International Journal of Innovative Research in Computer and Communication Engineering

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TITLE PCB Error Detection using IoT on a Conveyor Belt
ABSTRACT This paper presents a low-cost, IoT-enabled Automated Optical Inspection (AOI) system for detecting printed circuit board (PCB) manufacturing defects. To maximize system stability, the architecture divides the workload: an ESP32-S3 edge device handles real-time hardware actuation (ultrasonic proximity detection and conveyor motor control), while a local server handles intensive image processing. Overcoming the resolution limits and routing complexities of standard microcontroller cameras, the vision subsystem utilizes a commercial smartphone's high-resolution IP video stream. Upon detecting a PCB, the ESP32-S3 halts the conveyor and wirelessly triggers the server to capture an image and execute OpenCV-based image subtraction. This identifies defects like missing or misaligned components, demonstrating a highly scalable and budget-friendly machine vision solution for small enterprises.
AUTHOR PROF. PRATIK TAWDE, MAYANK SHIRKE, SUMEDH YADAV, MIR SONAWANE, HASIB MEER Department of Electronic and Telecommunication Vidyalankar Polytechnic, Mumbai, Maharashtra, India.
VOLUME 182
DOI DOI: 10.15680/IJIRCCE. 2026.1403052
PDF pdf/52_PCB Error Detection using IoT on a Conveyor Belt.pdf
KEYWORDS
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