论文标题
从事物的建模语言（thingml）到事物的机器学习（thingml2）
From Things' Modeling Language (ThingML) to Things' Machine Learning (ThingML2)
论文作者
论文摘要
在本文中，我们说明了如何增强物联网的现有最新建模语言和工具（IoT），称为ThingMl，以支持建模级别的机器学习。为此，我们扩展了ThingMl的特定领域特定语言（DSL）及其代码生成框架。我们的DSL允许人们定义可以执行数据分析的事物。此外，我们的代码生成器可以自动在Java和Python中生成完整的实现。生成的Python代码负责数据分析，并采用机器学习库的API，例如Keras，Tensorflow和Scikit Learn。我们的原型可作为GitHub上的开源软件提供。
In this paper, we illustrate how to enhance an existing state-of-the-art modeling language and tool for the Internet of Things (IoT), called ThingML, to support machine learning on the modeling level. To this aim, we extend the Domain-Specific Language (DSL) of ThingML, as well as its code generation framework. Our DSL allows one to define things, which are in charge of carrying out data analytics. Further, our code generators can automatically produce the complete implementation in Java and Python. The generated Python code is responsible for data analytics and employs APIs of machine learning libraries, such as Keras, Tensorflow and Scikit Learn. Our prototype is available as open source software on Github.
