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Low-cost coarse airborne particulate matter sensing for indoor occupancy detection

机译:低成本的粗空气颗粒物质感测室内占用检测

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In the energy-efficient smart building, occupancy detection and localization is an area of increasing interest, as services, such as lighting and ventilation, could be targeted towards individual occupants instead of an entire room or floor. Also, an increasing quantity and diversity of environmental sensors are being added to smart buildings to ensure the quality of services provided by the building. The need for particulate matter (PM) sensors in consumer devices such as air purifiers, is an example where manufacturing advances have made the sensors much less expensive than laboratory equipment. Beyond their original intended use, air quality, they can also be used for occupancy monitoring. The work presented in this article proposes to use a low-cost (< 8 USD) PM sensor to infer the local movement of occupants in a corridor by sensing the resuspension of coarse (≥ 2.5 μm) particles. To obtain meaningful values from the inexpensive sensors, we have calibrated them against a laboratory-grade instrument. After calibration, we conducted a 7.8 hour experiment measuring coarse PM within a pedestrian corridor of a heavily-used office area. Comparing against ground truth data obtained by a camera, we show that the PM sensor readings are correlated with human activity, thus enabling statistical methods to infer one from the other.
机译:在节能智能建筑中,占用检测和定位是越来越兴趣的领域,因为照明和通风等服务可以针对各个乘员而不是整个房间或地板。此外,增加了环境传感器的数量和多样性被添加到智能建筑中,以确保建筑物提供的服务质量。在诸如空气净化器的消费设备中的颗粒物质(PM)传感器的需要是制造前进使得传感器比实验室设备便宜得多的示例。超出其原始的预期用途,空气质量,它们也可用于占用监测。本文提出的工作建议使用低成本(<8美元)PM传感器来推断走廊中乘员的局部运动,通过感测粗(≥2.5μm)颗粒的重悬浮。为了从廉价的传感器获得有意义的值,我们已经将它们校准在实验室级仪器上。校准后,我们​​进行了7.8小时的实验测量粗PM,在一个使用的办公区的行人走廊内。与摄像机获得的地面真理数据进行比较,我们表明PM传感器读数与人类活动相关,从而使统计方法能够从另一个推断出一个。

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