Detection and Diagnosis of Virus Infection Based on Sensor in Internet of Medical Things

Abstract

Nowadays going to very difficult to each other’s in the worlds, everyone like man, women, child’s, animals even living things, etc. all the livings things facing problems of different diagnosis, but the most of one diagnosis as novel corona or corona are the highest position in death rates by the infection of human to human, human to animal, animal to human as well animal to animals. As much more in human beings. This virus detects some acid or medical diagnosis. So, at present the world faces some novel coronavirus which is detected on 10 January 2020, a new coronavirus producing a pneumonia outbreak in Wuhan City in central China was denoted as 2019-nCoV. We focus on advances in research and development of fast diagnosis wireless-based methods, as well as possible prophylactics and therapeutics to prevent or treat infection by the smart sensor fusion and decision making on the Internet of Medical Things. This paper proposed a new framework to detect and analyze any types of virus diseases like COVID-19, flue, influenza virus, respiratory syncytial virus, respiratory viral infection, etc. using smart sensors. The proposal provides a low-cost detection because smart devices like and virus detection device, smartphone, medical devices most of the medical employee have already held smartphones and medical devices which is connected by the internet. Now a day’s smartphones are powerful with existing computation more processors, large memory space, and a different number of sensors. The artificial Intelligence (AI) enabled framework reads the data from devices signal quantities to expect the evaluation of the severity of pneumonia as well as expecting the output of the illness using the Internet of Medical Things.

Keywords: Diagnostic, Influenza virus, syncytial virus, IoMT, Fitness function, Decision tree.