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Machine Learning for IoT Systems

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Internet of Things (IoT)

Abstract

The rapid increase in the number of smart devices hosting sophisticated applications is significantly affecting the landscape of the information com-munication technology industry. The Internet of Things (IoT) is gaining popularity and importance in man’s everyday life. However, the IoT challenges also increase with its evolution. The urge for IoT improvement and continuous enhancement becomes more important. Machine learning techniques are recently being exploit-ed within IoT systems to leverage their potential. This chapter comprehensively surveys of the use of algorithms that exploit machine learning in IoT systems. We classify such machine learning-based IoT algorithms into those which provide ef-ficient solutions to the IoT basic operation challenges, such as localization, clus-tering, routing and data aggregation, and those which target performance-related challenges, such as congestion control, fault detection, resource management and security.

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Authors and Affiliations

  1. Electronics and Electrical Communications Engineering Department, Cairo University, Giza, Egypt

    Ahmed Khattab & Nouran Youssry

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  1. Ahmed Khattab
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  2. Nouran Youssry
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Correspondence to Ahmed Khattab .

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Editors and Affiliations

  1. Department of Computer Science, Jamia Millia Islamia, New Delhi, India

    Mansaf Alam

  2. College of Computer & Information Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

    Kashish Ara Shakil

  3. Department of Computer Science, Jamia Millia Islamia, New Delhi, India

    Samiya Khan

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Khattab, A., Youssry, N. (2020). Machine Learning for IoT Systems. In: Alam, M., Shakil, K., Khan, S. (eds) Internet of Things (IoT). Springer, Cham. https://doi.org/10.1007/978-3-030-37468-6_6

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  • DOI: https://doi.org/10.1007/978-3-030-37468-6_6

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