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

Ryabinin, Konstantin; Чуприна, Светлана; Kolesnik, Mariia

doi:10.1007/978-3-319-93701-4_52

Cited by 10 publications

(7 citation statements)

References 9 publications

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“…The hardware part of PCI in this case is a glove-style device that detects spatial gestures by using inertial measurement unit (angular position detector) MPU6050 and programmable microcontroller ESP8266. Software part of PCI is SciVi visual analytics platform [19] that interprets the gestures and treats them as semantic filters for the data visualized as a graph. This graph demonstrates the relationships between the verbal behavior of people and their psychological characteristics revealed using machine learning methods [20][21][22].…”

Section: Perceptive-cognitive Interface Conceptmentioning

confidence: 99%

“…Traditionally, each stage of this life cycle is supported by different, often unrelated instruments. In this work we propose to utilize SciVi visual analytics platform [19] as a unified approach for PCI creation and usage. SciVi includes high-level flexible adaptation and customization mechanisms governed by ontologies.…”

Section: Testing and Debugging Of The Communication Between Pci And Amentioning

confidence: 99%

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Human-Oriented IoT-Based Interfaces for Multimodal Visual Analytics Systems

Ryabinin¹,

Белоусов²,

Чуприна³

et al. 2019

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This paper describes an approach to use modern programmable microelectronics and ontology engineering to create custom hardware human-machine interfaces for solving particular visual analytics tasks. The idea of these special interfaces is to involve additional modalities like motor or haptic into the analytics process to improve its quality and speed. We propose using tangible user interfaces built upon the Internet of Things technologies to present the visual analytics system as a cyber-physical one, melting together the real and virtual environments. To automate the creation of such an alloy we suggest a unified approach of composing the firmware for the interface hardware device and corresponding drivers for the computer; of calibration the device' sensors; of testing and debugging the communication between the interface device and the application it is supposed to steer; and of solving visual analytics tasks using the device created. All the mentioned steps are supported by the highlevel built-in mechanisms of SciVi visual analytics platform we created during the previous research and improved in the current work. Data flow diagrams are used to visually describe the data preprocessing and rendering, as well as the ways hardware interface affects them. Ontology engineering is used to ensure flexibility and extensibility of the entire platform combined with the semantic power of its individual blocks: the behavior of SciVi is fully governed by underlaying ontologies, which describe supported data formats and types, filters, rendering mechanisms, supported electronic components of the hardware interfaces, the ways to program them and to communicate with them. The proposed methods and means are tested by solving real-world visual analytics task of automated identification of the relationship between native speakers' psychological characteristics and their verbal behavior.

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Section: Perceptive-cognitive Interface Conceptmentioning

confidence: 99%

Section: Testing and Debugging Of The Communication Between Pci And Amentioning

confidence: 99%

Human-Oriented IoT-Based Interfaces for Multimodal Visual Analytics Systems

Ryabinin¹,

Белоусов²,

Чуприна³

et al. 2019

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“…Аппаратной частью PCI при решении данной задачи выступает перчатка-манипулятор, детектирующая пространственные жесты человека при помощи электронного гиростабилизатора (датчика пространственной ориентации) MPU6050 и программируемого мик-роконтроллера ESP8266. Программной частью выступает система визуальной аналитики SciVi [16], распознающая жесты и использующая их в качестве семантических фильтров для визуального анализа графа, демонстрирующего выявленные с использованием методов машинного обучения взаимосвязи между языковым поведением людей и их психологическими характеристиками [13,22,23].…”

Section: концепция перцептивно-когнитивного интерфейсаunclassified

“…Традиционно для каждого этапа используются отдельные, зачастую не связанные между собой инструменты. В рамках данной работы мы предлагаем унифицированный подход к созданию и использованию PCI с применением легко адаптируемых к специфике решаемой задачи методов и средств системы визуальной аналитики SciVi [16]. SciVi включает в себя онтологически управляемые высокоуровневые механизмы настройки как на различные источники данных, так и на средства генерации прошивок для легковесных электронных устройств разного типа, а также на способы декларирования алгоритмов фильтрации и визуализации данных.…”

Section: перцептивно-когнитивный интерфейс в системе визуальной аналиunclassified

“…Этапы проектирования и сборки аппаратной части PCI на данный момент не имеют средств высокоуровневой автоматизации, хотя входящая в состав SciVi онтология электронных компонентов [16] выполняет, среди прочего, и рекомендательную функцию, так как содержит описание разнообразных микроконтроллеров, сенсоров, актуаторов и коммутационных компонентов, а также способов их взаимодействия.…”

Section: перцептивно-когнитивный интерфейс в системе визуальной аналиunclassified

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Perceptive-Cognitive User Interface for Visual Analytics Systems

Рябинин¹,

Ryabinin²,

Белоусов³

et al. 2019

GraphiCon'2019 Proceedings. Volume 1

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The paper is devoted to using Internet of Things technologies for hardware human-machine interfaces development. Thanks to these technologies, it may be possible to improve the capabilities of visual analytics systems with multiple modalities: movements, audio, etc. It can speed up semantic data filtering and interpretation, increasing the efficiency of analytics. We suggest using ontology engineering methods and tools to automate both the programming of custom hardware human-machine interfaces and connecting them to the third-party software. The proposed concept is tested by solving the real-world tasks of discovering the relationships between the psychological characteristics of the native speakers and their verbal behavior.

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