Efficient and Intelligent Decision Support System for Smart Irrigation

Authors

  • Monika Saini
    Department of Mathematics & Statistics, Manipal University Jaipur, Jaipur-303007, India
  • Ashish Kumar
    Department of Mathematics & Statistics, Manipal University Jaipur, Jaipur-303007, India
  • Vijay Singh Maan
    Department of Mathematics & Statistics, Manipal University Jaipur, Jaipur-303007, India
  • Deepak Sinwar
    Department of computer and Communication, Manipal University Jaipur, Jaipur-303007, India

Keywords:

Markov model, Availability, Cold standby redundancy, Intelligent irrigation system

Abstract

The main aim of present analysis is to develop a novel efficient and intelligent irrigation system (EIIS). The proposed irrigation system configured using five components arranged in a series configuration along with the internal cold standby redundancy on sensor unit. The failure and repair rates are exponentially distributed. By using the Markovian birth-death process differential difference equations of the model are developed to derive the availability expressions and estimation of parameters. The availability of the system is optimized by employing Grey-Wolf optimization (GWO) and Dragon Fly algorithm (DA) for efficiency and performance evaluation. The derived results are helpful for the system designers.

Dimensions

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Published

2022-11-11

How to Cite

Efficient and Intelligent Decision Support System for Smart Irrigation. (2022). Journal of the Nigerian Society of Physical Sciences, 4(4), 945. https://doi.org/10.46481/jnsps.2022.945

Issue

Volume 4, Issue 4, November 2022

Section

Original Research
Copyright & Licensing

Copyright (c) 2022 Monika Saini, Ashish Kumar, Vijay Singh Maan, Deepak Sinwar

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Efficient and Intelligent Decision Support System for Smart Irrigation. (2022). Journal of the Nigerian Society of Physical Sciences, 4(4), 945. https://doi.org/10.46481/jnsps.2022.945

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