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Machine Learning Based Healthcare Service Dissemination Using Social Internet of Things and Cloud Architecture in Smart Cities

Author

Listed:
  • Vishnu Kumar Kaliappan

    (Department of Computer Science and Engineering, KPR Institute of Engineering and Technology, Coimbatore 641407, Tamil Nadu, India)

  • Sundharamurthy Gnanamurthy

    (Department of Computer Science and Engineering, Kuppam Engineering College Chittoor, Kuppam 517425, Andhra Pradesh, India)

  • Abid Yahya

    (Department of Electrical, Computer and Telecommunications Engineering, Botswana International University of Science and Technology, Palapye 10071, Botswana)

  • Ravi Samikannu

    (Department of Electrical, Computer and Telecommunications Engineering, Botswana International University of Science and Technology, Palapye 10071, Botswana)

  • Muhammad Babar

    (Robotics and Internet of Things Lab, Prince Sultan University, Riyadh 12435, Saudi Arabia)

  • Basit Qureshi

    (College of Computer and Information Sciences, Prince Sultan University, Riyadh 12435, Saudi Arabia)

  • Anis Koubaa

    (Robotics and Internet of Things Lab, Prince Sultan University, Riyadh 12435, Saudi Arabia)

Abstract

Smart healthcare using the cloud and the Internet of Things (IoT) allows for remote patient monitoring, real-time data collection, improved data security, and cost-effective storage and analysis of healthcare data. This paper proposes an information-centric dissemination scheme (ICDS) for smart healthcare services in smart cities. The proposed scheme addresses the time sensitiveness of healthcare data and aims to ensure consistent dissemination. The ICDS uses decision-tree learning to classify requests based on time-sensitive features, allowing prioritization of access. The scheme also involves segregating sensitive information and distributing digital health data within the classified time to retain time sensitiveness and prioritize access. The learning is then modified for the leaves based on data significance and minimum resources to reduce waiting times and improve availability.

Suggested Citation

  • Vishnu Kumar Kaliappan & Sundharamurthy Gnanamurthy & Abid Yahya & Ravi Samikannu & Muhammad Babar & Basit Qureshi & Anis Koubaa, 2023. "Machine Learning Based Healthcare Service Dissemination Using Social Internet of Things and Cloud Architecture in Smart Cities," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5457-:d:1102209
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    References listed on IDEAS

    as
    1. Amjad Rehman & Tanzila Saba & Khalid Haseeb & Teg Alam & Jaime Lloret, 2022. "Sustainability Model for the Internet of Health Things (IoHT) Using Reinforcement Learning with Mobile Edge Secured Services," Sustainability, MDPI, vol. 14(19), pages 1-14, September.
    2. Amjad Rehman Khan & Tanzila Saba & Tariq Sadad & Seng-phil Hong & Daqing Gong, 2022. "Cloud-Based Framework for COVID-19 Detection through Feature Fusion with Bootstrap Aggregated Extreme Learning Machine," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-7, May.
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    Cited by:

    1. Kiyotoshi Kou & Yi Dou & Ichiro Arai, 2024. "Analysis of the Forces Driving Public Hospitals’ Operating Costs Using LMDI Decomposition: The Case of Japan," Sustainability, MDPI, vol. 16(2), pages 1-15, January.

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