Evidence map›Paper›PMID 40281085›Full record

ArticleScientific reports2025

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

Xinying Liu, Zhihuan Zhao, Amin Rezaeipanah

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xinying LiuSchool of Mechanical and Electronic Engineering, Shandong Agricultural and Engineering University, Jinan, 250100, Shandong, China.
Zhihuan ZhaoSchool of Mechanical and Electronic Engineering, Shandong Agricultural and Engineering University, Jinan, 250100, Shandong, China. sdaeu2024@126.com.
Amin RezaeipanahDepartment of Computer Engineering, Persian Gulf University, Bushehr, Iran. rezaeipanah@pgu.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Energy-aware routingFuzzy systemIntelligent agricultureIntelligent irrigationIoT

Identifiers

PMID40281085
PMCPMC12032210

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.