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iWorksafe: Towards healthy workplaces during COVID-19 with an intelligent phealth app for industrial settings

The recent outbreak of the novel Coronavirus Disease (COVID-19) has given rise to diverse health issues due to its high transmission rate and limited treatment options. Almost the whole world, at some point of time, was placed in lock-down in an attempt to stop the spread of the virus, with resultin...

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Main Authors:	Kaiser, M. Shamim, Mahmud, Mufti, Taj Noor, Manan Binth, Zenia, Nusrat Zerin, Al Mamun, Shamim, Abir Mahmud, K. M., Azad, Saiful, Manjunath Aradhya, V. N., Stephan, Punitha, Stephan, Thompson, Kannan, Ramani, Hanif, Mohammed, Sharmeen, Tamanna, Chen, Tianhua, Hussain, Amir
Format:	Article
Language:	English
Published:	IEEE 2021
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/31832/1/iWorksafe-%20towards%20healthy%20workplaces%20during%20COVID-19.pdf http://umpir.ump.edu.my/id/eprint/31832/ https://doi.org/10.1109/ACCESS.2021.3050193 https://doi.org/10.1109/ACCESS.2021.3050193
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id	my.ump.umpir.31832
record_format	eprints
spelling	my.ump.umpir.318322021-08-20T08:36:27Z http://umpir.ump.edu.my/id/eprint/31832/ iWorksafe: Towards healthy workplaces during COVID-19 with an intelligent phealth app for industrial settings Kaiser, M. Shamim Mahmud, Mufti Taj Noor, Manan Binth Zenia, Nusrat Zerin Al Mamun, Shamim Abir Mahmud, K. M. Azad, Saiful Manjunath Aradhya, V. N. Stephan, Punitha Stephan, Thompson Kannan, Ramani Hanif, Mohammed Sharmeen, Tamanna Chen, Tianhua Hussain, Amir QA76 Computer software The recent outbreak of the novel Coronavirus Disease (COVID-19) has given rise to diverse health issues due to its high transmission rate and limited treatment options. Almost the whole world, at some point of time, was placed in lock-down in an attempt to stop the spread of the virus, with resulting psychological and economic sequela. As countries start to ease lock-down measures and reopen industries, ensuring a healthy workplace for employees has become imperative. Thus, this paper presents a mobile app-based intelligent portable healthcare (pHealth) tool, called i WorkSafe, to assist industries in detecting possible suspects for COVID-19 infection among their employees who may need primary care. Developed mainly for low-end Android devices, the i WorkSafe app hosts a fuzzy neural network model that integrates data of employees' health status from the industry's database, proximity and contact tracing data from the mobile devices, and user-reported COVID-19 self-test data. Using the built-in Bluetooth low energy sensing technology and K Nearest Neighbor and K-means techniques, the app is capable of tracking users' proximity and trace contact with other employees. Additionally, it uses a logistic regression model to calculate the COVID-19 self-test score and a Bayesian Decision Tree model for checking real-time health condition from an intelligent e-health platform for further clinical attention of the employees. Rolled out in an apparel factory on 12 employees as a test case, the pHealth tool generates an alert to maintain social distancing among employees inside the industry. In addition, the app helps employees to estimate risk with possible COVID-19 infection based on the collected data and found that the score is effective in estimating personal health condition of the app user. IEEE 2021-01-08 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/31832/1/iWorksafe-%20towards%20healthy%20workplaces%20during%20COVID-19.pdf Kaiser, M. Shamim and Mahmud, Mufti and Taj Noor, Manan Binth and Zenia, Nusrat Zerin and Al Mamun, Shamim and Abir Mahmud, K. M. and Azad, Saiful and Manjunath Aradhya, V. N. and Stephan, Punitha and Stephan, Thompson and Kannan, Ramani and Hanif, Mohammed and Sharmeen, Tamanna and Chen, Tianhua and Hussain, Amir (2021) iWorksafe: Towards healthy workplaces during COVID-19 with an intelligent phealth app for industrial settings. IEEE Access, 9 (9317697). 13814 -13828. ISSN 2169-3536 https://doi.org/10.1109/ACCESS.2021.3050193 https://doi.org/10.1109/ACCESS.2021.3050193
institution	Universiti Malaysia Pahang
building	UMP Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang
content_source	UMP Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Kaiser, M. Shamim Mahmud, Mufti Taj Noor, Manan Binth Zenia, Nusrat Zerin Al Mamun, Shamim Abir Mahmud, K. M. Azad, Saiful Manjunath Aradhya, V. N. Stephan, Punitha Stephan, Thompson Kannan, Ramani Hanif, Mohammed Sharmeen, Tamanna Chen, Tianhua Hussain, Amir iWorksafe: Towards healthy workplaces during COVID-19 with an intelligent phealth app for industrial settings
description	The recent outbreak of the novel Coronavirus Disease (COVID-19) has given rise to diverse health issues due to its high transmission rate and limited treatment options. Almost the whole world, at some point of time, was placed in lock-down in an attempt to stop the spread of the virus, with resulting psychological and economic sequela. As countries start to ease lock-down measures and reopen industries, ensuring a healthy workplace for employees has become imperative. Thus, this paper presents a mobile app-based intelligent portable healthcare (pHealth) tool, called i WorkSafe, to assist industries in detecting possible suspects for COVID-19 infection among their employees who may need primary care. Developed mainly for low-end Android devices, the i WorkSafe app hosts a fuzzy neural network model that integrates data of employees' health status from the industry's database, proximity and contact tracing data from the mobile devices, and user-reported COVID-19 self-test data. Using the built-in Bluetooth low energy sensing technology and K Nearest Neighbor and K-means techniques, the app is capable of tracking users' proximity and trace contact with other employees. Additionally, it uses a logistic regression model to calculate the COVID-19 self-test score and a Bayesian Decision Tree model for checking real-time health condition from an intelligent e-health platform for further clinical attention of the employees. Rolled out in an apparel factory on 12 employees as a test case, the pHealth tool generates an alert to maintain social distancing among employees inside the industry. In addition, the app helps employees to estimate risk with possible COVID-19 infection based on the collected data and found that the score is effective in estimating personal health condition of the app user.
format	Article
author	Kaiser, M. Shamim Mahmud, Mufti Taj Noor, Manan Binth Zenia, Nusrat Zerin Al Mamun, Shamim Abir Mahmud, K. M. Azad, Saiful Manjunath Aradhya, V. N. Stephan, Punitha Stephan, Thompson Kannan, Ramani Hanif, Mohammed Sharmeen, Tamanna Chen, Tianhua Hussain, Amir
author_facet	Kaiser, M. Shamim Mahmud, Mufti Taj Noor, Manan Binth Zenia, Nusrat Zerin Al Mamun, Shamim Abir Mahmud, K. M. Azad, Saiful Manjunath Aradhya, V. N. Stephan, Punitha Stephan, Thompson Kannan, Ramani Hanif, Mohammed Sharmeen, Tamanna Chen, Tianhua Hussain, Amir
author_sort	Kaiser, M. Shamim
title	iWorksafe: Towards healthy workplaces during COVID-19 with an intelligent phealth app for industrial settings
title_short	iWorksafe: Towards healthy workplaces during COVID-19 with an intelligent phealth app for industrial settings
title_full	iWorksafe: Towards healthy workplaces during COVID-19 with an intelligent phealth app for industrial settings
title_fullStr	iWorksafe: Towards healthy workplaces during COVID-19 with an intelligent phealth app for industrial settings
title_full_unstemmed	iWorksafe: Towards healthy workplaces during COVID-19 with an intelligent phealth app for industrial settings
title_sort	iworksafe: towards healthy workplaces during covid-19 with an intelligent phealth app for industrial settings
publisher	IEEE
publishDate	2021
url	http://umpir.ump.edu.my/id/eprint/31832/1/iWorksafe-%20towards%20healthy%20workplaces%20during%20COVID-19.pdf http://umpir.ump.edu.my/id/eprint/31832/ https://doi.org/10.1109/ACCESS.2021.3050193 https://doi.org/10.1109/ACCESS.2021.3050193
_version_	1709667689556869120
score	13.211869

iWorksafe: Towards healthy workplaces during COVID-19 with an intelligent phealth app for industrial settings

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