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International Journal of Fuzzy Logic and Intelligent Systems 2024; 24(3): 295-305

Published online September 25, 2024

https://doi.org/10.5391/IJFIS.2024.24.3.295

© The Korean Institute of Intelligent Systems

E-Healthcare System Using IoT-Based Wearable Device

Marvy Badr Monir Mansour, Amr Ayman, and Marwan Yehia

Department of Electrical Engineering, The British University in Egypt, Cairo, Egypt

Correspondence to :
Marvy Badr Monir Mansour (marvy.badr@bue.edu.eg)

Received: May 15, 2023; Revised: May 30, 2024; Accepted: August 24, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

E-healthcare services allow patients to receive the healthcare they need while becoming familiar with their local surroundings. In this study, an e-healthcare matching service system was developed to meet these standards, ensuring patients feel confident that the system is accountable for their healthcare needs while also accommodating healthcare travel schedules, practitioners’ licenses, and legal requirements. This system takes a comprehensive approach by focusing on the needs of patients rather than solely on the needs of healthcare practitioners or professionals. Specifically, it prioritizes individual patient needs and, rather than overlooking these needs when scheduling conflicts arise, aims to accommodate them as carefully as possible. Finally, we implemented and tested the system, and the results indicate that the model used in this study can enhance medical sustainability and significantly reduce medical costs.

Keywords: E-healthcare services, Embedded systems and sensors, Internet of Medical Things, Mobile telemedicine services, Telemonitoring systems

No potential conflict of interest relevant to this article was reported.

Marvy Badr Monir Mansour is currently working as an assistant professor of Computer Engineering in the Electrical Engineering Department at the Faculty of Engineering, The British University in Egypt (BUE), Egypt. Dr. Mansour earned her Ph.D. in 2018 from the Computer and Systems Engineering Department at Ain Shams University, Egypt. She received her M.Sc. in 2013 and B.Sc. (IEng) in 2007 with honors from the Computer Engineering Department at the Arab Academy for Science, Technology, and Maritime Transport (AASTMT), Egypt. Since 2019, Dr. Mansour has served as an advisory board member and reviewer for various prestigious journals and conferences. She has numerous notable publications in esteemed venues. Her research interests include, but are not limited to, cryptography, cybersecurity, AI, blockchain, vehicular networks, cloud computing, and edge technologies.

Amr Ayman is a computer engineer. He received his B.Sc. in 2021 from the Electrical Engineering Department at the Faculty of Engineering, The British University in Egypt (BUE). His research interests include E-healthcare, the Internet of Things, routing protocols, and wireless sensor networks.

Marwan Yehia is an IT Service Desk Engineer at Orange Business Services. He received his B.Sc. in 2021 from the Electrical Engineering Department at the Faculty of Engineering, The British University in Egypt (BUE). His research interests include computer networks, E-healthcare, and the Internet of Things.

Article

Original Article

International Journal of Fuzzy Logic and Intelligent Systems 2024; 24(3): 295-305

Published online September 25, 2024 https://doi.org/10.5391/IJFIS.2024.24.3.295

Copyright © The Korean Institute of Intelligent Systems.

E-Healthcare System Using IoT-Based Wearable Device

Marvy Badr Monir Mansour, Amr Ayman, and Marwan Yehia

Department of Electrical Engineering, The British University in Egypt, Cairo, Egypt

Correspondence to:Marvy Badr Monir Mansour (marvy.badr@bue.edu.eg)

Received: May 15, 2023; Revised: May 30, 2024; Accepted: August 24, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

E-healthcare services allow patients to receive the healthcare they need while becoming familiar with their local surroundings. In this study, an e-healthcare matching service system was developed to meet these standards, ensuring patients feel confident that the system is accountable for their healthcare needs while also accommodating healthcare travel schedules, practitioners’ licenses, and legal requirements. This system takes a comprehensive approach by focusing on the needs of patients rather than solely on the needs of healthcare practitioners or professionals. Specifically, it prioritizes individual patient needs and, rather than overlooking these needs when scheduling conflicts arise, aims to accommodate them as carefully as possible. Finally, we implemented and tested the system, and the results indicate that the model used in this study can enhance medical sustainability and significantly reduce medical costs.

Keywords: E-healthcare services, Embedded systems and sensors, Internet of Medical Things, Mobile telemedicine services, Telemonitoring systems

Fig 1.

Figure 1.

Flow-diagram of the proposed system.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 2.

Figure 2.

Abstract user interaction flowchart.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 3.

Figure 3.

OLED readings.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 4.

Figure 4.

File run.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 5.

Figure 5.

WEBRUN.bat terminal.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 6.

Figure 6.

Website homepage.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 7.

Figure 7.

Setup page.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 8.

Figure 8.

Live readings.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 9.

Figure 9.

User’s dashboard.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 10.

Figure 10.

Test phase for the system.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 11.

Figure 11.

Early experiments on breadboard.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 12.

Figure 12.

Schematic layout of system.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 13.

Figure 13.

PCB layout.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 14.

Figure 14.

Exterior view of final PCB.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 15.

Figure 15.

Interior view of final PCB.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 16.

Figure 16.

Database tables present in system.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 17.

Figure 17.

Tables of (a) tbl_devices and (b) tbl_users.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 18.

Figure 18.

Readings obtained and stored in table of tbl_readings.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 19.

Figure 19.

Terminal output.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 20.

Figure 20.

Device data readings.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 21.

Figure 21.

Figure A.1. Arduino code for reading output.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 22.

Figure 22.

Figure A.2. Python code for inserting readings to the database.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295

Fig 23.

Figure 23.

Figure A.3. Terminal output code.

The International Journal of Fuzzy Logic and Intelligent Systems 2024; 24: 295-305https://doi.org/10.5391/IJFIS.2024.24.3.295