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Data Lifecycle and Tagging for Internet of Things Applications

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AI 2016: Advances in Artificial Intelligence (AI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9992))

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Abstract

The number of sensors and the amount of data those sensors are collecting is increasing exponentially in the form of sensor networks collectively known as the Internet of Things (IoT). Using this large volume of IoT data in context-aware systems requires new preprocessing methods. This paper introduces an IoT data lifecycle, a proposed definition of an IoT-specific context tag, and required for an automated preprocessing method called data tagging before suggesting some uses of this IoT context tag and outlining possible directions for future research.

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Acknowledgement

This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (No: R-20160906-004163, Develo** Bigdata Autotagging and Tag-based DaaS System).

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Authors and Affiliations

  1. School of Electrical Engineering, KAIST, Daejeon, Republic of Korea

    Sanghong Ahn, Hyeontaek Oh & Jun Kyun Choi

  2. Department of Computer and Communications Engineering, Kangwon National University, ChunCheon, Republic of Korea

    Hwa Jong Kim

Authors
  1. Sanghong Ahn
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  2. Hyeontaek Oh
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  3. Hwa Jong Kim
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  4. Jun Kyun Choi
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Corresponding author

Correspondence to Jun Kyun Choi .

Editor information

Editors and Affiliations

  1. University of Tasmania, Hobart, Australia

    Byeong Ho Kang

  2. Auckland University of Technology, Auckland, New Zealand

    Quan Bai

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© 2016 Springer International Publishing AG

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Ahn, S., Oh, H., Kim, H.J., Choi, J.K. (2016). Data Lifecycle and Tagging for Internet of Things Applications. In: Kang, B.H., Bai, Q. (eds) AI 2016: Advances in Artificial Intelligence. AI 2016. Lecture Notes in Computer Science(), vol 9992. Springer, Cham. https://doi.org/10.1007/978-3-319-50127-7_61

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  • DOI: https://doi.org/10.1007/978-3-319-50127-7_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50126-0

  • Online ISBN: 978-3-319-50127-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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