Integrating IoT and Digital Twins to Transform Urban Governance

Abstract

This research explores the integration of Digital Twin (DT), Internet of Things (IoT), and artificial intelligence (AI) technologies for enhancing innovative city management. The primary objective was to develop a conceptual framework that improves cross-domain interoperability, energy efficiency, cybersecurity resilience, and citizen-centric governance. A scoping review methodology was employed, following PRISMA guidelines, to systematically identify and analyse 1,200 records from central databases, of which 100 studies met the inclusion criteria. The results demonstrated significant improvements in urban performance metrics when DT-IoT-AI systems were applied. Case studies reported up to 28% reduction in building energy consumption, 22% improvement in traffic flow efficiency, and 15% faster emergency response times through predictive simulations. Cybersecurity analysis revealed that nearly 40% of IoT-enabled DT systems exhibited vulnerabilities, underscoring the need for integrated resilience strategies. Error analysis revealed inconsistencies in data standardisation across 17% of the reviewed studies, which limited large-scale interoperability. Overall, the findings confirm that AI-driven DT platforms hold strong potential to transform urban management, but challenges of scalability, inclusivity, and security remain unresolved.