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J-MOC: Joint Measurement Operations Controller

Award Information
Agency: Department of Defense
Branch: Army
Contract: W91WAW-07-C-0011
Agency Tracking Number: A2-2757
Amount: $970,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: OSD05-CR3
Solicitation Number: 2005.3
Timeline
Solicitation Year: 2005
Award Year: 2007
Award Start Date (Proposal Award Date): 2007-03-08
Award End Date (Contract End Date): 2010-01-31
Small Business Information
12 Gill Street Suite 1400
Woburn, MA -
United States
DUNS: 967259946
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Nathan Bailey
 Human Factors Scientist
 (202) 842-1548
 nbailey@aptima.com
Business Contact
 Margaret Clancy
Title: Chief Financial Officer
Phone: (781) 496-2415
Email: clancy@aptima.com
Research Institution
N/A
Abstract

With an increasing focus on Joint operations, current military training exercises are becoming more complex, relying on live, virtual, and constructive (LVC) environments. Currently, performance measurement, assessment, and feedback for JTF trainees in Joint training exercises focuses on observations made by Observer/Trainers (O/Ts) during exercises. However, observer-based data collection presents several challenges to O/Ts. Using current paper and pencil methods, it is exceedingly difficult to collect and organize observations efficiently, to correlate and fuse observations in accordance with training requirements, and to use synthesized data to produce coherent AAR and exercise products. Moreover, given the complexity and volume of system data, sheer number of systems and observers involved, and distributed nature of LVC events, it is often difficult to establish the exercise context under which observations are collected. To address these challenges, we propose to develop the Joint Measurement Operations Controller (JMOC). JMOC will include components that 1) facilitate the collection and fusion of data across O/Ts during Joint LVC events, 2) fuse those data in ways that support the development of effective trainee feedback and exercise summary products to support learning, and 3) integrate observer-based and system-based data to provide a more comprehensive picture of training outcomes and effectiveness.

* Information listed above is at the time of submission. *

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