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Smart Mobility Digital Twin Based Automated Vehicle Navigation System: A Proof of Concept
The performance of SMDT is evaluated from two standpoints: (i) the rewards of the proposed navigation system on traffic efficiency and safety and, (ii) the latency and reliability of the SMDT platform.
Large Multi-Modal Models (LMMs) as Universal Foundation Models for AI-Native Wireless Systems
Diverging from NLP-based foundation models, the proposed framework promotes the design of large multi-modal models (LMMs) fostered by three key capabilities: 1) processing of multi-modal sensing data, 2) grounding of physical symbol representations in real-world wireless systems using causal reasoning and retrieval-augmented generation (RAG), and 3) enabling instructibility from the wireless environment feedback to facilitate dynamic network adaptation thanks to logical and mathematical reasoning facilitated by neuro-symbolic AI.
Internet of Federated Digital Twins (IoFDT): Connecting Twins Beyond Borders for Society 5.0
In contrast, this paper envisions a novel concept of an Internet of Federated Digital Twins (IoFDT) that holistically integrates heterogeneous and physically separated DTs representing different Society 5. 0 services within a single framework and system.
The Seven Worlds and Experiences of the Wireless Metaverse: Challenges and Opportunities
We then articulate how these experiences bring forth interactions between diverse metaverse constituents, namely, a) humans and avatars and b) connected intelligence systems and their digital twins (DTs).
Edge Continual Learning for Dynamic Digital Twins over Wireless Networks
To guarantee a robust connection between these two worlds, DTs should maintain accurate representations of the physical applications, while preserving synchronization between real and digital entities.
