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Calibration and Monitoring of IoT Devices by Means of Embedded Scientific Visualization Tools

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Authors: Shi Yong / Fu Haohuan / Tian Yingjie / Krzhizhanovskaya Valeria V. / Lees Michael Harold / Dongarra Jack / Sloot Peter M. A. / Ryabinin Konstantin / Chuprina Svetlana / Kolesnik Mariia

Extracted Abstract:

.In the paper we propose ontology based scientific visual- ization tools to calibrate and monitor various IoT devices in a uni- form way. We suggest using ontologies to describe associated controllers, chips, sensors and related data filters, visual objects and graphical scenes to provide self-service solutions for IoT developers and device makers. High-level interface of these solutions enables composing data flow dia- grams defining both the behavior of the IoT devices and rendering fea- tures. According to the data flow diagrams and the set of ontologies the firmware for IoT devices is automatically generated incorporating both the data visualization and device behavior code. After the firmware load- ing, it’s possible to connect to these devices using desktop computer or smartphone/tablet, get the visualization client code over HTTP, mon- itor the data and calibrate the devices taking into account monitoring results. To monitor the distributed IoT networks a new visualization model based on circle graph is presented. We demonstrate the imple- mentation of suggested approach within ontology based scientific visual- ization system SciVi. It was tested in a real world project of an interactive Permian Antiquities Museum exhibition creating. Keywords:IoT devices ·Scientific visualization tools Ontology engineering ·Data flow diagrams Firmware source code generation 1

Level 1: Include/Exclude

  • Papers must discuss situated information visualization* (by Willet et al.) in the application domain of CH.
    *A situated data representation is a data representation whose physical presentation is located close to the data’s physical referent(s).
    *A situated visualization is a situated data representation for which the presentation is purely visual – and is typically displayed on a screen.
  • Representation must include abstract data (e.g., metadata).
  • Papers focused solely on digital reconstruction without information visualization aspects are excluded.
  • Posters and workshop papers are excluded to focus on mature research contributions.
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