
The digital twin has long been the stuff of science fiction: for decades, people have dreamed of being able to predict and intervene in reality using three-dimensional, dynamic and interactive digital images of material objects. After all, superhero Iron Man also uses holograms to visualize, play through and control tools and processes. But what is a digital twin in the context of a smart city? And what is its added value alongside all the other digital and data-based solutions and applications on the market?
Digital twins were not just invented for digital urban development: In industrial production, three-dimensional digital images of material products have been used for optimization processes for years. Strictly speaking, the digital twin is the exact digital imitation of a reality. In the context of urban development, the term is usually used more loosely to describe digital 3D models of a city in which many different types of data are displayed for different applications. In such an urban digital model of buildings, streets and entire city districts, various data from different sources can be gradually added and supplemented. The aim is to turn the twin into a management tool that can provide up-to-date information and forecasts. But where are the limits for an image of such a multi-layered construct as a city? The digital twin in an urban context can hardly encompass all the processes that make up the city as a whole. Even a high-resolution virtual 3D model that integrates traffic or energy flows in (near) real time neglects characteristics such as social dynamics and economic functions. However, as these ultimately make up a city as a system, the urban digital twin ultimately remains a model – it is perhaps not possible or desirable to design it as a holistic image of reality. In a later expansion stage, the data can be enriched with models and algorithms to enable a better understanding of complex interactions and interdependencies between different processes in the city – for example, the relationships between weather, traffic, construction sites and energy systems. It is also possible to use simulations to create forecasts for urban behavior or planning variants. Where are we in the development process?
Module by module for networked simulations
The most important components of a digital city twin have been developed and tested in recent years. There are also the first commercial solutions operated by municipalities that are testing the digital city twin as an overall architecture. Numerous modules of a digital twin of the city are already open source and standardized and can therefore be easily replicated.
- The urban data platform as a hub and management system for static and dynamic data. Urban data platforms such as the open source platform from DKSR, for example, are already being used by local authorities.
- 3D models of cities in commercial or open source versions are also becoming increasingly popular.
- For certain domains, there are models for simulations and forecasts that are used as part of innovation projects or in the context of urban services – for example, flood early warning systems based on artificial intelligence, energy control in neighborhoods or dynamic traffic control based on environmental data or real-time information.
However, there are also a number of research and innovation projects that aim to develop and test a complete digital city twin. Two well-known ones are the German CUT (Connected Urban Twins) project and the European DUET project.
- For the Connected Urban Twins project funded by the Federal Ministry of Housing, Urban Development and Building, the cities of Munich, Leipzig and Hamburg are cooperating with each other to implement three different digital twins that contain common elements. These should also be able to be used in other cities thanks to common standards.
- The EU project DUET is investigating how decision-making in the public sector can be made more democratic and effective through the development and use of digital twins. 3D city models are being used to test the political impact in cities and regions.
So there are already great-sounding names, abbreviations and hard-working developments. And what is the added value of this development?
Step by step to multiple added value?
The question of the added value of digital twins is also a topic of debate among the experts. To what extent do we need such complex technology as a basis for making good decisions? Do we need to become the Tony Starks of digital urban design in order to save our world from the consequences of climate change? This will probably remain a contentious issue. But there are good arguments for the use of urban digital twins: after all, urban development in the current century is facing increasingly complex challenges. Climate change and climate adaptation are forcing us to think and plan domains such as mobility, logistics, energy and water in a networked way. Municipalities must react to independent processes. The urban space is becoming increasingly multifunctional, which must be taken into account in the life cycle of the measures to be planned, whether streets, buildings, neighborhoods or networks. The speed of technological innovations in the field of urban infrastructures and solutions requires a holistic and at the same time dynamic approach as well as a high degree of technological openness. (Investment) decisions must therefore be made under conditions of growing uncertainty. And this is where the strength of the digital city twin lies: it enables urban planners and developers such as logisticians, energy companies, transport operators and other decision-makers to plan better, more simply and jointly on the basis of data. Various future scenarios can be simulated with the twin, extreme situations can be tested and the impact on people, the environment and space can be anticipated before a planning decision is made. A digital twin is a tool that enables participation and cooperation and supports an intuitive, visually easy-to-transport understanding of different disciplines and domains. It can also be used to intervene in the operation of a city in real time and reactively, thus contributing to smoother and more resource-efficient services for citizens. These steps towards an urban digital twin as a planning tool for forecasting and decision-making purposes can be found in existing pilot projects. However, they are not yet fully developed. And finally, it must always be remembered that the future remains real – and therefore unpredictable in some areas. To come back to the possibilities: While services and solutions that already result from the existing possible uses of the twin may well be proprietary, as they sometimes require a high level of domain expertise, the digital twin should be disseminated as widely as possible, regardless of the provider, as the basic technology for the greatest possible added value. This, in turn, can only be achieved with an open source approach such as that of the DKSR Open Urban Data Platform, with which digital city twins can also be replicated and integrated into ever new environments.
What do you think? Can the digital city twin offer us new solutions – or will we find them much easier with other tools? If you have any questions, doubts or comments on the topic, please feel free to contact our experts Lukas Koch and Alanus von Radecki!