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State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability

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Engineering for Sustainable Future (INTER-ACADEMIA 2019)

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Abstract

Deep learning (DL) and machine learning (ML) methods have recently contributed to the advancement of models in the various aspects of prediction, planning, and uncertainty analysis of smart cities and urban development. This paper presents the state of the art of DL and ML methods used in this realm. Through a novel taxonomy, the advances in model development and new application domains in urban sustainability and smart cities are presented. Findings reveal that five DL and ML methods have been most applied to address the different aspects of smart cities. These are artificial neural networks; support vector machines; decision trees; ensembles, Bayesians, hybrids, and neuro-fuzzy; and deep learning. It is also disclosed that energy, health, and urban transport are the main domains of smart cities that DL and ML methods contributed in to address their problems.

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Author information

Authors and Affiliations

  1. Institute of Business Studies, Szent Istvan University, Godollo, 2100, Hungary

    Saeed Nosratabadi

  2. School of the Built Environment, Oxford Brookes University, Oxford, UK

    Amir Mosavi & Ramin Keivani

  3. Kalman Kando Faculty of Electrical Engineering, Obuda University, Budapest, Hungary

    Amir Mosavi

  4. Institute of Advanced Studies Koszeg, Koszeg, Hungary

    Sina Ardabili

  5. Escuela Técnica Superior de Arquitectura, Universidad Politécnica de Madrid-UPM, 28040, Madrid, Spain

    Farshid Aram

Authors
  1. Saeed Nosratabadi
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  2. Amir Mosavi
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  3. Ramin Keivani
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  4. Sina Ardabili
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  5. Farshid Aram
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Corresponding author

Correspondence to Amir Mosavi .

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Editors and Affiliations

  1. Obuda University, Budapest, Hungary

    Annamária R. Várkonyi-Kóczy

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Nosratabadi, S., Mosavi, A., Keivani, R., Ardabili, S., Aram, F. (2020). State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability. In: Várkonyi-Kóczy, A. (eds) Engineering for Sustainable Future. INTER-ACADEMIA 2019. Lecture Notes in Networks and Systems, vol 101. Springer, Cham. https://doi.org/10.1007/978-3-030-36841-8_22

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