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- W4285325993 abstract "Avoiding accidents at work has been a major concern for companies for years. Their impacts, such as financial, image, reputation, and human losses, are less tolerated world-wide. Traffic accidents in motor vehicles correspond to many accidents at work and can be caused by several factors. One of the main factors recurrently associated with accidents is when the driver sleeps. When sleeping, the driver completely loses control over the vehicle's actions, which can cause serious accidents. One of the approaches to prevent the driver from falling asleep is to predict the state of sleep (drowsiness). There are several ways to drowsiness detection, such as physiological data readings, driver's images, and blink frequency. There is no international standard on this topic or standout technology, so choosing the right market solution is problematic. This study analyzes these solutions, proposes selection criteria with functional and non-functional requirements, evaluates meaningful market solutions based on these criteria, and offers recommendations for deployment following the best technological practices." @default.
- W4285325993 created "2022-07-14" @default.
- W4285325993 creator A5063942179 @default.
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- W4285325993 date "2021-12-01" @default.
- W4285325993 modified "2023-10-16" @default.
- W4285325993 title "Drowsiness Detection Systems: Comparison and Technical Criteria for Industrial Deployment" @default.
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- W4285325993 doi "https://doi.org/10.1109/csci54926.2021.00347" @default.
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