This year Gartner, in their annual Top 10 Strategic Technologies Trends list, put Digital Twins at the number 4 spot, just behind all Autonomous Things, Augmented Analytics and AI-Driven Development. This is a pretty meteoric rise for Digital Twins which didn’t make the 2016 list at all, jumped in at number 5 in 2017 list, moved to number 4 in 2018 and has held its position in 2019.
So why have digital twins arrived on the Garter digital consciousness and what does it mean for the spatial industry? Firstly, let’s define what a Digital Twin is and how it is pertinent to the spatial industry.
A digital twin refers to a digital replica of a physical asset. A model that integrates external stimulus to constantly learn and update itself to represent in near real time its physical equivalent.
Many organisations have created digital twins to represent various things from aircraft engines and wind turbines, to offshore oil platforms and buildings. There is a growing use case in the utilities sector and even the healthcare sector is attempting to create digital twins of patients. Creating a digital twin means that you can test scenarios, optimise the operation and maintenance of physical assets or optimise manufacturing processes, or be warned of potential issues as they happen in real time.
In the spatial industry we have already experienced the Smart City. The Digital Twin City is perhaps simply the next evolution of the Smart City combining many smart sensors with 3D building models and transport networks to build a Digital Twin capable of modeling the city in near real time. However, a city is not simply just buildings, roads and other infrastructure. In 1948, German urbanist Hans Reichow compared a city to a living breathing organism and perhaps the one thing a Digital Twin city is missing is blood flowing through its arteries, or more simply people who inhabit the city.
Until recently, understanding population movement has been difficult. At Abley, we have developed numerous accessibility models to help us understand human movement and demand. For example, models that analyse road safety around schools, or models that assess the impact of changing bus routes on affected communities. With the growth of Mobility Analytics (the use of aggregated mobile phone data) the ability to understand population movement potentially becomes easier. Commuter behavior patterns and how they change in response to the weather can be assessed, or the ability to detect incidents and congestion in real time, or the ability to understand origin-destination models with realistic demographic modelling, or the ability to optimize retail networks can all start to become part of the analytical and modelling capability allowing city planners to understand the city like never before.
The Digital Twin City is getting a step closer to reality and cities like Singapore (https://reut.rs/2Q8MtEP) are showing us just how far they have come. But to have a Digital Twin City we must accept that we are part of it. Our location is more than just a location, it’s a gateway into understanding how the city lives and breathes.
Blog written by Chris Morris, Spatial Group Manager