Intelligent and automatic irrigation system based on internet of things using fuzzy control technology

Agriculture is a vital sector in the global economy but also a major contributor to water consumption and wastage due to inefficient irrigation techniques. To address this issue, smart irrigation systems using the Internet of Things (IoT) have emerged as a solution for optimizing water use. These systems utilize real-time sensor data to improve irrigation efficiency and agricultural productivity. This paper presents an automatic, low-cost intelligent irrigation system based on a fuzzy rule-based inference approach and an energy-aware routing algorithm. The proposed system determines the optimal irrigation method using sensor data and ensures efficient information transmission through a fast fuzzy-based routing mechanism. Additionally, it enables remote monitoring and control via mobile devices, enhancing user convenience. The system is designed to be intelligent, cost-effective, and portable, making it suitable for various agricultural applications such as greenhouses and farms. Simulation results demonstrate that the proposed method outperforms existing algorithms, including DLQR, SPIS, and FWIS, in terms of network lifetime and power consumption. By improving water efficiency and reducing resource wastage, this research contributes to sustainable agriculture. The proposed system provides a scalable and adaptable solution for modern farming, ensuring better irrigation management while conserving essential resources.

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Publication Details

Journal
Scientific Reports
Published
2025-04-25
DOI
https://doi.org/10.1038/s41598-025-98137-2
Citations
16
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
28.00
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article

Intelligent and automatic irrigation system based on internet of things using fuzzy control technology

Amin Rezaeipanah, Xinying Liu, Zhihuan Zhao
16 citations
Scientific Reports
Smart Agriculture and AI
28.00
article

Intelligent and automatic irrigation system based on internet of things using fuzzy control technology

Amin Rezaeipanah, Xinying Liu, Zhihuan Zhao
article en
16 citations

Abstract

Agriculture is a vital sector in the global economy but also a major contributor to water consumption and wastage due to inefficient irrigation techniques. To address this issue, smart irrigation systems using the Internet of Things (IoT) have emerged as a solution for optimizing water use. These systems utilize real-time sensor data to improve irrigation efficiency and agricultural productivity. This paper presents an automatic, low-cost intelligent irrigation system based on a fuzzy rule-based inference approach and an energy-aware routing algorithm. The proposed system determines the optimal irrigation method using sensor data and ensures efficient information transmission through a fast fuzzy-based routing mechanism. Additionally, it enables remote monitoring and control via mobile devices, enhancing user convenience. The system is designed to be intelligent, cost-effective, and portable, making it suitable for various agricultural applications such as greenhouses and farms. Simulation results demonstrate that the proposed method outperforms existing algorithms, including DLQR, SPIS, and FWIS, in terms of network lifetime and power consumption. By improving water efficiency and reducing resource wastage, this research contributes to sustainable agriculture. The proposed system provides a scalable and adaptable solution for modern farming, ensuring better irrigation management while conserving essential resources.

Scientific ReportsVol. 15(1)
Shandong University (CN)
Openalex Percentile: Top 0%
Smart Agriculture and AI
28.00
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