Semantic interoperability and digital-twin scalability

Establish semantic distortion measures, reusable multi-task representations, calibrated uncertainty, semantic-freshness criteria, model-mismatch handling, graceful degradation for unseen events, and scalable adaptive digital twins for goal-oriented S$^2$C$^2$I operation across heterogeneous SAGIN platforms.

Background

The paper proposes replacing purely bit-oriented processing with mission- and task-oriented representations, such as transmitting victim locations, confidence values, and hazard boundaries instead of raw disaster video when appropriate. It also proposes digital twins that represent platform motion, atmosphere, links, energy, thermal state, computing, storage, AI behavior, and service demand. The unresolved issue is how to preserve interoperability and operational reliability while adapting representation and twin fidelity to mission needs without exceeding available resources.

References

Nevertheless, semantic representations must remain interoperable among heterogeneous satellites, HAPs, UAVs, terrestrial networks, applications, and AI models. Open problems include semantic distortion measurement, multi-task representation reuse, uncertainty calibration, model mismatch, semantic freshness, and graceful degradation under previously unseen events.

— Toward S^2C^2I-Integrated High-Altitude Platforms: Architectures, Cross-Functional Design, Evaluation, and Deployment Perspectives  (2608.18587 - Luo et al., 19 Aug 2026) in Section VI, subsection “Goal-Oriented Semantic S$^2$C$^2$I and Digital Twins”