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Artificial Neural Networks Based Green Energy Harvesting for Smart World

  • Tigilu Mitiku
  • Mukhdeep Singh ManshahiaEmail author
Conference paper
  • 210 Downloads
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 141)

Abstract

Low-energy technologies in big data applications in remote areas are still unable to offer appropriate level of reliable environment. So it is of utmost importance to meet the energy consumption of Internet of Things (IoT) using renewable energy sources. Wind energy is a vital substitute of traditional fossil fuel due to better efficiency, cost and reliability, and better contribution for sustainable development in future energy generation all over the world. This study presents an artificial neural networks (ANN) based model of power output of wind energy harvesting system in relation with affecting factors such as wind velocity, air density, air pressure, temperature, and relative humidity to meet energy requirements of large scale big data applications in remote areas.

Keywords

Artificial neural networks Wind energy harvesting system Internet of things 

Notes

Acknowledgements

Authors would like to thank the researchers or academicians whose works have been cited in this review paper. Authors are also grateful to Punjabi University Patiala for offering sufficient library and internet facility and ministry of education of Ethiopia for financial support.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of MathematicsBule Hora UniversityBule HoraEthiopia
  2. 2.Department of MathematicsPunjabi UniversityPatialaIndia

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