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The increasing demand for digitalization and energy efficiency in vocational education has encouraged the development of intelligent classroom systems. This study proposes an integrated smart classroom 4.0 system based on the Internet of things (IoT) and embedded systems to improve attendance management, electrical safety, energy efficiency, and environmental monitoring. The proposed system integrates smart attendance, power monitoring, automatic lighting control, and environmental sensing into a unified architecture using ESP32 microcontrollers and a Raspberry Pi embedded server. Attendance is automated using radio frequency identification (RFID), fingerprint recognition, and non-contact body temperature measurement, achieving an average accuracy of 92.5% with a system latency of 1.1–1.4 s. Electrical monitoring using the PZEM-004T sensor shows zero error for voltage and current measurements and a maximum power measurement error of 0.31%, while overload and abnormal voltage conditions are successfully handled through automatic protection. Automatic lighting control based on YOLOv5s image processing achieves approximately 90% detection accuracy under high occupancy conditions. All subsystems communicate via the message queuing telemetry transport (MQTT) protocol and are visualized through a real-time web dashboard. The results demonstrate that the proposed system provides a low-cost, scalable, and reliable solution for energy-efficient and intelligent classroom management in vocational education environments.

biometric attendance system; energy-efficient classroom; internet of things-based classroom; message queuing telemetry transport protocol; real-time monitoring; smart classroom 4.0; you only look once-based detection;