Detailed Information

Cited 0 time in webofscience Cited 25 time in scopus
Metadata Downloads

Efficient Large-scale Medical Data (eHealth Big Data) Analytics in Internet of Things

Full metadata record
DC FieldValueLanguage
dc.contributor.authorPlageras, Andreas P.-
dc.contributor.authorStergiou, Christos-
dc.contributor.authorKokkonis, George-
dc.contributor.authorPsannis, Kostas E.-
dc.contributor.authorIshibashi, Yutaka-
dc.contributor.authorKim, Byung-Gyu-
dc.contributor.authorGupta, B. Brij-
dc.date.available2021-02-22T11:12:43Z-
dc.date.issued2017-07-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/8232-
dc.description.abstractRecent technologies such as Big Data could be used in order to help the improvement of other fields except for the telecommunication field. Due to the Health field, the Big Data technology could contribute with the aim to help for the purpose of analysis and management of the huge amounts of health data. The main objective of this research proposal is an analytical study of the technologies IoT, Cloud Computing (CC) and large-scale data (Big Data) to resolve various issues facing the health sector in relation to these technologies. The purpose of the research proposal is the collection of medical (e-health) big data in real time. The collection will be performed by sensor devices and actuators, which will wear patients who suffer from various ailments. Then is following, the transfer of these data through a network to a cloud server. Additionally, these data will be processed in the cloud which makes its analysis so as to become meaningless. By the analysis of these data is done the data mining. Finally, to address the various problems in the health sector, the transfer of the analyzed health data will be held by the devices of the relevant persons. Also, in our study, we will deal with the security of medical data which constitute personal data and must be protected. © 2017 IEEE.-
dc.format.extent7-
dc.language영어-
dc.language.isoENG-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.titleEfficient Large-scale Medical Data (eHealth Big Data) Analytics in Internet of Things-
dc.typeArticle-
dc.identifier.doi10.1109/CBI.2017.3-
dc.identifier.scopusid2-s2.0-85029407008-
dc.identifier.bibliographicCitationProceedings - 2017 IEEE 19th Conference on Business Informatics, CBI 2017, v.2, pp 21 - 27-
dc.citation.titleProceedings - 2017 IEEE 19th Conference on Business Informatics, CBI 2017-
dc.citation.volume2-
dc.citation.startPage21-
dc.citation.endPage27-
dc.type.docTypeConference Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusCloud computing-
dc.subject.keywordPlusData mining-
dc.subject.keywordPlusHealth-
dc.subject.keywordPlusHealth care-
dc.subject.keywordPlusInternet of things-
dc.subject.keywordPlusAnalytical studies-
dc.subject.keywordPlusCloud servers-
dc.subject.keywordPlusData technologies-
dc.subject.keywordPlusHealth data-
dc.subject.keywordPlusLarge scale data-
dc.subject.keywordPlusMedical data-
dc.subject.keywordPlusResearch proposals-
dc.subject.keywordPlusSensor device-
dc.subject.keywordPlusBig data-
dc.subject.keywordAuthorBig Data-
dc.subject.keywordAuthorCloud Computing-
dc.subject.keywordAuthorHealthcare-
dc.subject.keywordAuthorIoT-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/8012935-
Files in This Item
Go to Link
Appears in
Collections
ICT융합공학부 > IT공학전공 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Byung Gyu photo

Kim, Byung Gyu
공과대학 (인공지능공학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE