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An Investigation on the Impact of Machine Learning in Wireless Sensor Networks and Its Application Specific Challenges

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ICCCE 2020

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 698))

Abstract

The importance of Machine Learning (ML) in advanced system technologies are proven in literature. This chapter investigates the role of ML in Wireless Sensor Networks and the challenges specific to its applications. We discuss the background literature of the renowned ML concepts and ML techniques. Further we distinguish the role of ML in WSN with detailed literature review. Subsequently, ML techniques for WSN are discussed from the literature. This chapter ends with the description of Functional and application specific challenges.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India

    K. Praghash, K. Suresh Kumar, R. Sekar, R. Ramesh Kumar & S. Arun Metha

  2. Department of Electronics and Communication Engineering, Annamacharya Institute of Technology and Sciences, Rajampet, AP, India

    T. Karthikeyan

Authors
  1. K. Praghash
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  2. T. Karthikeyan
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  3. K. Suresh Kumar
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  4. R. Sekar
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  5. R. Ramesh Kumar
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  6. S. Arun Metha
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Corresponding author

Correspondence to K. Praghash .

Editor information

Editors and Affiliations

  1. BioAxis DNA Research Centre (P) Ltd., Hyderabad, India

    Amit Kumar

  2. Dynexsys, Sydney, NSW, Australia

    Stefan Mozar

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Praghash, K., Karthikeyan, T., Kumar, K.S., Sekar, R., Kumar, R.R., Metha, S.A. (2021). An Investigation on the Impact of Machine Learning in Wireless Sensor Networks and Its Application Specific Challenges. In: Kumar, A., Mozar, S. (eds) ICCCE 2020. Lecture Notes in Electrical Engineering, vol 698. Springer, Singapore. https://doi.org/10.1007/978-981-15-7961-5_39

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  • DOI: https://doi.org/10.1007/978-981-15-7961-5_39

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-7960-8

  • Online ISBN: 978-981-15-7961-5

  • eBook Packages: EngineeringEngineering (R0)

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