An Implementation of Early Warning System for Air Condition Using IoT and Instant Messaging

Air pollution poses a significant threat to human health and environmental sustainability, exacerbated by anthropogenic activities such as industrial emissions, vehicle exhaust, and fossil fuel combustion. Major pollutants include carbon monoxide (CO), nitrogen dioxide (NO2), hydrocarbons (HC), sulfur dioxide (SO2), ozone (O3), particulate matter (PM2.5), particulate matter (PM10), and etc. In this study, an Early Warning System (EWS) was developed integrating sensors, microcontroller, IEEE 802.11 network, web interface monitoring, and Instant Messaging. The system uses the CART algorithm to analyze the data, with sensors that detect CO, NO2, and HC. The evaluation of the system demonstrated its effectiveness, with recorded pollutant concentrations of 1.401 ppm for CO, 0.639 ppm for NO2, and 0.860 ppm for HC, and identified correlations between these pollutants. The EWS proved capable of providing timely alerts, ensuring continuous monitoring and management of indoor air quality, and contributing to public health and environmental protection.