Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare

The gradual prevalence of Internet of Things (IoT) and wireless communication technologies has enabled the wide adoption of various smart devices (e.g., smart watches) in provisioning the healthcare services to massive users. Besides monitoring the real-time health signals or conditions of users, sm...

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Autores principales:	Qiyun Zhang, Yuan Zhang, Caizhong Li, Chao Yan, Yucong Duan, Hao Wang
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Sport location user clustering privacy healthcare service simhash wireless network Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/0fafd1c62d0a4ad3b318406bbb8d0768
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id	oai:doaj.org-article:0fafd1c62d0a4ad3b318406bbb8d0768
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spelling	oai:doaj.org-article:0fafd1c62d0a4ad3b318406bbb8d07682021-11-19T00:05:03ZSport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare2169-353610.1109/ACCESS.2021.3051051https://doaj.org/article/0fafd1c62d0a4ad3b318406bbb8d07682021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9320517/https://doaj.org/toc/2169-3536The gradual prevalence of Internet of Things (IoT) and wireless communication technologies has enabled the wide adoption of various smart devices (e.g., smart watches) in provisioning the healthcare services to massive users. Besides monitoring the real-time health signals or conditions of users, smart devices can also record a series of sport-related user information such as user location information at a certain time point. The location sequence information is valuable to cluster the users who share the similar sport preferences or habits and therefore, is also playing a key role in providing wireless healthcare services to these users. However, the user location information is often sensitive to certain wireless users as they decline to reveal their daily sport behavior patterns to others. In this situation, a natural challenge is raised in securing the sensitive user location information while mining the users’ daily sport behavior patterns and provisioning better healthcare services to the users. Considering this challenge, we take advantage of the well-known SimHash technique to protect users’ location privacy while clustering the users who share similar sport preferences or habits for better healthcare services. At last, we validate the feasibility of the proposal through a set of simulated experiments conducted on a real-world dataset. Reported results demonstrate that our solution performs better than the other two competitive ones while securing user location information.Qiyun ZhangYuan ZhangCaizhong LiChao YanYucong DuanHao WangIEEEarticleSport locationuser clusteringprivacyhealthcare servicesimhashwireless networkElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 12906-12913 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Sport location user clustering privacy healthcare service simhash wireless network Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Sport location user clustering privacy healthcare service simhash wireless network Electrical engineering. Electronics. Nuclear engineering TK1-9971 Qiyun Zhang Yuan Zhang Caizhong Li Chao Yan Yucong Duan Hao Wang Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare
description	The gradual prevalence of Internet of Things (IoT) and wireless communication technologies has enabled the wide adoption of various smart devices (e.g., smart watches) in provisioning the healthcare services to massive users. Besides monitoring the real-time health signals or conditions of users, smart devices can also record a series of sport-related user information such as user location information at a certain time point. The location sequence information is valuable to cluster the users who share the similar sport preferences or habits and therefore, is also playing a key role in providing wireless healthcare services to these users. However, the user location information is often sensitive to certain wireless users as they decline to reveal their daily sport behavior patterns to others. In this situation, a natural challenge is raised in securing the sensitive user location information while mining the users’ daily sport behavior patterns and provisioning better healthcare services to the users. Considering this challenge, we take advantage of the well-known SimHash technique to protect users’ location privacy while clustering the users who share similar sport preferences or habits for better healthcare services. At last, we validate the feasibility of the proposal through a set of simulated experiments conducted on a real-world dataset. Reported results demonstrate that our solution performs better than the other two competitive ones while securing user location information.
format	article
author	Qiyun Zhang Yuan Zhang Caizhong Li Chao Yan Yucong Duan Hao Wang
author_facet	Qiyun Zhang Yuan Zhang Caizhong Li Chao Yan Yucong Duan Hao Wang
author_sort	Qiyun Zhang
title	Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare
title_short	Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare
title_full	Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare
title_fullStr	Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare
title_full_unstemmed	Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare
title_sort	sport location-based user clustering with privacy-preservation in wireless iot-driven healthcare
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/0fafd1c62d0a4ad3b318406bbb8d0768
work_keys_str_mv	AT qiyunzhang sportlocationbaseduserclusteringwithprivacypreservationinwirelessiotdrivenhealthcare AT yuanzhang sportlocationbaseduserclusteringwithprivacypreservationinwirelessiotdrivenhealthcare AT caizhongli sportlocationbaseduserclusteringwithprivacypreservationinwirelessiotdrivenhealthcare AT chaoyan sportlocationbaseduserclusteringwithprivacypreservationinwirelessiotdrivenhealthcare AT yucongduan sportlocationbaseduserclusteringwithprivacypreservationinwirelessiotdrivenhealthcare AT haowang sportlocationbaseduserclusteringwithprivacypreservationinwirelessiotdrivenhealthcare
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Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare

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