AirCloud:基于云的空气质量监测系统

Yun Cheng, Xiucheng Li, Zhijun Li, Shouxu Jiang, Yilong Li, Ji Jia, Xiaofan Jiang
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引用次数: 235

摘要

我们介绍了AirCloud的设计、实现和评估——一种新颖的客户端云系统,用于低成本的普遍和个人空气质量监测。在前端,我们创建了两种与互联网连接的颗粒物(PM2:5)监测仪——AQM和miniAQM,它们具有精心设计的机械结构,以实现最佳的空气流量。在云计算方面,我们创建了一个空气质量分析引擎,它可以根据传感器数据的融合来学习和创建空气质量模型。该引擎用于实时校准AQMs和mini-AQMs,并推断PM2:5浓度。我们使用5个月的数据和2个月的连续部署来评估AirCloud,并表明AirCloud能够以比以前的解决方案低得多的成本实现良好的准确性。我们还展示了第三方开发人员在AirCloud之上构建的三个实际应用程序,以进一步展示我们系统的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AirCloud: a cloud-based air-quality monitoring system for everyone
We present the design, implementation, and evaluation of AirCloud -- a novel client-cloud system for pervasive and personal air-quality monitoring at low cost. At the frontend, we create two types of Internet-connected particulate matter (PM2:5) monitors -- AQM and miniAQM, with carefully designed mechanical structures for optimal air-flow. On the cloud-side, we create an air-quality analytics engine that learn and create models of air-quality based on a fusion of sensor data. This engine is used to calibrate AQMs and mini-AQMs in real-time, and infer PM2:5 concentrations. We evaluate AirCloud using 5 months of data and 2 month of continuous deployment, and show that AirCloud is able to achieve good accuracies at much lower cost than previous solutions. We also show three real applications built on top of AirCloud by 3rd party developers to further demonstrate the value of our system.
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