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Intelligent Technologies for Internet of Vehicles pp 253–291Cite as

Deep Learning Approaches for IoV Applications and Services

Part of the Internet of Things book series (ITTCC)

Abstract

Internet of vehicles (IoV) has become an important revolution of intelligent transportation system (ITS). It became an emerging research area as the need for it has increased tremendously. With a great number of applications available, in addition to the intention to improve the quality of life and quality of services, the application of artificial intelligence (AI) techniques would dramatically enhance the performance of the IoV overall system. This chapter will discuss deep learning networks as a type of machine learning use in IoV with influence of Neural Networks (NN), where great amounts of unlabeled data are processed, classified and clustered. Deep learning network approaches i.e., Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Deep Reinforcement Learning (DRL), classification, clustering, and predictive analysis (regression) will briefly discussed in this chapter, in addition to review its ability to obtain better performing IoV applications.

Keywords

  • IoT
  • AI
  • IoV
  • Deep learning
  • Neural networks
  • CNN
  • RNN
  • Reinforcement learning
  • Classification
  • Clustering
  • Regression

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Author information

Authors and Affiliations

  1. Department of Electronics Engineering, Sudan University of Science and Technology, Khartoum, Sudan

    Lina Elmoiz Alatabani, Elmustafa Sayed Ali & Rashid A. Saeed

  2. Department of Electrical and Electronics Engineering, Red Sea University, Port Sudan, Sudan

    Elmustafa Sayed Ali

  3. Department of Computer Engineering, Taif University, Al-Taif, Saudi Arabia

    Rashid A. Saeed

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  1. Lina Elmoiz Alatabani
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  2. Elmustafa Sayed Ali
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  3. Rashid A. Saeed
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Editor information

Editors and Affiliations

  1. LASIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal

    Naercio Magaia

  2. Department of Management Science and Technology, Hellenic Mediterranean University, Agios Nikolaos, Lakonia, Greece

    Dr. George Mastorakis

  3. Department Computer Science, University of Nicosia, Nicosia, Cyprus

    Prof. Dr. Constandinos Mavromoustakis

  4. Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Heraklion, Greece

    Prof. Evangelos Pallis

  5. Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Heraklion, Greece

    Evangelos K. Markakis

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Alatabani, L.E., Ali, E.S., Saeed, R.A. (2021). Deep Learning Approaches for IoV Applications and Services. In: Magaia, N., Mastorakis, G., Mavromoustakis, C., Pallis, E., Markakis, E.K. (eds) Intelligent Technologies for Internet of Vehicles. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-030-76493-7_8

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  • DOI: https://doi.org/10.1007/978-3-030-76493-7_8

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