Efficient Large-scale Medical Data (eHealth Big Data) Analytics in Internet of Things
DC Field | Value | Language |
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dc.contributor.author | Plageras, Andreas P. | - |
dc.contributor.author | Stergiou, Christos | - |
dc.contributor.author | Kokkonis, George | - |
dc.contributor.author | Psannis, Kostas E. | - |
dc.contributor.author | Ishibashi, Yutaka | - |
dc.contributor.author | Kim, Byung-Gyu | - |
dc.contributor.author | Gupta, B. Brij | - |
dc.date.available | 2021-02-22T11:12:43Z | - |
dc.date.issued | 2017-07 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/8232 | - |
dc.description.abstract | Recent 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.extent | 7 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Efficient Large-scale Medical Data (eHealth Big Data) Analytics in Internet of Things | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/CBI.2017.3 | - |
dc.identifier.scopusid | 2-s2.0-85029407008 | - |
dc.identifier.bibliographicCitation | Proceedings - 2017 IEEE 19th Conference on Business Informatics, CBI 2017, v.2, pp 21 - 27 | - |
dc.citation.title | Proceedings - 2017 IEEE 19th Conference on Business Informatics, CBI 2017 | - |
dc.citation.volume | 2 | - |
dc.citation.startPage | 21 | - |
dc.citation.endPage | 27 | - |
dc.type.docType | Conference Paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Cloud computing | - |
dc.subject.keywordPlus | Data mining | - |
dc.subject.keywordPlus | Health | - |
dc.subject.keywordPlus | Health care | - |
dc.subject.keywordPlus | Internet of things | - |
dc.subject.keywordPlus | Analytical studies | - |
dc.subject.keywordPlus | Cloud servers | - |
dc.subject.keywordPlus | Data technologies | - |
dc.subject.keywordPlus | Health data | - |
dc.subject.keywordPlus | Large scale data | - |
dc.subject.keywordPlus | Medical data | - |
dc.subject.keywordPlus | Research proposals | - |
dc.subject.keywordPlus | Sensor device | - |
dc.subject.keywordPlus | Big data | - |
dc.subject.keywordAuthor | Big Data | - |
dc.subject.keywordAuthor | Cloud Computing | - |
dc.subject.keywordAuthor | Healthcare | - |
dc.subject.keywordAuthor | IoT | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/8012935 | - |
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