IoT-Based Thermal Comfort Monitoring System in High-Temperature Workspaces

Abstract

High-temperature work environments pose significant challenges to occupational safety and thermal comfort monitoring. This study presents the design and functional validation of an Internet of Things (IoT)-based thermal microclimate monitoring system intended for high-temperature indoor workspaces. The proposed system integrates multiple microclimate sensors with an ESP32-based platform to acquire temperature, humidity, air velocity, and globe temperature data. Sensor data are transmitted wirelessly to a cloud server for real-time visualization and computation of thermal comfort indices, including Predicted Mean Vote (PMV) and Wet Bulb Globe Temperature (WBGT). Prototype validation results demonstrate stable sensor operation and reliable real-time data transmission to the cloud platform. The system is shown to be feasible as a prototype solution for supporting thermal environment monitoring and occupational safety assessment in tropical climates. Future work will focus on full-scale field deployment, long-term performance evaluation, and integration of predictive control strategies for automated ventilation systems.