Quantum-Enabled Urban Planning: Reimagining Smart and Sustainable Cities Through Spatio-Temporal Big Data Intelligence

Cities are generating spatio-temporal big data at a scale, complexity, and velocity that increasingly exceed conventional analytical capacity, driven by rapid urbanisation, climate pressures, and digitalisation. Classical high-performance computing has substantially advanced urban analytics, yet it is approaching practical limits in large-scale combinatorial optimisation, high-dimensional data integration, and real-time decision support. This paper examines how quantum computing and quantum AI can augment such analytics for smart and sustainable urban planning, through the paradigm of quantum urbanism. The study combines a bibliometric mapping of 358 Scopus-indexed records with a structured narrative review and conceptual synthesis. Bibliometric analysis reveals four dominant research clusters, spanning quantum optimisation, quantum machine learning, quantum-secure smart city systems, and quantum communication, and a field still concentrated in computer science (28.4%) and engineering (21.7%), with social sciences accounting for only 7.0% of output, confirming a pronounced urban planning and governance gap. The review identifies land-use and mobility optimisation, energy and environmental monitoring, climate risk modelling, infrastructure resilience, and urban decision support as the domains of greatest near-term potential, while reported gains such as 10-15% reductions in vehicle delay remain proof-of-concept demonstrations on noisy intermediate-scale quantum hardware and in simulated environments. The study concludes that quantum computing is a complementary capability that augments rather than replaces existing planning systems, with hybrid quantum–classical workflows the most realistic near-term pathway. It contributes a conceptual framework linking quantum technologies to planning practice and the Sustainable Development Goals, and a research agenda spanning hardware scalability, governance, and institutional readiness.

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Publication Details

Journal
Preprints.org
Published
2026-10-28
DOI
https://doi.org/10.20944/preprints202610.2727.v1
Primary Topic
Smart Cities and Technologies
Type
preprint
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Quantum-Enabled Urban Planning: Reimagining Smart and Sustainable Cities Through Spatio-Temporal Big Data Intelligence

Wenda Li, Abdulrazzaq Shaamala, Tan Yiğitcanlar, Tahsin Hossain
Preprints.org
Smart Cities and Technologies
preprint

Quantum-Enabled Urban Planning: Reimagining Smart and Sustainable Cities Through Spatio-Temporal Big Data Intelligence

Wenda Li, Abdulrazzaq Shaamala, Tan Yiğitcanlar, Tahsin Hossain
preprint en

Abstract

Cities are generating spatio-temporal big data at a scale, complexity, and velocity that increasingly exceed conventional analytical capacity, driven by rapid urbanisation, climate pressures, and digitalisation. Classical high-performance computing has substantially advanced urban analytics, yet it is approaching practical limits in large-scale combinatorial optimisation, high-dimensional data integration, and real-time decision support. This paper examines how quantum computing and quantum AI can augment such analytics for smart and sustainable urban planning, through the paradigm of quantum urbanism. The study combines a bibliometric mapping of 358 Scopus-indexed records with a structured narrative review and conceptual synthesis. Bibliometric analysis reveals four dominant research clusters, spanning quantum optimisation, quantum machine learning, quantum-secure smart city systems, and quantum communication, and a field still concentrated in computer science (28.4%) and engineering (21.7%), with social sciences accounting for only 7.0% of output, confirming a pronounced urban planning and governance gap. The review identifies land-use and mobility optimisation, energy and environmental monitoring, climate risk modelling, infrastructure resilience, and urban decision support as the domains of greatest near-term potential, while reported gains such as 10-15% reductions in vehicle delay remain proof-of-concept demonstrations on noisy intermediate-scale quantum hardware and in simulated environments. The study concludes that quantum computing is a complementary capability that augments rather than replaces existing planning systems, with hybrid quantum–classical workflows the most realistic near-term pathway. It contributes a conceptual framework linking quantum technologies to planning practice and the Sustainable Development Goals, and a research agenda spanning hardware scalability, governance, and institutional readiness.

Preprints.org
Smart Cities and Technologies
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Quantum-Enabled Urban Planning: Reimagining Smart and Sustainable Cities Through Spatio-Temporal Big Data Intelligence — Wenda Li, Abdulrazzaq Shaamala, et al. · Preprints.org (2026) | TGRS Research Map | TGRS