Implementation of Edge Computing in a Learning Room Condition Monitoring System Using the MQTT Protocol

This research presents the development of a real-time classroom environmental monitoring system using edge computing and the MQTT protocol. The system is designed to monitor temperature, humidity, and illumination by utilizing an ESP32-based edge node equipped with DHT22 and BH1750 sensors. Data are processed locally and transmitted to an edge server running the Mosquitto broker, which stores the results and displays them through a web-based dashboard. Performance evaluation was conducted through experimental testing at distances of 5 and 10 meters, measuring delay and throughput using timestamp analysis and Wireshark traffic capture. The results show that the system operates functionally and maintains stable data transmission, with average throughput of 402.5 bps. However, the average delay of 1071.12 ms across both scenarios falls into the “poor” category based on TIPHON standards, indicating significant latency caused by Wi-Fi signal variability. Overall, the system successfully demonstrates the feasibility of edge-based IoT monitoring for learning spaces and provides a foundation for the development of smart classroom environments requiring continuous environmental supervision.