Optimizing Solar Powered Farming with Genetic Algorithm and Internet of Things

Energy efficiency improvements are urgently needed in the agricultural industry, which is expanding rapidly due to rising demand for both food and environmentally friendly methods of production. An innovative approach is presented to improve the management and performance of solar-powered agricultural systems, especially in the context of irrigation. The system combines Genetic Algorithms (GAs) with Internet of Things (IoT) technology. To keep the photovoltaic (PV) system operating at its peak efficiency, GA is used as a potent optimization tool to make real-time adjustments to the system's operational parameters. This optimization responds to changing circumstances in the environment to increase energy output. The developed system is implemented in MATLAB, and the results are shown. The IoT part of the system consists of sun irradiance, temperature, and humidity sensors that provide real-time data that may be used in making decisions. The data is sent to a centralized server or user interface for easy access and analysis. The GA-based MPPT system allows farmers to customize power production by adjusting the system's parameters.