9 January 2024 11:00 a.m. Senate Room, RV University, Bengaluru
Dr. Kavitha Chandra
Abstract
Modelling from the perspectives of software engineering and systems engineering has co-evolved over the last two decades as orthogonal approaches. Given the central role of software in modern cyber-physical systems and the increasing adoption of digital engineering practices, a critical need is a structure and process for collaborative design among system users, software developers, and systems engineers. Model-based systems engineering (MBSE) and systems modelling languages enable seamless cross-domain connectivity for design, simulation, and analysis of emerging technologies such as Augmented Reality (AR). This presentation discusses a co-design process referred to as a No-Code AR Systems (NCARS) framework for extending the capability of an existing AR application. NCARS enables content developed by multi-domain authors to be deployed on AR devices through a software layer that bridges the content to the game engine that drives the AR system. A model-based representation of the NCARS system is presented using the systems modelling language SysML and MBSE design principles. We discuss extending this baseline model to include the structure and behaviour of software components that support basic AR functions such as Annotation and task Navigation. The application of such model-based representation for extending the capability of the AR system with user-defined requirements is presented. The talk will also briefly discuss the design and content of a 12-credit graduate certificate on Digital Engineering that was recently offered to a group of students from the US Air Force civilian workforce to provide skills to support their Digital Transformation initiative.
Acknowledgements
This research was conducted in collaboration with researchers at Univ. of Akron (Prof. Shiva Sastry), Dassault Systemes (Dr. Bach Tran) and graduate students Emi Aoki, Flore Norceide and Vinh Tran at the University of Massachusetts Lowell. The authors acknowledge support from the National Science Foundation Future of Work at the Human Technology Frontier program under Grant Nos. #2128749 and #2128950 and the National Science Foundation Innovations in Graduate Education in Cyber-Physical Systems Engineering under Grant No. #2105701.