Use Cases
For the validation needs of the SAFE-6G framework, the consortium will focus on two metaverse use-cases deployed on a small-scale, fully operational infrastructure. The first use-case is an industrial metaverse for a production line, while the second is an educational metaverse. These use-cases employ novel sensing and capturing devices beyond traditional VR/AR headsets, including biometric signal capture devices.
The main technical challenge is the integration of various non-collocated devices, such as AR and VR headsets, projection systems, screens, tablets, and computers, into a network architecture that supports real-time collaboration. However, many current XR devices have limited 5G and 6G compatibility. Additionally, strong authentication and data safety requirements for students and teachers, including identity and emotional/behavioral data, must be addressed.
The proposed solution involves a distributed network architecture with edge and cloud computing, combining XR assets and collaboration software. The assessment will consider deployment scenarios, safety, cybersecurity, privacy, reliability, and resilience issues related to the SAFE-6G framework’s efficiency in these metaverse use-cases.
Industrial Metaverse of a production line
The first use-case is based on the Digital Twin (DT) of an industrial production line. DTs are powerful tools for industries to reflect on their existing installations and processes in order to gain flexibility within factories while optimizing production times. DT help organizations achieve predictive maintenance by providing detailed insights into equipment performance, enabling them to detect and anticipate issues before they become costly failures. Within SAFE-6G, this use-case aims to explore how a production line team could benefit from XR+AI services to take full advantage of the different capacities of their factory DT.
In particular, we will focus on the adaptation and rescheduling of machines and workers when an issue or change arises. XR components (based on the Unity framework) will be used to visualize simulated 3D workflows and machine/worker reorganization that will be generated by the AI. Besides, this use-case also involves remote collaboration between users to take decisions over these simulations and update the DT. In this use case, LoT is crucial as sensible factory data needs to be shared among users. Security risks directly involve production lines and physical safety of workers. An adapted architecture mostly based on on-premise services will be adopted and tested. Besides, we will consider existing tools such as Nvidia XR Cloud and Nvidia Omniverse, which are computing platforms that enable the development of Universal Scene Description-based 3D workflows and applications.
Metaverse for education
