Detecting solar panel damage with Amazon Rekognition Custom Labels

Enterprises perform quality control to ensure products meet production standards and avoid potential brand reputation damage. As the cost of sensors decreases and connectivity increases, industries adopt real-time imagery analysis to detect quality issues. At the same time, artificial intelligence (AI) advancements enable advanced automation, reduce overall cost and project time, and produce accurate defect detection results in manufacturing plants. As these technologies mature, AI-driven inspections are more common outside of the plant environment. This post describes our SOLVED (Solar Roving Eye Detector) project leveraging machine learning (ML) to identify damaged solar panels using Amazon Rekognition Custom Labels and alert operators to take corrective action.