An IoT-fuzzy intelligent approach for holistic management of COVID-19 patients

In this study, an internet of things (IoT)-enabled fuzzy intelligent system is introduced for the remote monitoring, diagnosis, and prescription of treatment for patients with COVID-19. The main objective of the present study is to develop an integrated tool that combines IoT and fuzzy logic to prov...

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Vydáno v:Heliyon Ročník 10; číslo 1; s. e22454
Hlavní autoři: Rahman, Muhammad Zia Ur, Akbar, Muhammad Azeem, Leiva, Víctor, Martin-Barreiro, Carlos, Imran, Muhammad, Riaz, Muhammad Tanveer, Castro, Cecilia
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Elsevier Ltd 15.01.2024
Elsevier
Témata:
Arduino microcontroller
blood pressure
computers
COVID-19 infection
Fuzzy logic
glucose
health services
Internet
Internet of things
Mobile application
patients
Personalized medicine
SARS-Cov2
Telemetry
temperature
wireless technology
Fuzzy logic
Internet of things
SARS-Cov2
Arduino microcontroller
Mobile application
Personalized medicine
Telemetry
ISSN:2405-8440, 2405-8440
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Shrnutí:In this study, an internet of things (IoT)-enabled fuzzy intelligent system is introduced for the remote monitoring, diagnosis, and prescription of treatment for patients with COVID-19. The main objective of the present study is to develop an integrated tool that combines IoT and fuzzy logic to provide timely healthcare and diagnosis within a smart framework. This system tracks patients' health by utilizing an Arduino microcontroller, a small and affordable computer that reads data from various sensors, to gather data. Once collected, the data are processed, analyzed, and transmitted to a web page for remote access via an IoT-compatible Wi-Fi module. In cases of emergencies, such as abnormal blood pressure, cardiac issues, glucose levels, or temperature, immediate action can be taken to monitor the health of critical COVID-19 patients in isolation. The system employs fuzzy logic to recommend medical treatments for patients. Sudden changes in these medical conditions are remotely reported through a web page to healthcare providers, relatives, or friends. This intelligent system assists healthcare professionals in making informed decisions based on the patient's condition.
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ISSN:2405-8440
2405-8440
DOI:10.1016/j.heliyon.2023.e22454