ML-Quadrat & DriotData: A Model-Driven Engineering Tool and a Low-Code Platform for Smart IoT Services

TL;DR

This paper introduces ML-Quadrat, a model-driven engineering tool for IoT, and DriotData, a low-code platform enabling non-experts to develop smart IoT services, with industry adoption and multiple web-based editors.

Contribution

It presents ML-Quadrat as an open-source EMF-based tool for IoT and AI integration, and introduces DriotData, a low-code platform for citizen developers to create IoT solutions.

Findings

ML-Quadrat supports heterogeneous IoT and AI technologies.

DriotData offers three web-based model editors for diverse user expertise.

The tools are adopted by industry as subscription services.

Abstract

In this paper, we present ML-Quadrat, an open-source research prototype that is based on the Eclipse Modeling Framework (EMF) and the state of the art in the literature of Model-Driven Software Engineering (MDSE) for smart Cyber-Physical Systems (CPS) and the Internet of Things (IoT). Its envisioned users are mostly software developers who might not have deep knowledge and skills in the heterogeneous IoT platforms and the diverse Artificial Intelligence (AI) technologies, specifically regarding Machine Learning (ML). ML-Quadrat is released under the terms of the Apache 2.0 license on Github. Additionally, we demonstrate an early tool prototype of DriotData, a web-based Low-Code platform targeting citizen data scientists and citizen/end-user software developers. DriotData exploits and adopts ML-Quadrat in the industry by offering an extended version of it as a subscription-based service to companies, mainly Small- and Medium-Sized Enterprises (SME). The current preliminary version of DriotData has three web-based model editors: text-based, tree-/form-based and diagram-based. The latter is designed for domain experts in the problem or use case domains (namely the IoT vertical domains) who might not have knowledge and skills in the field of IT. Finally, a short video demonstrating the tools is available on YouTube: https://youtu.be/VAuz25w0a5k