The thesis focuses on the optimization of a solar cell energy harvesting technology intended specifically for agricultural applications in Nigeria. At the core of the system is a bi-facial solar panel chosen to maximize the conversion of sunlight into electrical energy through absorption on both sides. This electrical energy drives an irrigation pump providing a sustainable irrigation system on a sample farm in Nigeria. To optimize the system, a water-cooling system is included to regulate the temperature of the solar panel. Furthermore, a soil moisture sensor, a temperature sensor and a light-intensity sensor are incorporated to collect necessary data and help develop the controllers for the system components. Finally, machine learning algorithms are integrated to analyze collected data and models are created to optimize the controllers and the entire system by extension.