Monitoring the psychophysiological state of an ACS dispatcher based on computer vision
UDC: 004.93
DOI: -
Authors:
VOLKOV DENIS A.
1,
KONSTANTINOVA DARIA A.2
1 National University of Oil and Gas "Gubkin University", Moscow, Russia
2 Сredit bank of Moscow, Moscow, Russia
Keywords: ACS, dispatcher, physiological state, computer vision, machine learning, Eye Aspect Ratio, Python, Mediapipe, OpenCV, InfluxDB
Annotation:
The article reviews a technic for monitoring the psychophysiological state of an ACS dispatcher based on computer vision technologies, as well as an application implementing this technic. The technic is distinguished by determining the position of the head, the frequency of blinking eyes by assessing the Eye Aspect Ratio indicator and the emotional state of the dispatcher using computer vision technologies. The application is implemented in the Python programming language using the Mediapipe, Transformers, and Opencv libraries. The application allows to determine the current state of the ACS dispatcher in real time. In the application, the proposed method is implemented based on the functionality of modules for detecting head position, determining the blink rate based on the Eye Aspect Ratio indicator, and determining emotions. All metrics calculated during the application's operation are stored in the time series DBMS InfluxDB for subsequent performance analysis. The developed technic and application can be used separately or integrated into software packages for studying the reliability of automated control systems.
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