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Face Mask Detection and Alert System

Authors

  • Shreya Khare SIES Graduate School of Technology, University of Mumbai
  • Shreya Mukherjee SIES Graduate School of Technology, University of Mumbai
  • Shaikh Nifa Kausar SIES Graduate School of Technology, University of Mumbai
  • Urvashi Patkar SIES Graduate School of Technology, University of Mumbai

DOI:

https://doi.org/10.21467/preprints.303

Abstract

In today’s era, as we all know how the year 2020 has brought an alarming pandemic with it and day by day, we are reaching a new peak of COVID cases. And due to which a main contribution asked from all the citizens is to follow all the safety norms to soothe the condition. One of the norms states to wear facemask all the time immediately after stepping out of their home. This paper proposes one of the methods to ensure that at least all people coming under any Closed-Circuit Television (CCTV) surveillance wears masks and that too properly. In this system we are using locally linear embedding (LLE) algorithm for face detection and convolutional neural network (CNNs) to reconfigure the image to fit into the network. And the neural network is trained with the help of image dataset. The method attains training accuracy and validation accuracy up to 99.87% and 93.41% respectively on two different datasets. If the system found out a person with no mask or not wearing it properly an alarm buzz outs to alter.

Keywords:

covid19, Machine learning, mask detection, alert

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References

GitHub-prajnasb/observations, [online] Available: https://github.com/prajnasb/observations.

Z. Allam and D. S. Jones, "On the Coronavirus (COVID-19) Outbreak and the Smart City Network: Universal Data Sharing Standards Coupled with Artificial Intelligence (AI) to Benefit Urban Health Monitoring and Management", Healthcare, vol. 8, no. 1, pp. 46, 2020.

M. Jiang, X. Fan and H. Yan, "RetinaMask: A Face Mask detector", 2020, [online] Available: http://arxiv.org/abs/2005.03950.

Mohammad Marufur Rahman, Motaleb Hossen Manik, Milon Islam, Saifuddin Mahmud and Jong-Hoon Kim, "An Automated System to Limit COVID-19 Using Facial Mask Detection in Smart City Network", IEEE International IOT Electronics and Mechatronics Conference (IEMTRONICS), 2020. Available https://ieeexplore.ieee.org/document/9216386

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Posted

2021-05-10

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