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An Optimization Scheme Based on Fuzzy Logic Control for Efficient Energy Consumption in Hydroponics Environment

Author

Listed:
  • Azimbek Khudoyberdiev

    (Department of Computer Engineering, Jeju National University, Jeju 63243, Korea)

  • Shabir Ahmad

    (Department of Computer Engineering, Jeju National University, Jeju 63243, Korea)

  • Israr Ullah

    (Department of Computer Science, Virtual University of Pakistan, Lahore 54000, Pakistan)

  • DoHyeun Kim

    (Department of Computer Engineering, Jeju National University, Jeju 63243, Korea)

Abstract

As the world population is increasing rapidly, food and water demands are the most crucial problem for humanity. In some areas of the world, water or environment is unsuitable for plant growth; hydroponic systems can provide a suitable environment for crop production with effective management of natural resources. Internet of Things paradigm based automated systems has been creating an excellent opportunity for monitoring and controlling agriculture by minimizing the cost and maximizing the profit significantly over the past decade. The reduction of the cost can be achieved by sufficient usage of resources and setting up optimum operational parameters for agricultural devices. This paper presents an optimization scheme with novel objective function for hydroponics environment parameters management with efficient energy consumption. The proposed approach provides optimal energy and resource utilization in the hydroponics system with setting up a working level and operational duration to the actuators. We have developed an optimization scheme with objective function for optimal humidity and water level control based on fuzzy logic, which can support the optimal measurement for crop growth with energy efficiency. Fuzzy logic control is applied for the compromise between actuators working level and operational duration. A real hydroponics environment has been implemented and presented to evaluate the effectiveness of the proposed approach. It can be assessed through the simulation results that the optimization module achieves a signification reduction (18%) in energy consumption as compared to the other scheme.

Suggested Citation

  • Azimbek Khudoyberdiev & Shabir Ahmad & Israr Ullah & DoHyeun Kim, 2020. "An Optimization Scheme Based on Fuzzy Logic Control for Efficient Energy Consumption in Hydroponics Environment," Energies, MDPI, vol. 13(2), pages 1-27, January.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:2:p:289-:d:305914
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    References listed on IDEAS

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    1. Wenquan Jin & Dohyeun Kim, 2018. "Consistent Registration and Discovery Scheme for Devices and Web Service Providers Based on RAML Using Embedded RD in OCF IoT Network," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    2. Yurii Nesterov, 2018. "Lectures on Convex Optimization," Springer Optimization and Its Applications, Springer, edition 2, number 978-3-319-91578-4, September.
    3. Gilmour, Daniel N. & Nayga, Rodolfo M. & Bazzani, Claudia & Price, Heather, 2018. "Consumers' Willingness to Pay for Hydroponic Lettuce: A Non-hypothetical Choice Experiment," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266668, Southern Agricultural Economics Association.
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    Cited by:

    1. Mahrokh Farvardin & Morteza Taki & Shiva Gorjian & Edris Shabani & Julio C. Sosa-Savedra, 2024. "Assessing the Physical and Environmental Aspects of Greenhouse Cultivation: A Comprehensive Review of Conventional and Hydroponic Methods," Sustainability, MDPI, vol. 16(3), pages 1-34, February.
    2. Cristian Napole & Oscar Barambones & Mohamed Derbeli & José Antonio Cortajarena & Isidro Calvo & Patxi Alkorta & Pablo Fernandez Bustamante, 2021. "Double Fed Induction Generator Control Design Based on a Fuzzy Logic Controller for an Oscillating Water Column System," Energies, MDPI, vol. 14(12), pages 1-19, June.

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