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Title: :  Deep Learning - Based COVID-19 Safety Monitoring
PaperId: :  14664
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 7 Issue 3 2021
DUI:    16.0415/IJARIIE-14664
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Steffy FrancisIES College of Engineering Chittilappilly
Jensy VIES College of Engineering Chittilappilly

Abstract

Computer Engineering
Covid-19, Face mask, Social distancing, Computer vision, Yolo v3,
As of June 2, 2021, the fatal coronavirus illness 2019 (COVID-19) has spread to over 180 nations, resulting in 28,175,044 confirmed cases and 331,895 deaths in India alone. The population's vulnerability is heightened by the lack of effective treatment drugs and immunity to COVID-19. The population's vulnerability is heightened by the lack of effective treatment drugs and immunity to COVID-19. Because there are no effective vaccines or medications available, the only viable way to combat the pandemic is to follow covid guidelines, such as social distancing and wearing masks etc. In order to automate the task of monitoring social-distancing, mask, and age of a person using surveillance footage, this study provides a deep learning-based system. The suggested framework employs the YOLO v3 object detection model to distinguish persons from the background using bounding boxes and assigned IDs.It was discovered that it had improved accuracy for all of the input videos that were evaluated.

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IJARIIE Steffy Francis, and Jensy V. "Deep Learning - Based COVID-19 Safety Monitoring" International Journal Of Advance Research And Innovative Ideas In Education Volume 7 Issue 3 2021 Page 2702-2708
MLA Steffy Francis, and Jensy V. "Deep Learning - Based COVID-19 Safety Monitoring." International Journal Of Advance Research And Innovative Ideas In Education 7.3(2021) : 2702-2708.
APA Steffy Francis, & Jensy V. (2021). Deep Learning - Based COVID-19 Safety Monitoring. International Journal Of Advance Research And Innovative Ideas In Education, 7(3), 2702-2708.
Chicago Steffy Francis, and Jensy V. "Deep Learning - Based COVID-19 Safety Monitoring." International Journal Of Advance Research And Innovative Ideas In Education 7, no. 3 (2021) : 2702-2708.
Oxford Steffy Francis, and Jensy V. 'Deep Learning - Based COVID-19 Safety Monitoring', International Journal Of Advance Research And Innovative Ideas In Education, vol. 7, no. 3, 2021, p. 2702-2708. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Deep_Learning___Based_COVID_19_Safety_Monitoring_ijariie14664.pdf (Accessed : ).
Harvard Steffy Francis, and Jensy V. (2021) 'Deep Learning - Based COVID-19 Safety Monitoring', International Journal Of Advance Research And Innovative Ideas In Education, 7(3), pp. 2702-2708IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Deep_Learning___Based_COVID_19_Safety_Monitoring_ijariie14664.pdf (Accessed : )
IEEE Steffy Francis, and Jensy V, "Deep Learning - Based COVID-19 Safety Monitoring," International Journal Of Advance Research And Innovative Ideas In Education, vol. 7, no. 3, pp. 2702-2708, May-Jun 2021. [Online]. Available: https://ijariie.com/AdminUploadPdf/Deep_Learning___Based_COVID_19_Safety_Monitoring_ijariie14664.pdf [Accessed : ].
Turabian Steffy Francis, and Jensy V. "Deep Learning - Based COVID-19 Safety Monitoring." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 7 number 3 ().
Vancouver Steffy Francis, and Jensy V. Deep Learning - Based COVID-19 Safety Monitoring. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2021 [Cited : ]; 7(3) : 2702-2708. Available from: https://ijariie.com/AdminUploadPdf/Deep_Learning___Based_COVID_19_Safety_Monitoring_ijariie14664.pdf
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