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

  • Fabián-Vinicio Constante-NicolaldeEmail author
  • Jorge-Luis Pérez-MedinaEmail author
  • Paulo Guerra-Terán
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (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”.

Keywords

Big Data Analysis Internet of Things Data mining Hadoop Radio frequency identification 

Notes

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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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Intelligent and Interactive Systems Lab (SI2-Lab)Universidad de Las AméricasQuitoEcuador
  2. 2.School of Technology and ManagementPolytechnic Institute of LeiriaLeiriaPortugal

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