论文标题
Aquamoho：局部低成本的户外空气质量在热毛机上传感
AQuaMoHo: Localized Low-Cost Outdoor Air Quality Sensing over a Thermo-Hygrometer
论文作者
论文摘要
有效的空气质量传感是最近任何智能城市提供的基本服务之一。大多数由难以安装和维护的稀疏部署空气质量监测站（AQMS）促进的，整体空间变化严重影响了与这些前部署的公共基础设施相距足够远的空气质量监测。为了减轻这种情况，我们在本文中提出了一个名为Aquamoho的框架，该框架可以通过AQI标签从低成本的热杂项（作为唯一的物理传感设备）获得的数据进行注释，并借助额外的公开爬行的该局部性的公开爬行的时空信息。 Aquamoho以基于LSTM的模型从一组随时可用的空间特征中利用了时间模式，并进一步使用时间关注进一步提高了注释的总体质量。从对两个不同城市的彻底研究中，我们观察到Aquamoho可以大大帮助以个人规模注释空气质量数据。
Efficient air quality sensing serves as one of the essential services provided in any recent smart city. Mostly facilitated by sparsely deployed Air Quality Monitoring Stations (AQMSs) that are difficult to install and maintain, the overall spatial variation heavily impacts air quality monitoring for locations far enough from these pre-deployed public infrastructures. To mitigate this, we in this paper propose a framework named AQuaMoHo that can annotate data obtained from a low-cost thermo-hygrometer (as the sole physical sensing device) with the AQI labels, with the help of additional publicly crawled Spatio-temporal information of that locality. At its core, AQuaMoHo exploits the temporal patterns from a set of readily available spatial features using an LSTM-based model and further enhances the overall quality of the annotation using temporal attention. From a thorough study of two different cities, we observe that AQuaMoHo can significantly help annotate the air quality data on a personal scale.
