Dynamic user interfaces for control systems

Abstract

Control systems monitor and command other devices, systems, and software within an infrastructure. Typically, control systems employ human-in-the-loop control for critical decision making and response. These end-users require easy access to accurate, actionable and relevant data to ensure quick and effective decision making. This work presents a framework for creating dynamic visual interfaces for improved situational awareness. The proposed framework determines the relevance of available information pieces and then applies the derived relevance scores to a visualization so that the most relevant and important information are emphasized to the end-users. In the presented work, a priori expert knowledge is encoded in the system through the use of Fuzzy Logic (FL) and the resulting FL inference system assigns scores to information pieces based on system state information and user defined relevance. These scores can then be used to organize and display the relevant data given the current situation and end-user roles. The proposed FL based scoring system was implemented on a real world control system dataset and we demonstrate how the information visualization is dynamically adapted to improve situational awareness. Further, we discuss potential methods the relevance scores can be incorporated into real world visualizations to increase the situational awareness in control systems.