (although not explicitly depicted in Figure 10) there will be multiple edge nodes connected to the 5G core, i.e., multiple lamp posts providing coverage for a certain region/location. Finally, the backhaul between the edges and the core will be assured by a fibre optic cable link. As can be seen in the previous figure, CVAE E2E service will be comprised by a set of VNFs running both at the edge and core NFVI. CVAE E2E service expects also for a specific slice for it to be created. The network resources associated with this slice are to be readjusted to the network demands at a given point in time. In the event of one or more emergencies being detected in one more edge deployments, real time video streams are expected to be broadcasted into the core NFVI thus increasing the network bandwidth demand.