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The performance of solar photovoltaic (PV) systems is significantly affected by environmental factors, particularly the accumulation of dust, dirt, and bird droppings on panel surfaces. In regions like Malaysia, where solar adoption is increasing, reduced panel efficiency due to surface contamination presents a major challenge, with potential energy losses of up to 50% if panels are not regularly cleaned. Manual cleaning methods are often labor-intensive, time-consuming, and costly, especially for large-scale installations. This study investigates effective cleaning techniques and proposes a conceptual design for an automatic solar panel cleaning system. Three cleaning methods were tested using a substitute solar panel surface: (1) a brush, (2) a silicone wiper, and (3) a silicone wiper combined with a microfiber cloth. Simulated contaminants—carbon dust and a water-flour mixture—were used to represent common pollutants. Results showed that the third method achieved the highest cleaning efficiency, removing up to 99% of surface contaminants. Based on this outcome, a proposed automated cleaning system design was developed using a mobile unit equipped with a silicone wiper, microfiber cloth, ATmega16 microcontroller, sensors, and a wireless charging dock. The system is intended to operate autonomously at scheduled intervals, offering a low-maintenance and scalable solution. With further development and prototyping, the proposed design has strong potential for commercialization, particularly in solar farms and commercial rooftop PV systems where regular cleaning is critical to maintaining performance. This solution could significantly reduce maintenance costs, enhance energy yield, and support the broader adoption of clean energy technologies.