Open AccessReal Time Social Distancing Statistics using AI and ML for Industries as a Permission to Run in COVID19 Pandemic
Author(s) -
Raj Davande,
Shailesh Khant
Publication year - 2021
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-1213
Subject(s) - social distance , permission , pandemic , python (programming language) , covid-19 , government (linguistics) , computer science , computer security , business , statistics , political science , mathematics , law , virology , medicine , operating system , infectious disease (medical specialty) , linguistics , philosophy , disease , pathology , outbreak
Implementation of social distancing norms in an industry during the pandemic by the help of existing CCTV cameras and a Python program paired along with a trained dataset. The program can identify the people and the distance between them hence giving untamperable statistics, through which an industry can prove to the government that social distancing is being followed and hence the govt. need not ban them from running.