Towards Information Flows in Recognition and Prediction Tasks with Internet of Things

Abstract

This paper describes the possibilities of communication through information flows in the tasks of recognition and prediction using the example of assessing the change in the state of defects in materials. In the context of communication between several system elements, an important part is the formation of adequate information flows and optimal messages. In this context, the grouping of information according to the principle of informativeness is proposed, using the example of the problem of recognition and further forecasting. Information transfer with the Internet of Things involves exchange over wireless networks and network protocols. In the paper, it is proposed to use the segmented area of the recognised object to check the forecast. The paper proposes to use the segmented region of the recognised object in the image and use it to check the prediction. In addition, sensor data can be utilised to test defect classification. This design of information flows can improve performance.