Bridging the Gap Between AI and Reality • Rhodes, Greece
Time: Wednesday, 5.11
Room: Room B
Authors: Lennart Landt, Martin Leucker, Carsten Burchardt
Abstract: Model-Based Systems Engineering (MBSE) is increasingly adopted to manage the growing complexity of modern systems, offering a structured, collaborative design approach through modeling languages like SysML. However, its adoption remains challenging due to steep learning curves and the need for interdisciplinary coordination. This paper investigates the use of voice-enabled AI avatars to simplify MBSE interaction by allowing users to query system artifacts using natural language. By integrating a speech-based interface with AI assistants and human-like avatars representing various engineering roles, we aim to lower entry barriers, foster collaboration, and support diverse perspectives inherent in MBSE. Our proposed pipeline converts model data into a machine-readable format for large language models (LLMs) to generate contextualized, role-based responses. We explore the potential of using MBSE models as a knowledge base for AI and examine how such tools can enhance system model comprehension. Contributions include a prototype implementation, support for multi-turn interactions, and an initial evaluation of the approach.
Paper: A_Voice-Enabled_Query_Framework_for_Systems_Engineering_Artefacts-paper.pdf