Autonomous Self-Powered Solar Panel Cleaner Design with Linear Resonant Actuators and Machine Learning

This research presents a novel, waterless, self-sustaining autonomous solar-panel cleaner that combines LDR sensing for dust monitoring, LRA vibration for dust removal, ML-based scheduling, and heat to energy harvesting using TEGs, achieving 95% dust clearance, consuming only 0.366 Wh/day, costing approximately $35 per unit, and delivering an estimated 70% reduction in maintenance costs.