Challenges in human centric intelligent systems for wireless sensor networks: A state of art

Author:

Alferaidi Ali1,Yadav Kusum1ORCID,Alharbi Yasser1,Alshudukhi Jalawi Sulaiman1ORCID,Alreshidi Abdulrahman1,Alreshidi Eissa Jaber1,Kachout Mnaouer1,Sharif Md Haidar1

Affiliation:

1. College of Computer Science and Engineering University of Ha'il Ha'il Kingdom of Saudi Arabia

Abstract

AbstractHuman centric computing is a technique that is gaining more attention nowadays and integrates innovative processing methods for analyzing extensive data collection. Human centric intelligent systems focus on handling the interactions between customers, companies, communities and systems of computing to represent social and institutional concepts effectively. However, this interaction between the companies and customers will lead to various privacy challenges in human centric intelligent systems. This paper briefly studies cyber‐physical systems and various privacy challenges in human centric intelligent systems. In parallel, this article enunciates the human‐centric pipe water monitoring system framework in detail. It also discusses the smart body area network (SBAN) as a typical example of space cooperation. SBAN employs low‐power wireless devices in a compact form that can be incorporated inside the human body for health monitoring. This study examines the challenges of privacy, propagation, and trust assessment that human‐centric systems face.

Publisher

Wiley

Subject

Electrical and Electronic Engineering

Reference53 articles.

1. A survey on recent advances in vehicular network security, trust, and privacy;Zhaojun L;IEEE Trans Intell Transp Syst,2019

2. A robust ECC‐based provable secure authentication protocol with privacy preserving for industrial internet of things;Xiong L;IEEE Trans Industr Inform,2018

3. Enforcing position‐based confidentiality with machine learning paradigm through mobile edge computing in real‐time industrial informatics;Sangaiah AK;IEEE Trans Industr Inform,2019

4. Security and privacy in ubiquitous sensor networks;Perez AJ;J Informat Process Syst,2018

5. An enhanced security framework for home appliances in smart home;Kang WM;HCIS,2017

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3