Open AccessSocial Distancing Detector using Deep Learning
Author(s) -
Manthri Sriharsha,
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Sowjanya Jindam,
Akhila Gandla,
Lalith Sai Allani,
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Publication year - 2022
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e6710.0110522
Subject(s) - social distance , python (programming language) , computer science , distancing , covid-19 , software , artificial intelligence , computer security , internet privacy , human–computer interaction , infectious disease (medical specialty) , medicine , operating system , disease , pathology
Social Distancing is the best possible way to detain the spread of Covid-19. Even though vaccine has been found and working effectively in saving the lives of people, social distancing is necessary to reduce the spread of virus to maximum extent which not only saves people from being infected but also reduces the impact of spreading of the disease. In our proposed system, we use Deep Learning with python to monitor social distancing in public places. This is a software tool that monitor if people are maintaining proper social distancing norms or not by analyzing real time video streams from CC camera. We use YOLO Model which is trained by COCO dataset.