IoT of Healthcare Innovation Solutions for Predictable Virus Detection
Main Article Content
Abstract
The evolution of health care systems from old models to more personalized frameworks facilitates easier diagnosis, treatment, and monitoring of patients, benefiting numerous individuals. Individuals receive remote treatment and care, which is essential for some during the global crisis exemplified by Predictable Virus Detection. This manuscript, A medical platform features an architecture reliant on middleware and database support for individuals with Coronavirus, primarily serving three user categories. The administrator is categorized into two user groups: doctors and patients. The doctor has an app that questions through the patient so he knows the patient that is being visited and extracts the health identity from him, and he questions the patient for sending him an OTP in the event that the patient does not have a mobile screen or an Internet connection. Alternatively, if QR inquires whether his laptop is intelligent and connected to the Internet. The individual will gain access to the system subsequent to the doctor's examination. The patient will conduct a self-examination using his equipment and present the results to his doctor. The physician is able to provide a prescription each time he transmits new readings. If the prescription is accurate, retain it and escalate the dosage; do not incorporate an additional dose. Physicians will utilize the prescription interface to transmit the prescription for cloud authentication and acquire an encrypted QR code, which will subsequently be provided to the medication receiver. The patient is afforded the opportunity to examine medicine information through the recipient's application. The entitlement to access QR protected cloud data is perpetual. The pharmacy can dispense the medication just as prescribed until the QR code's expiration date. The initiative aims to enhance access to healthcare facilities for patients and physicians, while adhering to GDPR regulations.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.