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...
| Published in: | Engineering Proceedings |
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| Main Authors: | , , |
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-11-01
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| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/58/1/93 |
| _version_ | 1850043275010899968 |
|---|---|
| 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. |
| format | Article |
| id | doaj-art-ecdbd986a8ba4e598bc8a95f9a7ebabd |
| institution | Directory of Open Access Journals |
| issn | 2673-4591 |
| language | English |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| 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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