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A Wearable Warning System Design for Mask Recognition via AR Smart Glasses
19th IEEE International Conference on Dependable, Autonomic and Secure Computing, 19th IEEE International Conference on Pervasive Intelligence and Computing, 7th IEEE International Conference on Cloud and Big Data Computing and 2021 International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2021 ; : 896-900, 2021.
Article in English | Scopus | ID: covidwho-1788647
ABSTRACT
Under the influence of COVID-19, various studies have shown that the most important transmission of the epidemic is droplet infection, it is the most effective way to control the epidemic by wearing a mask in a safe range. To confirm the situation of masks-wearing in public, a useful way is to use image-recognition technology to detect the people in the field. On the other hand, with the continued development of wearable devices, smart glasses have been widely used in many files such as handicapped person support. Based on the previous researches, it is already possible to incorporate facial recognition technology into smart glasses. Especially, the application of Augmented Reality (AR) technology on smart glasses can provide users with a lot of additional information, for example, to highlight the targets who been identified. Therefore, to identify the people who are not wearing masks more effectively, in this paper we try to design and wearable mask recognition warning system by using the AR smart glasses. The system can supply the warning messages about the person without masks in both visual and auditory way to the user to support the users including the handicapped persons who not being able to hear or see. The results of this study may provide guidelines to develop the epidemic prevention system and offers useful insights for the supporting of handicapped persons. © 2021 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: PiCom Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: PiCom Year: 2021 Document Type: Article