Internet of Things with Artificial Intelligence for Health Care Security

Ghazal, T M (2021) Internet of Things with Artificial Intelligence for Health Care Security. Arabian Journal for Science and Engineering. ISSN 2193-567X

[thumbnail of 22.pdf] Text
22.pdf - Published Version

Download (2MB)

Abstract

In recent years, health care facilities are moving towards technological advancements for precise patient monitoring and record management. Though it is technically advanced, the health care information and communication technology network's security is a significant challenge for health care. With the aid of standard algorithms, unstructured data existing outside organized databases (i.e., electronic documents and reports) is difficult to arrange and secure. The existing clustering method has a disadvantage of efficiency issues for recovering data transfer. This paper proposes the Internet of Things with Artificial Intelligence System (IoT-AIS) for health care security. Wireless sensor networks are developed by IoT technology. IoT network is used to bridge the physical and digital world. IoT-AIS is used to monitor the patient’s data and encrypt them. The encrypted data are stored in the cloud to maintain the patient data to access remotely. The IoT-AIS dashboard provides an individualized user interface for individual patients to maintain their records individually with single-user access. The proposed paper's simulation analysis proved that the Patient Record of health care could be encrypted and provide individualized access. The experimental results of IoT-AIS achieve the highest data transmission rate to 98.14% and the highest delivery rate of (98.90%), high period of standard responses (93.79%), less delay estimation (10.76%), improved throughput (98.23%), effective bandwidth monitoring (83.14%) energy usage (8.56%) and highest performance rate (98.4%) when compared to other methods.

Affiliation: Skyline University College
SUC Author(s): Ghazal, T M ORCID: https://orcid.org/0000-0003-0672-7924
All Author(s): Ghazal, T M
Item Type: Article
Uncontrolled Keywords: Technology, Wireless, Dashboard, Encrypted, Patient, Database, Artifcial Intelligence
Subjects: B Information Technology > BM Artificial Intelligence
Divisions: Skyline University College > School of IT
Depositing User: Mr Veeramani Rasu
Date Deposited: 11 Feb 2022 12:50
Last Modified: 11 Feb 2022 12:50
URI: https://research.skylineuniversity.ac.ae/id/eprint/83
Publisher URL: https://doi.org/10.1007/s13369-021-06083-8
Publisher OA policy: https://v2.sherpa.ac.uk/id/publication/21688
Related URLs:

Actions (login required)

View Item
View Item
Statistics for SkyRep ePrint 83 Statistics for this ePrint Item