Technologies for environmental and agricultural monitoring are on the rise, however, there is a lack of small, low-power, and lowcost sensing devices in the industry. One of these monitoring tools is a soil moisture sensor. Soil moisture has significant effects on crop health and yield, but commercial monitors are very expensive, require manual use, or constant attention. This calls for a simple and low-cost solution based on novel technology. In this work, we introduce smol: Sensing Soil Moisture using LoRa, a low-cost system to measure soil moisture using received signal strength indicator (RSSI) and transmission power. It is compact and can be deployed in the field to collect data automatically with little manual intervention. Our design is enabled by the phenomenon that soil moisture attenuates wireless signals, so the signal strength between a transmitter-receiver pair decreases. We exploit this physical property to determine the variation in soil moisture. We designed and tested our measurement-based prototype in both indoor and outdoor environments. With proper regression calibration, we show soil moisture can be predicted using LoRa parameters.
翻译:然而,环境和农业监测技术正在上升,但该行业缺乏小型、低功率和低成本的遥感设备,其中一个监测工具是土壤湿度传感器,土壤湿度对作物健康和产量有重大影响,但商业监测器非常昂贵,需要人工使用或不断关注。这需要基于新技术的简单和低成本解决方案。在这项工作中,我们引入了Smool:使用LoRa(LoRa)测量土壤湿度的低成本系统,该系统利用收到的信号强度指标和传输能力测量土壤湿度。该系统是紧凑的,可以在很少人工干预的情况下在实地自动收集数据。我们的设计是因为土壤湿度使无线信号减弱,因此发射机-接收器两组之间的信号强度下降。我们利用这种物理特性来确定土壤湿度的变化。我们在室内和室外环境中设计并测试了我们的测量原型。通过适当的回归校准,我们可以用Lora参数预测土壤湿度。