Murad Khan, Teef S. Alenezi, Shouq S. Alenezi, Sara S. Alenezi, Albandari A Alenezi, Basil Alothman, C. Joumaa
{"title":"A Framework to Combat COVID19 like Pandemic in Future","authors":"Murad Khan, Teef S. Alenezi, Shouq S. Alenezi, Sara S. Alenezi, Albandari A Alenezi, Basil Alothman, C. Joumaa","doi":"10.1109/ICTC55196.2022.9952927","DOIUrl":null,"url":null,"abstract":"This paper outlines a framework to prevent the COVID19 like pandemics for visitors to buildings or sites that receive many visitors. The proposed system is used to detect visitors who have not worn a facemask, or visitors with high body temperature, communicate daily visitor data to the security officer, sound an alarm to notify the officer, and screen the visitors with the results of the measurements. Also, the proposed solution uses deep learning and computer vision techniques to detect the facemask. Further, a testbed is designed based on an Arduino microcontroller connected to a PC for collecting, processing, and storing the data. Furthermore, the proposed system used a contactless infrared temperature sensor to avoid any chance to transfer the COVID-like disease to normal visitors. Finally, we tested the system by passing many subjects with and without face masks and high temperatures. The accuracy of the system shows that the system accurately detects each subject with and without a face mask and with high temperatures.","PeriodicalId":441404,"journal":{"name":"2022 13th International Conference on Information and Communication Technology Convergence (ICTC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 13th International Conference on Information and Communication Technology Convergence (ICTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTC55196.2022.9952927","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper outlines a framework to prevent the COVID19 like pandemics for visitors to buildings or sites that receive many visitors. The proposed system is used to detect visitors who have not worn a facemask, or visitors with high body temperature, communicate daily visitor data to the security officer, sound an alarm to notify the officer, and screen the visitors with the results of the measurements. Also, the proposed solution uses deep learning and computer vision techniques to detect the facemask. Further, a testbed is designed based on an Arduino microcontroller connected to a PC for collecting, processing, and storing the data. Furthermore, the proposed system used a contactless infrared temperature sensor to avoid any chance to transfer the COVID-like disease to normal visitors. Finally, we tested the system by passing many subjects with and without face masks and high temperatures. The accuracy of the system shows that the system accurately detects each subject with and without a face mask and with high temperatures.