A Fuzzy Logic- and Internet of Things-Based Smart Irrigation System

Conventional irrigation methods frequently generate excessive or inadequate watering, resulting in the wastage of water and energy and diminished agricultural yields. This study presents a novel intelligent irrigation system that incorporates fuzzy logic and the Internet of Things (IoT) to automate...

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Published in:Engineering Proceedings
Main Authors: MD Jiabul Hoque, Md. Saiful Islam, Md. Khaliluzzaman
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Subjects:
Online Access:https://www.mdpi.com/2673-4591/58/1/93
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author MD Jiabul Hoque
Md. Saiful Islam
Md. Khaliluzzaman
author_facet MD Jiabul Hoque
Md. Saiful Islam
Md. Khaliluzzaman
author_sort MD Jiabul Hoque
collection DOAJ
container_title Engineering Proceedings
description Conventional irrigation methods frequently generate excessive or inadequate watering, resulting in the wastage of water and energy and diminished agricultural yields. This study presents a novel intelligent irrigation system that incorporates fuzzy logic and the Internet of Things (IoT) to automate the control of water pumps, thereby eliminating the requirement for human intervention. This novel method enables users to effectively preserve water and electricity by mitigating the issues of excessive and insufficient irrigation of crops. The system utilizes climate sensors that are combined with electrical circuits and connected to an Arduino and a fuzzy inference system (FIS) model to consider climate conditions and soil moisture levels. The sensors are responsible for collecting data that are utilized by the FIS model to control the speed of the water pump effectively. The FIS model integrates fuzzy logic to analyse the data obtained by the Arduino. This analysis enables the Arduino to adjust the pump speed by considering a wide range of sensor inputs. The implementation of this autonomous system eliminates the requirement for human intervention and enhances agricultural productivity by accurately dispensing the optimal quantity of water at the proper intervals. The cessation of water supply occurs when the soil moisture levels reach a sufficient state and resumes when the moisture levels fall below predetermined limits, regulated by various environmental circumstances. A comparative analysis examines the suggested technology, drip irrigation, and manual flooding. The comparison results demonstrate that the intelligent irrigation system accomplishes water and energy conservation.
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spelling doaj-art-ecdbd986a8ba4e598bc8a95f9a7ebabd2025-08-20T00:30:41ZengMDPI AGEngineering Proceedings2673-45912023-11-015819310.3390/ecsa-10-16243A Fuzzy Logic- and Internet of Things-Based Smart Irrigation SystemMD Jiabul Hoque0Md. Saiful Islam1Md. Khaliluzzaman2Department of Computer and Communication Engineering, International Islamic University Chittagong (IIUC), Chattogram 4318, BangladeshDepartment of Electronics and Telecommunication Engineering, Chittagong University of Engineering & Technology (CUET), Chattogram 4349, BangladeshDepartment of Computer Science and Engineering, International Islamic University Chittagong (IIUC), Chattogram 4318, BangladeshConventional irrigation methods frequently generate excessive or inadequate watering, resulting in the wastage of water and energy and diminished agricultural yields. This study presents a novel intelligent irrigation system that incorporates fuzzy logic and the Internet of Things (IoT) to automate the control of water pumps, thereby eliminating the requirement for human intervention. This novel method enables users to effectively preserve water and electricity by mitigating the issues of excessive and insufficient irrigation of crops. The system utilizes climate sensors that are combined with electrical circuits and connected to an Arduino and a fuzzy inference system (FIS) model to consider climate conditions and soil moisture levels. The sensors are responsible for collecting data that are utilized by the FIS model to control the speed of the water pump effectively. The FIS model integrates fuzzy logic to analyse the data obtained by the Arduino. This analysis enables the Arduino to adjust the pump speed by considering a wide range of sensor inputs. The implementation of this autonomous system eliminates the requirement for human intervention and enhances agricultural productivity by accurately dispensing the optimal quantity of water at the proper intervals. The cessation of water supply occurs when the soil moisture levels reach a sufficient state and resumes when the moisture levels fall below predetermined limits, regulated by various environmental circumstances. A comparative analysis examines the suggested technology, drip irrigation, and manual flooding. The comparison results demonstrate that the intelligent irrigation system accomplishes water and energy conservation.https://www.mdpi.com/2673-4591/58/1/93fuzzy inference systemfuzzy logicInternet of Thingssensorssmart irrigation
spellingShingle MD Jiabul Hoque
Md. Saiful Islam
Md. Khaliluzzaman
A Fuzzy Logic- and Internet of Things-Based Smart Irrigation System
fuzzy inference system
fuzzy logic
Internet of Things
sensors
smart irrigation
title A Fuzzy Logic- and Internet of Things-Based Smart Irrigation System
title_full A Fuzzy Logic- and Internet of Things-Based Smart Irrigation System
title_fullStr A Fuzzy Logic- and Internet of Things-Based Smart Irrigation System
title_full_unstemmed A Fuzzy Logic- and Internet of Things-Based Smart Irrigation System
title_short A Fuzzy Logic- and Internet of Things-Based Smart Irrigation System
title_sort fuzzy logic and internet of things based smart irrigation system
topic fuzzy inference system
fuzzy logic
Internet of Things
sensors
smart irrigation
url https://www.mdpi.com/2673-4591/58/1/93
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