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A Proposed Architecture for IoT Big Data Analysis in Smart Supply Chain Fields

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Advances in Emerging Trends and Technologies (ICAETT 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1066))

Abstract

The growth of large amounts of data in the last decade from Cloud Computing, Information Systems, and Digital Technologies with an increase in the production and miniaturization of Internet of Things (IoT) devices. However, these data without analytical power are not useful in any field. Concentration efforts at multiple levels are required for the extraction of knowledge and decision-making being the “Big Data Analysis” an area increasingly challenging. Numerous analysis solutions combining Big Data and IoT have allowed people to obtain valuable information. Big Data requires a certain complexity. Small Data is emerging as a more efficient alternative, since it combines structured and unstructured data that can be measured in Gigabytes, Peta bytes or Terabytes, forming part of small sets of specific IoT attributes. This article presents an architecture for the analysis of data generated by IoT. The proposed solution allows the extraction of knowledge, focusing on the case of specific use of the “Smart Supply Chain fields”.

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Notes

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Acknowledgments

This work was possible thanks “Universidad de Las Américas” from Ecuador for the financing of research and Leiria Polytechnic Institute from Portugal.

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Authors and Affiliations

  1. Intelligent and Interactive Systems Lab (SI2-Lab), Universidad de Las Américas, Quito, Ecuador

    Fabián-Vinicio Constante-Nicolalde, Jorge-Luis Pérez-Medina & Paulo Guerra-Terán

  2. School of Technology and Management, Polytechnic Institute of Leiria, Leiria, Portugal

    Fabián-Vinicio Constante-Nicolalde

Authors
  1. Fabián-Vinicio Constante-Nicolalde
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  2. Jorge-Luis Pérez-Medina
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  3. Paulo Guerra-Terán
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Corresponding authors

Correspondence to Fabián-Vinicio Constante-Nicolalde or Jorge-Luis Pérez-Medina .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, Noord-Brabant, The Netherlands

    Miguel Botto-Tobar

  2. Universidad Técnica de Babahoyo, Babahoyo, Ecuador

    Joffre León-Acurio

  3. Universitat de Valencia, Valencia, Valencia, Spain

    Angela Díaz Cadena

  4. Centro de Investigación y Desarrollo Profesional, Babahoyo, Los Rios Province, Ecuador

    Práxedes Montiel Díaz

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Constante-Nicolalde, FV., Pérez-Medina, JL., Guerra-Terán, P. (2020). A Proposed Architecture for IoT Big Data Analysis in Smart Supply Chain Fields. In: Botto-Tobar, M., León-Acurio, J., Díaz Cadena, A., Montiel Díaz, P. (eds) Advances in Emerging Trends and Technologies. ICAETT 2019. Advances in Intelligent Systems and Computing, vol 1066. Springer, Cham. https://doi.org/10.1007/978-3-030-32022-5_34

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