Future IoT tools for COVID ‐19 contact tracing and prediction: A review of the state‐of‐the‐science
Autor: | Rashmi Gururajan, Xujuan Zhou, Vidya K. Sudarshan, Edward J. Ciaccio, Raj Gururajan, Oliver Faust, Kwan Hoong Ng, V. Jahmunah, Xiaohui Tao, U. Rajendra Acharya, Shu Lih Oh |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Computer science
Wearable computer 02 engineering and technology contact tracing 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Data visualization wearable devices Phone COVID‐19 Health care 0202 electrical engineering electronic engineering information engineering Global health Electrical and Electronic Engineering intelligent internet of things Wearable technology Research Articles Data collection business.industry deep learning Data science Electronic Optical and Magnetic Materials coronavirus disease 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition business Contact tracing digital tools Software Research Article |
Zdroj: | International Journal of Imaging Systems and Technology |
ISSN: | 1098-1098 0899-9457 |
DOI: | 10.1002/ima.22552 |
Popis: | 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 wearable device, infused with unique intelligent IoT features (complex data analysis and intelligent data visualization) embedded within the system to aid in COVID‐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. |
Databáze: | OpenAIRE |
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