Quality of Experience in Real-Time Streamed Remote-Rendered Digital Twins in Extended Reality

Sammanfattning

Extended reality (XR) and digital twins (DTs) are expected to play an important role in future Industry 4.0 applications. However, the computational demands of rendering and managing large numbers of DTs exceed the capabilities of standalone XR devices. A promising solution is to offload rendering tasks to external servers for the remote rendering 3D content. In such systems, network performance becomes a critical factor, as degraded network conditions can directly affect the user experience. To support the development of future industrial XR services, it is therefore essential to understand the relationship between quality of service (QoS) and quality of experience (QoE). This thesis presents a methodological and technical testbed for evaluating QoE in realtime streamed, remote-rendered 3D objects in XR environments. The implementation represents a mock remote-rendering setup in which the key components of a real deployment are replicated, while allowing the network connection between the XR device and the rendering server to be manipulated during testing. QoE was assessed through user questionnaires, and the evaluation was further expanded through the inclusion of computer vision and gaze data. The user study and those results show that the implemented testbed provides a systematic and repeatable approach for analyzing QoE under different network conditions. The findings show a clear correlation between worse QoS and reduced overall QoE. In addition, the results indicate that users’ visual attention in relation to rendered objects changes as network conditions worsen. While the QoE and MOS results showed significant empirical evidence, further work is needed to improve the accuracy of the computer vision and gaze data analysis. Overall, this thesis contributes a practical foundation for studying the impact of network performance on remote-rendered DTs in XR and empirical evidence supporting it. This will be a base for advancement of the future industry and optimization of their networks.