ACA-SSURS: Aerial Cloud Analytics for Surface SUrveillance and RF Situational Awareness

Current airborne sensors produce very large volumes of data, but the airborne battle managers aboard BMC2 platforms do not have the appropriate analytics to process this massive data. Lack of appropriate analytics represents a missed opportunity to extract additional and timely actionable intelligence, especially considering the fact that, in most cases, data bandwidth to the command center is limited and traditional airborne information flow is not platform-independent or flexible enough to address dynamic mission objectives. In fact, currently data analytics engines are not available even in larger command centers to learn and determine end user format and information needs in an efficient manner. Thus, there is a critical need for innovative data analytics tools that can provide responsive information for appropriate users in time for strategic and tactical warfighters. To address this need, Intelligent Automation, Inc. (IAI) proposes to develop ACA-SSURS that can support real-time or near-real time ingestion and exploitation of large volumes of data, and optimal or quasi-optimal information flow under bandwidth limitations for rapid dissemination. In Phase I, we developed core functionalities of ACA-SSURS and successfully demonstrated its feasibility. In Phase II, we will refine the design and develop a fully functional prototype system.