TY - JOUR
AU - Kaiser, M. Shamim
AU - Mahmud, Mufti
AU - Noor, Manan Binth Taj
AU - Zenia, Nusrat Zerin
AU - Mamun, Shamim Al
AU - Mahmud, K. M. Abir
AU - Azad, Saiful
AU - Aradhya, V. N. Manjunath
AU - Stephan, Punitha
AU - Stephan, Thompson
AU - Kannan, Ramani
AU - Hanif, Mohammed
AU - Sharmeen, Tamanna
AU - Chen, Tianhua
AU - Hussain, Amir
PY - 2021
DA - January
TI - iWorksafe: Towards Healthy Workplaces During COVID-19 With an Intelligent Phealth App for Industrial Settings
JO - IEEE Access
EP - 13828
VL - 9
DO - https://doi.org/10.1109/ACCESS.2021.3050193
AB - 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.
PB - IEEE
UR - https://www.napier.ac.uk/research-and-innovation/research-search/outputs/iworksafe-towards-healthy-workplaces-during-covid-19-with-an-intelligent-phealth-app-for
KW - Coronavirus (COVID-19)
KW - Digital health and technology
ER