Summaries - Office of Research & Innovation
Back COTS AI/ML Technology for Data Fusion and Track Management
|Division||Research & Sponsored Programs|
|Department||Naval Research Program|
Gallup, Shelley P.
Wood, Brian P.
Mun, Johnathan C.
Garza, Victor R.
MacKinnon, Douglas J.
|Sponsor||NPS Naval Research Program (Navy)|
Existing Artificial Intelligence and Machine Learning (AI/ML) technologies can automate the filtering and accuracy of multiple data streams into the Navy's Common Operating Picture/Common Tactical Picture (COP/CTP). However, this Commercial Off The Shelf (COTS) software is not being leveraged effectively by the US Navy, specifically, the Information Warfare (IW) community for data fusion in support of track data management and targeting.
Through analysis of current COTS AI/ML technologies, we will be able to posit how to optimize AI/ML software for accurate track data and disparate data source (such as GEOINT, radar data sets, and other imagery) fusion. We expect to find by completing a thorough analysis of track data and data sources input into AI/ML to fuse this informational data quickly and provide the most current/accurate intelligence. We will be able to proffer recommendations on how this all will be successfully accomplished. Additionally, the ROI of newly developed intelligence AI/ML technology (COP/CTP) will be evaluated. Once this research has been accomplished, specific improvements to various AI/ML algorithms for optimization may be examined and integration of any evaluated technology found during ROI research will be added.
|Keywords||AI/ML Artificial Intelligence Data Analysis Decision Aids Human-Machine Interaction Intelligence Fusion|
|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|