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

R. Morais, A. Valente & C. Serˆodio, A wireless sensor network for smart irrigation and environmental monitoring: A position article. In 5th European federation for information technology in agriculture, food and environment

and 3rd world congress on computers in agriculture and natural resources (EFITA/WCCA) (July, 2005) 845.

G. Vellidis, M. Tucker, C. Perry, C. Kvien & C. Bednarz, “A real-time wireless smart sensor array for scheduling irrigation”, Computers and electronics in agriculture 61 (2008) 44.

X. Kehui, X. Deqin & L. Xiwen, “Smart water-saving irrigation system in precision agriculture based on wireless sensor network”, Transactions of the Chinese society of Agricultural Engineering 26 (2010) 170.

E. Giusti & S. Marsili-Libelli, “A Fuzzy Decision Support System for irrigation and water conservation in agriculture”, Environmental Modelling & Software 63 (2015) 73.

H. Navarro-hell´?n, J. Mart´?nez-del-rincon, R. Domingo-miguel, F. Sotovalles & R. Torres-s´anchez, “A decision support system for managing irrigation in agriculture”, Computers and Electronics in Agriculture 124 (2016) 121.

D. Sinwar, V. S. Dhaka, M. K. Sharma & G. Rani, “AI-based yield prediction and smart irrigation”, Internet of Things and Analytics for Agriculture 2 (2020) 155.

A. Nasiakou, M. Vavalis & D. Zimeris, “Smart energy for smart irrigation”, Computers and Electronics in Agriculture 129 (2016) 74.

Z. Gu, Q. Zhiming, M. Liwang, G. Dongwei, X. Junzeng, F. Quanxiao, Y. Shouqi & F. Gary, “Development of an irrigation scheduling software based on model predicted crop water stress”, Computers and Electronics in Agriculture 143 (2017) 208.

Y. Shekhar, E. Dagur, S. Mishra, R. J. Tom, M. Veeramanikandan & S. Sankaranarayanan, “Intelligent IoT based automated irrigation system,” International Journal of Applied Engineering Research 12 (2017) 7306.

A. Goap, D. Sharma, A. K. Shukla & C. Rama Krishna, “An IoT based smart irrigation management system using Machine learning and open source technologies”, Computers and electronics in agriculture 155 (2018) 41, https://doi.org/10.1016/j.compag.2018.09.040

N. K. Nawandar & V. R. Satpute, “IoT based low cost and intelligent module for smart irrigation system”, Computers and electronics in agriculture 162 (2019) 979, https://doi.org/10.1016/j.compag.2019.05.027

W. Wang, Y. Cui, Y. Luo, Z. Li & J. Tan, “Web-based decision support system for canal irrigation management”, Computers and Electronics in Agriculture 161 (2019) 312.

A. S. Maihulla, & I. Yusuf, “Performance analysis of photovoltaic systems using (RAMD) analysis”, Journal of the Nigerian Society of Physical Sciences 3 (2021) 172.

G. R. Venkatakrishnan, R. Rengaraj, K. K. Sathish, R. K. Dinesh & T. Nishanth, “Implementation of modified differential evolution algorithm for hybrid renewable energy system”, Journal of the Nigerian Society of Physical Sciences 3 (2021) 209.

A. Kumar, M. Saini, N. Gupta, D. Sinwar, D. Singh, M. Kaur, & H. N. Lee, “Efficient stochastic model for operational availability optimization of cooling tower using metaheuristic algorithms”, IEEE Access 10 (2022) 24659.

M. Saini, D. Goyal, A. Kumar, & R. B. Patil, “Availability optimization of biological and chemical processing unit using genetic algorithm and particle swarm optimization”, International Journal of Quality & Reliability Management 39 (2022) 1704.

M. Saini, N. Gupta, V. G. Shankar & A. Kumar, “Stochastic modeling and availability optimization of condenser used in steam turbine power plants using GA and PSO”, Quality and Reliability Engineering International 38 (2022) 2670.

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

Similar Articles

81-90 of 242

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)