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Smart Entry System Following COVID-19 Protocols
2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022 ; : 137-140, 2022.
Article in English | Scopus | ID: covidwho-2029202
ABSTRACT
COVID-19 is an ongoing global pandemic and is continuing to be a fast-spreading virus all over the world. It transmits when people breathe in air contaminated by droplets and small airborne particles containing the virus. The risk becomes highest when people are nearby, but they can be over longer distances, while indoors. It is necessary to isolate such infected persons in public places with large gatherings. In addition to screening them, individual protection measures can also be taken.Two primary requirements that fulfil the entry to the public are by scanning of temperature to prevent person suspected and also to ensure one has masked face properly to permit entry. At the moment, all places use this system. But they are manual and depend on the person inspecting temperature and mask. There are few automated processes, but they do not have automatic entry control. Thus, there are risks of false entry of people inside the public place.In this paper, an integrated approach in mask detection and temperature scanning, indicated visually by LED and LCD Display, and further control entry with the operation of boom barrier has been presented. The information is also recorded to identify each entry. Open CV is used to detect masks and obtain better accuracy. An infrared temperature sensor and a proper guide to scan the temperature are used. Each step of the process is implemented on one Raspberry PI-based board. The system is suitably packaged and demonstrated. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022 Year: 2022 Document Type: Article