Rapid Multi-Sensor Fusion and Integration Using AI-enabled Machine Vision for Real-Time Operator Physiological Status

Rapid Multi-Sensor Fusion and Integration Using AI-enabled Machine Vision for Real-Time Operator Physiological Status

Real-time in-situ tracking of operator physiological status requires the integration and analysis of inputs from multiple sensors. Data formats and sample rates differ making the integration of data streams challenging. The use of external AIML Machine Vision can increase data analysis multivariate...

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Bibliographic Details
Published in:2021 IEEE Research and Applications of Photonics in Defense Conference (RAPID) pp. 1 - 2
Main Authors: Fries, David, Phillips, Jeff, McInnis, Madison, Tate, Connor
Format: Conference Proceeding
Language:English
Published: IEEE 01-08-2021
Subjects:
cockpit
Conferences
Data analysis
learning
Machine vision
Physiology
Real-time systems
Sensor fusion
Sensors
Online Access:Get full text
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Description
Summary:Real-time in-situ tracking of operator physiological status requires the integration and analysis of inputs from multiple sensors. Data formats and sample rates differ making the integration of data streams challenging. The use of external AIML Machine Vision can increase data analysis multivariate sensor fusion in such applications
DOI:10.1109/RAPID51799.2021.9521454