Enhanced/Operator Machine Interface

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$70,000.00
Award Year:
1997
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Award Id:
36928
Agency Tracking Number:
36928
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
12450 Fair Lakes Circle, Fairfax, VA, 22033
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
James J. Curcio
(703) 263-2800
Business Contact:
() -
Research Institute:
n/a
Abstract
The sensor processing requirements needed to counter today's threats pose a major challenge to the air avionics sensor operator (SENSO) due both to the complexity of the sensors and task load increases. Today's SENSO has limited opportunity for realistic anti-submarine warfare (ASW) practice and experience. In environments where experienced mentors are available, new operators are assisted while they gain the experience they need. The SENSO operating environment in the helicopter requires additional independence and more rapid decision making. This motivates a need for a flexible SENSO Operator Machine Interface (OMI) matched to individual operator capabilities. A flexible OMI can assist the SENSO in making rapid, appropriate, real time decisions for detection, contact evaluation, tracking, localization, and operational mode. Digital System Resources Inc., in association with Dr. Kent Williams, has conducted research in the use of embedded training systems with state-of-the-art training technologies and commercial off-the-shelf (COTS) hardware in a rapid prototyping software development environment. A key result was the use of cognitive modeling techniques to diagnose the skill and knowledge level of individual users with an Integrated Training System (ITS). This diagnostic procedure identifies weaknesses in user task knowledge which then serve as a source of information from which adaptations to the user interface are made. The result is an Adaptive OMI. The Adaptive OMI concept is designed to enhance the performance of the inexperienced SENSO by adaptively enhancing the OMI to match his demonstrated skills.

* information listed above is at the time of submission.

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