Remote Monitoring of COVID-19 Patients Using Multisensor Body Area Network Innovative System

Author:

Al-Barazanchi Israa12ORCID,Hashim Wahidah1ORCID,Ahmed Alkahtani Ammar3ORCID,Rasheed Abdulshaheed Haider24ORCID,Muwafaq Gheni Hassan5ORCID,Murthy Aparna6ORCID,daghighi Elika7ORCID,Shawkat Shihab A.8ORCID,Jaaz Zahraa A.19ORCID

Affiliation:

1. College of Computing and Informatics, Universiti Tenaga Nasional (UNITEN), Kajang, Malaysia

2. Computer Engineering Techniques Department, Baghdad College of Economic Sciences University, Baghdad, Iraq

3. Institute of Sustainable Energy, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Selangor, Malaysia

4. Department of Medical Instrumentation Technical Engineering, Medical Technical College, Al-Farahidi University, Baghdad, Iraq

5. Computer Techniques Engineering Department, Al-Mustaqbal University College, Hillah 51001, Iraq

6. Professional Engineers in Ontario, North York, Toronto, Ontario M2N 6K9, Canada

7. Technical and Vocational University, Tehran, Iran

8. University of Samarra, Samarra, Iraq

9. Computer Department, College of Science, Al-Nahrain University, Jadriya, Baghdad, Iraq

Abstract

As of late 2019, the COVID19 pandemic has been causing huge concern around the world. Such a pandemic posed serious threats to public safety, the well-being of healthcare workers, and the overall health of the population. If automation can be implemented in healthcare systems, patients could be better cared for and health industries could be less burdened. To combat such challenges, e-health requires apps and intelligent systems. Using WBAN sensors and networks, a doctor or medical professional can advise patients on the best course of action. Patients’ fitness could be assessed using WBAN sensors without interfering with their daily activities. When designing a monitoring system, system performance reliability for competent healthcare is critical. Existing research has failed to create a large device capable of handling a large network or to improve WBAN topologies for fast transmitting and receiving patient data. As a result, in this research, we create a multisensor WBAN (MSWBAN) intelligent system for transmitting and receiving critical patient data. To gather information from all cluster nodes and send it to multisensor WBAN, a novel additive distance-threshold routing protocol (ADTRP) is proposed. In small networks where data are managed by the transmitting node and the best data route is determined, this protocol has less redundancy. An edge-cutting-based routing optimization (ES-EC-R ES-EC-RO) is used to find the best route. The Trouped blowfish MD5 (TB-MD5) algorithm is used to encrypt and decrypt data, and the encrypted data are stored in a cloud database for security. The performance metrics of our proposed model are compared to current techniques for the best results. End-to-end latency is 63 ms, packet delivery is 95%, security is 95.7%, and throughput is 9120 bps, according to the results. The purpose of this article is to encourage engineers and front-line workers to develop digital health systems for tracking and controlling virus outbreaks.

Funder

Universiti Tenaga Nasional

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

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