Abstract
Many people in society are facing problems related to health care, and diseases in the body are unable to be identified even with the presence of sensing technologies. The major reason for such failures in the identification process is that no virtual technologies are identified in the market. Most healthcare solicitations aim to design a particular application that provides information only about sensing values and fails to recall the virtual representation of that represented values. Therefore, this article provides an integration platform that connects the sensing devices with virtual reality/audio reality (VR/AR) techniques, which are applied in real time for detecting the presence of infections inside the body. In addition, one type of swarm intelligent algorithm is implemented in the recognition procedure with a modified fitness function and it is termed fruit fly optimization (FFO). The process of FFO provides much low layer perception, thus enhancing the output for smooth operation. To examine the real-time conditions, the projected AR/VR procedure is applied with biomedical sensors where three different case studies are separated. From the comparative numerical results, it is pragmatic that the proposed method provides better numerical results with 65% full-scale representations and less than 0.5 dB of distortion at 0.3% tuning force.