The solar panel cleaning robot and real–time asset tracking record control via IOT system

Abstract

This study presents the design and development of an IoT-enabled solar panel cleaning robot aimed at enhancing autonomous maintenance efficiency and enabling real-time asset tracking. The robot’s movement and navigation were analyzed using differential kinematics and static analysis. A microcontroller-based control system with integrated IoT functionality allows remote operation via a web-based interface. Embedded GPS capabilities automatically log real-time location data (latitude and longitude) to Google Sheets for performance monitoring. The robot was tested on a solar panel array measuring 4.8 × 8.72 meters (81.86 m²), completing the cleaning process in 15 minutes. Compass accuracy was evaluated using the Mean Absolute Percentage Error (MAPE) across three movement patterns: Vertical Spiral (168.19), Horizontal (11.31), and Cycle Spiral (44.78), highlighting variations in directional performance. The integration of IoT and GPS with autonomous control provides a practical, scalable solution for efficient solar panel maintenance and location tracking. The robot demonstrates strong potential for real-world application in large-scale solar energy systems. Future enhancements will focus on improving precision navigation using sensor fusion techniques, such as Kalman and Butterworth filters, to increase the accuracy and stability of GPS and compass data under diverse environmental conditions.