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Urban Computing for Sustainable Smart Cities: Recent Advances, Taxonomy, and Open Research Challenges

Author

Listed:
  • Ibrahim Abaker Targio Hashem

    (Department of Computer Science, College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates)

  • Raja Sher Afgun Usmani

    (Department of Software Engineering, Faculty of Computing, and Information Technology, University of Sialkot, Sialkot 51040, Pakistan)

  • Mubarak S. Almutairi

    (College of Computer Science and Engineering, University of Hafr Albatin, Hafar Al-Batin 39524, Saudi Arabia)

  • Ashraf Osman Ibrahim

    (Faculty of Computer Science and Information Technology, Alzaiem Alazhari University, Khartoum North 13311, Sudan)

  • Abubakar Zakari

    (Faculty of Computer Science and Information Technology, University Malaya, Jalan Universiti, Kuala Lumpur 50603, Malaysia)

  • Faiz Alotaibi

    (Department of Computer Science and Information Technology, UPM, Seri Kembangan 43400, Malaysia)

  • Saadat Mehmood Alhashmi

    (Department of Computer Science, College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates)

  • Haruna Chiroma

    (College of Computer Science and Engineering, University of Hafr Albatin, Hafar Al-Batin 39524, Saudi Arabia)

Abstract

The recent proliferation of ubiquitous computing technologies has led to the emergence of urban computing that aims to provide intelligent services to inhabitants of smart cities. Urban computing deals with enormous amounts of data collected from sensors and other sources in a smart city. In this article, we investigated and highlighted the role of urban computing in sustainable smart cities. In addition, a taxonomy was conceived that categorized the existing studies based on urban data, approaches, applications, enabling technologies, and implications. In this context, recent developments were elucidated. To cope with the engendered challenges of smart cities, we outlined some crucial use cases of urban computing. Furthermore, prominent use cases of urban computing in sustainable smart cities (e.g., planning in smart cities, the environment in smart cities, energy consumption in smart cities, transportation in smart cities, government policy in smart cities, and business processes in smart cities) for smart urbanization were also elaborated. Finally, several research challenges (such as cognitive cybersecurity, air quality, the data sparsity problem, data movement, 5G technologies, scaling via the analysis and harvesting of energy, and knowledge versus privacy) and their possible solutions in a new perspective were discussed explicitly.

Suggested Citation

  • Ibrahim Abaker Targio Hashem & Raja Sher Afgun Usmani & Mubarak S. Almutairi & Ashraf Osman Ibrahim & Abubakar Zakari & Faiz Alotaibi & Saadat Mehmood Alhashmi & Haruna Chiroma, 2023. "Urban Computing for Sustainable Smart Cities: Recent Advances, Taxonomy, and Open Research Challenges," Sustainability, MDPI, vol. 15(5), pages 1-32, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:3916-:d:1075658
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    References listed on IDEAS

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    Cited by:

    1. Mubarak Saad Almutairi, 2024. "Evolutionary Multi-Objective Feature Selection Algorithms on Multiple Smart Sustainable Community Indicator Datasets," Sustainability, MDPI, vol. 16(4), pages 1-25, February.
    2. Ana Perišić & Ines Perišić & Branko Perišić, 2023. "Simulation-Based Engineering of Heterogeneous Collaborative Systems—A Novel Conceptual Framework," Sustainability, MDPI, vol. 15(11), pages 1-24, May.
    3. José Gerardo Carrillo-González & Guillermo López-Maldonado & Juan Lopez-Sauceda & Francisco Perez-Martinez, 2023. "Method for Selecting the Vehicles That Can Enter a Street Network to Maintain the Speed on Links above a Speed Threshold," Sustainability, MDPI, vol. 15(13), pages 1-29, June.
    4. Daniel G. Costa & João Carlos N. Bittencourt & Franklin Oliveira & João Paulo Just Peixoto & Thiago C. Jesus, 2024. "Achieving Sustainable Smart Cities through Geospatial Data-Driven Approaches," Sustainability, MDPI, vol. 16(2), pages 1-30, January.
    5. Catalin Vrabie, 2023. "E-Government 3.0: An AI Model to Use for Enhanced Local Democracies," Sustainability, MDPI, vol. 15(12), pages 1-19, June.

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