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Semantics and Clustering Techniques for IoT Sensor Data Analysis: A Comprehensive Survey

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Book cover Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 174))

Abstract

Semantics is used to exchange information from one place to another place in a meaningful way. The data is generated from various heterogeneous devices, communication protocols, and data formats that are enormous in nature. This is a significant problem for Internet of Things (IoT) application developers to make the IoT generated data interoperable. In the existing approaches, there is a lack of well-defined standards and established tools to solve the semantic interoperability problem in IoT smart city applications. Smart cities are much popular these days. Currently, smart city applications are facing a problem with a lack of semantic interoperable standards. At present, there is no unified interoperable methodology to redeploy and reuse the IoT smart data for smart city applications. Having the smart city become interoperable in nature, there is a need to focus on architecture, framework, work progress of IoT smart data, semantic interoperable services and applications, and provide security to smart city applications. In this chapter, firstly, exposes the all-applicable semantic interoperable standards in smart city applications to become a semantic web of things in comprehensive survey manner. Secondly, the unsupervised clustering mechanisms are discussed for performing analysis on IoT sensor data and highlight with much more attention towards the issues, challenges, and current research directions. Finally, this chapter concludes with proposed semantic reasoning mechanism for unified accessible resources in IoT smart city applications.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Pondicherry Engineering College, Pondicherry, India

    Sivadi Balakrishna & M. Thirumaran

Authors
  1. Sivadi Balakrishna
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  2. M. Thirumaran
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Correspondence to Sivadi Balakrishna .

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Editors and Affiliations

  1. CSIE Department, National Dong Hwa University, New Taipei City, Taiwan

    Sheng-Lung Peng

  2. Department of Computer Science and Engineering, Brainware University, Kolkata, West Bengal, India

    Souvik Pal

  3. Department of Communications Engineering, Xiamen University, Xiamen City, Fujian, China

    Lianfen Huang

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Balakrishna, S., Thirumaran, M. (2020). Semantics and Clustering Techniques for IoT Sensor Data Analysis: A Comprehensive Survey. In: Peng, SL., Pal, S., Huang, L. (eds) Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm. Intelligent Systems Reference Library, vol 174. Springer, Cham. https://doi.org/10.1007/978-3-030-33596-0_4

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