基于lorawan的物联网空气质量传感器网络的公共利益部署

J. M. Howerton, Benjamin Leo Schenck
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引用次数: 4

摘要

该项目的目标是在夏洛茨维尔实施基于lorawan的空气质量传感器网络,并利用其数据生成COVID-19爆发之前和期间的空气质量比较空间模型。该网络的实施需要向遍布全市的志愿者分发“物联网”(TTN) LoRa网关和我们自己定制的传感器套件。我们的传感器套件可测量温度,湿度,二氧化碳和颗粒物(PM) 2.5和10,使我们能够根据EPA的空气质量指数进行测量,并跟上现代研究趋势,显示二氧化碳作为空气质量指标的重要性。初步空间分析比较了2020年3月11日(UVA宣布所有班级都将在线上课)前后的空气质量,结果显示,二氧化碳水平几乎普遍下降,但颗粒物质的变化尚无定论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Deployment of a LoRaWAN-Based IoT Air Quality Sensor Network for Public Good
The goals of this project are to implement a LoRaWAN-based network of air quality sensors in Charlottesville and to use its data to generate a comparative spatial model of air quality before and during the COVID-19 outbreak. The implementation of this network required the distribution of “The Things Network” (TTN) LoRa gateways and our own custom-made sensor kits to volunteers distributed throughout the city. Our sensor kits measure temperature, humidity, CO2, and Particulate Matter (PM) 2.5 and 10, allowing us to take measurements in line with the EPA’s air quality index as well as to keep up with modern trends in research showing the importance of CO2 as an air quality metric. Preliminary spatial analysis comparing air quality before and after March 11, 2020, the day that UVA announced all classes would move online, shows a near universal decline in carbon dioxide levels, but inconclusive changes in particulate matter.
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