Sensing Classroom Temperature, Relative Humidity, Illuminance, CO₂, and Noise: An Integral Solution Based on an IoT...

Area of Science:

• Environmental Science
• Building Technology
• Sensor Networks

Background:

• Optimal Indoor Environmental Quality (IEQ) monitoring necessitates continuous measurement of thermal comfort, illuminance, indoor air quality, and noise.
• Existing Internet of Things (IoT) devices are often not suitable for dense deployments across various building types (schools, hospitals, offices) to capture all critical IEQ parameters.
• Lack of integrated IoT solutions hinders comprehensive IEQ assessment in diverse built environments.

Purpose of the Study:

• To propose and detail an innovative IoT device capable of measuring multiple IEQ variables simultaneously.
• To address the gap in current technology for dense, multi-parameter IEQ monitoring in commercial and institutional buildings.
• To present a replicable and scalable IoT solution for advanced IEQ assessment.

Main Methods:

• Development of a novel IoT device designed to measure thermal comfort, illuminance, indoor air quality, and noise.
• Implementation of the device within a tree-like radio frequency network, enabling flexible roles (sensor, hub, router).
• Experimental validation of the device's performance and system design for replicability.

Main Results:

• The developed IoT device successfully measures key IEQ variables, fulfilling the study's primary objective.
• Experimental results demonstrate satisfactory performance and confirm the system's design integrity.
• The device's adaptability in network roles (sensor, hub, router) was validated.

Conclusions:

• The proposed IoT device offers a comprehensive solution for continuous IEQ monitoring across multiple parameters.
• The system's design ensures replicability, facilitating widespread adoption in various building settings.
• Theoretical analysis indicates high scalability potential, paving the way for future advancements in smart building environmental management.