Virtual Reality Training on Issues of Youth Firearm Possession.
PI. Tang. $20,000. 8/5/2024-8/4/2025.
Funded by the God.Restoring.Order (GRO) Community, this research project will develop two VR scenarios that simulate environments designed to educate youth on applying critical skills in risky situations.
Team: Ming Tang, XR-Lab, Aaron Mallory, GRO.
The XR-Lab is excited to collaborate with the GRO community to leverage cutting-edge XR technologies to develop a virtual reality (VR) training app that enhances the curriculum by reinforcing key skills through immersive VR activities. Together, we will assess the feasibility of integrating VR technology into the GRO’s training program, engaging users with a compelling narrative while equipping them with practical knowledge for real-world application.
Automatic Scene Creation for Augmented Reality Work Instructions Using Generative AI. Siemens. PI. Ming Tang. co-PI: Tianyu Jiang. $25,000. UC. 4/1/2024-12/31/2024
Sponsor: Siemens through UC MME Industry 4.0/5.0 Institute
Investigate integration of LLM Gen-AI with Hololens-based training.
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)
