Summaries - Office of Research & Innovation
Research Summaries
Back Use AI/ML/Automation to Improve C4ISR Interoperability Mapping and testing Capabilities.
Fiscal Year | 2023 |
Division | Research & Sponsored Programs |
Department | Naval Research Program |
Investigator(s) | Das, Arijit |
Sponsor | NPS Naval Research Program (Navy) |
Summary | MCTSSA presented important ground work in their System Requirements Clustering with Machine Learning (ML) Technical Report which showcased and demonstrated that ML can be an effective means for conducting requirements analysis in support of test and evaluation (T&E) efforts. We will build upon this by reviewing and improving on the natural language processing (NLP) effort with the artifacts MCTSSA developed, and conduct research to improve existing algorithms, to effectively create test cases and documents. Maturing the artificial intelligence (AI)-backed analysis effort could streamline the effort required to analyze requirements and develop test cases. Exploring ways to improve and evolve data accessibility could allow for a more interactive dashboard available to MCTSSA leadership and test engineers. Incorporating automation as part of the source-to-destination process, this research will have a consequential impact for the fielding of C4I systems, thus supporting the warfighters (by providing interoperable working C4I systems that meet warfighter system requirements). |
Keywords | automation, mapping, requirements, command and control, c2, c4, interoperability, machine learning |
Publications | Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal |
Data | Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal |