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Lessons from complex networks to smart cities

Nature Cities volume 2, pages 127–134 (2025)Cite this article

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Abstract

A smart city is an urban area that uses technology, data and digital infrastructure to improve the quality of life for its citizens, enhance the efficiency of city services and promote sustainability. Complex networks can enable the extraction of useful information from technologies, such as the Internet of Things, artificial intelligence and big data analytics, in a comprehensive way. This would enable common urban challenges, such as traffic congestion, pollution, waste management and energy usage, to be addressed. Network theory offers a strong framework for analyzing and visualizing complex relationships in urban environments, including transportation, social interactions and infrastructure. This interdisciplinary approach aids in comprehensive city modeling and serves as a vital tool for policymakers to improve the robustness and resilience of urban landscapes.

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Fig. 1: Mechanisms for urban growth and transformation.

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Acknowledgements

M.D.D. acknowledges partial financial support from the INFN grant LINCOLN from MUR funding within the PRIN 2022 PNRR (DD n. 1214 31-07-2023) project no. P2022A889F and from MUR funding within the FIS (DD n. 1219 31-07-2023) project no. FIS00000158. G. Chirici declares partial support from PRIN 2020 MULTIFOR ‘Multi-scale observations to predict Forest response to pollution and climate change’ PRIN_2020_LS9 and from the project NBFC ‘National Biodiversity Future Center’ funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 – Call for tender No. 3138 16/12/2021, rectified by Decree n. 3175 18/12/2021 of Italian Ministry of University and Research funded by the European Union – NextGenerationEU; Award Number: Project code CN_00000033, Concession Decree No. 1034 of 1706/2022 adopted by the Italian Ministry of University and Research, CUP B83C220002910001. G. Caldarelli acknowledges support from EU proposal HumanE-AI-Net no. 952026 and EU proposal NODES CNECT/2022/5162608.

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Author notes

  1. These authors contributed equally: Guido Caldarelli, Manlio De Domenico.

Authors and Affiliations

  1. Institute of Complex Systems (ISC) and Interdepartmental Centre for Cities Science (ICSC), National Research Council (CNR), Rome, Italy

    Guido Caldarelli

  2. DSMN and ECLT, Ca’ Foscari University of Venice, Venice, Italy

    Guido Caldarelli & Jacopo Moi

  3. London Institute for Mathematical Science, Royal Institution, London, UK

    Guido Caldarelli

  4. DSPS, University of Florence, Florence, Italy

    Leonardo Chiesi

  5. Fondazione per il Futuro delle Città, Florence, Italy

    Leonardo Chiesi, Gherardo Chirici, Bianca Galmarini, Stefano Mancuso & Jacopo Moi

  6. Department of System Design Engineering, Keio University, Yokohama, Japan

    Leonardo Chiesi

  7. DAGRI, University of Florence, Florence, Italy

    Gherardo Chirici & Stefano Mancuso

  8. DIDA, University of Florence, Florence, Italy

    Bianca Galmarini

  9. Department of Physics and Astronomy ‘Galileo Galilei’, University of Padua, Padua, Italy

    Manlio De Domenico

  10. INFN Sezione di Padova, Padua, Italy

    Manlio De Domenico

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G. Caldarelli and M.D.D. designed the paper’s focus and contributed equally to the writing of the manuscript. All of the authors contributed to the production of the paper.

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Caldarelli, G., Chiesi, L., Chirici, G. et al. Lessons from complex networks to smart cities. Nat Cities 2, 127–134 (2025). https://doi.org/10.1038/s44284-024-00188-5

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