Open AccessReal-time fatigue features detection
Author(s) -
A. I. Gaidar,
Pavel Yakimov
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1368/5/052017
Subject(s) - mental fatigue , task (project management) , control (management) , state (computer science) , computer science , engineering , psychology , applied psychology , artificial intelligence , systems engineering , algorithm
Fatigue detection is a very important goal because often tired people lose control of a certain task. So the driver falls asleep during a long trip. Driver’s state is very important because one of the main reasons for motor vehicular accidents is related to driver’s fatigue. To prevent accidents a driver fatigue monitoring and control system that works in real time is required. The main purpose of this study to build a base for developing the drowsiness control system. The article presents drowsiness features study, such as the closed eye, the yawn are required for building the system.