Future IoT tools for COVID-19 contact tracing and prediction: A review of the state-of-the-science
Article
Article Title | Future IoT tools for COVID-19 contact tracing and prediction: A review of the state-of-the-science |
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ERA Journal ID | 36561 |
Article Category | Article |
Authors | Jahmunah, Vicnesh (Author), Sudarshan, Vidya K. (Author), Oh, Shu Lih (Author), Gururajan, Raj (Author), Gururajan, Rashmi (Author), Zhou, Xujuan (Author), Tao, Xiaohui (Author), Faust, Oliver (Author), Ciaccio, Edward J. (Author), Ng, Kwan Hoong (Author) and Acharya, U. Rajendra (Author) |
Journal Title | International Journal of Imaging Systems and Technology |
Journal Citation | 31 (2), pp. 455-471 |
Number of Pages | 17 |
Year | 2021 |
Publisher | John Wiley & Sons |
Place of Publication | United States |
ISSN | 0899-9457 |
1098-1098 | |
Digital Object Identifier (DOI) | https://doi.org/10.1002/ima.22552 |
Web Address (URL) | https://onlinelibrary.wiley.com/doi/full/10.1002/ima.22552 |
Abstract | In 2020 the world is facing unprecedented challenges due to COVID-19. To address these challenges, many digital tools are being explored and developed to contain the spread of the disease. With the lack of availability of vaccines, there is an urgent need to avert resurgence of infections by putting some measures, such as contact tracing, in place. While digital tools, such as phone applications are advantageous, they also pose challenges and have limitations(eg, wireless coverage could be an issue in some cases). On the other hand, wearable devices, when coupled with the Internet of Things (IoT), are expected to influence lifestyle and healthcare directly, and they may be useful for health monitoring during the global pandemic and beyond. In this work, we conduct a literature review of contact tracing methods and applications. Based on the literature review, we found limitations in gathering health data, such as insufficient network coverage. To address these shortcomings, we propose a novel intelligent tool that will be useful for contact tracing and prediction of COVID-19 clusters. The solution comprises a phone application combined with a wear-able device, infused with unique intelligent IoT features (complex data analysis and intelligent data visualization) embedded within the system to aid inCOVID-19 analysis. Contact tracing applications must establish data collection and data interpretation. Intelligent data interpretation can assist epidemiological scientists in anticipating clusters, and can enable them to take necessary action in improving public health management. Our proposed tool could also be used to curb disease incidence in future global health crises. |
Keywords | contact tracing, coronavirus disease, COVID-19, deep learning, digital tools, intelligent internet of things, wearable devices |
ANZSRC Field of Research 2020 | 460206. Knowledge representation and reasoning |
Institution of Origin | University of Southern Queensland |
Byline Affiliations | Ngee Ann Polytechnic, Singapore |
Singapore University of Social Sciences (SUSS), Singapore | |
School of Management and Enterprise | |
Department of Health, Queensland | |
Sheffield Hallam University, United Kingdom | |
Columbia University, United States | |
University of Malaya, Malaysia | |
Kumamoto University, Japan | |
Asia University, Taiwan | |
School of Management and Enterprise |
https://research.usq.edu.au/item/q63y4/future-iot-tools-for-covid-19-contact-tracing-and-prediction-a-review-of-the-state-of-the-science
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