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An Overview of the Machine Learning Applied in Smart Cities

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Smart Cities: A Data Analytics Perspective

Abstract

Smart cities are a rapidly evolving reality that is emerging as a path to be followed in the development of urban centers outline at the sustainability and quality of life of its inhabitants worldwide. They surprise us with the creativity of the solutions for more efficient use of available resources, reducing the impact of our lives on the environment through digital transformation. Machine Learning is a technology that allows models to be trained on data sets before they are implemented, it is a type of algorithm that improves automatically and gradually with the number of experiments in which it is placed to train. Where computers can learn according to the expected responses through associations of different data, which can be images, numbers, and everything that this technology can identify. This artificial intelligence can also stimulate changes in utility business models, which means that users can benefit from better services resulting in greater mobility and comfort. Solving connected problems related to the optimization of urban planning and integrating city services for personalized results, concerning the use of specific services by the inhabitants. In this context, this chapter is motivated to provide a scientific contribution related to the discussion and overview of Smart Cities and Machine Learning, addressing their key points and their importance, their interconnection, and use, with a precise bibliographic background, singularizing and stereotyping the competence of technologies.

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Authors and Affiliations

  1. School of Electrical and Computer Engineering (FEEC), University of Campinas, UNICAMP, Av. Albert Einstein – 400, Barão Geraldo, Campinas – SP, Brazil

    Reinaldo Padilha França, Ana Carolina Borges Monteiro, Rangel Arthur & Yuzo Iano

Authors
  1. Reinaldo Padilha França
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  2. Ana Carolina Borges Monteiro
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  3. Rangel Arthur
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  4. Yuzo Iano
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Correspondence to Reinaldo Padilha França .

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Editors and Affiliations

  1. College of Computing and Information Technology, University of Bisha, Bisha, Saudi Arabia

    Mohammad Ayoub Khan

  2. College of Computing and Information Technology, University of Bisha, Bisha, Saudi Arabia

    Fahad Algarni

  3. College of Computing and Information Technology, University of Bisha, Bisha, Saudi Arabia

    Mohammad Tabrez Quasim

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França, R.P., Monteiro, A.C.B., Arthur, R., Iano, Y. (2021). An Overview of the Machine Learning Applied in Smart Cities. In: Khan, M.A., Algarni, F., Quasim, M.T. (eds) Smart Cities: A Data Analytics Perspective. Lecture Notes in Intelligent Transportation and Infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-030-60922-1_5

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  • DOI: https://doi.org/10.1007/978-3-030-60922-1_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60921-4

  • Online ISBN: 978-3-030-60922-1

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