A Digital Twins in Smart Cities for Building Resilient Urban Infrastructures

Labash, Huda; Kareem Abass, Haithem; Ziiada Zhumabaevna, Murzakmatova; Bodnar, Nataliia; Abdulkhaleq Ali, Ammar

doi:10.22034/jipm.2025.728355

A Digital Twins in Smart Cities for Building Resilient Urban Infrastructures

Document Type : Original Article

Authors

Huda Labash ¹

Haithem Kareem Abass ²

Murzakmatova Ziiada Zhumabaevna ³

Nataliia Bodnar ⁴

Ammar Abdulkhaleq Ali ⁵

¹ Al-Turath University, Baghdad 10013, Iraq

² Al-Mansour University College, Baghdad 10067, Iraq

³ Osh State University, Osh City 723500, Kyrgyzstan

⁴ Al-Rafidain University College Baghdad 10064, Iraq

⁵ Madenat Alelem University College, Baghdad 10006, Iraq

10.22034/jipm.2025.728355

Abstract

ABSTRACT
Background: Digital twin (DT) technologies have become significant enablers of urban management, utilising real-time information, data analytics, and IoT connectivity to manage challenging urban issues. Nonetheless, existing studies reveal the capacity of the DTs, while their generalization, flexibility, and cross-disciplinary application for various urban environments are not thoroughly studied yet.
Objective: This article aims to evaluate the effectiveness of DT technologies in improving traffic management, energy efficiency, infrastructure maintenance, and public safety across six case study cities: There are Singapore, Helsinki, Barcelona, Dubai, New York, and Tokyo. The study examines how DTs can be extended and implemented to target urban issues and how their use operational performance might be optimized.
Methods: The study used quantitative data processing, on-line data analysis with factorization and machine learning, and assessment of the case studies. Quantitative measures which included traffic flow, energy loss, down time, and response to emergency situations were investigated pre and post DT application. The improvements mentioned were statistically confirmed, and the metrics of scalability and adaptability were evaluated in the course of the cities.
Results: DT technologies increased traffic flow by up to 42.9%, reduced energy losses by 35%, minimum down time was 42%, emergency response was 44.9%. This was the case because the network had high IoT coverage and because DTs were applied to the context when it specifically needed them.
Conclusion: The study proves that DTs can be implemented in different environments due to their flexibility to accommodate different urban conditions. AI and cross domain integration can add to the effectiveness of DT in general and both are inarguably now crucial for the management of contemporary urban environment.

Keywords

KEYWORDS: Digital Twins

Smart Cities

Urban Infrastructure

Resilience

Real-Time Monitoring

Predictive Analytics

Sustainability

Data Integration

Simulation

Urban Planning

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