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Summary:
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A digital twin fundamentally serves as a digital representation of physical entities, environments, processes, and their states. In cities and communities, such digital representations are valuable for integrating heterogeneous urban data, visualizing complex systems, and supporting simulation-based analysis across multiple domains such as mobility, infrastructure, environment, and public services.
However, a digital representation alone is not sufficient to address the complexity and dynamics of urban environments. While a digital twin can represent current or historical conditions and may support predefined simulations, it does not inherently provide the capability to interpret complex patterns, infer latent conditions, predict future situations, or recommend appropriate actions under changing circumstances. In other words, the digital twin provides the representation foundation, but not necessarily the intelligence required for advanced analysis and adaptive decision-making.
This limitation becomes more significant in cities and communities, where large-scale and heterogeneous data are continuously generated from diverse sources, and where conditions evolve dynamically across interconnected systems. To derive meaningful intelligence from such digital representations, additional capabilities are needed to process data, identify patterns, forecast changes, optimize alternatives, and support timely responses.
For this reason, integration with AI is necessary. AI can complement the digital representation provided by the digital twin by enabling predictive, prescriptive, and adaptive intelligence on top of represented urban data and models. Through such integration, the digital twin can serve not only as a representation of cities and communities, but also as a basis for more intelligent understanding, anticipation, and management of urban conditions.
Accordingly, standardization is needed to define requirements for AI-integrated digital twins for cities and communities, including how AI capabilities can be consistently, interoperably, and trustworthily incorporated with digital twin representations.
To enhance digital twin being intelligent, this draft Recommendation provide the concept and the requirements of AI AI-integrated digital twins for cities and communities.
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