Mini XR Training Simulation

Overview

This repository contains a mini project demonstrating data-driven XR/VR training for construction worker tasks. The project simulates joint angles, task time, and discomfort, then visualizes them in a simple WebXR/A-Frame environment.

The goal is to showcase how analytics can be integrated into XR-based feedback, enabling users to see real-time color-coded discomfort levels based on simulated data.

Project Structure

MiniXRDemo/

├── worker_task_data.json # Simulated task dataset with color mapping

├── mini_xr_training.py # Python file for data simulation & analysis

├── index.html # A-Frame VR environment

├── README.md # This file

Tools and Libraries Used

Python & Analytics:

• Python 3.x

• pandas, numpy

• matplotlib, seaborn, plotly

• scikit-learn (LinearRegression)

XR/VR Visualization:

• WebXR / A-Frame

• HTML, JavaScript

• JSON for feeding data to VR scene

Development Tools:

• VS Code (editor)

• Live Server extension (for local hosting)

How It Works

Data Simulation (Python):

• Joint angles, task time, and discomfort scores are generated for workers and tasks.

• A linear regression model predicts discomfort from the simulated angles and task times.

• Discomfort is mapped to color codes (green/yellow/red) for VR visualization.

• JSON file is exported (worker_task_data.json) to feed into the VR environment.

VR Visualization (A-Frame):

• The index.html reads the JSON and displays a cube representing a worker’s task.

• Cube color updates every few seconds according to the discomfort score.

• Text panels show Worker ID, Task, and Discomfort.

Viewing the VR Environment

Option 1: Local

• Clone this repository.

• Open VS Code and open the project folder.

• Open index.html.

• Start Live Server in VS Code. The browser will open and you will see the cube changing colors according to discomfort.

Option 2: Recorded Demo

For users who cannot run locally, a screen recording demonstrates the VR environment. Find the Google Drive Demo Link Here

Key Insights

• The model predicts mid-range discomfort accurately but underestimates extreme values (1 or 5).

• Color-coded VR cube provides quick visual feedback of task risk and discomfort.

• The workflow demonstrates end-to-end integration of Python analytics with XR visualization.

How to Run

-Clone repo git clone https://github.com/ModestaUZO/Mini-XR-Training-Simulation.git cd MiniXRDemo

-Open index.html in VS Code and run Live Server

Future Work

• Add more workers/tasks.

• Animate cube limbs based on joint angles.

• Host VR environment live online for full interaction.