Virtual Booth

QC SMART LAB: IoT-Enabled Predictive Quality Control Learning System for TVET

Abstract

QC SMART LAB is an innovative learning system developed to integrate Quality Control (QC) education with Industry 4.0 technologies in TVET learning environments. The system combines ESP32-based sensors, digital data acquisition, an interactive dashboard and data analytics to provide students with a practical and engaging approach to quality inspection and decision-making. Through real-time measurement and digital visualisation, inspection data can be collected, monitored and analysed using charts, trends and quality indicators. This enables students to move beyond conventional theory-based and manual QC learning towards hands-on, data-driven quality control practices that closely reflect modern industrial environments. QC SMART LAB also introduces the foundation for predictive quality control by enabling quality data patterns to be analysed for early identification of potential abnormalities. The system is scalable and can be further enhanced through AI-based anomaly detection, machine vision, additional IoT sensors and learning analytics. QC SMART LAB therefore provides a practical bridge between TVET quality control education and Industry 4.0, while enhancing students’ digital, analytical and quality management competencies.

Keywords: QC SMART LAB, Quality Control, IoT, AI, Industry 4.0, TVET.