LLM-Enhanced Digital Twin for Asset
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
The research will develop and validate an LLM-enabled framework to convert Digital Twin data into actionable insights for