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

Authors
Plageras, Andreas P.Stergiou, ChristosKokkonis, GeorgePsannis, Kostas E.Ishibashi, YutakaKim, Byung-GyuGupta, B. Brij
Issue Date
Jul-2017
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
Big Data; Cloud Computing; Healthcare; IoT
Citation
Proceedings - 2017 IEEE 19th Conference on Business Informatics, CBI 2017, v.2, pp 21 - 27
Pages
7
Journal Title
Proceedings - 2017 IEEE 19th Conference on Business Informatics, CBI 2017
Volume
2
Start Page
21
End Page
27
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/8232
DOI
10.1109/CBI.2017.3
ISSN
0000-0000
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.
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공과대학 (인공지능공학부)
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