Abstract
Numerous members of society struggle with health care issues, and despite the use of sensing technology, diseases in the body are still unable to be detected. The main cause of this identification process failure is the absence of any recognized virtual technology on the market.
The majority of health care solicitations seek to create a specific application that simply delivers data on sensing values and ignores the virtual representation of those values. So, in order to detect the existence of viruses inside the body, this article offers an integration platform that links sensing devices with Virtual/Audio Reality (VR/AR) approaches. Additionally, a specific form of swarm intelligence algorithm known as Fruit Fly (FF) is used in the recognition process with a modified fitness function. The FF technique offers a lot of low layer awareness, which improves the output for efficient operation. The proposed AR/VR technique is used with biological sensors to analyze the real-time situations, and five different case studies are divided.
It is logical to conclude from the experimental results that all validated case studies offer excellent productivity and are adaptable to all environmental circumstances.