Consider your drive to work. How much traffic you encounter will depend on a number of factors: the weather on any given day; the quality of public transport and cycle routes; the efficiency of the town planning in your city; how many people can afford to live within walking distance of their workplace, and so on. You can think of the workings of a city and how people move around it as a complex, dynamic system that is always reacting to changing circumstances. If we can better understand this system and visualise how it works, we can make decisions to improve its efficiency. And that’s where digital twins come in.

A digital twin is a computational model of a complex system that is continually updated with real-world data. The system being modelled could be a city, a manufacturing process, some industrial machinery or even biological systems within the human body. By creating a simulation of a system we can experiment with potential improvements to see how well they work before trying them in the real world. We can discover and understand connections between different parts of the system that were previously invisible to us. We can predict potential points of failure and take action before problems arise, and we can develop new products and medicines.