Home|Journals|Articles by Year

Directory for Medical Articles
 

Research Article

EEO. 2021; 20(5): 4169-4177


Designing the IoT based Social Distancing Monitoring System for Reducing the impact of Covid-19

HUSAM K SALIH JUBOORI, Mohanad F Jwaid, Mohammed Alaa H. Altemimi.


Abstract

The unprecedented pandemic of 2019 that was COVID-19 of the Health Organization (WHO) has left hundreds of governments precarious around the world. The strain on virtually every nation in the world of the COVID 19 virus, the consequences of which the Chinese alone had previously seen. Along with fear of overwhelming care systems, a large proportion of these countries were compelled, due to lack of resources to resist the COVID 19 outbreak, to partly or completely cut off. Social distancing is essential if viral diseases such as COVID-19 are to be prevented. By reducing close physical contact between people, we reduce the chance of capturing and spreading the virus throughout the community. The pandemic has been rapidly exploited by various research communities since it started and IoT is one of the pioneers in this field, taking advantage of a wide variety of technologies to address this global threat. The IoT system / liable devices / applications are used in the context of COVID-19 to reduce COVID-19 spread to others in early diagnostic procedures, patient monitoring and post-patient recuperation practice of defined protocols. We emphasize here for an Open-CV, Computer Vision and Deep Learning surveillance method to keep track of footpaths and prevent overcrowding. The objects can be detected using Closed Circuit TV (CCTV) and Drones can be used to detect and measure the distance between the crowds by the camera.

Key words: COVID-19, IoT, Social Distancing, Deep Learning, Computer Vision






Full-text options


Share this Article



Online Article Submission
• ejmanager.com
• ojshosting.net







Do you want to use OJS for your journal ?
work with an experienced partner
www.OJSHosting.net

eJManager.com
Review(er)s Central
About BiblioMed
License Information
Terms & Conditions
Privacy Policy
Contact Us

The articles in Bibliomed are open access articles licensed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-nc-sa/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.