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Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World

Abstract

As COVID-19 hounds the world, the common cause of finding a swift solution to manage the pandemic has brought together researchers, institutions, governments, and society at large. The Internet of Things (IoT), artificial intelligence (AI)-including machine learning (ML) and Big Data analytics-as well as Robotics and Blockchain, are the four decisive areas of technological innovation that have been ingenuity harnessed to fight this pandemic and future ones. While these highly interrelated smart and connected health technologies cannot resolve the pandemic overnight and may not be the only answer to the crisis, they can provide greater insight into the disease and support frontline efforts to prevent and control the pandemic. This article provides a blend of discussions on the contribution of these digital technologies, propose several complementary and multidisciplinary techniques to combat COVID-19, offer opportunities for more holistic studies, and accelerate knowledge acquisition and scientific discoveries in pandemic research. First, four areas, where IoT can contribute are discussed, namely: 1) tracking and tracing; 2) remote patient monitoring (RPM) by wearable IoT (WIoT); 3) personal digital twins (PDTs); and 4) real-life use case: ICT/IoT solution in South Korea. Second, the role and novel applications of AI are explained, namely: 1) diagnosis and prognosis; 2) risk prediction; 3) vaccine and drug development; 4) research data set; 5) early warnings and alerts; 6) social control and fake news detection; and 7) communication and chatbot. Third, the main uses of robotics and drone technology are analyzed, including: 1) crowd surveillance; 2) public announcements; 3) screening and diagnosis; and 4) essential supply delivery. Finally, we discuss how distributed ledger technologies (DLTs), of which blockchain is a common example, can be combined with other technologies for tackling COVID-19.

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References
1.
Imran A, Posokhova I, Qureshi H, Masood U, Riaz M, Ali K . AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app. Inform Med Unlocked. 2020; 20:100378. PMC: 7318970. DOI: 10.1016/j.imu.2020.100378. View

2.
Lee K, Ni X, Lee J, Arafa H, Pe D, Xu S . Mechano-acoustic sensing of physiological processes and body motions via a soft wireless device placed at the suprasternal notch. Nat Biomed Eng. 2019; 4(2):148-158. PMC: 7035153. DOI: 10.1038/s41551-019-0480-6. View

3.
Seshadri D, Li R, Voos J, Rowbottom J, Alfes C, Zorman C . Wearable sensors for monitoring the physiological and biochemical profile of the athlete. NPJ Digit Med. 2019; 2:72. PMC: 6646404. DOI: 10.1038/s41746-019-0150-9. View

4.
Bernardini M, Morettini M, Romeo L, Frontoni E, Burattini L . Early temporal prediction of Type 2 Diabetes Risk Condition from a General Practitioner Electronic Health Record: A Multiple Instance Boosting Approach. Artif Intell Med. 2020; 105:101847. DOI: 10.1016/j.artmed.2020.101847. View

5.
Driggin E, Madhavan M, Bikdeli B, Chuich T, Laracy J, Biondi-Zoccai G . Cardiovascular Considerations for Patients, Health Care Workers, and Health Systems During the COVID-19 Pandemic. J Am Coll Cardiol. 2020; 75(18):2352-2371. PMC: 7198856. DOI: 10.1016/j.jacc.2020.03.031. View