LLM-Enhanced Digital Twin for Asset & Facility Management
Politecnico di Milano is offering a research fellowship focused on Digital Twins (DTs) that combine sensor data with BIM-derived geometric, semantic and contextual information to support building and infrastructure management. The project investigates using Large Language Models as natural-language interfaces to DTs, enabling access to data without deep technical expertise.
The research will develop and validate an LLM-enabled framework to convert Digital Twin data into actionable insights for
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The research will develop and validate an LLM-enabled framework to convert Digital Twin data into actionable insights for
#J-18808-Ljbffr