Introduction
Since its inception in 2015, The Alan Turing Institute has established the largest concentration of digital twins research in the UK, in areas from aerospace and civil engineering to urban modelling and agricultural monitoring. The Turing is developing twins that are informed by the latest thinking in artificial intelligence (AI), with the aim of addressing grand societal challenges and generating tangible, real-world benefits.
What is a digital twin?
Put simply, a digital twin is a computer model that simulates an object or process in the physical world. This could be a jet engine, bridge, wind turbine, Formula One car, supply chain, biological system, factory, or even an entire city. The digital twin is regularly updated with sensor data from its physical counterpart, and by analysing the twin, decision makers can gain insights into the behaviour of the physical system, allowing them to improve its design and/or functioning.
The idea of using a digital simulation to understand a physical object is not a new one. In 1970, for instance, NASA mission controllers used computer simulations of the stricken Apollo 13 spacecraft to safely bring the astronauts home following an onboard explosion. Over the past decade, however, digital twins have reached new levels of sophistication, thanks to the decreasing cost of computation, the availability of low-cost, high-fidelity sensors, and advances in wireless communication technologies.
At the Turing, we expect AI to play an ever more important role in digital twin technology, whether in optimising the design of the twins themselves, or in identifying hidden patterns and structures in their output data. This is a technology that holds untapped potential across so many domains, from health, climate and energy to engineering, logistics, economics and beyond.
