Ontology-based neurointerface IoT integration approach

Recently, there is a surge of interest in employing neurocomputer interfaces for a control contours implementation, especially for different infrastructures of Internet of Things. However, due to a low-level nature of such devices and related software tools, neurointerface integration with a large variety of IoT devices is quite a tedious task, and the one that requires a lot of knowledge in the neuroscience and signal processing to boot. In the paper, we propose an ontology-driven solution for facing the upcoming challenges of unified integration of brain-computer interfaces into IoT ecosystems. We demonstrate an adaptable mechanism for integrating brain-computer interfaces into the Internet of Things infrastructure by introducing an intermediate layer – a smart mediator that will be responsible for communication between the environment and the neurointerface. The mediator’s software is generated automatically, and this process is driven by a managing ontology. The proposed formal model and the system's implementation are described. The approach we have developed enables researchers and engineers without strong background in brain–computer interface to automate the integration neurointerfaces with different infrastructures of Internet of Things.