Cloud-assisted Industrial Internet of Things (IIoT) – Enabled framework for health monitoring

The promising potential of the emerging Internet of Things (IoT) technologies for interconnected medical devices and sensors has played an important role in the next-generation healthcare industry for quality patient care. Because of the increasing number of elderly and disabled people, there is an...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computer networks (Amsterdam, Netherlands : 1999) Netherlands : 1999), 2016-06, Vol.101, p.192-202
Hauptverfasser: Hossain, M. Shamim, Muhammad, Ghulam
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 202
container_issue
container_start_page 192
container_title Computer networks (Amsterdam, Netherlands : 1999)
container_volume 101
creator Hossain, M. Shamim
Muhammad, Ghulam
description The promising potential of the emerging Internet of Things (IoT) technologies for interconnected medical devices and sensors has played an important role in the next-generation healthcare industry for quality patient care. Because of the increasing number of elderly and disabled people, there is an urgent need for a real-time health monitoring infrastructure for analyzing patients’ healthcare data to avoid preventable deaths. Healthcare Industrial IoT (HealthIIoT) has significant potential for the realization of such monitoring. HealthIIoT is a combination of communication technologies, interconnected apps, Things (devices and sensors), and people that would function together as one smart system to monitor, track, and store patients’ healthcare information for ongoing care. This paper presents a HealthIIoT-enabled monitoring framework, where ECG and other healthcare data are collected by mobile devices and sensors and securely sent to the cloud for seamless access by healthcare professionals. Signal enhancement, watermarking, and other related analytics will be used to avoid identity theft or clinical error by healthcare professionals. The suitability of this approach has been validated through both experimental evaluation, and simulation by deploying an IoT-driven ECG-based health monitoring service in the cloud.
doi_str_mv 10.1016/j.comnet.2016.01.009
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1816085874</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1389128616300019</els_id><sourcerecordid>4064694441</sourcerecordid><originalsourceid>FETCH-LOGICAL-c437t-3938ef11744f71de7bac5e4ac20e1e168f0b8c731298abc861971938606c224a3</originalsourceid><addsrcrecordid>eNp9kLFOwzAQhiMEEqXwBgyWWMqQ4Evc2FmQUFWgEhJLmS3XuVCXJC62A2LjHXhDngRXZWJguv-k__t19yfJOdAMKJRXm0zbrseQ5XHLKGSUVgfJCATPU07L6jDqQlQp5KI8Tk6831BKGcvFKJGz1g51qrw3PmBNFn09-OCMaqMM6GIqsQ1Zrk3_7MlksbDLS_L9-UXmvVq1EWic6vDduhfSWEfWqNqwJp3tTbAuMqfJUaNaj2e_c5w83c6Xs_v04fFuMbt5SDUreEiLqhDYAHDGGg418pXSU2RK5xQBoRQNXQnNC8groVZalFBxiExJS53nTBXjZLLP3Tr7OqAPsjNeY9uqHu3gJQgoqZgKzqL14o91YwfXx-sk8IqySgCH6GJ7l3bWe4eN3DrTKfchgcpd63Ij963LXeuSgoytR-x6j2F89s2gk14b7DXWxqEOsrbm_4AfDLiMug</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1790498171</pqid></control><display><type>article</type><title>Cloud-assisted Industrial Internet of Things (IIoT) – Enabled framework for health monitoring</title><source>Elsevier ScienceDirect Journals</source><creator>Hossain, M. Shamim ; Muhammad, Ghulam</creator><creatorcontrib>Hossain, M. Shamim ; Muhammad, Ghulam</creatorcontrib><description>The promising potential of the emerging Internet of Things (IoT) technologies for interconnected medical devices and sensors has played an important role in the next-generation healthcare industry for quality patient care. Because of the increasing number of elderly and disabled people, there is an urgent need for a real-time health monitoring infrastructure for analyzing patients’ healthcare data to avoid preventable deaths. Healthcare Industrial IoT (HealthIIoT) has significant potential for the realization of such monitoring. HealthIIoT is a combination of communication technologies, interconnected apps, Things (devices and sensors), and people that would function together as one smart system to monitor, track, and store patients’ healthcare information for ongoing care. This paper presents a HealthIIoT-enabled monitoring framework, where ECG and other healthcare data are collected by mobile devices and sensors and securely sent to the cloud for seamless access by healthcare professionals. Signal enhancement, watermarking, and other related analytics will be used to avoid identity theft or clinical error by healthcare professionals. The suitability of this approach has been validated through both experimental evaluation, and simulation by deploying an IoT-driven ECG-based health monitoring service in the cloud.</description><identifier>ISSN: 1389-1286</identifier><identifier>EISSN: 1872-7069</identifier><identifier>DOI: 10.1016/j.comnet.2016.01.009</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Cloud computing ; Cloud-assisted system ; ECG monitoring ; Electronic devices ; Health care ; Healthcare Industrial Internet of Things (HealthIIoT) ; Industrial applications ; Internet ; Internet of Things ; IoT-driven healthcare ; Medical devices ; Medical electronics ; Medical equipment ; Medical personnel ; Monitoring ; Monitoring systems ; Older people ; Patients ; People with disabilities ; Quality of care ; Sensors ; Signal watermarking ; Telemedicine ; Theft ; Validation studies ; Watermarking</subject><ispartof>Computer networks (Amsterdam, Netherlands : 1999), 2016-06, Vol.101, p.192-202</ispartof><rights>2016 Elsevier B.V.</rights><rights>Copyright Elsevier Sequoia S.A. Jun 4, 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c437t-3938ef11744f71de7bac5e4ac20e1e168f0b8c731298abc861971938606c224a3</citedby><cites>FETCH-LOGICAL-c437t-3938ef11744f71de7bac5e4ac20e1e168f0b8c731298abc861971938606c224a3</cites><orcidid>0000-0001-5906-9422 ; 0000-0002-9781-3969</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1389128616300019$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Hossain, M. Shamim</creatorcontrib><creatorcontrib>Muhammad, Ghulam</creatorcontrib><title>Cloud-assisted Industrial Internet of Things (IIoT) – Enabled framework for health monitoring</title><title>Computer networks (Amsterdam, Netherlands : 1999)</title><description>The promising potential of the emerging Internet of Things (IoT) technologies for interconnected medical devices and sensors has played an important role in the next-generation healthcare industry for quality patient care. Because of the increasing number of elderly and disabled people, there is an urgent need for a real-time health monitoring infrastructure for analyzing patients’ healthcare data to avoid preventable deaths. Healthcare Industrial IoT (HealthIIoT) has significant potential for the realization of such monitoring. HealthIIoT is a combination of communication technologies, interconnected apps, Things (devices and sensors), and people that would function together as one smart system to monitor, track, and store patients’ healthcare information for ongoing care. This paper presents a HealthIIoT-enabled monitoring framework, where ECG and other healthcare data are collected by mobile devices and sensors and securely sent to the cloud for seamless access by healthcare professionals. Signal enhancement, watermarking, and other related analytics will be used to avoid identity theft or clinical error by healthcare professionals. The suitability of this approach has been validated through both experimental evaluation, and simulation by deploying an IoT-driven ECG-based health monitoring service in the cloud.</description><subject>Cloud computing</subject><subject>Cloud-assisted system</subject><subject>ECG monitoring</subject><subject>Electronic devices</subject><subject>Health care</subject><subject>Healthcare Industrial Internet of Things (HealthIIoT)</subject><subject>Industrial applications</subject><subject>Internet</subject><subject>Internet of Things</subject><subject>IoT-driven healthcare</subject><subject>Medical devices</subject><subject>Medical electronics</subject><subject>Medical equipment</subject><subject>Medical personnel</subject><subject>Monitoring</subject><subject>Monitoring systems</subject><subject>Older people</subject><subject>Patients</subject><subject>People with disabilities</subject><subject>Quality of care</subject><subject>Sensors</subject><subject>Signal watermarking</subject><subject>Telemedicine</subject><subject>Theft</subject><subject>Validation studies</subject><subject>Watermarking</subject><issn>1389-1286</issn><issn>1872-7069</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNp9kLFOwzAQhiMEEqXwBgyWWMqQ4Evc2FmQUFWgEhJLmS3XuVCXJC62A2LjHXhDngRXZWJguv-k__t19yfJOdAMKJRXm0zbrseQ5XHLKGSUVgfJCATPU07L6jDqQlQp5KI8Tk6831BKGcvFKJGz1g51qrw3PmBNFn09-OCMaqMM6GIqsQ1Zrk3_7MlksbDLS_L9-UXmvVq1EWic6vDduhfSWEfWqNqwJp3tTbAuMqfJUaNaj2e_c5w83c6Xs_v04fFuMbt5SDUreEiLqhDYAHDGGg418pXSU2RK5xQBoRQNXQnNC8groVZalFBxiExJS53nTBXjZLLP3Tr7OqAPsjNeY9uqHu3gJQgoqZgKzqL14o91YwfXx-sk8IqySgCH6GJ7l3bWe4eN3DrTKfchgcpd63Ij963LXeuSgoytR-x6j2F89s2gk14b7DXWxqEOsrbm_4AfDLiMug</recordid><startdate>20160604</startdate><enddate>20160604</enddate><creator>Hossain, M. Shamim</creator><creator>Muhammad, Ghulam</creator><general>Elsevier B.V</general><general>Elsevier Sequoia S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>E3H</scope><scope>F2A</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-5906-9422</orcidid><orcidid>https://orcid.org/0000-0002-9781-3969</orcidid></search><sort><creationdate>20160604</creationdate><title>Cloud-assisted Industrial Internet of Things (IIoT) – Enabled framework for health monitoring</title><author>Hossain, M. Shamim ; Muhammad, Ghulam</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c437t-3938ef11744f71de7bac5e4ac20e1e168f0b8c731298abc861971938606c224a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Cloud computing</topic><topic>Cloud-assisted system</topic><topic>ECG monitoring</topic><topic>Electronic devices</topic><topic>Health care</topic><topic>Healthcare Industrial Internet of Things (HealthIIoT)</topic><topic>Industrial applications</topic><topic>Internet</topic><topic>Internet of Things</topic><topic>IoT-driven healthcare</topic><topic>Medical devices</topic><topic>Medical electronics</topic><topic>Medical equipment</topic><topic>Medical personnel</topic><topic>Monitoring</topic><topic>Monitoring systems</topic><topic>Older people</topic><topic>Patients</topic><topic>People with disabilities</topic><topic>Quality of care</topic><topic>Sensors</topic><topic>Signal watermarking</topic><topic>Telemedicine</topic><topic>Theft</topic><topic>Validation studies</topic><topic>Watermarking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hossain, M. Shamim</creatorcontrib><creatorcontrib>Muhammad, Ghulam</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>Library &amp; Information Sciences Abstracts (LISA)</collection><collection>Library &amp; Information Science Abstracts (LISA)</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computer networks (Amsterdam, Netherlands : 1999)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hossain, M. Shamim</au><au>Muhammad, Ghulam</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cloud-assisted Industrial Internet of Things (IIoT) – Enabled framework for health monitoring</atitle><jtitle>Computer networks (Amsterdam, Netherlands : 1999)</jtitle><date>2016-06-04</date><risdate>2016</risdate><volume>101</volume><spage>192</spage><epage>202</epage><pages>192-202</pages><issn>1389-1286</issn><eissn>1872-7069</eissn><abstract>The promising potential of the emerging Internet of Things (IoT) technologies for interconnected medical devices and sensors has played an important role in the next-generation healthcare industry for quality patient care. Because of the increasing number of elderly and disabled people, there is an urgent need for a real-time health monitoring infrastructure for analyzing patients’ healthcare data to avoid preventable deaths. Healthcare Industrial IoT (HealthIIoT) has significant potential for the realization of such monitoring. HealthIIoT is a combination of communication technologies, interconnected apps, Things (devices and sensors), and people that would function together as one smart system to monitor, track, and store patients’ healthcare information for ongoing care. This paper presents a HealthIIoT-enabled monitoring framework, where ECG and other healthcare data are collected by mobile devices and sensors and securely sent to the cloud for seamless access by healthcare professionals. Signal enhancement, watermarking, and other related analytics will be used to avoid identity theft or clinical error by healthcare professionals. The suitability of this approach has been validated through both experimental evaluation, and simulation by deploying an IoT-driven ECG-based health monitoring service in the cloud.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.comnet.2016.01.009</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-5906-9422</orcidid><orcidid>https://orcid.org/0000-0002-9781-3969</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1389-1286
ispartof Computer networks (Amsterdam, Netherlands : 1999), 2016-06, Vol.101, p.192-202
issn 1389-1286
1872-7069
language eng
recordid cdi_proquest_miscellaneous_1816085874
source Elsevier ScienceDirect Journals
subjects Cloud computing
Cloud-assisted system
ECG monitoring
Electronic devices
Health care
Healthcare Industrial Internet of Things (HealthIIoT)
Industrial applications
Internet
Internet of Things
IoT-driven healthcare
Medical devices
Medical electronics
Medical equipment
Medical personnel
Monitoring
Monitoring systems
Older people
Patients
People with disabilities
Quality of care
Sensors
Signal watermarking
Telemedicine
Theft
Validation studies
Watermarking
title Cloud-assisted Industrial Internet of Things (IIoT) – Enabled framework for health monitoring
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T10%3A29%3A50IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Cloud-assisted%20Industrial%20Internet%20of%20Things%20(IIoT)%20%E2%80%93%20Enabled%20framework%20for%20health%20monitoring&rft.jtitle=Computer%20networks%20(Amsterdam,%20Netherlands%20:%201999)&rft.au=Hossain,%20M.%20Shamim&rft.date=2016-06-04&rft.volume=101&rft.spage=192&rft.epage=202&rft.pages=192-202&rft.issn=1389-1286&rft.eissn=1872-7069&rft_id=info:doi/10.1016/j.comnet.2016.01.009&rft_dat=%3Cproquest_cross%3E4064694441%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1790498171&rft_id=info:pmid/&rft_els_id=S1389128616300019&rfr_iscdi=true