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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| Published in: | Heliyon Vol. 10; no. 1; p. e22454 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
England
Elsevier Ltd
15.01.2024
Elsevier |
| Subjects: | |
| ISSN: | 2405-8440, 2405-8440 |
| Online Access: | Get full text |
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| Abstract | 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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| AbstractList | 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.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. 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. |
| ArticleNumber | e22454 |
| Author | Leiva, Víctor Martin-Barreiro, Carlos Imran, Muhammad Castro, Cecilia Rahman, Muhammad Zia Ur Akbar, Muhammad Azeem Riaz, Muhammad Tanveer |
| Author_xml | – sequence: 1 givenname: Muhammad Zia Ur orcidid: 0000-0003-2304-8392 surname: Rahman fullname: Rahman, Muhammad Zia Ur organization: Department of Mechanical, Mechatronics and Manufacturing Engineering, University of Engineering and Technology Lahore, Faisalabad, Pakistan – sequence: 2 givenname: Muhammad Azeem surname: Akbar fullname: Akbar, Muhammad Azeem organization: Department of Software Engineering, LUT University, Lappeenranta, Finland – sequence: 3 givenname: Víctor orcidid: 0000-0003-4755-3270 surname: Leiva fullname: Leiva, Víctor email: victorleivasanchez@gmail.com organization: Escuela de Ingeniería Industrial, Universidad Católica de Valparaíso, Valparaíso, Chile – sequence: 4 givenname: Carlos orcidid: 0000-0002-8797-681X surname: Martin-Barreiro fullname: Martin-Barreiro, Carlos email: cmmartin@espol.edu.ec organization: Facultad de Ciencias Naturales y Matemáticas, ESPOL, Guayaquil, Ecuador – sequence: 5 givenname: Muhammad surname: Imran fullname: Imran, Muhammad organization: Department of Mechanical, Mechatronics and Manufacturing Engineering, University of Engineering and Technology Lahore, Faisalabad, Pakistan – sequence: 6 givenname: Muhammad Tanveer orcidid: 0000-0002-4391-9821 surname: Riaz fullname: Riaz, Muhammad Tanveer organization: Department of Mechanical, Mechatronics and Manufacturing Engineering, University of Engineering and Technology Lahore, Faisalabad, Pakistan – sequence: 7 givenname: Cecilia surname: Castro fullname: Castro, Cecilia organization: Centre of Mathematics, Universidade do Minho, Braga, Portugal |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38163138$$D View this record in MEDLINE/PubMed |
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| Keywords | Fuzzy logic Internet of things SARS-Cov2 Arduino microcontroller Mobile application Personalized medicine Telemetry |
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