Abstract

In this study, "smart home" systems were designed against Covid-19 virus, which negatively affects life all over the world, and viruses that may become epidemics later. Our homes need to be more hygienic and safe than yesterday. One of these hygiene rules is the masks that cover our nose and mouth. It is very important to use a mask to prevent further spread of the virus. Whether or not the people in smart homes are wearing masks at home will be diagnosed with the deep learning method. Hosts will be warned if they do not have masks. Brightness level control card and illuminator have been added to smart home entrances to better identify people's faces. With PID, the illumination level is fixed at the desired value, and with IOT technology, people can follow the illumination level at the smart home entrance from the mobile application.

Details

Title
DEEP LEARNING BASED MASK DETECTION IN SMART HOME ENTRIES DURING THE EPIDEMIC PROCESS
Author
Cerit, B 1 ; Bayir, R 2 

 Department of Mechatronics Engineering, Graduate School of Natural and Applied Sciences, Karabuk University, Karabuk, Turkey; Department of Mechatronics Engineering, Graduate School of Natural and Applied Sciences, Karabuk University, Karabuk, Turkey 
 Department of Mechatronics Engineering, Technology Faculty, Karabuk University, Karabuk, Turkey; Department of Mechatronics Engineering, Technology Faculty, Karabuk University, Karabuk, Turkey 
Pages
159-163
Publication year
2020
Publication date
2020
Publisher
Copernicus GmbH
ISSN
16821750
e-ISSN
21949034
Source type
Conference Paper
Language of publication
English
ProQuest document ID
2463242634
Copyright
© 2020. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.