It has been suggested that digital twin technology divides opinion among artificial intelligence (AI) practitioners.

Either they think it is completely irrelevant to AI or they have no opinion because they have never heard of it.

What are digital twins?

According to the Alan Turing Institute, a digital twin is a computer model that simulates an object or process in the physical world.

The object could be a jet engine, a bridge, a wind turbine, a Formula One car, a supply chain, a biological system, a 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 or functioning.

The UK has some major digital twin projects underway that are ground-breaking in their ambition, such as delivering the world’s first AI system to control a section of airspace in live trials and work with air traffic controllers to help manage the complexities of their role. Or using connected digital twins to understand how critical infrastructure assets work as part of a wider system, particularly in adapting to climate change.

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Making UK infrastructure more climate-resilient

Earlier this week, the UK’s Institution of Civil Engineers (ICE) published a paper that discussed ways in which the UK can strengthen the resilience of its infrastructure system. One of the four suggestions involves digital twins.

Specifically, the ICE suggests digital twin technologies can build evidence and highlight the impacts of possible future policy decisions, as well as retrospectively measure the impact of those already in progress. Digital twins can also close the data gap to help us understand how infrastructure assets work together as part of a wider system.

The UK’s infrastructure will need to be designed and operated in a way that copes better with today’s extremes and is resilient to the more ‘extreme extremes’ of the future. 

Project Bluebird

Project Bluebird brings together the Alan Turing Institute and air traffic control services provider NATS Holdings to explore further what role AI can play in air traffic management.

The intention is to deliver the world’s first AI system capable of controlling a section of airspace and working with air traffic controllers to help manage the complexities of their role. In the UK alone, air traffic controllers handle as many as 8,000 planes each day, issuing instructions to keep aircraft safely separated.

The project has three main research themes: to develop a probabilistic digital twin of UK airspace, which will help predict future flight trajectories and their likelihoods; build a machine learning system that collaborates with humans to control UK airspace; and design methods and tools that promote safe, explainable, and trustworthy use of AI in air traffic control system.