Description: This project focuses on developing a Digital Twin system that creates a real-time virtual replica of a physical infrastructure asset, such as a building, bridge, or industrial facility. By integrating sensor data, 3D modelling (e.g., BIM), IoT systems, and simulation techniques, the Digital Twin can monitor the asset’s performance, predict future behaviour, and assist in decision-making for maintenance, optimization, and lifecycle management.

The goal is to enhance operational efficiency, reduce downtime, and improve system reliability through data-driven insights and predictive analytics.

Required Skills & Traits: Programming Skills: Proficiency in Python and/or JavaScript for backend or simulation scripting

3D Modelling & BIM Tools: Familiarity with tools like Revit, AutoCAD, or Unity/Unreal Engine for visualizations

IoT and Embedded Systems: Basic understanding of sensors, Raspberry Pi/Arduino, and real-time data acquisition

Data Handling: Experience with APIs, databases (SQL/NoSQL), and real-time data processing frameworks

Analytical Thinking: Ability to break down complex systems into components for simulation and modelling

Expected Outcomes: A functional prototype of a Digital Twin system for a selected infrastructure asset

Integration of real-time sensor data with a 3D model

Dashboard or interface for monitoring key parameters (e.g., temperature, stress, vibration, occupancy)

Report or documentation covering the design, implementation, and impact of the Digital Twin

Demonstration of predictive analytics or fault detection based on collected data

A scalable framework that can be adapted to other domains (smart buildings, factories, etc)

Specific courses required for project execution

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Station Overview

Project 1

Title: Digital Twins for Real-Time Monitoring and Simulation of Infrastructure Systems