Pervasive intelligent multi-node health monitoring system for monitoring basketball players health and energy using IoT and 6G technology

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS
Duqian Ding, Juan Li
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引用次数: 3

Abstract

Effective health monitoring of players in team sports like basketball allows for understanding external requirements and internal response concerning exercise and competition phases. The explosive growth of wireless devices stimulates the advancement of the internet-of-things (IoT) and 6G technologies, capable of connecting enormous and various “things” through wireless communications. Players face health issues while playing basketball are severe lower body lesions like ankle sprains, shortness of breath, teeth, head, fingers, and hand. To overcome these issues, in this paper, the Pervasive Intelligent Multi-node Health Monitoring System (PIMN-HMS) has been proposed for basketball player’s continuous health tracking based on IoT and 6G communication. With the aid of wearable monitoring sensors to gathers health information and monitor exercise records. The system consists of several sensor nodes, a network coordinator, which monitors physical movements and heart rate, and a personal server on a personal digital assistant using 6G networks. The numerical results have been performed, and the suggested PIMN-HMS model enhances the accuracy ratio of 96.7%, prediction ratio of 97.3%, low latency ratio of 11.2%, delay rate of 22.3%, and efficiency ratio of 98.7% compared to other existing models.
利用物联网和6G技术监测篮球运动员健康和能量的普适智能多节点健康监测系统
在篮球等团队运动中,对运动员进行有效的健康监测,可以了解运动和比赛阶段的外部要求和内部反应。无线设备的爆炸式增长刺激了物联网(IoT)和6G技术的发展,这些技术能够通过无线通信连接巨大而多样的“事物”。球员在打篮球时面临的健康问题是严重的下半身损伤,如脚踝扭伤、呼吸短促、牙齿、头部、手指和手。针对这些问题,本文提出了基于物联网和6G通信的篮球运动员持续健康跟踪的普适智能多节点健康监测系统(PIMN-HMS)。借助可穿戴式监测传感器收集健康信息,监测运动记录。该系统由多个传感器节点、监测身体运动和心率的网络协调器以及使用6G网络的个人数字助理上的个人服务器组成。数值计算结果表明,PIMN-HMS模型与现有模型相比,准确率提高了96.7%,预测率提高了97.3%,低延迟率提高了11.2%,延迟率提高了22.3%,效率提高了98.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
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