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A Covid-19 viral transmission prevention system for embedded devices utilising deep learning

机译:利用深度学习的嵌入式设备COVID-19病毒传播预防系统

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摘要

The coronavirus pandemic (COVID-19) has created an urgent need for different monitoring systems to prevent viral transmission because of its severity and contagious aspect. This paper proposes design and implementation of a hardware-software solution that uses supervised machine learning algorithms to examine an individual and determine if he/she poses a viral transmission danger. The solution proposed was developed utilising an ARM embedded device along with different sensors to detect and monitor COVID-19 symptoms and, at the same time, to enforce wearing of a mask by using deep learning computer vision.
机译:由于冠状病毒大流行的严重性和传染性,迫切需要不同的监测系统来防止病毒传播。本文提出了一个软硬件解决方案的设计和实现,该方案使用有监督的机器学习算法来检查个人,并确定他/她是否构成病毒传播的危险。提出的2019冠状病毒疾病的诊断方法是利用ARM嵌入式设备和不同的传感器来检测和监测COVID-19症状,同时,通过使用深度学习计算机视觉来强制戴口罩。

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