A COMPREHENSIVE REVIEW OF IRRIGATION SYSTEMS: SOIL MOISTURE SENSORS, IoT CONNECTIVITY AND INTELLIGENT DECISION-SUPPORT MODELS

Abstract

This article presents a comprehensive review of smart irrigation systems, including an analysis of the main types of soil moisture sensors, atmospheric and plant-oriented sensing technologies, as well as methods for their calibration and integration into field monitoring networks. Particular attention is given to the development of IoT communication technologies, such as LoRaWAN, NB-IoT, Wi-Fi, ZigBee and BLE, and their role in building scalable and energy-efficient network architectures for agricultural environments. The paper also examines modern technologies for soil moisture measurement. Furthermore, various classes of computing platforms and controllers used for irrigation automation are reviewed. The analysis covers the principal decision-making approaches: soil water balance models and evapotranspiration calculations (ET₀, Kc), threshold-based logical algorithms, rule-based decision support systems, as well as modern forecasting methods that employ machine learning, neural networks and hybrid models. Special emphasis is placed on comparing the advantages and limitations of different technological classes and assessing their impact on water-use efficiency, operational cost reduction and the sustainability of agricultural production under conditions of climatic variability. The review highlights that hybrid IoT-based solutions integrating sensor data, physical models and artificial intelligence algorithms demonstrate the highest potential. The results provide a holistic view of the technological foundation of modern precision irrigation systems and outline promising directions for future research and practical implementation.