Advanced Visualization and Support Environment (ADVISE)

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-09-M-6983
Agency Tracking Number: F083-024-0247
Amount: $99,920.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solicitation Year: 2008
Solicitation Topic Code: AF083-024
Solicitation Number: 2008.3
Small Business Information
625 Mount Auburn Street, Cambridge, MA, 02138
DUNS: 115243701
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Scott Potter, PhD
 Principal Scientist
 (617) 491-3474
Business Contact
 Gail Zaslow
Title: Contract Specialist
Phone: (617) 491-3474
Research Institution
An operator within the JSpOC faces a continuous and rapid flow of intelligence from disparate and distributed sensors, theatre participants, and other operators, all of which may or may not accurately reflect the current operational situation. Despite having technology that fuses these heterogeneous data sources, this abundance of information does not guarantee mission success or even improved SSA; rather it can overload JSpOC operators, resulting in confusion, poor analysis, and ineffective decision-making. To improve the accuracy, efficiency, and usefulness of these fusion algorithms employed within the JSpOC, we present our proposed effort to design and demonstrate a Framework Leveraging Operator Reasoning in Data Association and Filtering Algorithms (FLORIDA) to support improved SSA. First, we will perform a systematic evaluation of the JSpOC work domain to understand operator reasoning and decision-making requirements. Second, we will establish a meta-information ontology facilitating the augmentation of existing and future fusion algorithms with qualitative metrics. Third, we will select and augment several computation techniques currently employed within fusion algorithms. Fourth, we will design preliminary controls and visualizations that facilitate operator interaction with the FLORIDA-enhanced multi-source data fusion algorithms. Finally, we will develop and evaluate a demonstration prototype incorporating the above elements. BENEFIT: We see considerable promise in the commercial application of rapidly prototyped information and meta-information display and control techniques, specifically in the financial industry, where investment decision-making is fraught with uncertainty, and risk management is critical to investment strategy. We also see applications in commercial space asset management environments, where data quality and data recency are critical to asset protection. We also plan to transition the information and meta-information interface techniques developed with FLORIDA into the next version of our BNet® Bayesian belief network application.

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

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