Digital Twin, LLM & IIOT

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IIOT for legacy and intelligent factory machines with XR and LLM feedback with a Digital Twin demonstration of real-time IOT for architecture/building applications using Omniverse.

  • PIs: Sam Anand, Ming Tang

$40,000. UC Industry 4.0/5.0 Institute Consortium Research Project: 01.2024-01.2025

The project centers on the development of a Digital Twin (DT) and a multi-agent Large Language Model (LLM) framework designed to access and interpret real-time and historical data through an Industrial Internet of Things (IIoT) platform. Real-time data is sourced from legacy machines and smart machines, integrating Building Information Modeling (BIM) with environmental sensors. The multi-agent LLM framework comprises specialized agents and supports diverse user interfaces, including screen-based systems, Virtual Reality (VR) environments, and mobile devices, enabling versatile interaction, data visualization, and analysis.

Environment Sensors for Digital Twin model. XR-Lab and SM-Lab at Digital Futures Building.

Integration of Reality capture, IOT, LLM into a digital twin model.  

 

Digital Twin of Digital Futures Building. 

Primary Objective: To develop a conversational large language modeling system that acquires data from legacy machines, digital machines, environmental data, real-time data, and historical data within an IIoT environment to create a digital twin for assisting in real-time maintenance and assistance (Application Use Case: Digital Future’s Building) 

1. Autodesk DT

Live Demo with Autodesk DT.  Please get in touch with Ming Tang to request a password. 

  

2. Unreal + Omniverse DT

Demonstration videos

 

The original BIM model was provided by GBBN and Messer Construction. Copyright 2024.

Student: Sourabh Deshpande, Anuj Gautam , Manish Raj Aryal, Mikhail Nikolaenko, Aayush Kumar, Eian Bennett, Ahmad Alrefai