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Evaluation of IoT Data Visualization Tools and Techniques

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Data Visualization

Abstract

Internet of things (IoT) is a fully proven technology in the era of automation. IoT is a connected network of embedded systems with sensors and actuators. IoT generates huge volumes of data due to large number of implanted IoT devices everywhere. This generated data needs to be processed and analyzed to optimize operations and facilitate decision making. Data analytics plays a vital role in decision making. IoT has its applications in several areas: environmental monitoring, infrastructure management, manufacturing, energy management, medical and healthcare systems, building and home automation, transportation and many more. In every IoT application, a large amount of data has been generated with variations in it. Analysis, optimization and visualization of such huge data require smart tools and technologies. For example, some data requires specific algorithms to build models as a classification, whereas others require clustering and anomaly detection. The data visualization tools and techniques available for IoT data are very useful to get a better understanding of IoT, its framework, functions, and missions. There is still need for research and literature about data visualization tools and techniques for IoT and the challenges related to it. In this chapter, we have included various open-source commercial tools and techniques available in the market. We have also studied the benefits and challenges of existing tools. We analyzed and evaluated the suitability of existing tools and capabilities to gain leverage and support for IoT data visualization.

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Author information

Authors and Affiliations

  1. Applied Research Center, Florida International University, Miami, USA

    Suresh K. Peddoju & Himanshu Upadhyay

Authors
  1. Suresh K. Peddoju
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  2. Himanshu Upadhyay
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Correspondence to Suresh K. Peddoju .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    S. Margret Anouncia

  2. Department of Computer Science, University of Houston-Victoria, Victoria, TX, USA

    Hardik A. Gohel

  3. Department of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    Subbiah Vairamuthu

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Peddoju, S.K., Upadhyay, H. (2020). Evaluation of IoT Data Visualization Tools and Techniques. In: Anouncia, S., Gohel, H., Vairamuthu, S. (eds) Data Visualization. Springer, Singapore. https://doi.org/10.1007/978-981-15-2282-6_7

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  • DOI: https://doi.org/10.1007/978-981-15-2282-6_7

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2281-9

  • Online ISBN: 978-981-15-2282-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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