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Social Distancing Monitoring and Alerting System using YOLO Deep Learning Algorithm
1st IEEE International Conference on Automation, Computing and Renewable Systems, ICACRS 2022 ; : 646-650, 2022.
Article in English | Scopus | ID: covidwho-2257062
ABSTRACT
The Covid-19 disease is caused by the severe acute respiratory (SAR) syndrome coronavirus-2 and becomes the reason for the Global Pandemic since 2019. Until July 2022, the total reported cases were 572 million and reported deaths were 6.38 million around the world. In many countries the infections caused severe damages. It not only took the precious lives but also caused few other national damages like economic crisis. The only solution to stop this pandemic is to increase the vaccination and reducing the spreads. The covid 19 virus is an airborne disease and spread when people breathe virus contaminated air. The WHO and all the nations were insisting to maintain social distance to control the virus spreading. But maintaining the social distance in public places is very hard. In this project we developed a method for detecting social distance. The system uses Raspberry Pi processor to detect the distance between two people from the live video stream. The YOLOv3 technique is used to detect the object from single frame of the video. © 2022 IEEE
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 1st IEEE International Conference on Automation, Computing and Renewable Systems, ICACRS 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 1st IEEE International Conference on Automation, Computing and Renewable Systems, ICACRS 2022 Year: 2022 Document Type: Article