A Simulated IoT Embedded System for Classroom Indoor Air Quality, Noise, and Lighting Monitoring: Architecture and Firmware Performance Analysis

Environmental conditions such as inadequate lighting, excessive noise, and poor indoor air quality can negatively affect students’ health, comfort, and academic performance. Although recent Internet of Things (IoT) technologies have enabled low-cost environmental monitoring systems, most studies provide limited validation of the embedded firmware responsible for deterministic multi-sensor acquisition and real-time operation. This paper proposes and virtually validates an energy-efficient embedded firmware architecture for a low-cost IoT environmental monitoring node for smart classrooms. The system integrates ESP32-based firmware with MQ-135, LDR, and KY-037 sensors, local alarm management, LCD visualization, and HTTP-based wireless communication. Hardware–software co-simulation was performed in Proteus Virtual System Modeling (VSM) before physical implementation. Ten experimental scenarios evaluated firmware execution, sensor integration, alarm coordination, fault handling, IoT communication, and power consumption. The proposed architecture maintained stable deterministic execution under all scenarios, with instantaneous current consumption ranging from 100 mA to 280 mA, 100% successful HTTP transmissions (HTTP status code 200), and an average communication latency of 378 ms. These results demonstrate that virtual prototyping provides an effective framework for early firmware verification, reducing development risks while supporting the deployment of reliable and scalable IoT environmental monitoring systems for smart classroom applications.