Experimenting on Digital Twins Helps us Understand Reality

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It’s hard to predict the future, but with enough data we can at least get better at it. That’s exactly what digital twins are all about. By using as much real world data as possible to model out anything from a building, to a person, to a city in a digital space we can run simulations on what can work best for the real world counterpart. Of course, since simulations are only as good as the data source (and how we process the data) there are limits to effectiveness of digital twins; still, the idea that we can effectively model solutions and their potential outcomes in higher fidelity is appealing.

With the rise of the internet of things, sensor technology is increasingly being installed in our homes and workplaces, as well as the physical infrastructure that surrounds us. Meanwhile, cloud computing makes it easier than ever for data to be shared across different devices and networks.

As a result, businesses and other organisations have been able to build up huge volumes of data. Not all of this is private either – online sources such as the London Datastore are making live data readily available to anyone who wants to use it.

“We see digital twins as a way of improving decision making,” Hayes told Dezeen.

“A city is effectively a system of systems – water, electricity, housing, schools, hospitals, prisons, natural environment – it all fits together,” she said. “When you start to connect the datasets from these digital twins, you can build a bird’s eye view of a city, which gives you better information about the consequences of your decisions.”

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