Method of Ensuring Semantic Interoperability in the Sensor Data Processing

Introduction. Currently, the volume of sensor data from heterogeneous sources is significantly increasing. This leads to the need of improving the efficiency of sensor data management by addressing semantic interoperability. The aim of the work was to reduce the errors in interpreting sensor data by comparing and evaluating the similarity between descriptions of the parameters of measurement objects and the concepts used to describe measured quantities and units, utilizing semantic annotations. Methods. The research employs an ontological approach as its primary method. Since most sensor data pertains to the measurement of object parameters, the proposed method involves comparing and assessing the similarity of parameter descriptions based on an ontology of measured quantities, units of measurement, and sensor types. To achieve this, a semantic interoperability system is proposed for the Industrial Internet of Things (IIoT) and sensor systems. Additionally, a sequence diagram is developed to facilitate the exchange of requests and informational messages between IoT devices, the IIoT system, and the semantic interoperability system. Results. The resulting model, developed using expert knowledge, can support import substitution by enabling compatibility with new types of sensors.