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Big Data Architecture for Environmental Analytics

  • Ritaban Dutta
  • Cecil Li
  • Daniel Smith
  • Aruneema Das
  • Jagannath Aryal
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 448)

Abstract

This paper aims to develop big data based knowledge recommendation framework architecture for sustainable precision agricultural decision support system using Computational Intelligence (Machine Learning Analytics) and Semantic Web Technology (Ontological Knowledge Representation). Capturing domain knowledge about agricultural processes, understanding about soil, climatic condition based harvesting optimization and undocumented farmers’ valuable experiences are essential requirements to develop a suitable system. Architecture to integrate data and knowledge from various heterogeneous data sources, combined with domain knowledge captured from the agricultural industry has been proposed. The proposed architecture suitability for heterogeneous big data integration has been examined for various environmental analytics based decision support case studies.

Keywords

big data architecture machine learning semantics 

References

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Copyright information

© IFIP International Federation for Information Processing 2015

Authors and Affiliations

  • Ritaban Dutta
    • 1
  • Cecil Li
    • 1
  • Daniel Smith
    • 1
  • Aruneema Das
    • 2
  • Jagannath Aryal
    • 2
  1. 1.CSIRO Digital Productivity Flagship, CSIRO HobartTASAustralia
  2. 2.CSIRO HobartUniversity of TasmaniaTASAustralia

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