Face Mask Detection with Temperature Check

Rupali Sharma*, Abha Chaubey**, Sidhhartha Chaubey***
*-*** Department of Computer Science and Engineering, Shri Shankaracharya Group of Institutions, Bhilai, Chhattisgarh, India.
Periodicity:December - February'2022
DOI : https://doi.org/10.26634/jit.11.1.18578

Abstract

The coronavirus (COVID-19) pandemic is causing a worldwide health catastrophe, so according to the World Health Organization (WHO), wearing masks in public is an effective safety method. The COVID-19 pandemic has forced governments around the world to impose quarantines to prevent transmission of the virus. According to reports, wearing masks in public does reduce the threat of transmission of the virus. An efficient and cost-effective way to use Artificial Intelligence (AI) to create a secure environment in a manufacturing environment. A hybrid model for using a deep and classic face mask detection device will be proposed. The face mask detection dataset includes the mask, and without mask photos, it uses the Open-Source Computer Vision Library (OpenCV) to detect faces in real-time from the stay circulation through the webcam. It uses the dataset to build a computer vision COVID-19 face mask detector using Python, OpenCV, TensorFlow, and Keras. Using computer vision and deep learning, the goal is to understand whether a character in a picture or video stream is wearing a mask or not using computer vision and deep learning.

Keywords

Mask Detection, Temperature Check, Python, OpenCV, Convolution Neural Network, COVID-19, Machine Learning.

How to Cite this Article?

Sharma, R., Chaubey, A., and Chaubey, S. (2022). Face Mask Detection with Temperature Check. i-manager’s Journal on Information Technology, 11(1), 1-9. https://doi.org/10.26634/jit.11.1.18578

References

[1]. Chiang, D. (2020). Detect Faces and Determine Whether People are Wearing Mask. Face Mask Detection.
[2]. Dhaya, R. (2020). Deep net model for detection of covid-19 using radiographs based on roc analysis. Journal of Innovative Image Processing (JIIP), 2(3), 135-140. https://doi.org/10.36548/jiip.2020.3.003
[3]. Fang, Y., Nie, Y., & Penny, M. (2020). Transmission dynamics of the COVID 19 outbreak and effectiveness of government interventions: A data driven analysis. Journal of Medical Virology, 92(6), 645-659. https://doi.org/10.1002/jmv.25750
[4]. Hussain, S. A., & Al Balushi, A. S. A. (2020). A real time face emotion classification and recognition using deep learning model. In Journal of Physics: Conference series (Vol. 1432, No. 1, p. 012087). IOP Publishing.
[5]. Manoharan, S. (2019). Study on Hermitian graph wavelets in feature detection. Journal of Soft Computing Paradigm (JSCP), 1(1), 24-32. https://doi.org/10.36548/jscp.2019.1.003
[6]. Rota, P. A., Oberste, M. S., Monroe, S. S., Nix, W. A., Campagnoli, R., Icenogle, J. P., ... & Bellini, W. J. (2003). Characterization of a novel coronavirus associated with severe acute respiratory syndrome. Science, 300(5624), 1394-1399. https://doi.org/10.1126/science.1085952
[7]. Said, Y. (2020). Pynq-YOLO-Net: An embedded quantized convolutional neural network for face mask detection in COVID-19 pandemic era. International Journal of Advanced Computer Science and Applications, 11(9), 100-106.
[8]. Wang, Z., Wang, G., Huang, B., Xiong, Z., Hong, Q., Wu, H., ... & Liang, J. (2020). Masked face recognition dataset and application. arXiv preprint arXiv:2003.09093. https://doi.org/10.48550/arXiv.2003.09093
[9]. World Health Organization. (2020). Coronavirus Disease 2019 (COVID-19): Situation Report, 73. Retrieved from https://apps.who.int/iris/bitstream/handle/10665/331686/nCoVsitrep02Apr2020-eng.pdf
[10]. Yadav, S. (2020). Deep learning based safe social distancing and face mask detection in public areas for covid-19 safety guidelines adherence. International Journal for Research in Applied Science & Engineering Technology (IJRASET), 8(7), 1368-1375.
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.