• Pornima Harishchandra Wagh
• Prof.Ganesh S. Wayal

The performance of photovoltaic (PV) systems is greatly influenced by environmental factors such as dust accumulation, humidity, and temperature, which reduce energy output and overall efficiency. To overcome these challenges, a wide range of cleaning approaches have been developed, including solar-powered robots, automatic cleaning mechanisms, IoT-enabled monitoring systems, AI-driven predictive models, and transparent self-cleaning coatings. These technologies demonstrate a clear evolution from simple mechanical systems to intelligent, autonomous, and self-sustaining solutions. While recent advancements have improved adaptability and efficiency, challenges remain in terms of scalability, cost, energy consumption, and long-term durability. Preventive coating technologies show promise but require further testing across diverse climatic conditions. The study concludes that hybrid solutions integrating predictive intelligence, IoT-based monitoring, self-powered robotic cleaning, and durable coating methods offer the most effective pathway for achieving sustainable, efficient, and autonomous solar panel maintenance.

Solar photovoltaic (PV) systems, Solar panel cleaning, Autonomous robots, Artificial intelligence, IoT-based monitoring, Self-cleaning coatings, Energy efficiency, Sustainable maintenance, ESP8266, ESP32 Cam, Motor driver

"AI Based Solar Panel Cleaning Robot", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 9, page no.e459-e461, September-2025, Available :http://www.jetir.org/papers/JETIR2509452.pdf

"AI Based Solar Panel Cleaning Robot", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 9, page no. ppe459-e461, September-2025, Available at : http://www.jetir.org/papers/JETIR2509452.pdf