ADVANCED AGRICULTURAL IRRIGATION: USING PREDICTIVE MODELING TO MANAGE WATER EFFICIENTLY.
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Abstract
The increasing global population, along with climate change and water shortages, underscores the need for efficient and sustainable agricultural practices. The advent of affordable IoT-based sensors and actuators presents significant opportunities for this transformation. These devices can be easily integrated to enable advanced monitoring and irrigation control techniques on farms, leading to energy and water savings and reduced costs. This paper introduces an economically driven periodic predictive controller that leverages the cyclical nature of irrigation. The controller aims to optimize water and energy usage while maintaining sufficient soil moisture levels for crops to achieve maximum yield. It utilizes soil moisture data from various depths and solves a constrained optimization problem that accounts for water and energy costs, crop transpiration, and a precise nonlinear dynamic model of soil water dynamics. This innovative strategy is compared to a traditional irrigation method managed by a human expert in a specific case study, showing significant reductions in water and energy consumption without sacrificing crop yields. Abstract: The increasing global population, along with climate change and water shortages, underscores the need for efficient and sustainable agricultural practices. The advent of affordable IoT-based sensors and actuators presents significant opportunities for this transformation. These devices can be easily integrated to enable advanced monitoring and irrigation control techniques on farms, leading to energy and water savings and reduced costs. This paper introduces an economically driven periodic predictive controller that leverages the cyclical nature of irrigation.
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References
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