Precision Agriculture Meets IoT: Advanced Detection Systems for Crop Health

A special issue of AgriEngineering (ISSN 2624-7402). This special issue belongs to the section "Computer Applications and Artificial Intelligence in Agriculture".

Deadline for manuscript submissions: closed (31 August 2025) | Viewed by 565

Special Issue Editors


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Guest Editor
Department of Information and Electronic and Electronic Engineering, International Hellenic University, Alexander Campus, Sindos, Thessaloniki, Greece
Interests: electronic circuits; IoT; precision agriculture; electronic systems for measuring the motion of micro-electro-mechanical devices; sensors and actuators; control systems; machine vision
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Guest Editor
Department of Information and Electronic and Electronic Engineering, International Hellenic University, Alexander Campus, Sindos, Thessaloniki, Greece
Interests: analog electronics; measurement systems; sensors; instrumentation; IoT; precision agriculture

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Guest Editor
Department of Agriculture, International Hellenic University, Alexander Campus, Sindos, Thessaloniki, Greece
Interests: soil science; physical and chemical properties of soils; soil fertility; problematic soils and soil pollution; sustainable management of soils; restoration and management of degraded soils; applications of precision agriculture in soil science

Special Issue Information

Dear Colleagues,

Using the Internet of Things (IoT) can help farmers implement sophisticated sensing systems to monitor crop health remotely and in real-time. Advances in IoT technology have provided new capabilities that can be incorporated into precision agriculture, such as disease detection, monitoring of soil and environmental conditions, and optimization of water and fertilizer use. These systems provide, through remote communication between nodes, enable the farmer to intervene in the field, either automatically or manually using decision-making systems.

These monitoring systems incorporate sensors to collect field data. The data are transmitted to the central nodes where they are analyzed and processed. In some cases, data analysis and processing, which may be carried out using artificial intelligence and machine learning, allow for the timely detection of problems and accurate assessment of crop conditions.

This Special Issue aims to bring together recent developments and applications of the Internet of Things (IoT) and precision agriculture for advanced detection systems in crop health and original research articles and reviews are welcome.

This Special Issue focuses on, but is not limited to, agricultural engineering in the following areas:

  • IoT systems for crop health monitoring;
  • Sensors and detection technologies for precision agriculture;
  • Data analytics and artificial intelligence in agriculture;
  • Networking and communication in agricultural applications;
  • Electronic circuits and embedded systems for agricultural applications;
  • Intelligent crop monitoring and management systems;
  • Wireless sensor networks (WSNs) for agricultural applications;
  • Machine learning and predictive algorithms for agriculture;
  • Multispectral imaging and camera systems;
  • Noninvasive imaging of crops;
  • Laser scanning thermography.

Dr. Kyriakos Tsiakmakis
Dr. Argyrios Hatzopoulos
Dr. Stefanos Stefanou
Guest Editors

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Keywords

  • precision agriculture
  • IoT
  • detection systems
  • crop health
  • plant monitoring
  • smart farming
  • sustainable agriculture
  • data analytics in agriculture
  • sensors
  • electronic and embedded systems in agriculture

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Published Papers (1 paper)

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Research

18 pages, 5552 KB  
Article
Development of a Low-Cost Measurement System for Soil Electrical Conductivity and Water Content
by Emmanouil Teletos, Kyriakos Tsiakmakis, Argyrios T. Hatzopoulos and Stefanos Stefanou
AgriEngineering 2025, 7(10), 329; https://doi.org/10.3390/agriengineering7100329 - 1 Oct 2025
Abstract
Soil electrical conductivity (EC) and water content are key indicators of soil health, influencing nutrient availability, salinity stress, and crop productivity. Monitoring these parameters is critical for precision agriculture. However, most existing measurement systems are costly, which restricts their use in practical field [...] Read more.
Soil electrical conductivity (EC) and water content are key indicators of soil health, influencing nutrient availability, salinity stress, and crop productivity. Monitoring these parameters is critical for precision agriculture. However, most existing measurement systems are costly, which restricts their use in practical field conditions. The aim of this study was to develop and validate a low-cost, portable system for simultaneous measurement of soil EC, water content, and temperature, while maintaining accuracy comparable to laboratory-grade instruments. The system was designed with four electrodes arranged in two pairs and employed an AC bipolar pulse method with a constant-current circuit, precision rectifier, and peak detector to minimize electrode polarization. Experiments were carried out in sandy loam soil at water contents of 13%, 18%, and 22% and KNO3 concentrations of 0, 0.1, 0.2, and 0.4 M. Measurements from the developed system were benchmarked against a professional impedance analyzer (E4990A). The findings demonstrated that EC increased with both frequency and water content. At 100 Hz, the mean error compared with the analyzer was 8.95%, rising slightly to 9.98% at 10 kHz. A strong linear relationship was observed between EC and KNO3 concentration at 100 Hz (R2 = 0.9898), and for the same salt concentration (0.1 M KNO3) at 100 Hz, EC increased from ~0.26 mS/cm at 13% water content to ~0.43 mS/cm at 22%. In conclusion, the developed system consistently achieved <10% error while maintaining a cost of ~€55, significantly lower than commercial devices. These results confirm its potential as an affordable and reliable tool for soil salinity and water content monitoring in precision agriculture. Full article
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