Comparative Analysis of System Architectures for Federated Data Exchange

Digital Twin (DT) technology has become a critical component of smart city evolution, providing real-time analytics, predictive modelling, and operational efficiency enhancements. This paper presents a comparative analysis of system architectures for federated data exchange between digital twins with the purpose of creating a cohesive urban intelligence framework. This framework should enable seamless collaboration across academia, industry, and local authorities, ensuring the sustainable and scalable deployment of digital twin ecosystems. We investigated challenges related to federated data exchange, and analyzed high-level architectures for FDT implementation, emphasizing modularity, real-time processing, and adaptive decision support systems to enhance urban planning, mobility, environmental monitoring, and resilience strategies. A core recommendation is the establishment of a Federated Digital Twin (FDT) platform using a fully composable system architecture, incorporating advanced AI-driven analytics, decentralized data management, and robust interoperability standards.