ITM Web Conf.
Volume 40, 2021International Conference on Automation, Computing and Communication 2021 (ICACC-2021)
|Number of page(s)||6|
|Published online||09 August 2021|
Ensuring social distancing using machine learning
Department of Computer Engineering, Ramrao Adik Institute of Technology, India
COVID-19 (Coronavirus) has affected our daily life and is slackening the global economy. In this fight against the COVID-19, social-distancing is proving to be an effective measure to slow down the transmission of coronavirus. In order to control the spread of transmission of COVID-19, social distancing is the best measure which aims to avoid close contact of people. In order to control the spread of transmission of COVID-19, social distancing is the best measure which aims to avoid close contact of people. With the aim of ensuring social- distancing norms in workplace and public places, we can develop a social-distancing detection tool that monitors if people are staying at a safe distance from each other. This can be done by examining real-time video streams from the cameras. In order to provide an effective solution, we are developing a model which has mainly two phases - firstly object detection phase where people will be detected from the video streams. Secondly showing the statistical analysis in the form of dashboards and sending alerts to concerned authorities to take necessary actions.
Key words: COVID-19 / object detection / YOLO V3 / alerts
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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