GT-Craft: A Framework for Fast Prototyping Geospatial-Based Digital Twins in Unity 3D

A digital twin presents promising opportunities and potential benefits for various industrial use cases by enabling simulation and prediction on the virtual representation of the real-world environment. However, the implementation and maintenance costs for the digital twin are prohibitively high, restricting its widespread adoption. To address this issue, we present a framework, GT-Craft, which enables fast prototyping the geospatial-based digital twin at scale. GT-Craft automates the generation of the digital twin by using the streamed geospatial data and the semantic information extracted from deep neural network (DNN) models. As GT-Craft generates digital twins on the Unity game engine, the Unity-based simulators and game applications can seamlessly use the digital twins generated by GT-Craft. The presented framework is compatible with non-Unity-based applications and existing 3D software and simulation tools, e.g., Blender, Apple Reality Composer, and NVIDIA Omniverse, as it supports exporting the generated digital twin in the universal scene description (USD) format, which is an emerging industrial open standard for exchanging and editing 3D contents.

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Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1109/sec62691.2024.00043
Citations
2
Primary Topic
3D Modeling in Geospatial Applications
Type
article
Field-Weighted Citation Impact
0.53

Funders

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article

GT-Craft: A Framework for Fast Prototyping Geospatial-Based Digital Twins in Unity 3D

Salam Akoum, Thomas Novlan, Ada Gavrilovska, Jin Heo
2 citations
3D Modeling in Geospatial Applications
0.53
article

GT-Craft: A Framework for Fast Prototyping Geospatial-Based Digital Twins in Unity 3D

Salam Akoum, Thomas Novlan, Ada Gavrilovska, Jin Heo
article en
2 citations

Abstract

A digital twin presents promising opportunities and potential benefits for various industrial use cases by enabling simulation and prediction on the virtual representation of the real-world environment. However, the implementation and maintenance costs for the digital twin are prohibitively high, restricting its widespread adoption. To address this issue, we present a framework, GT-Craft, which enables fast prototyping the geospatial-based digital twin at scale. GT-Craft automates the generation of the digital twin by using the streamed geospatial data and the semantic information extracted from deep neural network (DNN) models. As GT-Craft generates digital twins on the Unity game engine, the Unity-based simulators and game applications can seamlessly use the digital twins generated by GT-Craft. The presented framework is compatible with non-Unity-based applications and existing 3D software and simulation tools, e.g., Blender, Apple Reality Composer, and NVIDIA Omniverse, as it supports exporting the generated digital twin in the universal scene description (USD) format, which is an emerging industrial open standard for exchanging and editing 3D contents.

Georgia Institute of Technology (US)
National Science Foundation
Openalex Percentile: Top 32%
3D Modeling in Geospatial Applications
0.53
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