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PRISM: Decision-Centric Predictive Sensing for Cognitive Digital Twins in 6G
US & West ·
A PRISM engine is proposed that transforms a digital twin from a passive single-task optimizer into a persistent network-wide reasoning system. It directs sensing toward anticipated decision needs rather than following fixed schedules, enabling multi-domain knowledge accumulation.
Why it matters
This demonstrates an approach to managing sensing resources in digital twins that could improve monitoring efficiency and decision-making in large networks.
A method detects cyber-physical attacks by monitoring temporal inconsistencies between a physical system and its digital twin. A predictor trained on normal behavior generates multi-horizon features from residuals to flag anomalies.
A two-layer control architecture for frequency regulation in power systems with high inverter-based generation is proposed. The primary layer uses optimized droop and Virtual Synchronous Machine control, while the secondary layer uses Model Predictive Control (MPC) integrated into existing grid control structures with constraint awareness. A reduced-order Kalman-Bucy observer estimates state and disturbances from measurable outputs.
Analysts discuss that building a digital twin of Mercury Systems' operations using Palantir technologies could improve transparency and management efficiency, potentially enhancing the company's investment appeal.
