Intelligent Operating Environments for Enhancing Warfighter Performance and Health

Abstract

This project advances a unifying cyber-physical system (CPS) architecture that integrate the sensing of warfighter operational environments and data streams from wearable biometric sensors worn by warfighters. The CPS architecture provides a comprehensive approach to assessing the performance and health of warfighters in relevant Navy and Marine Corp operational applications. A key element of the proposed CPS is the integration of computer vision and deep learning methods that can track warfighters in their environments using cameras. Automated detection and classification of warfighter performance based on convolutional neural networks processing images will provide a means of spatiotemporal tracking of warfighters performance. Discrete sensor measurements from sensors embedded in the environment and biometric wearable sensors will augment the CPS architecture offering a complete view of how the operational environment influences the warfighter. Combinations of warfighter location, behavior and biometric data with environmental data will offer unprecedented insights leading to better understanding of warfighter health when operating in complex and harsh environments. The project will validate the proposed framework using lab-based experimental testing and will seek collaborations with military laboratories (USARIEM, NHRC, CCD) as additional validation partners.

Document Details

Document Type
DoD Grant Award
Publication Date
Dec 04, 2020
Source ID
N000142112033

Entities

People

  • Jerome Lynch

Organizations

  • Board of Regents of the University of Michigan
  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks
  • Cyber