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Energy Harvesting in Wireless Sensor Networks

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Artificial Intelligence and Evolutionary Computations in Engineering Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 394))

Abstract

In recent years, wireless sensor networks (WSNs) have grown dramatically and made a great progress in many applications. But having limited life, batteries, as the power sources of wireless sensor nodes, have restricted the development and application of WSNs which often requires a very long lifespan for better performance. In order to make the WSNs prevalent in our lives, an alternative energy source is required. Environmental energy is an attractive power source, and it provides an approach to make the sensor nodes self-powered with the possibility of an almost infinite lifetime. The goal of this survey is to present a comprehensive review of the recent literature on the various possible energy harvesting technologies from ambient environment for WSNs.

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Author information

Authors and Affiliations

  1. Dr. M.G.R. Educational and Research Institute University, Chennai, India

    R. Ramya

  2. Department of ECE, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai, India

    G. Saravanakumar

  3. Department of ECE, Dr MGR Educational and Research Institute University, Chennai, India

    S. Ravi

Authors
  1. R. Ramya
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  2. G. Saravanakumar
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  3. S. Ravi
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Corresponding author

Correspondence to R. Ramya .

Editor information

Editors and Affiliations

  1. Electrical and Electronics Engineer, SRM Engineering College, Kattankulathur, Tamil Nadu, India

    Subhransu Sekhar Dash

  2. Electrical & Electronics Engineering, Velammal Engineering College, Chennai, Tamil Nadu, India

    M. Arun Bhaskar

  3. Dept Electrical & Electronics Engg, IIT Delhi, New Delhi, India

    Bijaya Ketan Panigrahi

  4. Indian Statistical Institute, Kolkata, India

    Swagatam Das

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© 2016 Springer India

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Ramya, R., Saravanakumar, G., Ravi, S. (2016). Energy Harvesting in Wireless Sensor Networks. In: Dash, S., Bhaskar, M., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 394. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2656-7_76

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  • DOI: https://doi.org/10.1007/978-81-322-2656-7_76

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2654-3

  • Online ISBN: 978-81-322-2656-7

  • eBook Packages: EngineeringEngineering (R0)

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