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Innovation is the catalyst for the technology of the future. It is important to develop new and better technologies that can continuously monitor the environmental impact, e.g., for air quality control or emission detection. In the recently at BAM developed Universal Pump Sensor Control (UPSC3) module, different components and sensors are fused. The combination of the individual components makes the UPSC3 module an excellent monitoring and reference system for the development and characterization of gas specific sensors. Measurements over long periods are possible, for mixed gas loads or for certain gas measurements. The system is part of a mobile sensor network of several sensor units, which can also be used as standalone systems.
The motivation and objective of this research is to develop gas sensors based on fluorescence detection with range of ppm / ppb. For this task a reference system is required, which contains volatile organic compound (VOC) sensors for reference data from different scenarios. The integrated multi-sensor unit can measure different gases through the integrated 3-fold VOC sensor, which can be adapted to the addressed scenario. . The system-integrated flow control, with pump and flow sensor, allows the gas molecules to be transported directly to the VOC sensor. The entire measurement is permanently stored on an integrated memory card. If the previously determined limit range is exceeded, an alarm is generated. The system is an important tool towards further developments in the field of gas sensors and is primarily used for the validation of chemically based gas sensors.
In this paper, we show that a micro unmanned aerial vehicle (UAV) equipped with commercially available gas sensors can address environmental monitoring and gas source localization (GSL) tasks. To account for the challenges of gas sensing under real-world conditions, we present a probabilistic approach to GSL that is based on a particle filter (PF). Simulation and real-world experiments demonstrate the suitability of this algorithm for micro UAV platforms.
In this paper, we show that a micro unmanned aerial vehicle (UAV) equipped with commercially available gas sensors can address environmental monitoring and gas source localization (GSL) tasks. To account for the challenges of gas sensing under real-world conditions, we present a probabilistic approach for GSL that is based on a particle filter (PF). Simulation and real-world experiments demonstrate the suitability of this algorithm for micro UAV platforms.