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Management of safe distancing on construction sites during COVID-19: A smart real-time monitoring system
The outbreak of Coronavirus Disease 2019 (COVID-19) poses a great threat to the world. One mandatory and efficient measure to prevent the spread of COVID-19 on construction sites is to ensure safe distancing during workers’ daily activities. However, manual monitoring of safe distancing during const...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8685176/ https://www.ncbi.nlm.nih.gov/pubmed/34955588 http://dx.doi.org/10.1016/j.cie.2021.107847 |
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author | Goh, Yang Miang Tian, Jing Chian, Eugene Yan Tao |
author_facet | Goh, Yang Miang Tian, Jing Chian, Eugene Yan Tao |
author_sort | Goh, Yang Miang |
collection | PubMed |
description | The outbreak of Coronavirus Disease 2019 (COVID-19) poses a great threat to the world. One mandatory and efficient measure to prevent the spread of COVID-19 on construction sites is to ensure safe distancing during workers’ daily activities. However, manual monitoring of safe distancing during construction activities can be toilsome and inconsistent. This study proposes a computer vision-based smart monitoring system to automatically detect worker breaching safe distancing rules. Our proposed system consists of three main modules: (1) worker detection module using CenterNet; (2) proximity determination module using Homography; and (3) warning alert and data collection module. To evaluate the system, it was implemented in a construction site as a case study. This study has two key contributions: (1) it is demonstrated that monitoring of safe distancing can be automated using our approach; and (2) CenterNet, an anchorless detection model, outperforms current state-of-the-art approaches in the real-time detection of workers. |
format | Online Article Text |
id | pubmed-8685176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86851762021-12-20 Management of safe distancing on construction sites during COVID-19: A smart real-time monitoring system Goh, Yang Miang Tian, Jing Chian, Eugene Yan Tao Comput Ind Eng Article The outbreak of Coronavirus Disease 2019 (COVID-19) poses a great threat to the world. One mandatory and efficient measure to prevent the spread of COVID-19 on construction sites is to ensure safe distancing during workers’ daily activities. However, manual monitoring of safe distancing during construction activities can be toilsome and inconsistent. This study proposes a computer vision-based smart monitoring system to automatically detect worker breaching safe distancing rules. Our proposed system consists of three main modules: (1) worker detection module using CenterNet; (2) proximity determination module using Homography; and (3) warning alert and data collection module. To evaluate the system, it was implemented in a construction site as a case study. This study has two key contributions: (1) it is demonstrated that monitoring of safe distancing can be automated using our approach; and (2) CenterNet, an anchorless detection model, outperforms current state-of-the-art approaches in the real-time detection of workers. Elsevier Ltd. 2022-01 2021-12-07 /pmc/articles/PMC8685176/ /pubmed/34955588 http://dx.doi.org/10.1016/j.cie.2021.107847 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Goh, Yang Miang Tian, Jing Chian, Eugene Yan Tao Management of safe distancing on construction sites during COVID-19: A smart real-time monitoring system |
title | Management of safe distancing on construction sites during COVID-19: A smart real-time monitoring system |
title_full | Management of safe distancing on construction sites during COVID-19: A smart real-time monitoring system |
title_fullStr | Management of safe distancing on construction sites during COVID-19: A smart real-time monitoring system |
title_full_unstemmed | Management of safe distancing on construction sites during COVID-19: A smart real-time monitoring system |
title_short | Management of safe distancing on construction sites during COVID-19: A smart real-time monitoring system |
title_sort | management of safe distancing on construction sites during covid-19: a smart real-time monitoring system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8685176/ https://www.ncbi.nlm.nih.gov/pubmed/34955588 http://dx.doi.org/10.1016/j.cie.2021.107847 |
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