Use Case 1: XR-driven edge-enabled industrial B5G applications

VERGE partner Arçelik has production and product design units in different locations around the globe, delivering built-in &  freestanding major appliances, smart household appliances, heating ventilation-AC, consumer electronics, etc. The product design requires engineers from different locations to collaborate in the design phase. Concept creation, technology development, structural design and structural analysis are performed at one location, while prototyping, verification, testing and commissioning activities are performed at another location. The travel and circulation of product designers in different locations are both costly and time-consuming. With extended reality tools, designers can work on the same product design simultaneously. The knowledge transfer and real time data sharing between different management units can be enhanced by the utilisation of real-time AR/VR technologies, which provide fast expert support for resolving technical problems or experience sharing. Technical support and collaboration design teams at different locations require the existence of experts in many different branches. Currently, it is not possible to tackle issues through working on the same CAD item simultaneously by designers who are located at different plants. Execution of simultaneous design activities of designers in different locations, revision and revision of designs are critical for compliance with the project schedule. Instant feedback to abrupt design problems requires collaboration of different experts from different locations, therefore agile connection means are required to avoid affecting the flow of the production line. By employing B5G XR tools, it will be made feasible to remotely advise and inspect the technical problems by experts at different locations.

Use Case 2: Edge-assisted Autonomous Tram

Autonomous trams must be equipped with a multitude of sensors, such as Lidar, radars, GNSS, IMU (Inertial Measurement Unit), infrared and visible cameras, etc., enabling them to sense and collect a wide range of information on the surrounding area of the tram. This information must be then processed to promptly detect any potentially hazardous situations (e.g., pedestrians or vehicles on the tracks) and initiate the necessary actions to avert them (e.g.,from notifying the driver to ultimately activating the breaking system in a fully autonomous tram). This processing has strict real-time requirements and a high computational complexity, which can be mitigated by offloading part of the computation to the edge. Furthermore, in line with the vision of smart cities, information collected by the city environment (e.g., from city IoT sensors and cameras) can significantly increase the situational awareness and resiliency of the tram, providing valuable information on potential blind spots or events not captured by the tram sensors. Edge computing can, hence, be leveraged to fuse together the information coming from the tram and the city, forming a truly distributed edge computing system.

In this context, this use case will showcase the potential of the VERGE edge architecture to deliver the distributed and AI-based edge capabilities needed to achieve innovative smart mobility applications towards autonomous tram operation.