IoT Sensor Node to Evaluate Indoor Air Quality in Air Conditioner Systems

Indoor air quality is a critical aspect of human health, and the measurement of various parameters such as carbon dioxide (CO
2
), carbon monoxide (CO), particulate matter with a diameter of 10 micrometers or less (PM
10
), particulate matter with a diameter of 2.5 micrometers or less (PM
2.5
), and volatile organic compounds (VOCs), serves as indicators for assessing indoor air quality. This study focuses on the development of a wireless sensor node using Internet of Things (IoT) technologies and components, including the ESP32 microcontroller and Bosch BME 680 gas sensor. A comprehensive case study was conducted to investigate the impact of three key factors on indoor air quality: sensor installation height, the presence of air vents, and work shifts. The primary objective was to determine the feasibility of installing air quality meters in commercial air conditioner equipment and assess whether this approach yields comparable measurements to those obtained at the height of people’s workstations. Each factor was evaluated at two levels, and a complete factorial experiment with repetitions was performed to examine interactions among the factors. The results revealed that both sensor installation height and work shifts had a significant influence on indoor air quality and an intriguing interaction effect between work shifts and installation height was observed. Specifically, higher sensor installation heights were associated with lower pollutant concentrations. Moreover, the study found that indoor air quality tended to be poorer during the second work shift compared to the first shift. These findings provide valuable insights for the development of effective strategies for managing indoor air quality.