The arrival of the digital twins Imagine Fornite meets Minecraft meets the real-world city you live and work in – what a computer game that would be. Imagine working in a data-rich 5D on-screen world that updates in real time and in which you can play ‘what if’ scenarios. We’re actually there right now. By Chris Kirchhoff*
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ake an accurate 3D representation of reality, be it your factory, sewage works, a portion of the CBD or an entire city. Now add to this the fourth dimension of how this world and its surrounding environment – such as weather, traffic, population growth and supporting services – drive changes over time. Then, layer behind this income, expenses and flow of money, as the fifth dimension, and you have yourself a digital twin. The growing internet of things (IoT) enables data to stream backwards and forwards between our real world and our computers. That enables this ‘game’ to work. The IoT enables us to livestream data from the urban environment. This is what’s moved our old-fashioned 3D maps into live digital representations of the real world. This is how a digital twin becomes a dynamic everchanging representation of reality, providing us with both reactive and predictive feedback. For reactive feedback, we can consider that as live traffic data comes in, we can adjust
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traffic flows to ensure better peak-time use of the current roads in our city. Predictive feedback is when we use our digital twin to do future planning. Examples include simulations of population growth or cost increases or droughts to understand how best to allocate the finite resources available in the most sustainable manner. You can look at a digital twin as a Wi-Fi-enabled Lego set. Are you considering a new taxi rank? Imaging putting together a Lego model of the planned rank. As you make changes, you have a dashboard of data showing you how many people you can move through the rank, how peak-time traffic flows around the rank will change and, critically, how your residents can save time moving through the rank. Once the taxi rank is built, you can add sensors such as traffic count, temperature, water and sewage flows, and cameras. This allows for your digital twin to suggest, in real time, how to reactively use the resources in the rank most efficiently.
Modelling evolution In the last century, the first digital 3D models of our environment began to emerge. Over the past 40 years or so, the 3D CAD model has grown into a building information model (BIM). The latter includes a 3D illustration of our building or environment, as well as implanted metadata about the components that make up the model. So, what are the tools needed to create a digital twin? As a foundation, you need accurate, up-todate geospatial data – the ‘where’. The upside is that mapping has become super-efficient. By combining laser or lidar scanning with aeroplaneor drone-based aerial mapping, a 3D model of the built environment can be efficiently collected.
