Diseño de un nodo sensor Edge IoT para el monitoreo de contaminantes atmosféricos

Abstract

Air pollution is an environmental and public health issue that requires effective monitoring solutions. This work presents a low-cost Edge IoT sensor node for air pollutant monitoring, designed to expand geographic coverage and improve accessibility to environmental data. The system uses an ESP32 as the processing unit, sensors to measure particulate matter and pollutant gases, and a LoRa module for long-distance data transmission. An exponential moving average filter was implemented to reduce measurement noise, and comparative calibrations were conducted with reference stations. Results indicate that the node provides reliable measurements of PM10, PM2.5, CO, and NO2, although with lower accuracy compared to specialized monitoring stations. However, its integration with robust platforms allows it to complement traditional monitoring networks. This solution represents a scalable and accessible alternative to support decision-making related to air quality and environmental policies.