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Intelligent Technologies for Internet of Vehicles pp 225–252Cite as

Machine Learning Technologies in Internet of Vehicles

Part of the Internet of Things book series (ITTCC)

Abstract

Recently, there was much interest in Technology which has emerged greatly to the development of smart cars. Internet of Vehicle (IoV) enables vehicles to communicate with public networks and interact with surrounding environment. It also enables vehicles to exchange information in addition to collect information about other vehicles and roads. However, actual applications of smart IoV systems face many challenges. These challenges are related to different problematic issues like big data connection with IoV, cloud network, data processing, and efficient communication between a large amount of different vehicles types, in addition to optimum decision data processing on or off board. Intelligence of the huge amount of data that can be processed to reduce road congestion and improve traffic management, as well as ensuring road safety is an important issue in future IoV trends.

Artificial Intelligence (AI) technology with Machine Learning (ML) mechanisms offers smart solutions that can improve IoV network efficiency. For example, decision for data processing at various layers i.e. on-board units (OBUs), Fog level or cloud level are one of the problems which need ML algorithms. Other critical issues that can be resolved by ML mechanisms are time, energy, rapid topology of IoV, optimization quality of experience (QoE) and channel modeling. These issues need to be optimized. This chapter provides theoretical fundamentals for ML models, algorithms in IoV applications and future directions.

Keywords

  • IoV
  • Machine learning
  • V2E
  • Deep learning
  • Optimization QoE
  • Autonomous driving
  • Smart transportation

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Author information

Authors and Affiliations

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

    Elmustafa Sayed Ali, Mona Bakri Hassan & Rashid A. Saeed

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

    Elmustafa Sayed Ali

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

    Rashid A. Saeed

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  1. Elmustafa Sayed Ali
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  2. Mona Bakri Hassan
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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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Ali, E.S., Hassan, M.B., Saeed, R.A. (2021). Machine Learning Technologies in Internet of Vehicles. 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_7

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  • DOI: https://doi.org/10.1007/978-3-030-76493-7_7

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