Recently, an indoor environment monitoring system using the internet of things sensor has been actively used to secure the thermal comfort of occupants, reduce energy use, and control indoor air quality. However, most commercial sensor and control applications are limited to the unilateral sharing of measurement results and simple operation control of related equipment. This study describes the development of a system for real-time and easy monitoring of the indoor environment and energy consumption. This study then describes the application of the system to the living lab. The system was built using Raspberry Pi and embedded sensors (temperature, humidity, PM1.0, PM2.5, PM10, and CO2) to collect indoor air quality-related data. The data can be safely stored for a long time, and residents can easily check and interact with the data. This study presents the problems and requirements that occurred during the development and implementation of the proposed system, data measured in the living lab and discusses the analysis results. The proposed system is expected to support continuous and efficient environment monitoring and control seasonal energy use by recognizing changes in the indoor environment according to the behavior of residents and estimating energy consumption.
