论文标题
物联网钱包：基于机器学习的传感器投资组合应用程序
IoT Wallet: Machine Learning-based Sensor Portfolio Application
论文作者
论文摘要
在本文中，提出了建筑传感器钱包的应用程序。当前，给定的系统从事物网络（TTN）云系统收集传感器数据，将数据存储到涌入数据库中，并将处理后的数据呈现给用户仪表板。基于用户的类型，可以查看数据，或者最高用户可以将传感器注册到系统中。此外，系统可以根据可以通过用户界面调整的规则来通知用户。该系统的特殊特征是机器学习服务，可以在各种情况下使用，并在整个案例研究中提供了一种新型方法，可以从给定地下Lora洛拉信标节点的信号强度估算土壤水分。
In this paper an application for building sensor wallet is presented. Currently, given system collects sensor data from The Things Network (TTN) cloud system, stores the data into the Influx database and presents the processed data to the user dashboard. Based on the type of the user, data can be viewed-only, controlled or the top user can register the sensor to the system. Moreover, the system can notify users based on the rules that can be adjusted through the user interface. The special feature of the system is the machine learning service that can be used in various scenarios and is presented throughout the case study that gives a novel approach to estimate soil moisture from the signal strength of a given underground LoRa beacon node.
