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Big Data, Internet of Things and Cloud Convergence for E-Health Applications

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New Contributions in Information Systems and Technologies

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 353))

Abstract

Big data storage and processing are considered as one of the main applications for cloud computing systems. Furthermore, the development of the Internet of Things (IoT) paradigm has advanced the research on Machine to Machine (M2M) communications and enabled novel tele-monitoring architectures for E-Health applications. However, there is a need for converging current decentralized cloud systems, general software for processing big data and IoT systems. The purpose of this paper is to analyze existing components and methods of integrating big data processing with cloud M2M systems based on Remote Telemetry Units (RTUs) and to propose a converged E-Health architecture built on Exalead CloudView, a search based application. Finally, we discuss the main findings of the proposed implementation and future directions.

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References

  1. Kahn, E.: Natural language processing, big data, bioinformatics and biology. International Journal of Biology and Biomedical Engineering 8, 107–117 (2014)

    Google Scholar 

  2. Ochian, A., Suciu, G., Fratu, O., Suciu, V.: Big data search for environmental telemetry. In: IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), pp. 182–184 (2014)

    Google Scholar 

  3. Vermesan, O., Friess, P., Guillemi, P., Gusmeroli, S.: Internet of Things Strategic Research Agenda. In: Internet of Things – Global Technological and Societal Trends. River Publishers (2011)

    Google Scholar 

  4. Suciu, G., Halunga, S., Fratu, O., Vasilescu, A., Suciu, V.: Study for Renewable Energy Telemetry using a Decentralized Cloud M2M System. In: IEEE 15th International Symposium on Wireless Personal Multimedia Communications (WPMC), pp. 1–5 (2013)

    Google Scholar 

  5. McFedries, P.: The cloud is the computer. IEEE Spectrum 45(8), 20–22 (2008)

    Article  Google Scholar 

  6. Hassan, M.M., Song, B., Huh, E.N.: A framework of sensor-cloud integration opportunities and challenges. In: Proceedings of International Conference Ubiquitous Information Management Communication, pp. 618–626 (2009)

    Google Scholar 

  7. Fox, G.C., Kamburugamuve, S., Hartman, R.D.: Architecture and measured characteristics of a cloud based internet of things. In: International Conference on IEEE Collaboration Technologies and Systems (CTS), pp. 6–12 (2012)

    Google Scholar 

  8. Kranz, M., Holleis, P., Schmidt, A.: Embedded Interaction - Interacting with the Internet of Things. IEEE Internet Computing 14(2), 46–53 (2010)

    Article  Google Scholar 

  9. Jara, A.J., Genoud, D., Bocchi, Y.: Sensors data fusion for Smart Cities with KNIME - A real experience in the SmartSantander Testbed. In: 2014 IEEE World Forum on Internet of Things (WF-IoT), pp. 173–174 (2014)

    Google Scholar 

  10. McAfee, A., Brynjolfsson, E., Davenport, T.H., Patil, D.J., Barton, D.: Big Data. The management revolution. Harvard Bus Rev 90(10), 61–67 (2012)

    Google Scholar 

  11. The 3rd Generation Partnership Project (3GPP), TS 23.888 “System improvements for Machine-Type Communications (MTC),” Version 11.0.0 (2012)

    Google Scholar 

  12. Saad, W., Abbes, H., Jemni, M., Cerin, C.: Designing and implementing a cloud-hosted SaaS for data movement and sharing with SlapOS. International Journal of Big Data Intelligence 1(2), 18–35 (2014)

    Article  Google Scholar 

  13. Shah, T., Rabhi, F., Ray, P.: Investigating an ontology-based approach for Big Data analysis of inter-dependent medical and oral health conditions. In: Cluster Computing, pp. 1–17 (2014)

    Google Scholar 

  14. Eckstein, R.: Interactive search processes in complex work situations - a retrieval framework. University of Bamberg Press 10, 62–67 (2011)

    Google Scholar 

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Correspondence to George Suciu .

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© 2015 Springer International Publishing Switzerland

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Suciu, G., Suciu, V., Halunga, S., Fratu, O. (2015). Big Data, Internet of Things and Cloud Convergence for E-Health Applications. In: Rocha, A., Correia, A., Costanzo, S., Reis, L. (eds) New Contributions in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 353. Springer, Cham. https://doi.org/10.1007/978-3-319-16486-1_15

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  • DOI: https://doi.org/10.1007/978-3-319-16486-1_15

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16485-4

  • Online ISBN: 978-3-319-16486-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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