Abstract: Unmanned Aerial Vehicles (UAVs) equipped with low-cost sensing platforms are increasingly employed for environmental monitoring due to their mobility, rapid deployment capability, and ability to acquire spatially distributed measurements in areas that are difficult to access using conventional ground-based instrumentation. This article presents a lightweight multi-sensor UAV platform based on the ESP32 microcontroller, designed for low-cost and flexible environmental sensing applications. The proposed system integrates four sensing modules: an MPU6050 inertial measurement unit (IMU) for attitude estimation, a NEO-6M GPS receiver for geolocation, an MQ135 gas sensor for air-quality monitoring, and an ESP32-CAM module for visual documentation. A unified data acquisition and synchronization framework is developed to align heterogeneous sensor streams operating at different sampling rates. Sensor-specific compensation strategies are implemented to mitigate IMU bias and drift, gas-sensor stabilization effects, and GPS measurement noise. In addition, measurement uncertainty is quantified following the principles of the Guide to the Expression of Uncertainty in Measurement (GUM), providing a systematic evaluation of the reliability of the sensed data. The proposed system is experimentally validated through UAV flight tests, demonstrating stable operation and consistent multi-sensor integration. The results show coherent reconstruction of UAV trajectory and attitude, as well as repeatable variations in gas sensor response correlated with UAV motion and spatial position. These findings demonstrate the feasibility of the proposed sensor synchronization and fusion framework for low-cost UAV-based environmental sensing, although comparative evaluation against alternative fusion baselines is left for future work.
Keywords: UAV instrumentation, ESP32, Sensor fusion, IMU calibration, Gas sensing, GPS tracking, Environmental monitoring.
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