IIoT Laboratory Model for Remote Control System Applications

This paper describes how the Industrial Internet of Things (IIoT) technology can be used to build an efficient laboratory learning model of a remote and distributed control system. We describe the development of simple Internet of Things (IoT) devices for industrial application of online process measurements. Our experiences are presented with implementation of the IIoT data concentrator based on different hardware platforms. The data are transferred to the cloud system, where the application of fault detection and analysis was realized and visualized by free web technologies. A Fault Detection and Isolation (FDI) application was developed for a laboratory model of connected hydraulic tanks, by implementing the data driven Principal Component Analysis (PCA) method with partial models for isolation purposes.