TERRAIN: Temporal Exploitation and Reasoning using Resource-Activity Inference Networks

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-13-P-1065
Agency Tracking Number: O123-LD3-4037
Amount: $150,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2013
Solitcitation Year: 2012
Solitcitation Topic Code: OSD12-LD3
Solitcitation Number: 2012.3
Small Business Information
Aptima, Inc.
12 Gill Street, Suite 1400, Woburn, MA, -
Duns: 967259946
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Charlotte Shabarekh
 Senior Research Engineer
 (781) 496-2465
 cshabarekh@aptima.com
Business Contact
 Thomas McKenna
Title: Chief Financial Officer
Phone: (781) 496-2443
Email: mckenna@aptima.com
Research Institution
 Stub
Abstract
Detecting targets and predicting threat networks hidden in high volume all-source intelligence is a central challenge in the intelligence Processing, Exploitation and Dissemination (PED) cycle. Failure to maintain a common picture and shared situational awareness across disparate sensor products can result in enormous information loss, placing the entire team and intelligence community at a severe disadvantage. By improving the tasking of sensors, only the most salient intelligence will be collected, thus reducing the volume of data to be analyzed and optimizing the PED cycle. Aptima proposes to develop Temporal Exploitation and Reasoning using Resource-Activity Inference Networks (TERRAIN), an integrated system for Tasking, Collection, Processing, Exploitation and Dissemination (TC-PED). TERRAIN system will innovatively combine three critical functions in support of Marine Corps missions: active sensor stream analysis, threat situation estimation, and sensor allocation planning to produce a sensor tasking system that maximizes limited resources by identifying gaps in the current coverage and forecasting where future sensor coverage need will be greatest. Designed with Hadoop"s Map-Reduce Architecture for integration to a cloud-based computing environment, TERRAIN will be a lightweight, online system that scales to a high volume of streaming, multi-intelligence sensor feeds.

* information listed above is at the time of submission.

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