土壤湿度传感与商品RFID系统

Ju Wang, Liqiong Chang, S. Aggarwal, Omid Salehi-Abari, Srinivasan Keshav
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引用次数: 59

摘要

基于测量温室中每个花盆土壤水分水平的智能灌溉不仅可以提高植物的生产力和质量,还可以节约用水。然而,现有的土壤湿度传感器过于昂贵,无法在每个花盆中部署。因此,我们引入了GreenTag,这是一种低成本的基于rfid的土壤湿度传感系统,其精度与昂贵的土壤湿度传感器相当。我们的关键思想是将两个RFID标签附加到植物的容器上,以便土壤含水量的变化在读取器上反映在其差分最小响应阈值(DMRT)度量中。我们表明,低通滤波DMRT度量对RF环境(例如,来自人体运动)和锅位置的变化都具有鲁棒性。在现实环境中,GreenTag实现了90%的湿度估计误差为5%,而使用昂贵的土壤湿度传感器的误差为4%。此外,尽管射频环境和容器位置发生了变化,这种精度仍然保持不变。我们还在一个真实的温室中展示了GreenTag的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Soil moisture sensing with commodity RFID systems
Intelligent irrigation based on measurements of soil moisture levels in every pot in a greenhouse can not only improve plant productivity and quality but also save water. However, existing soil moisture sensors are too expensive to deploy in every pot. We therefore introduce GreenTag, a low-cost RFID-based soil moisture sensing system whose accuracy is comparable to that of an expensive soil moisture sensor. Our key idea is to attach two RFID tags to a plant's container so that changes in soil moisture content are reflected in their Differential Minimum Response Threshold (DMRT) metric at the reader. We show that a low-pass filtered DMRT metric is robust to changes both in the RF environment (e.g., from human movement) and in pot locations. In a realistic setting, GreenTag achieves a 90-percentile moisture estimation errors of 5%, which is comparable to the 4% errors using expensive soil moisture sensors. Moreover, this accuracy is maintained despite changes in the RF environment and container locations. We also show the effectiveness of GreenTag in a real greenhouse.
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