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


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”.

Año de publicación:

2020

Keywords:

  • Big Data Analysis
  • Radio frequency identification
  • Data Mining
  • Hadoop
  • internet of things

Fuente:

scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Computación en la nube
  • Ciencias de la computación
  • Logística

Áreas temáticas:

  • Ciencias de la computación
  • Métodos informáticos especiales
  • Funcionamiento de bibliotecas y archivos