# From Things' Modeling Language (ThingML) to Things' Machine Learning (ThingML2)

arXiv: https://arxiv.org/abs/2009.10632 · HTML: https://mlsanity.com/paper/2009.10632/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Sep 2020.

## Built on by (most cited first, 8 of 8)

- [A domain-specific language for describing machine learning datasets](https://mlsanity.com/paper/2207.02848/) (2022)
- [A Model-Driven Approach to Machine Learning and Software Modeling for the IoT](https://mlsanity.com/paper/2107.02689/) (2021)
- [Supporting AI Engineering on the IoT Edge through Model-Driven TinyML](https://mlsanity.com/paper/2107.02690/) (2021)
- [ML-Quadrat & DriotData: A Model-Driven Engineering Tool and a Low-Code Platform for Smart IoT Services](https://mlsanity.com/paper/2107.02692/) (2021)
- [A Framework to Model ML Engineering Processes](https://mlsanity.com/paper/2404.18531/) (2024)
- [Towards a Domain-Specific Modelling Environment for Reinforcement Learning](https://mlsanity.com/paper/2410.09368/) (2024)
- [Data Analytics and Machine Learning Methods, Techniques and Tool for Model-Driven Engineering of Smart IoT Services](https://mlsanity.com/paper/2102.06445/) (2021)
- [MDE4QAI: Towards Model-Driven Engineering for Quantum Artificial Intelligence](https://mlsanity.com/paper/2107.06708/) (2021)

## Abstract (arXiv)

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.