Integrated low-cost air quality monitoring system, comparison and reliability of a low-cost particulate matter (PM2.5) sensors.

Air pollution is one of the most significant environmental challenges of modern society, with particulate matter (PM2.5) being among the most harmful pollutants due to its severe impact on human health and the environment. Continuous air quality monitoring is essential; however, the installation and operation of certified monitoring stations involve high costs, limiting the spatial coverage of monitoring networks. The aim of this research work was the design, development, and evaluation of a low-cost, IoT-based air quality monitoring system. The proposed system was built around the ESP32 microcontroller and integrated PMS5003 and SPS30 particulate matter sensors together with the AHT20 temperature and relative humidity sensor. Data acquisition, storage, and visualization were achieved using InfluxDB and Grafana, while the ESP32 deep sleep mode was employed to reduce power consumption. The recorded data were compared with measurements obtained from the Open-Meteo website (as reference measurements) while the performance and reliability of the low-cost sensors were evaluated using linear regression analysis and the coefficient of determination (R²). The experimental results demonstrated a high correlation (R²) between the measured and reference values for temperature and relative humidity, while both PM2.5 sensors successfully captured the overall variation trend of particulate matter concentrations. Among the two sensors, the SPS30 achieved the best overall performance, exhibiting higher correlation and greater measurement stability than the PMS5003. Although deviations from the reference station were observed, mainly due to differences in installation conditions and local environmental factors, the study demonstrated that the use of a low-cost IoT-based monitoring system can provide wide spatial coverage and more accurate air quality measurements. Finally, the proposed low-cost air quality monitoring station can be used as a cost-effective complementary solution to conventional air quality monitoring networks.