The Cyprus Digital Twin architecture for resilient smart cities and critical infrastructure systems

Digital twins are increasingly used to support the monitoring and management of urban infrastructure, yet their application to disaster preparedness and critical-infrastructure resilience remains fragmented across individual hazards and infrastructure sectors. This article presents the Cyprus Digital Twin (CyDT), a modular, scenario-driven platform for integrating heterogeneous data, infrastructure models, simulation tools, and stakeholder-oriented services within a common digital environment. CyDT combines geospatial, historical, demographic, and streaming data with distributed workflow execution, domain-specific simulators, interactive visualization, application programming interfaces, and controlled access to public and confidential datasets. The platform is demonstrated through four scenarios addressing wastewater contamination of a drinking-water network, blast propagation in an industrial area, wildfire interaction with power infrastructure, and windstorm impacts on co-located power and telecommunication assets. The scenarios show how CyDT connects hazard evolution with infrastructure exposure, potential failure, population impact, and alternative mitigation actions. In particular, the contamination scenario quantifies how network intervention can reduce population exposure, while the windstorm scenario demonstrates that infrastructure sectors exposed to the same hazard may experience significantly different disruption patterns because of differences in asset distribution and fragility. Collectively, the results illustrate the value of a reusable digital-twin architecture for exploring vulnerabilities, comparing response strategies, and communicating the spatial and temporal consequences of disruptive events. The study also identifies model validation, computational responsiveness, interoperability, data governance, and organizational integration as key requirements for progressing from research-oriented scenario analysis toward operational decision support.