Applications · Established · Intermediate

Digital Twin

A continuously updated virtual model of a physical asset, process or system used for monitoring and what-if analysis.

What Digital Twin is

A digital twin is fed by live sensor data, so it reflects the current state of the real thing rather than a design-time snapshot.

How it works

Sensor streams update a physics or data-driven model; machine learning predicts degradation and simulates interventions before they are applied physically.

Why it matters

It turns maintenance and operations from reactive to predictive, which is where much of the industrial value of AI sits.

Common uses

→Predictive maintenance of turbines and engines
→Factory throughput optimisation
→Building energy management
→Utility network planning

Strengths

✓Test changes without downtime
✓Early fault warning

Watch for

✓Requires reliable sensor infrastructure
✓Model drift versus the physical asset

Continue exploring

Simulation for AI AI and the Internet of Things Time Series Forecasting Anomaly Detection