Data as the content of digital twin cities

Smart technology and innovative solutions are increasingly needed to enable the sustainable and climate-resilient growth of urban conglomerates. The development of data collection systems, cloud computing, the Internet of Things (IoT), 3D modelling, and Artificial Intelligence (AI) paved the way to a new way of managing cities through digital twin cities.

Basically, a digital twin is a virtual digital model that corresponds to the physical object in the real world. When applied to a city, it allows to replicate and correlate a number of factors and systems such as the physical environment, available natural resources, infrastructure and transportation, public services, and more. The idea behind it is to tackle severe issues such as resource depletion, environmental pollution, traffic congestion, or public security, thus promoting more sustainable and livable communities.

Digital twin cities represent a booming market. According to Marketsandmarkets, the global digital twin market will reach $48.2 billion by 2026; China alone is expected to reach $17.3 billion by 2025. Despite the resounding hype, the concept is still in its early stages and many projects are still in the planning phases.

The recently published reportDigital Twin Cities: Key Insights and Recommendations” by the World Economic Forum and China Academy of Information and Communication Technology bring together some ideas and best practices to help optimize the planning, design, development and use of digital twin platforms in cities. The report refers to the SODPA model and discusses the five key elements of digital twin cities: (1) Strategy and talent development, (2) Operation and business, (3) Data and infrastructure, (4) Platform and technology, and (5) Application and scenario.

The report defines data as the ‘content of a digital twin city’, the essential component to have an accurate and granular view of urban systems. Having a reliable network infrastructure with smart sensors to collect and transmit relevant field information is indeed the precondition upon which a digital twin city operates – exactly as the neural network and neurons allow the human body to sense what happens inside and outside it.

Think of urban mobility. Digital twin models aggregate data about environmental conditions, operating transportation systems, road and traffic conditions, etc. and overlap them with geographic information systems (GIS) to create a virtual live map of the city’s transport network. This empowers data-driven decisions on route planning, traffic management, and emergency intervention when and where needed.

The above-mentioned report warns city managers not to imagine digital twin cities as a mere amalgamation of data: they are a dynamic and digital replication of cites, providing a more holistic and actionable view of urban communities.

Digital twin cities bring together the physical and digital worlds to unleash new ways of managing urban areas. They have the potential to transform cities into more intelligent entities, leading to high-quality urban development and sustainable growth.

Photo credit: JC Gellidon on Unsplash

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