IoT-Based COVID-19 Diagnosing and Monitoring Systems: A Survey

Abstract

To date, the novel Coronavirus (SARS-CoV-2) has infected millions and has caused the deaths of thousands of people around the world. At the moment, five antibodies, two from China, two from the U.S., and one from the UK, have already been widely utilized and numerous vaccines are under the trail process. In order to reach herd immunity, around 70% of the population would need to be inoculated. It may take several years to hinder the spread of SARS-CoV-2. Governments and concerned authorities have taken stringent measurements such as enforcing partial, complete, or smart lockdowns, building temporary medical facilities, advocating social distancing, and mandating masks in public as well as setting up awareness campaigns. Furthermore, there have been massive efforts in various research areas and a wide variety of tools, technologies and techniques have been explored and developed to combat the war against this pandemic. Interestingly, machine learning (ML) algorithms and internet of Things (IoTs) technology are the pioneers in this race. Up till now, several real-time and intelligent COVID-19 diagnosing, and monitoring systems have been proposed to tackle the COVID-19 pandemic. In this article we have analyzed a wide range of IoTs technologies which can be used in diagnosing and monitoring the infected individuals and hotspot areas. Furthermore, we identify the challenges and also provide our vision about the future research on COVID-19.

Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application

“…The LogNNet network can be used to predict a diagnosis based on blood biochemical parameters. This result is an important step in smart human sensors for IoT application, as the COVID-19 status and other blood-related health parameters are difficult to analyze on the IoT edges (in contrast to more widespread parameters, such as temperature or heartbeat) [ 97 , 98 , 99 ]. Our approach is applicable to the development of personalized bionic systems (smart suit for a person or AmI environment with people), wherein disease status recognition is a regular digital service for healthcare or well-being applications in everyday life [ 45 ].…”