Summaries - Research
Back Big Data ML and AI for Combat ID and Combat Systems – Design, Demonstrate and Proof of Concept
|Division||Research & Sponsored Programs|
|Department||Naval Research Program|
Boger, Dan C.
|Sponsor||NPS Naval Research Program (Navy)|
|Summary||According to the topic description, the heterogeneous nature of tactical data supplemented by National Technical Means requires that non-linear relationships between data elements in the Data Lake be identified. Machine Learning (ML) and Artificial Intelligence (AI) are emerging technologies that may address Common Tactical Pictures (CTP) and Combat Identification (CID) challenges. Related Deep Analytics including ML and AI that apply unsupervised learning, self-taught learning, deep learning, pattern recognition, anomaly detection, and data fusion. Big Data, Deep Analytics and AI/ML are critical to design futuristic combat systems such as adaptive, cooperative and learning combat systems along with authoritative data sources, standards and interoperability from sensors, platforms, and weapons for mission requirements, it is also imperative to test and adapt commercially available tools to meet the ongoing needs and requirements for military requirements. This proposal seeks to work with the industry / academia to build proof of concepts and demonstrations to apply commercial AI/MI tools to the CID and Combat Systems applications. The goal is to demonstrate a logical, incremental introduction of the technologies into CID, Common Tactical Pictures and combat systems.|
|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|