Augmented Reality and Artifcial Intelligence Based Smart Circuit Trainer with PCB Fault Detection

Abstract

Learning electronics and inspecting circuit boards can be challenging, especially when students struggle to visualize circuits or when labs lack affordable diagnostic tools. At the same time, professional PCB inspection systems are often expensive, making them impractical for education and lower level use. To address these challenges, this project introduces an AR and AI-Based Smart Circuit Trainer with PCB Fault Detection—a system designed to make circuit learning more interactive while also providing automated fault analysis for printed circuit boards. Using Augmented Reality students can view and build circuits in 3D and identify components and receive step-by-step guidance. The AI-powered fault detection feature analyzes PCB images and compares them with reference designs to detect issues such as broken tracks, soldering errors or missing components or lines on PCB board. The hardware setup progresses from a simple manual inspection model to a fully automated system for accurate and reliable scanning. By combining AR for learning and AI for smart inspection, this project offers an automatic and cost-effective solution that supports students, teachers and small-scale electronic development with real-time visualization and intelligent fault detection.