SBIR/STTR Research Award

Optimizing Naval Aviation Training Through Adaptive Human Performance Modeling and AI-Driven Learning Solutions

Award identifier eaea572b632defcceff58aad9b97ffea1c489f5b11a5e54db266cb1040f7fef0Awarding agency Department of Defense · Navy

Award amount

$139,975

Program and phase

STTR · Phase I

Award year

2025

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Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
VECTRONA LLC
Proposal award date
2025-07-10
Contract end date
2026-01-20
UEI
WLQ8GB5RJJJ5
Solicitation number
25.A
Topic code
N25A-T005

Research abstract

Naval aviation demands peak human performance under extreme conditions, yet current training methodologies fail to leverage advanced insights into psychological and physiological predictors of success. Vectrona, in partnership with Old Dominion University (ODU) and Aviation Systems Engineering Company (ASEC), proposes an innovative, data-driven training framework that optimizes individual aviator performance through real-time physiological monitoring, adaptive AI/ML analytics, and personalized training interventions.Our Phase I effort will establish a validated taxonomy of traits correlated with elite performance in naval aviation, leveraging biometric data, cognitive resilience modeling, and insights from high-performance domains such as drone racing and esports. This effort will integrate cutting-edge physiological monitoring techniques—including eye-tracking and biometric analytics—to develop predictive models that enhance training effectiveness and reduce attrition. By analyzing key performance indicators and training inefficiencies, we will design a scalable, adaptable training framework tailored to individual needs.The Phase I initiative will focus on three core objectives: (1) conducting a discovery and gap analysis to identify key physiological and cognitive performance factors(2) developing a conceptual framework for an adaptive training system utilizing real-time biometric feedback(3) assessing the feasibility of integrating AI/ML-driven predictive modeling into existing naval aviation training platforms. Our approach ensures alignment with the Navy’s objectives by enabling real-time adaptation of training programs to optimize learning outcomes, enhance resilience to motion sickness, and accelerate skill acquisition.The expected outcomes of this research include a validated performance trait taxonomy, a conceptual framework for adaptive training, and feasibility assessments for system integration. This initiative will lay the foundation for a transformative approach to naval aviation training, enhancing operational readiness while significantly improving training efficiency, retention, and mission success.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

6 SBIR/STTR records share this UEI (2019–2025). Reported award amounts total $2,704,315. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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