The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIV-4/W3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-4/W3-2020, 159–163, 2020
https://doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-159-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-4/W3-2020, 159–163, 2020
https://doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-159-2020

  23 Nov 2020

23 Nov 2020

DEEP LEARNING BASED MASK DETECTION IN SMART HOME ENTRIES DURING THE EPIDEMIC PROCESS

B. Cerit1 and R. Bayir2 B. Cerit and R. Bayir
  • 1Department of Mechatronics Engineering, Graduate School of Natural and Applied Sciences, Karabuk University, Karabuk, Turkey
  • 2Department of Mechatronics Engineering, Technology Faculty, Karabuk University, Karabuk, Turkey

Keywords: Smart Home, Deep Learning, Artificial Intelligence, IOT, Mobile Application, PID

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.