Industry 4.0/5.0 grant


Immersive vs. Traditional Training​ – a comparison of training modalities​

PIs: Tamara Lorenz, Ming Tang

  • Dr. Tamara Lorenz. Associate Professor. Embodied Interactive Systems Lab, Industry 4.0 & 5.0 Institute (I45I), Center for Cognition, Action, and Perception (CAP)
  • Ming Tang. Professor. Extended Reality Lab, Industry 4.0 & 5.0 Institute (I45I), Institute for Research in Sensing (IRiS)

Consortium Research Project: evaluate the effectiveness of an immersive training protocol against different traditional training modalities. 

Grant. $40,000. By UC Industry 4.0/5.0 Institute 01.2023-01.2024

Open Questions

  • Is immersive training equally as effective or better than traditional training? 
  • Is immersive training beneficial for specific types of training (skill, behavior), while other modalities are better for other types (e.g. knowledge acquisition)?
  • Does the benefit of immersive VR training warrant the initial investment in equipment and subsequent investment in project building, running, and sustenance?


  • Evaluation of the effectiveness of an immersive training protocol against different traditional training modalities. 
  • Evaluation of modality-dependent benefits for different learning goals. 
  • Derivation of assessment metrics for VR training against other training modalities. 

Training scenario: DAAP Fire Evacuation

traditional training with slides and maps.

VR training with an immersive and interactive experience.



Thanks to the Institute’s Industrial Advisory Board (IAB) and industry patrons, including Siemens, Kinetic Vision, John Deere, Stress Engineering Services, Innovative Numberics, and Ethicon. 

Next Phase experiments

Multi-player test



 2017 Virtual DAAP Fire Evacuation project.


At UC News

New UC institute looks ahead to ‘Industry 5.0’. UC will harness collective talent across campus to help companies solve new challenges. by Michael Miller.  December 8, 2022



Therapeutic Crisis Intervention Simulation

VR-based Employee Safety Training. Therapeutic Crisis Intervention Simulation 


  1. Virtual Reality for Employee Safety Training. Phase I. Sponsored research by the Cincinnati Children’s Hospital Medical Center. PI. Ming Tang. $16,631. Period: 6.2022- 09.2022.
  2. Virtual Reality for Employee Safety Training.Therapeutic Crisis Intervention Simulation-Phase II.  Sponsored research by the Cincinnati Children’s Hospital Medical Center. PI. Tang. $22,365. Period: 2.2023- 12.2023.

Under the leadership of Ming Tang, the XR-Lab is collaborating with the Cincinnati Children’s Hospital Medical Center (CCHMC) to develop a VR-based simulation to enhance employee safety training. This initiative involves creating a virtual hospital environment with AI-controlled characters to facilitate research on diverse scenarios encountered during therapeutic crisis interventions. A vital feature of this simulation is the VR dialogue between a staff member and a teenage patient exhibiting aggressive behavior and mental illness. The primary objective is to equip staff members with the necessary skills to de-escalate tense situations effectively and adhere to appropriate protocols, thereby ensuring a safer and more controlled environment for staff and patients.


  • Ming Tang, Nancy Daraiseh, Maurizio Macaluso, Krista Keehn, Harley Davis, Aaron Vaughn, Katheryn Haller,  Joseph Staneck, Emily Oehler
  • Employee Safety Learning Lab, CCHMC
  • Extended Reality (XR) Lab, UC

Field of research: Virtual Reality, Safety Training, Therapeutic Crisis Intervention, Mental Health,  Human Behavior Simulation

screenshots from  Mobile VR Quest 2 headset.


NSF: Future of Work

Ming Tang worked as a co-investigator on the project funded by the NSF Grant. 

Future of Work: Understanding the interrelationships between humans and technology to improve the quality of work-life in smart buildings.

Grant: #SES-2026594 PI:  David W. Wendell. co-PIs: Harfmann, Anton; Fry, Michael; Rebola, Claudia; co-Is: Pravin Bhiwapurkar, Ann Black, Annulla Linders, Tamara Lorenz, Nabil Nassif, John Seibert, Ming Tang, Nicholas Williams, and Danny T.Y. Wu.  01-01-2021 -12-31-2021 National Science Foundation $149,720. Awarded Level: Federal 


The primary goal of this proposed planning project is to assemble a diverse, multidisciplinary team of experts dedicated to devising a robust methodology for the collection, analysis, and correlation of existing discipline-specific studies and data. This endeavor focuses on buildings and their occupants, aiming to unearth previously undiscovered interactions. Our research will specifically delve into the intricate interrelationships between four key areas: 1) the overall performance of buildings, 2) the indoor and outdoor environmental conditions, 3) the physical health of the occupants, and 4) their satisfaction with the work environment. This comprehensive approach is designed to provide a holistic understanding of the dynamic between buildings and the well-being of the individuals within them.


Prof. Anton Harfmann developed the sensor towers.


Ming Tang spearheaded the development of a Digital Twin model, an innovative project integrating multiple historical sensor data sets into a comprehensive, interactive 3D model. This model encompasses several vital features: the capture, analysis, and visualization of historical data; cloud-based data distribution; seamless integration with Building Information Models (BIM); and an intuitive Web User Experience (UX). Building elements are extracted as metadata from the BIM model and then overlaid in screen-based and Virtual Reality (VR) interfaces, offering a multi-dimensional data view. Further details are available at the Cloud-based Digital Twin project for a more in-depth exploration of this work.


See more details on the Digital Twin workflow.


Building Safety Analysis with Machine Learning

Grant received:

  1. Geospatial Imagery Analytics Research. Phase I. Sponsored research by the Cincinnati Insurance Companies. PI. Tang. Co-PI: Jiaqi Ma. $59,000. Period: 02.2020- 12.2021. Completed.
  2. Geospatial Imagery Analytics Research. Phase II. Sponsored research by the Cincinnati Insurance Companies. P.I. Tang. $79,980. Period: 10.2021- 08.2022. Grant: G402236. 2021. Ongoing.
  3. Geospatial Imagery Analytics Research. Phase III. Sponsored research by the Cincinnati Insurance Companies. PI. Tang. $15,709. Period: 6.2022- 06.2023.
  4. Geospatial Imagery Analytics Research. Phase-4. Sponsored research by the Cincinnati Insurance Companies. PI. Tang. $48,646. Period: 1.2023- 10.2023.
  5. Geospatial Imagery Analytics Research. Phase-5. Sponsored research by the Cincinnati Insurance Companies. PI. Tang. $72,350. Period: 10.2023- 11.2024.

The goal is to use A. I, Machine Learning, Deep Learning algorithm to understand the correlations between building safety to its typology and context. Please contact Professor Ming Tang if you are a UC student and interested in participating in the project.

Login to the project resource page. ( password needed)


Eye-Tracking for Drivers’ Visual Behavior

Impacts of Work Zone Traffic Signage Devices and Environment Complexity on Drivers’ Visual Behavior and Workers Safety.

Ph.D student: Adebisi, Adekunle. CEAS – Civil & Arch Eng & Const Mgmt

Undergraduate student: Nathan Deininger, 

Faculty. Ming Tang

The objective of this study is to investigate the safety of roadway workers under varying environmental and work zone conditions. To achieve the objectives, a driving simulator-based experiment is proposed to evaluate drivers’ visual attention under various work zone scenarios using eye-tracking technologies.


  • Using Eye- Tracking to Study the Effectiveness of Visual Communication. UHP Discovery funding. University Honor Program. UC. $5,000. Faculty advisor. 2021.
  • Adekunle Adebisi  (Ph.D student at the College of Engineering and Applied Science) applied and received a $3,200 Emerging Fellowship Award By Academic Advisory Council for Signage Research and Education (AACSRE).