Diachok R. Methods and means of intellectualization of information and measurement systems with a multi-sensor configuration.

The dissertation is devoted to solving the current scientific and technical task of developing methods and means of intellectualizing information and measurement systems with a multi-sensor configuration. Substantiates the relevance of the topic of the dissertation research, formulates the purpose of the study and the scientific and technical tasks necessary for its achievement, shows the connection of the survey with scientific programs and topics, provides the scientific novelty of the obtained results, their practical value and the personal contribution of the recipient, provides information about approval of work results. Analyzes literary sources regarding modern approaches to applying methods and means of intellectualization of information and measurement systems with a multi-sensor configuration, namely their structure, architectural solutions, and server software. Also considered is the architecture of multisensory data fusion, which is one of the critical tasks in designing a multisensory system. The analysis showed that the emergence of systems with many sensors, such as the Internet of Things, could introduce novelty into this well-studied topic. This section considers three aspects of the MSDF architecture: classification, optimal selection, and standardized presentation. It presents the offered information processing tools in the researched systems, the result of which is an assessment of the state of the research. The intelligent architecture of monitoring physical objects, features of statistical processing of measurement results, methods of checking signals in information, and measurement systems are also presented. The fundamental relations for Pearson smoothing of histograms are considered. Presents the research results on improving the method of dynamic error detection in the information and measurement system, improving the technique of cleaning network data in the wireless sensor based on artificial intelligence technology in the information and measurement system. An expert real-time information and measurement system based on SCADA technology was built to control the operation of industrial facilities. Presents the research results of the data-cleaning talent management method in wireless sensor networks based on intelligence technology. Specific forms of application of wireless sensor networks are analyzed. The characteristics of the structure of wireless sensor networks are presented, and a data-cleaning technology based on the clustering model is proposed. A cluster-based replication record deletion algorithm is proposed, and the accuracy of data cleaning methods is verified. In addition, the theory of dynamic damage analysis of industrial Internet protocols and determination of the necessary data of dynamic multimodal communication of the sensor is outlined, and the method of fuzzy tests in combination with dynamic multimodal data transmission is proposed. The results of testing the process of testing information industrial protocols are presented. Presents an optimized fog-based trust method to prevent third-party interference when establishing trust relationships between sensor and cloud service providers in multi-sensor systems. Behavioral trust between nodes is established at the level of wireless sensor networks, and data trust of nodes and objects is established in the fog layer. With more detailed data analysis in the fog layer, it becomes possible to monitor the trust status of the entire network, detect data attacks, and recover from misjudged nodes. This way, the fog layer can be built as a reliable third party. The obtained result proves that our proposed trust mechanism has certain advantages in reducing energy consumption, ensuring the trust state of edge nodes and the network, detecting hidden data attacks, and recovering nodes with incorrect evaluation.