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Ground-Truth-Aware Stress Testing of a Closed-Loop Smart-Building Digital Twin Under Sensor Drift and Missing Data
US & West ·
A ground-truth-aware simulation framework is introduced that separates the latent physical state from a corrupted sensing layer and compares practical control policies with an oracle controller. The model includes 20 zones, models occupancy-driven CO2 and ventilation-energy trade-offs, sensor drift, and missing data, allowing to assess the impact of sensing errors on closed-loop performance.
Why it matters
This is important as it highlights the need to account for data quality when evaluating digital twins, which affects the reliability of building control and other systems.
The National University of Singapore (NUS) and the Society of Algorithmic Intelligence (SoAI) is hosting IntelligenceX 2026: Global Quantum × AI Frontier, from 24 to 26 September 2026 at NUS University Town, focused on advances at the intersection of quantum computing and artificial intelligence…
A pre-registered study with 317 participants compared AI-moderated, human-moderated and static interviews. AI moderation matched human depth, covered more themes and, at fixed budget, surfaced more customer needs; digital twins built from interview data were validated against held-out responses to marketing stimuli.