Extended Reality (XR) technologies are increasingly used in industrial engineering to support design validation, operator training, system analysis, and Digital Twin–enabled decision making. Despite recent advances in web-based visualisation frameworks, building VR environments that are flexible, semantically consistent, and interoperable with engineering data sources remains a significant challenge. This paper presents VEB.js, a web-based, model-driven virtual environment designed to address these limitations and provide an open, reconfigurable platform for research and education in industrial engineering. VEB.js automatically generates 3D scenes from structured data, ensuring semantic consistency and runtime adaptability, while integrating with Digital Twin and IoT infrastructures through lightweight protocols such as HTTP and MQTT, which enable real-time data-driven updates and synchronisation. Furthermore, VEB.js includes a synthetic data generation module capable of producing annotated datasets to support AI-based computer vision workflows. Implemented on top of modern WebGL/WebXR technologies, VEB.js offers cross-platform accessibility without installation, making it suitable for research experimentation, interactive learning, and scalable virtual applications.

A Virtual Environment Based on Babylon.js (VEB.js) to Support Engineering Research and Education

Urgo, Marcello
2026-01-01

Abstract

Extended Reality (XR) technologies are increasingly used in industrial engineering to support design validation, operator training, system analysis, and Digital Twin–enabled decision making. Despite recent advances in web-based visualisation frameworks, building VR environments that are flexible, semantically consistent, and interoperable with engineering data sources remains a significant challenge. This paper presents VEB.js, a web-based, model-driven virtual environment designed to address these limitations and provide an open, reconfigurable platform for research and education in industrial engineering. VEB.js automatically generates 3D scenes from structured data, ensuring semantic consistency and runtime adaptability, while integrating with Digital Twin and IoT infrastructures through lightweight protocols such as HTTP and MQTT, which enable real-time data-driven updates and synchronisation. Furthermore, VEB.js includes a synthetic data generation module capable of producing annotated datasets to support AI-based computer vision workflows. Implemented on top of modern WebGL/WebXR technologies, VEB.js offers cross-platform accessibility without installation, making it suitable for research experimentation, interactive learning, and scalable virtual applications.
2026
Lecture Notes in Computer Science
9783032334992
9783032335005
Synthetic Data; Virtual Reality; Web Application;
Synthetic Data
Virtual Reality
Web Application
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1325625
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