VR analytics to assess the user experience in immersive digital twins

This project has been funded through two actions of the Turing Institute at Manchester: a feasibility project first and a current consolidator project.

Enabling human-in-the-loop interventions in immersive digital twins

Turing-Manchester Consolidator Project

Duration: January – March, 2023

Goal

The project provides functionalities to enable humans-in-the-loop in the context of digital twins that are run on immersive environments. This opens new opportunities to observe and quantify the effects of human actions on digital twins through:

• Increased realism by a) making the immersive environment reactive to user actions and b) by including texture rich 3D models will make the environment (and the digital twin) more engaging and realistic. This will increase the external validity of the experiments around the urban planning use case as the perceptions of users and their decisions will be closer to reality.
• More and better data by introducing functionalities for collecting self-reported data within the environment and logging richer interactions. The increased realism aspect mentioned above does also contribute to having more (due to higher engagement) and better data (due to increased realism).

The training received by Esri, the world leading supplier of geographical information systems will not only impact on the project but will serve for capacity building for teaching purposes at School of Environment, Education and Development (SEED) and the Alliance Manchester Business School (AMBS).

A VR analytics framework to assess the user experience of digital twins

Turing-Manchester Feasibility Project

Duration: April – September, 2022

Goal

Digital twins are often represented through Virtual Reality/Augmented Reality (VR/AR) models. The experience with such models has typically been evaluated qualitatively, which yields an in-depth understanding but lacks breadth and is costly. Currently, tool support for quantitatively evaluating immersive models VR/AR is lacking and measuring the immersive experience is still an open research question. Therefore, we do not know if digital twins are serving their intended purpose.

In this project we will address this gap by developing an affordable VR/AR experimental framework for testing hypotheses in immersive environments including digital twins.

Team

Members
Markel Vigo (PI, Department of Computer Science)
Gail Millin-Chalabi (CoI, Department of Planning and Environmental Management)
Nuno Pinto (CoI, Department of Planning and Environmental Management)
Qudamah Quboa (CoI, Alliance Manchester Business School)
Ron Bar-Ad (RA, Department of Social Statistics)
Olga Menukhin (RA, Alliance Manchester Business School)

Outputs

• GitHub repository with the updated version of MRAT
• Data from user studies