Cities are complex systems, but what if we could model every aspect of them to predict the future? How could such a model assist with urban planning and addressing climate change with greater certainty? Digital Twins are virtual replicas of the real world that help us predict and monitor changes. There are lots of digital twins being established across the globe. Currently, a Digital Twin of Earth is being developed to simulate hazards and track human activities.
Across the world, urban areas are creating digital twins to provide information, models, and scenarios for national and local decisions ranging from building energy efficiency to emergency services and crisis response, such as Digital Twin Victoria. The theory is that by creating a twin, we are more likely to identify where things go wrong and what needs adapting and, therefore, predict the future with certainty. This is why the concept emerged from NASA in the late 1960s to simulate and predict failure in physical spacecraft systems. For urban settings, digital twins are constructed by a range of embedded sensors such as air quality and CCTV cameras, use a range of AI models for analysis and usually feature data dashboards to show the dynamics of a city such as the Newcastle Urban Observatory.
Virtual Singapore is perhaps the most established urban digital twin and has collected large-scale 3D data, including underground utilities, to support a range of government departments and provide a single-source platform for citizens. Digital Twins are emerging, but how should they be designed? The danger of these new approaches is that they do not repeat the mistakes of the Sidewalk Labs, Toronto waterfront project in 2021, an abandoned smart city project that failed to communicate its benefits as well as raise ethics and privacy issues in how data was collected by the people set to live there. Sidewalk Labs is an example of a top-down development that lacked citizen consultation. This raises an important question about how urban digital twins should be deployed and designed and who they are for; how can they be trustworthy and reliable?
There is real potential to predict climate change in areas such as the impact of flooding, as seen in the CReDo case study and its impact on energy infrastructure, or DUET, a digital copy of real-world assets that informs government policy. Our new research highlights the way urban digital twins can be designed as systems, and the Alan Turing network DTNET+ is exploring the impact of digital twins across UK sectors.
As Asaf Tzachor et al states,
“digital twins may model entire systems within which different objects are embedded, thereby making predictions about their behaviour over time and under different conditions and constraints.” (Tzachor et al. 2022).
It is important that citizens have a say in this process, as digital twins will be used to make decisions about all aspects of everyday life. This could include using digital twins to improve public spaces and food systems, develop self-driving cars and traffic management, or simulate large-scale urban redevelopment, such as in Virtual Gothenburg, Sweden. One particular research aspect explored the use of an augmented reality (AR) smartphone app in which users can contribute information and communicate preferences and observations to city officials and the digital twin.
As cities and urban areas develop their digital twins, we can begin to see the potential for citizen tourism through the metaverse, such as the one created by Zoan for Helsinki, Finland, which started in 2015. Michael Batty has written about the role of computing in shaping urban behaviour and development, and digital twins may represent the next phase of this evolution. However, there is no universal approach; urban digital twins must reflect the unique characteristics of the settings they model, making them distinct to different geographies around the world.
Moreover, citizen engagement with these platforms is crucial, as decisions will be based on the models created. Digital twins can be constructed from the ground up, with active citizen participation in their development, as demonstrated in Herrenberg, Germany, allowing people to engage with and envision the future of their environment.
We are on the cusp of a new phase in computing for urban environments. It is essential to discuss how these systems are designed for the future and their purpose and to understand their predictive capabilities for tomorrow.
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