Perceptive-Cognitive User Interface for Visual Analytics Systems
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 ofdiscovering the relationships between the psychological characteristics ofthe native speakers and their verbal behavior.
visual analytics, Internet of Things, human-machine interface, ontology engineering