Enabling Privacy-Preserving Natural Language Access to Industrial Smart Meter Data
arXiv:2611.09372v1 Announce Type: new Abstract: Energy management officers and grid operators increasingly rely on smart meter data for anomaly detection, performance monitoring, and strategic decision-making. However, extracting actionable insights from large-scale, heterogeneous telemetry databases requires…
Excerpt provided by arXiv cs.AI via its public feed. Full reporting belongs to the original publisher.
Read the full story on arXiv cs.AI
Related coverage
arXiv cs.AI · 13h ago
The Infrastructure Divide: Analyzing Community Stance on Data Center Development via Reddit
arXiv cs.AI · 13h ago
TimeHF 2.0: Multimodal, Multivariate, and Multi-Region Collaborative Forecasting for Large-Scale Retail Supply Chains
arXiv cs.AI · 13h ago
Agentic discrete-event simulation for manufacturing system design: an open 3D simulator, a benchmark and an industrial case
AWS Machine Learning · 1d ago
How CrossnoKaye grounds physical AI with Amazon Bedrock AgentCore