Citation :

Juan Marcos Vilca Condori, Paul Fernando Sanz Pacheco, Jorge Leonardo Huarca Quispe, "IoT System for Monitoring and Controlling Air Quality in Industrial Environments with Local Alerts," International Journal of Electrical and Electronics Engineering, vol. 13, no. 5, pp. 118-126, 2026. Crossref, https://doi.org/10.14445/23488379/IJEEE-V13I5P110

Abstract

This article presents the development of an IoT system for real-time monitoring and control of air quality in industrial environments, focused on protecting the health and reducing risks to operators caused by pollutants generated in everyday production or chemical processes. The system is based on an electronic card with an ESP32 microcontroller using ESP-NOW for wireless communication between the control card that integrates the LoRa SX1278 module and control devices such as relays, integrating high-performance sensors for measuring CO₂, H₂, CO, PM2.5, and PM10 particulate matter, volatile organic compounds, toxic gases of electrochemical origin, as well as ambient temperature and humidity. The measurements are processed through this system to generate a standardized risk index on a scale of 0 to 100, shown in digits on a large numerical display, and sent to the cloud via the Adafruit IO platform for cloud monitoring, as well as enabling the automatic activation of visual alerts through a color-coded signaling system and audible alarms. A 60% to 68% reduction in the level of exposure of operators to critical pollutants is estimated after its implementation, as well as the ease of collecting data in the cloud for further analysis, making it a useful tool for the traceability of industrial risks that pose an environmental risk to the atmosphere and occupational health, providing support for industrial safety audits such as ISO 45001 as a prevention system and the sustained improvement of working conditions in industrial environments.

Keywords

Industrial Air Quality Monitoring, Internet of Things (IoT), Real-Time Environmental Monitoring, Occupational Health and Safety, LoRa-Based Sensor Networks

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