A Method for Designing a Heterogeneous Network of a Monitoring System Based on Predictive Modeling of the Functioning Processes of its Subsystems

The article discusses an approach to decomposing a spatially distributed monitoring system (MS) into hierarchical levels. An original method for parameterizing the MS model for subsequent use in machine learning is presented. The possibility of using neural network technologies for data processing and the formation of a hierarchical dependence of parameters within the subsystems of the monitoring system, which allows solving the problem of designing its heterogeneous data transmission network based on specified requirements, has been demonstrated. The use of physical-informed machine learning (PIML) is proposed as a method for increasing the accuracy of the neural network by taking into account physical processes. A MS decomposition scheme based on physical equations is presented.