This thesis presents the design, development, and testing of a dual-axis self-rotating solar panel system aimed at optimizing photovoltaic energy output through automatic sun tracking. By integrating low-cost components such as LDR sensors, a Raspberry Pi 5, and servo motors, the system continuously adjusts the panel’s orientation to face the sun perpendicularly. The control algorithm, written in Python, ensures real-time responsiveness and improved efficiency over fixed-panel systems. Experimental results demonstrate a significant increase in energy output, ranging between 25% and 45%. The study also includes economic analysis, highlighting the system’s cost-effectiveness despite higher initial investment. Overall, the thesis illustrates a practical and scalable solution to enhance renewable energy utilization through automation and intelligent tracking technology.