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Ubiquitous Healthcare Monitoring over Wireless Networks

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: 1 October 2025 | Viewed by 515

Special Issue Editor


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Guest Editor
Wireless Information and Networking Lab, Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, Republic of Korea
Interests: healthcare; wireless local area networks; artificial intelligence

Special Issue Information

Dear Colleagues,

The success of smart watches and health trackers has attracted a growing research interest in continuous health monitoring systems. These systems follow a three-tier architecture containing a sensing system, communication network and a data processing framework. The fifth-generation cellular network and the Wi-Fi 7 networks are capable of ultra-low latency communication, which is critical for the timely delivery of sensed data and their real-time processing. Quality-of-service compliance is necessary to ensure that critical monitoring data are delivered within strict delay (< 1 millisecond) and reliability (BER< 10^(−6)) bounds. Moreover, real-time processing of the collected sensor data can play a critical role in autonomous first aid and alert generation systems by using novel AI-based algorithms. The development of ultra-high reliability and low latency communication (URLLC) with fast and robust AI models along with real-time data processing are critical in realizing such systems.

This Special Issue invites original research articles on the following topics:

  • URLLC over Beyond 5G and 6G networks.
  • URLLC over IEEE 802.11 WLANs.
  • AI models for wireless communication.
  • AI for biomedical signal processing.

Dr. Yazdan Ahmad Qadri
Guest Editor

Manuscript Submission Information

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Keywords

  • internet of things in healthcare
  • QoS communication
  • Wi-Fi
  • URLLC
  • artificial intelligence
  • digital signal processing

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Published Papers (1 paper)

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Research

18 pages, 713 KiB  
Article
Energy-Aware Ultra-Reliable Low-Latency Communication for Healthcare IoT in Beyond 5G and 6G Networks
by Adeel Iqbal, Tahir Khurshaid, Ali Nauman and Sang-Bong Rhee
Sensors 2025, 25(11), 3474; https://doi.org/10.3390/s25113474 - 31 May 2025
Viewed by 94
Abstract
Ultra-reliable low-latency communication (URLLC) is a cornerstone of beyond 5G and future 6G networks, particularly for mission-critical applications such as the healthcare Internet of Things. In applications such as remote surgery, emergency services, and real-time health monitoring, it is imperative to ensure stringent [...] Read more.
Ultra-reliable low-latency communication (URLLC) is a cornerstone of beyond 5G and future 6G networks, particularly for mission-critical applications such as the healthcare Internet of Things. In applications such as remote surgery, emergency services, and real-time health monitoring, it is imperative to ensure stringent latency and reliability requirements. However, the energy constraints of wearable and implantable medical devices pose stringent challenges to conventional URLLC methods. This paper proposes an energy-aware URLLC framework that dynamically prioritizes healthcare traffic to optimize transmission energy and reliability. The framework integrates a priority-aware packet scheduler, adaptive transmission control, and edge-enabled reliability management. Extensive Monte Carlo simulations are carried out on various network loads and varying edge computing delays to evaluate performance metrics, like latency, throughput, reliability score, energy consumption, delay violation rate, and Jain’s fairness index. Results illustrate that the suggested technique achieves lower latency, energy consumption, and delay violation rates and higher throughput and reliability scores, sacrificing Jain’s fairness index graciously at peak network overload. This study is a potential research lead for green URLLC in healthcare IoT systems to come. Full article
(This article belongs to the Special Issue Ubiquitous Healthcare Monitoring over Wireless Networks)
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