AI for System Engineering

Effort to support a phased approach to integrate AI into the system engineering process, leveraging existing resources ARCIT and SETIT, and emerging Model Based Systems Engineering MBSE.
Develop and pilot AI tools to assist in the analysis of ITS project requirements. This will involve using Natural Language Processing NLP to parse, categorize, and identify potential conflicts or ambiguities in text based requirements documents. Use machine learning to analyze historical ITS project data e.g., budgets, timelines, change orders, reported issues to predict potential risks and identify early warning signs of project failure. Develop AI agents that can assist systems architects in generating and evaluating system architectures. This will involve integrating AI into MBSE tools that use languages like SysML. Utilize AI to automate significant portions of the VVT process, which is often time consuming and manual. Research and develop AI systems that can monitor the performance of an operational ITS and recommend or even implement minor architectural or operational changes to improve efficiency or resilience.