A Domain-Specific Language and Model-Based Engine for Implementing IoT Dashboard Web Applications

The Internet of Things (IoT) has become one of the fundamental pillars of the digital transformation of society, with favorable impacts on people’s quality of life. Furthermore, IoT systems generate large volumes of data at very high speeds, which come from diverse sources (heterogeneous sensors), requiring the permanent adaptation of the content and the way of presenting the information to the user; hence, a low-level implementation approach becomes unproductive. In this context, Model-Driven Engineering (MDE) has proven to be an appropriate software development approach to cope with the complexity and evolution of IoT systems. However, there are few proposals for Domain-Specific Languages (DSLs) aimed at building dashboards that synthesize the metrics and fundamental monitoring data of an IoT system. Therefore, this paper proposes a DSL and a model-based transformation engine to design and automatically implement IoT dashboard visualization web applications that combine pages, panels, charts, grids, data filters, hyperlinks, and labels with warnings and prescriptive recommendations. In addition, the proposed solution abstracts implementation details from heterogeneous data sources (physical and virtual sensors), making them transparent to domain experts. The empirical evaluation of the solution through a quasi-experiment based on the Method Evaluation Model (MEM) showed that the participants perceived the solution as useful and easy to use, so they would be willing to use it in the future.