IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i4p1077-d207097.html
   My bibliography  Save this article

Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018

Author

Listed:
  • Jovani Taveira de Souza

    (Department of Production Engineering, Federal University Technology, Av. Monteiro Lobato, 84016-210, Ponta Grossa, Paraná, Brazil)

  • Antonio Carlos de Francisco

    (Department of Production Engineering, Federal University Technology, Av. Monteiro Lobato, 84016-210, Ponta Grossa, Paraná, Brazil)

  • Cassiano Moro Piekarski

    (Department of Production Engineering, Federal University Technology, Av. Monteiro Lobato, 84016-210, Ponta Grossa, Paraná, Brazil)

  • Guilherme Francisco do Prado

    (Department of Production Engineering, Federal University Technology, Av. Monteiro Lobato, 84016-210, Ponta Grossa, Paraná, Brazil)

Abstract

Smart cities (SC) promote economic development, improve the welfare of their citizens, and help in the ability of people to use technologies to build sustainable services. However, computational methods are necessary to assist in the process of creating smart cities because they are fundamental to the decision-making process, assist in policy making, and offer improved services to citizens. As such, the aim of this research is to present a systematic review regarding data mining (DM) and machine learning (ML) approaches adopted in the promotion of smart cities. The Methodi Ordinatio was used to find relevant articles and the VOSviewer software was performed for a network analysis. Thirty-nine significant articles were identified for analysis from the Web of Science and Scopus databases, in which we analyzed the DM and ML techniques used, as well as the areas that are most engaged in promoting smart cities. Predictive analytics was the most common technique and the studies focused primarily on the areas of smart mobility and smart environment. This study seeks to encourage approaches that can be used by governmental agencies and companies to develop smart cities, being essential to assist in the Sustainable Development Goals.

Suggested Citation

  • Jovani Taveira de Souza & Antonio Carlos de Francisco & Cassiano Moro Piekarski & Guilherme Francisco do Prado, 2019. "Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018," Sustainability, MDPI, vol. 11(4), pages 1-14, February.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:4:p:1077-:d:207097
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/4/1077/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/4/1077/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marsal-Llacuna, Maria-Lluïsa & Colomer-Llinàs, Joan & Meléndez-Frigola, Joaquim, 2015. "Lessons in urban monitoring taken from sustainable and livable cities to better address the Smart Cities initiative," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 611-622.
    2. Wang, Xin & Li, Zhengwei & Meng, Haixing & Wu, Jiang, 2017. "Identification of key energy efficiency drivers through global city benchmarking: A data driven approach," Applied Energy, Elsevier, vol. 190(C), pages 18-28.
    3. Regina Negri Pagani & João Luiz Kovaleski & Luis Mauricio Resende, 2015. "Methodi Ordinatio: a proposed methodology to select and rank relevant scientific papers encompassing the impact factor, number of citation, and year of publication," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2109-2135, December.
    4. Murillo Vetroni Barros & Cassiano Moro Piekarski & Antonio Carlos De Francisco, 2018. "Carbon Footprint of Electricity Generation in Brazil: An Analysis of the 2016–2026 Period," Energies, MDPI, vol. 11(6), pages 1-14, June.
    5. Li, Huajiao & An, Haizhong & Wang, Yue & Huang, Jiachen & Gao, Xiangyun, 2016. "Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 657-669.
    6. Huchang Liao & Ming Tang & Li Luo & Chunyang Li & Francisco Chiclana & Xiao-Jun Zeng, 2018. "A Bibliometric Analysis and Visualization of Medical Big Data Research," Sustainability, MDPI, vol. 10(1), pages 1-18, January.
    7. Miltiadis D. Lytras & Vijay Raghavan & Ernesto Damiani, 2017. "Big Data and Data Analytics Research: From Metaphors to Value Space for Collective Wisdom in Human Decision Making and Smart Machines," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 13(1), pages 1-10, January.
    8. Vito Albino & Umberto Berardi & Rosa Maria Dangelico, 2015. "Smart Cities: Definitions, Dimensions, Performance, and Initiatives," Journal of Urban Technology, Taylor & Francis Journals, vol. 22(1), pages 3-21, January.
    9. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    10. M. Sajid Khan & Mina Woo & Kichan Nam & Prakash K. Chathoth, 2017. "Smart City and Smart Tourism: A Case of Dubai," Sustainability, MDPI, vol. 9(12), pages 1-24, December.
    11. Rubén Pérez-Chacón & José M. Luna-Romera & Alicia Troncoso & Francisco Martínez-Álvarez & José C. Riquelme, 2018. "Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities," Energies, MDPI, vol. 11(3), pages 1-19, March.
    12. Seunghwan Myeong & Yuseok Jung & Eunuk Lee, 2018. "A Study on Determinant Factors in Smart City Development: An Analytic Hierarchy Process Analysis," Sustainability, MDPI, vol. 10(8), pages 1-17, July.
    13. Ming Tang & Huchang Liao & Zhengjun Wan & Enrique Herrera-Viedma & Marc A. Rosen, 2018. "Ten Years of Sustainability (2009 to 2018): A Bibliometric Overview," Sustainability, MDPI, vol. 10(5), pages 1-21, May.
    14. Yinger Zheng & Haixia Zheng & Xinyue Ye, 2016. "Using Machine Learning in Environmental Tax Reform Assessment for Sustainable Development: A Case Study of Hubei Province, China," Sustainability, MDPI, vol. 8(11), pages 1-20, November.
    15. Jurado, Sergio & Nebot, Àngela & Mugica, Fransisco & Avellana, Narcís, 2015. "Hybrid methodologies for electricity load forecasting: Entropy-based feature selection with machine learning and soft computing techniques," Energy, Elsevier, vol. 86(C), pages 276-291.
    16. Rolando Armas & Hernán Aguirre & Fabio Daolio & Kiyoshi Tanaka, 2017. "Evolutionary design optimization of traffic signals applied to Quito city," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-37, December.
    17. Fateh Nassim Melzi & Allou Same & Mohamed Haykel Zayani & Latifa Oukhellou, 2017. "A Dedicated Mixture Model for Clustering Smart Meter Data: Identification and Analysis of Electricity Consumption Behaviors," Energies, MDPI, vol. 10(10), pages 1-21, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jun Houng Kim & Seok-Jin Eom, 2019. "The Managerial Dimension of Open Data Success: Focusing on the Open Data Initiatives in Korean Local Governments," Sustainability, MDPI, vol. 11(23), pages 1-15, November.
    2. Francis Rathinam & Sayak Khatua & Zeba Siddiqui & Manya Malik & Pallavi Duggal & Samantha Watson & Xavier Vollenweider, 2021. "Using big data for evaluating development outcomes: A systematic map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
    3. Nammi Kim & Seungwoo Yang, 2021. "Characteristics of Conceptually Related Smart Cities (CRSCs) Services from the Perspective of Sustainability," Sustainability, MDPI, vol. 13(6), pages 1-48, March.
    4. Marcela Marçal Alves Pinto & João Luiz Kovaleski & Rui Tadashi Yoshino & Regina Negri Pagani, 2019. "Knowledge and Technology Transfer Influencing the Process of Innovation in Green Supply Chain Management: A Multicriteria Model Based on the DEMATEL Method," Sustainability, MDPI, vol. 11(12), pages 1-33, June.
    5. Ana De Las Heras & Amalia Luque-Sendra & Francisco Zamora-Polo, 2020. "Machine Learning Technologies for Sustainability in Smart Cities in the Post-COVID Era," Sustainability, MDPI, vol. 12(22), pages 1-25, November.
    6. Murillo Vetroni Barros & Rômulo Henrique Gomes Jesus & Bruno Silva Ribeiro & Cassiano Moro Piekarski, 2023. "Going in Circles: Key Aspects for Circular Economy Contributions to Agro-industrial Cooperatives," Circular Economy and Sustainability, Springer, vol. 3(2), pages 861-880, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gallego-Losada, María-Jesús & Montero-Navarro, Antonio & García-Abajo, Elisa & Gallego-Losada, Rocío, 2023. "Digital financial inclusion. Visualizing the academic literature," Research in International Business and Finance, Elsevier, vol. 64(C).
    2. Cezary Stępniak & Dorota Jelonek & Magdalena Wyrwicka & Iwona Chomiak-Orsa, 2021. "Integration of the Infrastructure of Systems Used in Smart Cities for the Planning of Transport and Communication Systems in Cities," Energies, MDPI, vol. 14(11), pages 1-19, May.
    3. Appio, Francesco Paolo & Lima, Marcos & Paroutis, Sotirios, 2019. "Understanding Smart Cities: Innovation ecosystems, technological advancements, and societal challenges," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 1-14.
    4. Wang, Mengmeng & Zhou, Tao & Wang, Di, 2020. "Tracking the evolution processes of smart cities in China by assessing performance and efficiency," Technology in Society, Elsevier, vol. 63(C).
    5. Yi Feng & Shaoze Cui, 2021. "A review of emergency response in disasters: present and future perspectives," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(1), pages 1109-1138, January.
    6. Tuba Bircan & Almila Alkim Akdag Salah, 2022. "A Bibliometric Analysis of the Use of Artificial Intelligence Technologies for Social Sciences," Mathematics, MDPI, vol. 10(23), pages 1-17, November.
    7. Maria Vincenza Ciasullo & Orlando Troisi & Mara Grimaldi & Daniele Leone, 2020. "Multi-level governance for sustainable innovation in smart communities: an ecosystems approach," International Entrepreneurship and Management Journal, Springer, vol. 16(4), pages 1167-1195, December.
    8. María Pinto & Rosaura Fernández-Pascual & David Caballero-Mariscal & Dora Sales, 2020. "Information literacy trends in higher education (2006–2019): visualizing the emerging field of mobile information literacy," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1479-1510, August.
    9. Yi-Ming Guo & Zhen-Ling Huang & Ji Guo & Hua Li & Xing-Rong Guo & Mpeoane Judith Nkeli, 2019. "Bibliometric Analysis on Smart Cities Research," Sustainability, MDPI, vol. 11(13), pages 1-18, June.
    10. Johannes Stübinger & Lucas Schneider, 2020. "Understanding Smart City—A Data-Driven Literature Review," Sustainability, MDPI, vol. 12(20), pages 1-23, October.
    11. Ming Tang & Huchang Liao & Zhengjun Wan & Enrique Herrera-Viedma & Marc A. Rosen, 2018. "Ten Years of Sustainability (2009 to 2018): A Bibliometric Overview," Sustainability, MDPI, vol. 10(5), pages 1-21, May.
    12. Assumpció Huertas & Antonio Moreno & Jordi Pascual, 2021. "Place Branding for Smart Cities and Smart Tourism Destinations: Do They Communicate Their Smartness?," Sustainability, MDPI, vol. 13(19), pages 1-18, October.
    13. Weisheng Chiu & Thomas Chun Man Fan & Sang-Back Nam & Ping-Hung Sun, 2021. "Knowledge Mapping and Sustainable Development of eSports Research: A Bibliometric and Visualized Analysis," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    14. Kai Chen & Xiaoping Lin & Han Wang & Yujie Qiang & Jie Kong & Rui Huang & Haining Wang & Hui Liu, 2022. "Visualizing the Knowledge Base and Research Hotspot of Public Health Emergency Management: A Science Mapping Analysis-Based Study," Sustainability, MDPI, vol. 14(12), pages 1-23, June.
    15. Gallego-Losada, Rocío & Montero-Navarro, Antonio & Rodríguez-Sánchez, José-Luis & González-Torres, Thais, 2022. "Retirement planning and financial literacy, at the crossroads. A bibliometric analysis," Finance Research Letters, Elsevier, vol. 44(C).
    16. Magdalena Mucowska, 2021. "Trends of Environmentally Sustainable Solutions of Urban Last-Mile Deliveries on the E-Commerce Market—A Literature Review," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
    17. Anita Mendiratta & Shveta Singh & Surendra Singh Yadav & Arvind Mahajan, 2023. "Bibliometric and Topic Modeling Analysis of Corporate Social Irresponsibility," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(3), pages 319-339, September.
    18. Wu, Hanjun & Hong Tsui, Kan Wai & Ngo, Thanh & Lin, Yi-Hsin, 2020. "Impacts of aviation subsidies on regional wellbeing: Systematic review, meta-analysis and future research directions," Transport Policy, Elsevier, vol. 99(C), pages 215-239.
    19. Haitham Nobanee & Fatima Youssef Al Hamadi & Fatma Ali Abdulaziz & Lina Subhi Abukarsh & Aysha Falah Alqahtani & Shayma Khalifa AlSubaey & Sara Mohamed Alqahtani & Hamama Abdulla Almansoori, 2021. "A Bibliometric Analysis of Sustainability and Risk Management," Sustainability, MDPI, vol. 13(6), pages 1-16, March.
    20. Marcos Nahuel Martínez Stanziani, 2020. "Índices de Ciudades Inteligentes: construcción y análisis de un indicador para la ciudad de Bahía Blanca," Asociación Argentina de Economía Política: Working Papers 4374, Asociación Argentina de Economía Política.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:4:p:1077-:d:207097. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.