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Sensors in Smart Irrigation Systems
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Sensors in Smart Irrigation Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Smart Agriculture".

Deadline for manuscript submissions: 15 July 2025 | Viewed by 3131

Special Issue Editors

Dr. Mohamed Riduan Abid

E-Mail Website
Guest Editor
TSYS School of Computer Science, Columbus State University, Columbus, GA 31907, USA
Interests: cloud & edge computing; big data processing; smart grids; distributed systems; wireless mesh networks
Special Issues, Collections and Topics in MDPI journals
Dr. Tareq Abu Hamed

E-Mail Website
Co-Guest Editor
The Arava Institute for Environmental Studies, Kibbutz Ketura, D.N. Hevel Eilot 8884000, Israel
Interests: IoT; solar energy; hydrogen; AgriPV

Special Issue Information

Dear Colleagues,

The Special Issue explores the pivotal role of Information and Communication Technologies (ICT) in advancing sustainable agricultural practices. With the global population steadily increasing, the demand for food is rising, making sustainable agriculture crucial for human survival. Sensors, a key element of ICT, offer innovative solutions by enabling precise monitoring and control of essential agricultural processes, particularly irrigation and fertilization.

These sensors collect vast amounts of data from farms, covering soil conditions, humidity, crop health, weather, and water usage—data that meet the characteristics of big data, including volume, velocity, and variety. Real-time processing of these data, which can be facilitated by cloud-based solutions and IoT technologies, would allow for immediate responses and precision control.

In this context, smart irrigation stands out as a critical application, enhancing efficient water management and aiding in the conservation of groundwater—a resource that is increasingly scarce. Furthermore, the real-time metering of water usage, combined with insights into soil and environmental conditions, would empower farmers to optimize both water and fertilizer applications. Developing and deploying mobile applications can provide customized guidance on the type, amount, and timing of fertilizers, promoting soil health and minimizing chemical runoff into water sources. Through the integration of these technologies, we can cultivate a more sustainable and resilient agricultural ecosystem, securing food resources for future generations.

Dr. Mohamed Riduan Abid
Dr. Tareq Abu Hamed
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • smart irrigation
  • smart agriculture
  • sensor networks
  • IoT
  • big data analytics
  • control
  • cloud computing
  • real-time data processing
  • mobile applications

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Published Papers (3 papers)

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Research

19 pages, 5162 KiB  
Article
Comparative Analysis of Soil Moisture- and Weather-Based Irrigation Scheduling for Drip-Irrigated Lettuce Using Low-Cost Internet of Things Capacitive Sensors
by Ahmed A. Abdelmoneim, Christa M. Al Kalaany, Giovana Dragonetti, Bilal Derardja and Roula Khadra
Sensors 2025, 25(5), 1568; https://doi.org/10.3390/s25051568 - 4 Mar 2025
Viewed by 840
Abstract
Efficient irrigation management is crucial for optimizing water use and productivity in agriculture, particularly in water-scarce regions. This study evaluated the effectiveness of soil-based and weather-based irrigation management using a low-cost (DIY) Internet of Things (IoT) capacitive soil moisture sensor on drip-irrigated lettuce. [...] Read more.
Efficient irrigation management is crucial for optimizing water use and productivity in agriculture, particularly in water-scarce regions. This study evaluated the effectiveness of soil-based and weather-based irrigation management using a low-cost (DIY) Internet of Things (IoT) capacitive soil moisture sensor on drip-irrigated lettuce. A field experiment was conducted to compare water productivity and water use efficiency between the two management approaches. The soil-based system utilized real-time data from IoT sensors to guide irrigation scheduling, while the weather-based system relied on evapotranspiration data. The IoT-enabled system used 28.8% less water and reduced the pumping hours by 16.2% compared with the conventional weather-based methods. In terms of crop water productivity (CWP), the IoT system reached 16 kg/m3, which was 52.5% higher than the conventional method (10.5 kg/m3). Furthermore, the developed DIY sensor was compared with existing commercial soil moisture sensors, namely, Teros 54 and Drill& Drop. The developed prototype demonstrated reliability and accuracy comparable to other commercial sensors, with an R2 = 0.6, validating its utility for enhanced data-driven irrigation, giving its initial low cost (USD 62). These findings highlight the potential of low-cost soil-based IoT systems in enhancing irrigation efficiency and supporting sustainable agriculture, particularly in resource-limited settings. Full article
(This article belongs to the Special Issue Sensors in Smart Irrigation Systems)
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15 pages, 4481 KiB  
Article
A Novel Time Domain Reflectometry (TDR) System for Water Content Estimation in Soils: Development and Application
by Alessandro Comegna, Simone Di Prima, Shawcat Basel Mostafa Hassan and Antonio Coppola
Sensors 2025, 25(4), 1099; https://doi.org/10.3390/s25041099 - 12 Feb 2025
Viewed by 855
Abstract
Nowadays, there is a particular need to estimate soil water content accurately over space and time scales in various applications. For example, precision agriculture, as well as the fields of geology, ecology, and hydrology, necessitate rapid, onsite water content measurements. The time domain [...] Read more.
Nowadays, there is a particular need to estimate soil water content accurately over space and time scales in various applications. For example, precision agriculture, as well as the fields of geology, ecology, and hydrology, necessitate rapid, onsite water content measurements. The time domain reflectometry (TDR) technique is a geophysical method that allows, in a time-varying electric field, the determination of dielectric permittivity and electrical conductivity for a wide class of porous materials. Measuring the volumetric water content in soils is the most frequent application of TDR in soil science and soil hydrology. TDR has grown in popularity over the last 40 years because it is a practical and non-destructive technique that provides laboratory and field-scale measurements. However, a significant limitation of this technique is the relatively high cost of TDR devices, despite the availability of a range of commercial systems with varying prices. This paper aimed to design and implement a low-cost, compact TDR device tailored for classical hydrological applications. A series of laboratory experiments were carried out on soils of different textures to calibrate and validate the proposed measuring system. The results show that the device can be used to obtain predictions for monitoring soil water status with acceptable accuracy (R2 = 0.95). Full article
(This article belongs to the Special Issue Sensors in Smart Irrigation Systems)
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25 pages, 3804 KiB  
Article
Abnormal Operation Detection of Automated Orchard Irrigation System Actuators by Power Consumption Level
by Shahriar Ahmed, Md Nasim Reza, Md Rejaul Karim, Hongbin Jin, Heetae Kim and Sun-Ok Chung
Sensors 2025, 25(2), 331; https://doi.org/10.3390/s25020331 - 8 Jan 2025
Viewed by 1026
Abstract
Information and communication technology (ICT) components, especially actuators in automated irrigation systems, are essential for managing precise irrigation and optimal soil moisture, enhancing orchard growth and yield. However, actuator malfunctions can lead to inefficient irrigation, resulting in water imbalances that impact crop health [...] Read more.
Information and communication technology (ICT) components, especially actuators in automated irrigation systems, are essential for managing precise irrigation and optimal soil moisture, enhancing orchard growth and yield. However, actuator malfunctions can lead to inefficient irrigation, resulting in water imbalances that impact crop health and reduce productivity. The objective of this study was to develop a signal processing technique to detect potential malfunctions based on the power consumption level and operating status of actuators for an automated orchard irrigation system. A demonstration orchard with four apple trees was set up in a 3 m × 3 m soil test bench inside a greenhouse, divided into two sections to enable independent irrigation schedules and management. The irrigation system consisted of a single pump and two solenoid valves controlled by a Python-programmed microcontroller. The microcontroller managed the pump cycling ‘On’ and ‘Off’ states every 60 s and solenoid valves while storing and transmitting sensor data to a smartphone application for remote monitoring. Commercial current sensors measured actuator power consumption, enabling the identification of normal and abnormal operations by applying threshold values to distinguish activation and deactivation states. Analysis of power consumption, control commands, and operating states effectively detected actuator operations, confirming reliability in identifying pump and solenoid valve failures. For the second solenoid valve in channel 2, with 333 actual instances of normal operation and 60 actual instances of abnormal operation, the model accurately detected 316 normal and 58 abnormal instances. The proposed method achieved a mean average precision of 99.9% for detecting abnormal control operation of the pump and solenoid valve of channel 1 and a precision of 99.7% for the solenoid valve of channel 2. The proposed approach effectively detects actuator malfunctions, demonstrating the potential to enhance irrigation management and crop productivity. Future research will integrate advanced machine learning with signal processing to improve fault detection accuracy and evaluate the scalability and adaptability of the system for larger orchards and diverse agricultural applications. Full article
(This article belongs to the Special Issue Sensors in Smart Irrigation Systems)
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