Abstract
The paper discusses the development of an algorithm for an intelligent system for monitoring the sleepiness of a crew in real time using a neural network model. The following signs of sleepiness were investigated: the frequency of yawning, the direction of gaze, the frequency and speed of blinking of the eyelids, and the duration of eye closure.
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