Integration of Adaptive Technologies with Healthcare for the Early Identification and Control of COVID-19 Pandemic Disease

Abstract

The impact of the COVID-19 pandemic has spread all over the world and it has affected voluminously everyday lives of billions. Social consequences and virus spread that needs to be addressed to take proper action to resolve the challenges faced during this pandemic period. The pandemic needs proper surveillance, monitoring, diagnosis, and identification of infected patients. Most researchers continue to give ways to detect and control the pandemic diseases of this type. Pandemic has made researchers from all areas and virologists consider cross-disciplinary approaches to combat with COVID-19. It needs to be immediate decisions to deal with uncertain conditions. During such a pandemic, the incorporation of healthcare technologies would bring about many solutions with high benefits. Reliable, sustainable, and accessible approaches can be the emphasis of the new digital healthcare approach. In this direction, IoT based smart solutions are introduced and analyzed. The emergencies spanning the globe demand a smart healthcare solution to manage people's lives at every stage. The first pandemic break-out in any part of the world needs early detection of disease and infected individuals to take reasonable measures forward to contain the spread. Web and Mobile based IoT system integrated with healthcare to support the solution that needs to be solved by the emergency posed during this pandemic. To locate COVID-19 cases and reduce the effects of the pandemic, IoT-enabled cognitive solutions are provided. It also addresses new ubiquitous technologies such as AI, Machine Learning, and Big Data Analytics with new innovative methods to integrate the solutions, including wearable devices, RFID, GPS, mobile apps, etc. Concerning the COVID-19 pandemic, the benefits and operational difficulties faced in digitizing these healthcare-cognitive IoT approaches are analyzed. The study would also address internal and external concerns such as practicality, cost, time to measure and execute, and coverage for implementation of this solution. These solutions may include human-machine interaction with the right decision-making capabilities. The paper also focuses on the ethical issues raised in introducing modern interoperable and predictive Healthcare IoT solutions.