Interaction and feedback loops in user interface for digital engineering design

Анотація

Digital engineering design relies on interaction and feedback loops to support user engagement and improve workflows. Interaction in user interfaces (UI) allows designers to adapt interfaces to user and context requirements, analyze system data, and provide visible feedback. This approach fosters an immersive and responsive design environment, especially in industrial use cases. Feedback loops, visual, auditory, or haptic, provide insights into system behavior, potential errors, and impact of design adjustments. User-system interaction is studied using various methods, including real-time observation, system logs or analytics tracking, and developing user thought process models. These methods focus on context-rich data from real-world settings, allowing for iterative improvements and refinements in user-centered design. Interaction systems are not limited to a single input or output device but often provide multiple ways of interaction or manipulation. 

Standard components in innovative system interactions include sensors for data collection, actuators for response execution, processing units for data analysis, communication modules for connectivity, and user interfaces for seamless interaction. The interaction design process includes software in the preliminary stages, hardware and digital devices, and a CPU or other smart-emended device. The user-to-system interaction process involves input, processing, and output. The user inputs through devices like keyboards, touchscreens, or sensors. The system interprets this input, processes it using algorithms, and determinesan appropriate response. After processing, the system provides the user output. Feedback is then provided, completing the loop and enabling further interaction. This iterative process fosters effective communication between the user and the system. In industrial applications, this process occurs within device limitations and context. The application layer, chatbot system layer, and LLM models layer are three stages of user interaction activity classification in intelligent systems. The application layer provides user-facing interfaces, while the chatbot system layer facilitates interaction with the system's logic. The LLM layer enhances interaction quality and system intelligence by processing user input and generating relevant responses.