Wearable Internet of Medical Things Sensor Devices, Big Healthcare Data, and Artificial Intelligence-based Diagnostic Algorithms in Real-Time COVID-19 Detection and Monitoring Systems
Wearable Internet of Medical Things Sensor Devices, Big Healthcare Data, and Artificial Intelligence-based Diagnostic Algorithms in Real-Time COVID-19 Detection and Monitoring Systems

Summary/Abstract: Based on an in-depth survey of the literature, the purpose of the paper is to explore wearable Internet of Medical Things sensor devices, big healthcare data, and artificial intelligence-based diagnostic algorithms in real-time COVID-19 detection and monitoring systems. Using and replicating data from Accenture, Deloitte, The Economist, eMarketer, Gartner, GE Healthcare, Ginger, McKinsey, MIT Technology Review Insights, PwC, R2G, SSCG Media Group, Statista, and Sykes, we performed analyses and made estimates regarding the integration of connected wearable medical devices and clinical data. Real-time COVID-19 symptom data can be gathered by use of wearable sensors placed on the patient’s body. Smart data fusion from Internet of Things devices is adequate when diagnosing COVID-19 primarily. Wearable medical devices are instrumental in remote health monitoring systems. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.

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