Monitoring Social Distancing Compliance Using Image Processing Algorithm

Lai, Yi Lun and Deshinta, Arrova Dewi (2022) Monitoring Social Distancing Compliance Using Image Processing Algorithm. INTI JOURNAL, 2022 (24). ISSN e2600-7320

Text ij2022_24.pdf - Published Version Download (550kB)

Abstract

Since the outbreak in December 2019, Malaysia has been in the throes of the Covid-19 pandemic, which has had a particularly enormous impact on both the country and the people. Although the government has actively constructed a set of effective standard operating procedures (SOP) to ease the epidemic, such as wearing masks, washing hands often, and maintaining social distance, these have had little effect, and the pandemic continues to grow. As a result, many people have been unable to maintain social distance, allowing the disease to spread to others. According to this viewpoint, a social distancing monitoring system could be a useful tool for monitoring and reminding people to maintain adequate social distance in real time. This system allows for real-time video and CCTV surveillance, as well as effective distance analysis to determine whether the effective social distance has been attained. This strategy can also be used in a variety of venues, including school cafeterias, malls, public spaces, and so on. Otherwise, because shopping malls have a lot of CCTV cameras, the technology can also be deployed there. When a site has a significant number of people but no social distance between them, the system will warn management to improve the location's security measures.

Item Type:	Article
Uncontrolled Keywords:	Social Distancing, Image Processing, Convolutional Neural Network, Surveillance
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	14 Jul 2022 05:18
Last Modified:	14 Mar 2024 08:04
URI:	http://eprints.intimal.edu.my/id/eprint/1638

Actions (login required)

View Item