Interoperability in Smart Cities: A Systematic Review of Unified Digital Twin Models

Abstract

Smart Cities (SCs) leverage advanced technologies and data analytics to optimize infrastructure and services for economic and quality of life benefits. However, realizing the potential of SCs requires interoperability between different systems, which remains challenging due to fragmentation. Thus, unified architectures are needed to enable effective coordination through common languages and protocols. Digital Twin (DT) models, bidirectional virtual representations of physical assets, show immense promise for unifying SCs by integrating massive heterogeneous data streams. Although there have been numerous studies investigating unified models for SCs, in the context of DT, most studies narrowly focus on using DT for different systems within cities rather than citywide implementation. As a response, this study identified 34 recent papers investigating interoperability and unified models in SCs, out of which 19 papers were focused on developing unified models for SCs and 15 papers were focused on unified DT models in SCs. These 15 papers were systematically reviewed, identifying the key factors, benefits, and challenges of such models. To help city leaders and to make focused, context-aware decisions aligned to their objectives, whole factors were categorized into four groups, including relevance-based, influence-based, complexity-based, and risk-based. To guide future research, the study highlights edge computing and implementing blockchains as underrepresented areas within the realm of SCs.