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• W4285193710 abstract "Interconnectivity and smart automation of Internet of Things in recent times have led to the concept of Industry 4.0. Together with the improvement in productivity and new business models, employment conditions should take advantage of these new technologies. Safety in the workplace is one of the most sensitive topics on matters that needs targeted and accurate solutions. The safety can be guaranteed by investigating the attention states of the workers, and in particular, their drowsiness levels. Several technologies have faced this problem by using biometrics, but how many of them are applicable in a real-case-use scenario of Industry 4.0? This article aims to answer this question by discussing available data and methods that can be used in specific workplaces. We highlight their limitations and accuracy to sketch out the recent literature that may contribute to worker safety in Industry 4.0. Finally, we point out a gap that needs to be filled in order to implement these strategies on a large scale." @default.
• W4285193710 created "2022-07-14" @default.
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• W4285193710 date "2022-12-01" @default.
• W4285193710 modified "2023-09-24" @default.
• W4285193710 title "Drowsiness Detection in the Era of Industry 4.0: Are We Ready?" @default.
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• W4285193710 doi "https://doi.org/10.1109/tii.2022.3173004" @default.
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