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Contactless Mask Monitoring and Biometric Attendance System
2nd International Conference on Signal and Information Processing, IConSIP 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2228123
ABSTRACT
This paper attempts to give an overview of the system which is designed keeping social distancing guidelines in mind. Our system will detect in real-time, if the person in the captured live video is wearing a mask properly or not using a mask detecting algorithm developed using deep learning and neural networks with an accuracy of 96.05%. If and only if the person is wearing a mask, they will be allowed to scan the iris and hence record their attendance, which can be stored in excel or CSV formats. The location of iris biometric is translated to a real-life position in the 3D space with the resolution of 0.lmm. To scan the located biometric this system comprises a robotic arm. End effector of this robotic arm traverses to the translated position of the person's eye to scan iris with an iris scanner. The system employs a 'four degrees of motion' robotic arm that can autonomously align itself to the iris with an accuracy of 96.86%. It is battery operated and has a cylindrical workspace with maximum range of 300mm, hence it is easily deployable in institutions requiring secure authorization while monitoring COVID-19 safety norms. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2nd International Conference on Signal and Information Processing, IConSIP 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2nd International Conference on Signal and Information Processing, IConSIP 2022 Year: 2022 Document Type: Article