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

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Abstract

In the paper we propose ontology based scientific visualization tools to calibrate and monitor various IoT devices in a uniform 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 diagrams defining both the behavior of the IoT devices and rendering features. 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 loading, it’s possible to connect to these devices using desktop computer or smartphone/tablet, get the visualization client code over HTTP, monitor 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 implementation of suggested approach within ontology based scientific visualization system SciVi. It was tested in a real world project of an interactive Permian Antiquities Museum exhibition creating.

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APA

Ryabinin, K., Chuprina, S., & Kolesnik, M. (2018). Calibration and Monitoring of IoT Devices by Means of Embedded Scientific Visualization Tools. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10861 LNCS, pp. 655–668). Springer Verlag. https://doi.org/10.1007/978-3-319-93701-4_52

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