Robust Environmental Sensing Using UAVs
Robust Environmental Sensing Using UAVs
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DOI：
10.1145/3464943
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发表时间：
2021-07
期刊：
影响因子：
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通讯作者：
Ahmed Boubrima;E. Knightly
中科院分区：
文献类型：
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作者：
Ahmed Boubrima;E. Knightly
在本文中，我们首先研究了空气污染测量的质量，并表征了无人机安装的气体传感器的主要误差源，我们构建了Astro+，这是一个空中污染平台，并使用它来收集综合的数据集。然后，在本文的第二部分中，气体传感器的质量利用了天气条件对污染测量的质量，以设计无人驾驶飞机任务计划算法，即使我们在高空污染的质量中，也可以根据自己的高度污染，从而适应无人机的轨迹。污染动力很高。
In this article, we first investigate the quality of aerial air pollution measurements and characterize the main error sources of drone-mounted gas sensors. To that end, we build ASTRO+, an aerial-ground pollution monitoring platform, and use it to collect a comprehensive dataset of both aerial and reference air pollution measurements. We show that the dynamic airflow caused by drones affects temperature and humidity levels of the ambient air, which then affect the measurement quality of gas sensors. Then, in the second part of this article, we leverage the effects of weather conditions on pollution measurements’ quality in order to design an unmanned aerial vehicle mission planning algorithm that adapts the trajectory of the drones while taking into account the quality of aerial measurements. We evaluate our mission planning approach based on a Volatile Organic Compound pollution dataset and show a high-performance improvement that is maintained even when pollution dynamics are high.