Automated Human and System Performance Assessment in Operational Environments

Period of Performance: 03/27/2013 - 10/20/2013

$377K

Phase 2 STTR

Recipient Firm

Advanced Anti-terror Technologies Corp.
13900 CR 455 Unit 107 #306
Clermont, FL 34711
Principal Investigator
Firm POC

Research Institution

Old Dominion University
IA Div. Human Factors & Erg MGB 346X
Nolfolk, VA 23529
Institution POC

Abstract

Our Fused-Realities-Assessments-Modules(FRAM) enables innovative new levels and types of automated quantification strategies for combining human and system performance in real-time for fused performance monitoring and after-action-review purposes. FRAM accomplishes this by fusing output of normative models of behaviors (cognitive/procedural/team), human states (physiological/affective), system states (simulation models and/or operational vehicle states), and contextual situation states (live/virtual/constructive/serious-game scripts/scenarios). Innovatively all of the monitored states data streams can be visualized and analyzed separately, and/or grouped and customized for specific assessments. Our scientific combined model is technologically implemented on Commercial-Off-The-Shelf (COTS) laptops/tablets with inexpensive COTS sensors, along with innovative translation and interface software modules between the operator controller interface and the virtual simulation environment (or operational system). FRAM s modular architecture enables technological customizations as an add-on self-contained deployable suite to existing simulations, serious-games, and operational systems. FRAM transition priorities include automated combined human and UxV system interfaces performance assessments capacities added onto existing popular open-source advanced simulations enables objective assessments for best-of-breed interface selections, along with future evolutions of the UxV operator controller interfaces. After ensuring the validity of our combined model assessment science in militarily relevant scenarios, we envision supporting parallel evolutions of standards and associated human training for all UxV interfaces.