Edge-AI Solar Farm Defect Detection & Autonomous Cleaning Rover
All-terrain tracked solar panel inspection rover with edge-camera micro-crack detection, spinning microfiber brush, and auto-docking charging station.
Project Overview
A compact tracked mechanical rover built from laser-cut aluminum and acrylic with twin high-torque gear motors, rotating cylindrical microfiber roller, ESP32-CAM optical inspection module, and automatic edge-detection sensors for rooftop solar arrays. ### Real-World Problem Dust accumulation and microscopic micro-cracks reduce solar PV energy efficiency by up to 35% and cause irreversible panel hot-spot burnouts. ### Practical Student Solution Autonomously traverses panel rows dry-cleaning dust without water while scanning for hot-spot defects using onboard vision edge inference. ### Hardware Modules & Sensors - ESP32-CAM AI SBC - Dual Tracked Chassis Base - High-Torque DC Motors - Microfiber Cleaning Roller - IR Fall-Prevention Edge Sensors - 12V Rechargeable LiFePO4 Battery ### Commercial & Institutional Value Premier flagship project for Mechanical, Mechatronics, and Renewable Energy engineering students.
Modern commercial and industrial infrastructure requires automated, real-time sensing and telemetry. Conventional manual monitoring suffers from high latency, human error, and lack of predictive fault visibility for Edge-AI Solar Farm Defect Detection & Autonomous Cleaning Rover.
A turnkey engineering prototype integrating high-precision sensor modules, dedicated microcontroller unit, and cloud telemetry protocols to automate measurement, trigger alert thresholds, and provide remote dashboard control.