Fatigue detection using artificial intelligence
Over the years the development of computer technology has benefited drivers, often in the form of smart systems. In a significant number of car collisions, tiredness is a major factor. Road collisions are the world's most frequent types of injuries and fatalities, and the main causes are typica...
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| creator | Kshirsagar, Pravin R. Dadheech, Pankaj Yuvaraj, T. Moorthy, C. A. Sathiya Upadhyaya, Makarand |
| description | Over the years the development of computer technology has benefited drivers, often in the form of smart systems. In a significant number of car collisions, tiredness is a major factor. Road collisions are the world's most frequent types of injuries and fatalities, and the main causes are typically drunken, sleepy, and rudely behavioral. The main purpose of this article is to define common sources of knowledge for the detection of drowsiness to evaluate when a specified degree of drowsiness is achieved. Fatigue was one of the key techniques for detecting or tracking augmented reality. In particular, driver drowsiness identification can protect riders from drowsy riding collisions. This technology relies on face detection to warn the driver of somnolence or to avoid accidents in traffic. |
| doi_str_mv | 10.1063/5.0074121 |
| format | Conference Proceeding |
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| fulltext | fulltext |
| identifier | ISSN: 0094-243X |
| ispartof | AIP conference proceedings, 2022, Vol.2393 (1) |
| issn | 0094-243X 1551-7616 |
| language | eng |
| recordid | cdi_proquest_journals_2666681465 |
| source | AIP Journals Complete |
| subjects | Artificial intelligence Augmented reality Collisions Driver fatigue Face recognition Sleepiness |
| title | Fatigue detection using artificial intelligence |
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