This article presents the development and implementation of an intelligent atmospheric monitoring system based on UAV and IoT technology, as an alternative to the traditional static stations used in industrial environments. The proposal integrates a drone equipped with environmental sensors for the measurement of temperature, pressure, humidity, particulate matter (PM), gas, and CO₂, together with an IoT architecture based on a Raspberry Pi 5 that enables data acquisition, storage in an SQL database, and real-time visualization through a dashboard accessible on the local network. The modular design of the system facilitates its scalability and the possible future integration of multiple drones to increase the spatial and temporal density of sampling. During November and December 2025, two daily flights of approximately 15 minutes were carried out, generating a dataset that made it possible to analyze the temporal behavior of the meteorological and pollutant variables. The results show that atmospheric conditions directly influence the dispersion and variability of pollutants, with significant fluctuations observed in dust and gases, while CO₂ exhibited greater stability as a background indicator. The findings demonstrate that dynamic UAV-based monitoring offers greater flexibility, spatial coverage, and the ability to detect isolated episodes compared with fixed systems, establishing itself as an efficient, low-cost technological solution with high potential for application in industrial environmental management and regulatory compliance.

Keywords

UAV, IoT, air quality monitoring, drone, environmental management.