Aquaculture is a rapidly growing industry that is increasingly recognized as a vital source of nutrition for the world's expanding population. Traditional fish farming is labor-intensive and non-technical, with unskilled workers and unorganized feed distribution resulting in high costs and environmental deterioration. To address these concerns, a solar-powered, automated fish-feeding boat has been designed and implemented in this study. This innovative system utilizes machine learning and a microcontroller-based control unit (i.e., a memory and input/output interface with I2C communication protocol) to deliver feed at a predetermined time at precise intervals in each day without human intervention, ensuring optimal fish nutrition and growth. The integration of solar power into the boat's operation exemplifies a commitment to environmentally sustainable practices by significantly reducing its carbon footprint. Furthermore, the automation of the fish-feeding process not only minimizes reliance on manual labor but also contributes to substantial cost savings, heightened operational precision, and improved overall efficiency. Collectively, these advancements enhance the economic sustainability and efficient management of aquaculture ventures.