USA flag logo/image

An Official Website of the United States Government

Situational Awareness as a Man-Machine Map Reduce Job

Award Information

Agency:
Department of Defense
Branch:
Navy
Award ID:
Program Year/Program:
2013 / STTR
Agency Tracking Number:
N13A-024-0113
Solicitation Year:
2013
Solicitation Topic Code:
N13A-T024
Solicitation Number:
2013.A
Small Business Information
Soar Technology, Inc.
3600 Green Court Suite 600 Ann Arbor, MI -
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2013
Title: Situational Awareness as a Man-Machine Map Reduce Job
Agency / Branch: DOD / NAVY
Contract: N00014-13-P-1179
Award Amount: $79,774.00
 

Abstract:

Improving situational awareness and accuracy of decisions in complex missions relying on streaming open-source data requires scalable information extraction and fusion in collaboration between Man and Machine reasoning. SoarTech, with its proven track-record of basic and applied research and transition into actual deployment, will bring forward advanced imagery and text processing technology integrated in a Hadoop-based distribution framework from its academic partners CUBRC and Dr. Corso from the University of Buffalo. The resulting stream of entity and behavior recognition events from large-scale unstructured and uncalibrated raw data from many sources is fused with a continuously adapting agent simulation and extended into probabilistic predictions of alternative futures. Human intelligence and knowledge is effectively integrated throughout the recognition-fusion-prediction process through a task-aware collaboration environment. As equal participants in the ongoing information-fusion process, decision-makers gain a deeper understanding of the current scenario and the impact of decision alternatives, and thus arrive at better decisions. Our proposed objectives for Phase-I include the demonstration of the feasibility of recognition of HADR-mission-relevant entities and behaviors and the feasibility of such recognition and the subsequent fusion/prediction at scale. We also propose to develop initial use-cases, identify target transition partners, and draft key component and system architecture designs.

Principal Investigator:

Sven Brueckner
Lead Researcher
(734) 887-7642
sven.brueckner@soartech.com

Business Contact:

Andrew Dallas
Vice President
(734) 887-7603
contracts@soartech.com
Small Business Information at Submission:

Soar Technology, Inc.
3600 Green Court Suite 600 Ann Arbor, MI -

EIN/Tax ID: 383382261
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Research Institution Information:
CUBRC
4455 Genessee Street
Buffalo, NY 14225-
Contact: Adam Stotz
Contact Phone: (716) 204-5123