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Anomalous Data Onboard Identification System (ADONIS)

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8649-20-P-0815
Agency Tracking Number: FX201-CSO1-0326
Amount: $49,998.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: J201-CSO1
Solicitation Number: X20.1
Solicitation Year: 2020
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-03-09
Award End Date (Contract End Date): 2020-06-09
Small Business Information
5717 Huberville Avenue Suite 300
Dayton, OH 45431-1111
United States
DUNS: 002231525
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Stephen Rosencrantz
 (937) 252-2710
Business Contact
 Daniel C. Cyphers
Phone: (937) 252-2710
Research Institution

Analysts are faced with significant increases in the amount and complexity of data as sensor and imaging technologies decrease in size and expense, increase in capability, and are employed on an increasingly broad range of platforms. Managing the amount and technical complexity of data is a challenge for even trained and experienced crews. In addition, large numbers of small Unmanned Aerial Systems (sUAS), and associated sensors, are being rapidly developed and deployed, further increasing the amount of data that needs exploited. Skyward proposes to develop a novel capability to determine, assess, categorize, and counter ground threats via anomaly detection which will reduce data processing times and increase analytical focus.  The Anomaly Detection Onboard Identification System (ADONIS) will implement uniquely developed algorithms and miniaturized hardware to quickly and autonomously process real-time sensor data onboard UAS platforms. Processed data will result in tips and cues to be disseminated from aircraft to the ground. These tips and cues will indicate the presence of potential anomalies within large volumes of data, so analysts can focus on the most actionable information first.  Our solution builds on several proven commercial technologies and is adaptable to most DoD and commercial sUAS-based sensors (e.g., LIDAR, SAR, EO/IR, Hyperspectral).  Artificial Intelligence (AI) or statistical averaging algorithms will be developed and demonstrated using existing government/commercial software and deployed to lightweight, commercial AI acceleration hardware for use on sUAS platforms.  ADONIS will demonstrate the capability to more rapidly and efficiently assess threats, thereby increasing resiliency and security for Future Bases, Installations and Airmen, and substantially reducing O&M costs.

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

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