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Persistent Vigilance

Award Information
Agency: Department of Defense
Branch: Army
Contract: W15P7T-08-C-L402
Agency Tracking Number: A072-103-0933
Amount: $119,950.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A07-103
Solicitation Number: 2007.2
Timeline
Solicitation Year: 2007
Award Year: 2008
Award Start Date (Proposal Award Date): 2008-02-26
Award End Date (Contract End Date): 2009-07-20
Small Business Information
122 Fourth Avenue
Indialantic, FL 32903
United States
DUNS: 130550262
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Richard Hull
 VP, Chief Scientist
 (321) 984-3370
 rhull@modusoperandi.com
Business Contact
 Peter Dyson
Title: President/CEO
Phone: (321) 984-3370
Email: pdyson@modusoperandi.com
Research Institution
N/A
Abstract

Operation Iraqi Freedom and Operation Enduring Freedom clearly demonstrate the need for actionable intelligence within tactically useful timelines. ‘Actionable’ means contextually relevant to the mission; ‘tactically useful’ means timely intelligence supporting effective dynamic battle command. The DCGS-A Warfighter will have access to an unprecedented volume of intelligence data (13 PORs spanning seven intelligence domains). In addition, Army ISR data will be combined with joint service, coalition forces, national agency, mission and cultural context information. Modus Operandi proposes Persistent Vigilance, a predictive intelligence capability for unambiguous situational awareness based on intelligent semantic agents. Our objective is for multi-source exploitation to complement existing fusion applications creating a DCGS-A capability with the flexibility to support future military, humanitarian and peace keeping operations. Of critical importance is the ability to generate context sensitive intelligence products which do not overwhelm analysts and are capable of traveling the last tactical mile to disadvantaged users. To accomplish this objective, Modus Operandi will leverage existing technology and perform important research on increasing the velocity of intelligence cycles. Agent-based semantic reasoning over flattened networks is a key solution element. An existing information ontology solution and agent framework will provide the necessary foundation to semantically reason over appropriate corporate memory.

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

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