An Architectural Framework for Urban Digital Twin Design: A Case Study on Hydrogeological Risk Management

Real-time risk assessment has become essential in modern risk management, enabling organizations to effectively react to dynamic threats in various sectors. Real-time risk assessment leverages advanced technologies such as machine learning, data analytics, and Internet of Things ((loT) devices to provide timely insights for decision-making. Cyber-physical systems can play a crucial role by integrating computational and physical processes, allowing real-time monitoring and control of complex systems. The synergy between cyber-physical systems and real-time risk assessment is particularly crucial in urban environments, where the complexity of risks makes it essential for them to be mutually dependable and resilient. Digital twins can further enhance urban management by providing virtual representations that facilitate real-time monitoring and analysis. This paper proposes an architectural framework compliant with the Digital Twin Space model, which integrates digital twins and data spaces to improve urban data management while ensuring privacy and security. A case study on hydrogeological risk management is proposed to demonstrate the effectiveness of the framework through a minimal FIWARE-based early warning system. The findings highlight the importance of developing systematic methodologies for urban digital twin design to ensure its functionality, reliability, and adaptability in increasingly complex urban environments.