Jul 2026· 2026 6th International Conference on Inventive Computation and Information Technologies (ICICIT)· pp. 256-262· 0 citations· 16 references
Abstract
Precision agriculture is based on the efficient management of water in the areas that are characterized by water scarcity and rising labor costs. The paper introduces a new IoT-based solar-powered smart irrigation system based on the low-power, long-range (LoRa) communication protocol to measure and regulate various environmental indicators. In the proposed system, the real-time soil moisture, temperature, humidity, rainfall, and water level sensors are incorporated, which allows independent irrigation based on a threshold-based decision algorithm. Information on field nodes is relayed via LoRa to a central receiver and at the same time uploaded to an IoT platform in order to view it remotely, conduct historical analysis, and monitor it in real-time. The integration of solar energy would also assure continuous off-grid performance, enhanced efficiency of energy, and sustainability. This framework delivers a fully closed-loop system with sensing, actuation, feedback, and renewable energy unlike the current solutions where the solution focuses on monitoring or single-function automation. The experimental validation has shown that the system has good long-range communication, low power use, and exact irrigation control, which means that it can be used to optimize water use, minimize human efforts and support scalable precision farming methods. Experimental analysis demonstrated 27.1% water savings, reliable communication up to 2 km, and stable off-grid operation under real-time agricultural conditions. which means that it can be used to optimize water use, minimize human efforts and be used to support scalable precision farming methods. The piece brings on board a viable, energy saving and sustainable method of agriculture in modern times, which are applicable in various crop settings.
Smart agriculture has made it easier to use IoT, wireless communication and renewable energy technologies to improve farming efficiency. This paper presents the development and testing of a solar-powered, LoRa-based IoT smart farming system. The system continuously monitors important parameters such as temperature, humidity and soil moisture using sensors deployed in the field. The collected data is transmitted over long distances using LoRa communication to a receiver unit. Cloud platforms like Google Sheets and Firebase are used for data storage and remote monitoring, making the system easily accessible. The system provides intelligent suggestions on the amount of water required based on real-time soil and environmental conditions. A simple rule-based decision system analyzes the data and recommends appropriate irrigation levels and crop-related insights. This helps farmers make better decisions without fully automating the process. The system reduces manual effort, improves water management and offers a practical, low-cost solution for smart and sustainable agriculture.
N. Gautham, D. G. Thrisha, S. Karthik et al.· International Conference on...· 0 citations
Measuring the water table level is a critical factor in irrigated agriculture in arid regions, as it can significantly influence the exchange of water and nutrients with crops. This work presents the design, implementation, and field validation of an open-source, solar-powered IoT device for autonomous groundwater level monitoring, combining long-range low-power LoRa communication, a non-contact pressure-based level sensor using the trapped-air capillary method, and an efficient power management stage that seamlessly switches between solar and battery power. Unlike existing commercial leveloggers, which are costly and lack integrated wireless telemetry and solar-based autonomy, the proposed platform is presented as a fully open-source, low-cost alternative purpose-built for unattended deployment in areas without grid power or cellular coverage. The system was validated through a multi-day field trial and dedicated communication tests, demonstrating a stable power conversion efficiency of 84–90%, a five-day autonomous operation without any deep-discharge event, high linearity (R2 = 0.9998) of the level module over a 0–2 m range with a resolution of approximately 1.94 mm per ADC count, and a reliable LoRa link of up to 8.51 km in an urban/suburban environment despite non-line-of-sight conditions. With an estimated hardware cost of approximately $100 USD per unit, the device represents a low-cost, low-maintenance tool capable of generating knowledge about water resources to optimize irrigation and crop management in the face of climate change.
Danilo Coletto Gallego, J. Vanzolini, Rodrigo M. Santos et al.· Hardware· 0 citations
Modern agriculture faces challenges such as water wastage, unpredictable weather conditions, lack of real-time monitoring, and dependence on manual irrigation methods. To address these issues, this paper presents a smart agriculture monitoring and irrigation control system based on the ESP32 microcontroller using ESP-NOW wireless communication. The proposed system consists of one main control node and two sensor nodes placed in the agricultural field to monitor parameters such as temperature, humidity, soil moisture, rainfall, and motion. Based on predefined threshold values, the irrigation system automatically controls the water pump to reduce water wastage and improve efficiency. The collected sensor data is transmitted wirelessly to the main node using ESP-NOW and then uploaded to a cloud platform through Wi-Fi for remote monitoring using a mobile application. The system is powered by solar energy with a rechargeable Li-ion battery backup, making it suitable for remote and off-grid agricultural areas. Experimental results demonstrate reliable sensing, stable multi-node operation, efficient wireless communication, and effective automatic irrigation control, making the proposed model an affordable, scalable, and energy-efficient solution for smart agriculture.
Unknown authors· ITEGAM- Journal of Engineeri...· 0 citations
Agriculture is increasingly challenged by water scarcity, climate change, and rising energy demands, requiring more efficient and sustainable irrigation solutions. Conventional irrigation systems often lack the capability to adapt their operation to changing soil conditions and renewable energy availability, resulting in inefficient water and energy use. This study proposes a digital twin-based framework for energy management and irrigation optimization in photovoltaic (PV)-powered smart agriculture systems using Internet of Things (IoT) soil monitoring. The proposed system integrates a physical irrigation infrastructure, an IoT monitoring network, a fuzzy logic control layer, and a digital twin environment that periodically synchronizes the virtual model with IoT measurements to support the system representation and decision-making. The digital twin models soil moisture, temperature, nutrient levels, PV energy generation, battery state of charge, and irrigation water consumption. The virtual representation was periodically aligned with the physical system using measurements transmitted through the long-range (LoRa)-based network. An energy-aware irrigation scheduling strategy was developed to optimize irrigation timing based on soil conditions, battery status, and solar energy availability. The framework was evaluated using field data collected in a real apple orchard through an ESP32-based IoT platform and a standalone PV-powered irrigation system; quantitative experimental validation was performed for the soil twin. The results demonstrate high soil twin synchronization accuracy, with an overall RMSE of 1.47 percentage points and R2 of 0.981, based on experimental field measurements. The energy twin and irrigation twin were evaluated using experimentally acquired sensor data together with model-based performance assessment, demonstrating the potential of the proposed digital twin framework for integrated water–energy management in smart agriculture.
R. Kabakchieva, Plamen Stanchev, Nikolay Hinov· Electronics· 0 citations
Efficient irrigation management requires complementary information on atmospheric demand, soil conditions, and crop water stress. This study presents a low-power Internet of Things (IoT)-based irrigation system that integrates these components within a unified monitoring and control framework. The system combines LoRa communication, ESP32-based sensor nodes, soil and meteorological sensing, FAO-56 reference evapotranspiration (ET0), and canopy-temperature-based Crop Water Stress Index (CWSI). Irrigation decisions rely on the complementary use of ET0, in situ soil measurements, and CWSI rather than on a single indicator. A hybrid time-, event-, and query-driven acquisition strategy was implemented to adapt node activity and limit communication overhead. The system was deployed under outdoor conditions in Oujda, Morocco, demonstrating integrated sensing, wireless data transmission, crop-stress monitoring, and automated irrigation control. Energy characterization further showed distinct consumption profiles across sensing, communication, actuation, and low-power operating states, supporting the use of duty cycling to limit active node operation. The results demonstrate the feasibility of integrating environmental, soil, and crop-level information within a low-power IoT framework for adaptive irrigation management.
Y. Ayat, A. E. Moussati, Oumayma Rachdi et al.· IoT· 0 citations
Rainfed agriculture is highly vulnerable to rainfall variability and limited irrigation infrastructure, resulting in unstable agricultural production, particularly during prolonged dry periods. This study aimed to develop a detailed engineering design for an integrated solar-powered irrigation system equipped with Internet of Things monitoring for rainfed farmland in Kembang Sari Village. The study employed a research-and-development approach focusing on electrical-load analysis, photovoltaic and battery sizing, pump and reservoir configuration, hydraulic-system design, and sensor-based monitoring architecture. The proposed system integrates photovoltaic modules, a solar charge controller, lithium iron phosphate batteries, an inverter, a 1.5-hp irrigation pump, a water reservoir, and sensors for soil moisture, water level, flow rate, battery condition, and pump status. The results showed a total connected load of 1,156 W and a daily energy requirement of approximately 6,019 Wh. Considering an overall system efficiency of 80% and five peak-sun hours per day, the required generation capacity was estimated at 7,523.75 Wh/day. The recommended configuration consists of seven 250-Wp photovoltaic modules with a total capacity of 1.75 kWp, a minimum 50-A charge controller, a 6-kW inverter, and two 48-V 100-Ah lithium iron phosphate batteries. The hydraulic subsystem uses a pump with an estimated 12-m head and a 36-m³ reservoir to support a target water supply of approximately 36 m³/day. The integrated monitoring system enables remote supervision, automatic protection, and data-informed irrigation management. The design provides a technically coherent basis for prototype construction, although field validation is required to assess actual solar generation, pump performance, water adequacy, sensor reliability, maintenance requirements, and economic feasibility.
W. Pasek, Resti Awan, Fabiano Yanel Ayawaila et al.· EDUCATIONE· 0 citations