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AgenticTwin: An Agentic LLM Framework for Anomaly Detection in Digital Twins
US & West ·
The proposed AgenticTwin framework integrates large language model (LLM) reasoning with a digital twin-based anomaly detection pipeline. It grounds LLM explanations in anomaly classifier outputs and enables natural-language queries from operators, addressing the challenge of interpreting anomalies in complex systems.
Why it matters
This advances AI-driven explanation of anomalies in complex cyber-physical systems, which is critical for operational management of large-scale infrastructures.
Hanwha Construction, together with E8, Seoul University, and the Korea Institute of Construction Technology, participates in a national project to develop and validate a digital twin-based building energy management simulator using BIM. The project aims to improve energy efficiency.
