• Pornima Wagh
• Ganesh Wayal

The efficiency of solar photovoltaic (PV) systems is significantly affected by the deposition of dust, dirt, and other environmental particles on the panel surface, leading to power losses of up to 40% in harsh conditions. Traditional cleaning methods such as manual wiping or water spraying are labor-intensive, consume excessive resources, and are unsuitable for real-time operations in large-scale solar farms. This paper presents an AI-based solar panel cleaning robot that integrates automation, artificial intelligence, and IoT technologies to ensure sustainable and efficient panel maintenance. The system employs an ATmega328 microcontroller as the central control unit, supported by an ESP32-CAM module for real-time monitoring and image capture of dust accumulation. A motor driver and dual-motor mechanism provide autonomous mobility across the PV surface, while a relay-controlled water pump ensures efficient cleaning when required. The integration of AI algorithms enables predictive decision-making, allowing the robot to initiate cleaning only when dust levels exceed a threshold, thereby reducing unnecessary water and power consumption. Communication is facilitated through an HC-05 Bluetooth module, enabling remote monitoring and control. Experimental validation demonstrates that the proposed system effectively enhances panel efficiency, reduces maintenance costs, and supports sustainable solar energy harvesting. The results highlight the potential of AI-driven robotics in addressing one of the most critical real-time challenges of the renewable energy sector.

Solar PV, Cleaning Robot, Artificial Intelligence, IoT, ATmega328, ESP32-CAM, Renewable Energy.

"AI BASED SOLAR PANEL CLEANING ROBOT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 10, page no.a232-a236, October-2025, Available :http://www.jetir.org/papers/JETIR2510028.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 10, page no. ppa232-a236, October-2025, Available at : http://www.jetir.org/papers/JETIR2510028.pdf