Incorporating integrated digital copies of city systems and their environments into the design of smart cities will require new approaches based on advanced modeling and digital twin platforms to ensure a smooth transition from the use of digital twins in manufacturing and industrial contexts.
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The Role of Digital Twins for Smart Cities
While the digital twin concept is well-established in manufacturing and industrial contexts for using digital replicas of physical systems to accelerate and optimize design, management, monitoring, and maintenance of production facilities, it is a new paradigm for smart cities.
Digital twin technologies are firmly rooted in the modeling paradigm. Cities are especially interested in predictive models for flooding, traffic, energy generation, and consumption patterns, but also the economy itself. Porsche holding-owned leading traffic modeling supplier PTV has been developing sophisticated models of road traffic systems for many years. Digital twins will also have a critical role to play in scenario planning and impact assessment of various emergency situations and as input for the design of resilient smart city systems.
Digital twins consist of integrated, real-time, three-dimensional (3D) models of a city’s physical assets, including streets, buildings, public spaces, and a suite of sensors to monitor a wide range of parameters related to power and water flow, emergency services, and service consumption patterns. They are integrated digital copies of smart city systems and their environments, allowing the development and implementation of more holistic resilience policies based on the modeling of interdependencies between vertical systems and infrastructure. Bringing disparate systems and models together under one unified framework is a key benefit of digital twin technologies.
Suppliers offering digital twin solutions for smart cities include Microsoft (Azure Digital Twins) and Cityzenith (Smart World Pro software).
Two Examples: Cambridge and Rotterdam
Cities across the globe are discovering the benefits of digital twin technologies, as illustrated by the two examples below:
Cambridge: Smart Cambridge and the Cambridge Centre for Smart Infrastructure and Construction (CSIC) are developing a digital twin prototype, combining traditional urban modeling techniques, new data sources, and advanced data analytics. The project is funded by the Ove Arup Foundation and the Centre for Digital Built Britain and is aimed at the detailed modeling of commute patterns, consumer attitudes, and traffic habits, including the impact of trends/investments in transportation, housing, flexible working, and new technologies. The main objectives are linked to sustainability in terms of the reduction of congestion and air pollution.
Rotterdam: Focused on the port area, Rotterdam’s digital twin project is centered on Artificial Intelligence (AI)-based predictive analytics to improve urban planning and inform long-term infrastructure investments, but it will also be used for near-real-time service and maintenance operations such as firefighting, leveraging 3D models of buildingsand real-time building occupant data, improved waste management service and efficiency, thelocation monitoring of emergency services to optimize response effectiveness, and water and road traffic management. The relevance of the digital twin project goes beyond the physical infrastructure to include the digital and social environments. It consists of three layers: data sources and sensors, the generic platform, and the application layer. Interoperability guidelines derived from the European Union (E.U.)'s ESPREssO project were applied. Openness is enabled through application programming interfaces (APIs) and data marketplaces.
Smart Cities as Industrial Entities Require New Approaches
While smart cities have and are still being talked about in terms of eGovernment platforms aimed at increasing the livability of cities and improving the convenience for citizens, they should also be seen as very complex interconnected industrial systems, kind of like uber plants in terms of energy generation, water and gas utilities, road and building infrastructure, water management and control, security systems, etc. In order to accurately monitor and predict operations and guarantee the continuity of public service, especially in relation to resilience objectives, digital twins are now making their appearance in initial applications like traffic flow and water/flood design simulation and monitoring. Increasing complexity and growing dependencies between systems from different verticals require new approaches based on advanced modeling and digital twin platforms to manage and protect urban super structures.
Smart cities need to be incorporated in the wider Industries 4.0 debate and suppliers need to extend their horizon beyond the narrow concept of isolated manufacturing plants to include the smart cities opportunity. Many of the concepts applied to manufacturing and other industrial verticals can be ported to smart city contexts, but with different operational and commercial modalities in terms of time frames, co-funding, business models, and data sharing agreements.