LAPSE:2023.9296v1
Published Article

LAPSE:2023.9296v1
Intelligent Control of Irrigation Systems Using Fuzzy Logic Controller
February 27, 2023
Abstract
In this paper, we explain the design and implementation of an intelligent irrigation control system based on fuzzy logic for the automatic control of water pumps used in farms and greenhouses. This system enables its user to save water and electricity and prevent over-watering and under-watering of the crop by taking into account the climatic parameters and soil moisture. The irrigation system works without human intervention. The climate sensors are packaged using electronic circuits, and the whole is interfaced with an Arduino and a Simulink model. These sensors provide information that is used by the Simulink model to control the water pump speed; the speed of the water pump is controlled to increase or decrease the amount of water that needs to be pushed by the pump. The Simulink model contains the fuzzy control logic that manages the data read by the Arduino through sensors and sends the command to change the pump speed to the Arduino by considering all the sensor data. The need for human intervention is eliminated by using this system and a more successful crop is produced by supplying the right amount of water to the crop when it is needed. The water supply is stopped when a sufficient amount of moisture is present in the soil and it is started as soon as the soil moisture levels drops below certain levels, depending upon the environmental factors.
In this paper, we explain the design and implementation of an intelligent irrigation control system based on fuzzy logic for the automatic control of water pumps used in farms and greenhouses. This system enables its user to save water and electricity and prevent over-watering and under-watering of the crop by taking into account the climatic parameters and soil moisture. The irrigation system works without human intervention. The climate sensors are packaged using electronic circuits, and the whole is interfaced with an Arduino and a Simulink model. These sensors provide information that is used by the Simulink model to control the water pump speed; the speed of the water pump is controlled to increase or decrease the amount of water that needs to be pushed by the pump. The Simulink model contains the fuzzy control logic that manages the data read by the Arduino through sensors and sends the command to change the pump speed to the Arduino by considering all the sensor data. The need for human intervention is eliminated by using this system and a more successful crop is produced by supplying the right amount of water to the crop when it is needed. The water supply is stopped when a sufficient amount of moisture is present in the soil and it is started as soon as the soil moisture levels drops below certain levels, depending upon the environmental factors.
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Keywords
automatic irrigation control system, fuzzy logic, intelligent control, irrigation system
Subject
Suggested Citation
Singh AK, Tariq T, Ahmer MF, Sharma G, Bokoro PN, Shongwe T. Intelligent Control of Irrigation Systems Using Fuzzy Logic Controller. (2023). LAPSE:2023.9296v1
Author Affiliations
Singh AK: Department of Electrical Engineering, Faculty of Engineering & Technology, Jamia Millia Islamia (A Central University), New Delhi 110025, India
Tariq T: Department of Electrical Engineering, Faculty of Engineering & Technology, Jamia Millia Islamia (A Central University), New Delhi 110025, India [ORCID]
Ahmer MF: Department of Electrical and Electronics Engineering, Mewat Engineering College, Nuh 122107, India
Sharma G: Department of Electrical Engineering Technology, University of Johannesburg, Johannesburg 2006, South Africa [ORCID]
Bokoro PN: Department of Electrical Engineering Technology, University of Johannesburg, Johannesburg 2006, South Africa [ORCID]
Shongwe T: Department of Electrical Engineering Technology, University of Johannesburg, Johannesburg 2006, South Africa
Tariq T: Department of Electrical Engineering, Faculty of Engineering & Technology, Jamia Millia Islamia (A Central University), New Delhi 110025, India [ORCID]
Ahmer MF: Department of Electrical and Electronics Engineering, Mewat Engineering College, Nuh 122107, India
Sharma G: Department of Electrical Engineering Technology, University of Johannesburg, Johannesburg 2006, South Africa [ORCID]
Bokoro PN: Department of Electrical Engineering Technology, University of Johannesburg, Johannesburg 2006, South Africa [ORCID]
Shongwe T: Department of Electrical Engineering Technology, University of Johannesburg, Johannesburg 2006, South Africa
Journal Name
Energies
Volume
15
Issue
19
First Page
7199
Year
2022
Publication Date
2022-09-30
ISSN
1996-1073
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PII: en15197199, Publication Type: Journal Article
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LAPSE:2023.9296v1
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https://doi.org/10.3390/en15197199
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Feb 27, 2023
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