• Login
    View Item 
    •   Home
    • Electrical and Computer Engineering
    • Faculty Research and Publications
    • Articles
    • View Item
    •   Home
    • Electrical and Computer Engineering
    • Faculty Research and Publications
    • Articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Effat University RepositoryCommunitiesPublication DateAuthorsTitlesSubjectsPublisherJournalTypeDepartmentSupervisorThis CollectionPublication DateAuthorsTitlesSubjectsPublisherJournalTypeDepartmentSupervisorProfilesView

    My Account

    Login

    Statistics

    Display statistics

    Interoperable IoMT Approach for Remote Diagnosis with Privacy-Preservation Perspective in Edge Systems

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    Interoperable IoMT Approach for ...
    Size:
    6.041Mb
    Format:
    PDF
    Download
    Author
    Subramaniam, E.V.D.
    Srinivasan, K.
    Mian Qaisar, Saeed cc
    Pławiak, P.
    Subject
    Internet of Medical Things (IoMT)
    patient privacy
    authentication
    clustering
    Date
    2023-08-28
    
    Metadata
    Show full item record
    Abstract
    The emergence of the Internet of Medical Things (IoMT) has brought together developers from the Industrial Internet of Things (IIoT) and healthcare providers to enable remote patient diagnosis and treatment using mobile-device-collected data. However, the utilization of traditional AI systems raises concerns about patient privacy. To address this issue, we present a privacy-enhanced approach for illness diagnosis within the IoMT framework. Our proposed interoperable IoMT implementation focuses on optimizing IoT network performance, including throughput, energy consumption, latency, packet delivery ratio, and network longevity. We achieve these improvements using techniques such as device authentication, energy-efficient clustering, environmental monitoring using Circular-based Hidden Markov Model (C-HMM), data verification using Awad’s Entropy-based Ten-Fold Cross Entropy Verification (TCEV), and data confidentiality using Twine-LiteNet-based encryption. We employ the Search and Rescue Optimization algorithm (SRO) for optimal route selection, and the encrypted data are securely stored in a cloud server. With extensive network simulations using ns-3, our approach demonstrates substantial enhancements in the specified performance metrics compared with previous works. Specifically, we observe a 20% increase in throughput, a 15% reduction in packet drop rate (PDR), a 35% improvement in network lifetime, and a 10% decrease in energy consumption and delay. These findings underscore the efficacy of our approach in enhancing IoT network interoperability and protection, fostering improved patient care and diagnostic capabilities.
    Department
    Electrical and Computer Engineering
    Publisher
    MDPI
    Journal title
    Sensors
    DOI
    https://doi.org/10.3390/s23177474
    ae974a485f413a2113503eed53cd6c53
    https://doi.org/10.3390/s23177474
    Scopus Count
    Collections
    Articles

    entitlement

     
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.