Next-Generation Water Management and Crop Modeling of Sustainable Energy in PLC Based on Agrivoltaics Systems With IoT
The integration of PLC controllers and LoRaWAN-IoT in sensor-based Agrivoltaics Systems (AVS) presents a cutting-edge approach to sustainable energy management and precision agriculture. AVS strives to combine solar energy generation with agriculture to optimize land utilization. Nevertheless, these...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11071536/ |
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| Summary: | The integration of PLC controllers and LoRaWAN-IoT in sensor-based Agrivoltaics Systems (AVS) presents a cutting-edge approach to sustainable energy management and precision agriculture. AVS strives to combine solar energy generation with agriculture to optimize land utilization. Nevertheless, these systems encounter various issues, particularly regarding water management, energy efficiency, and communication between agricultural components. Moreover, standard crop models fail to adjust to shifting climate conditions, resulting in inaccurate yield forecasts. Smart control systems are essential for managing energy production and consumption in agricultural activities. Tackling these issues is essential for improved resource utilization, lowering costs, and promoting sustainable agriculture. This paper proposes an IoT-driven framework for optimizing water management and dynamic crop modelling, ensuring efficient resource utilization in agrivoltaics environments. By combining PLC for high-speed data transmission and LoRaWAN for long-range, low-power connectivity, the system enables seamless communication between distributed sensors, minimizing infrastructure costs and enhancing scalability. Real-time data analytics is employed to improve water conservation, crop health prediction, and energy efficiency. Additionally, the dynamic crop modelling framework adapts to climatic variations, optimizing land use for both agriculture and renewable energy generation. The experimental demonstration of this model is performed in MATLAB, and simulation results and real-world case studies validate the effectiveness in terms of planting area quality, energy production, and beam and diffuse shading factors. The comparative analysis is performed among the baseline methods for the parameters like power generation, Irrigation supply, yield production and irrigation water productivity calculation, and Voltage/current analysis. This research highlights the potential of LoRaWAN-IoT and PLC-based agrivoltaics systems in fostering sustainable farming while promoting the dual use of land for agriculture and renewable energy generation. |
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| ISSN: | 2169-3536 |