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Analytics Everywhere: Generating Insights from the Internet of Things

Academic Article
Publication Date:
2019
abstract:
The Internet of Things is expected to generate an unprecedented number of unbounded data streams that will produce a paradigm shift when it comes to data analytics. We are moving away from performing analytics in a public or private cloud to performing analytics locally at the fog and edge resources. In this paper, we propose a network of tasks utilizing edge, fog, and cloud computing that are designed to support an Analytics Everywhere framework. The aim is to integrate a variety of computational resources and analytical capabilities according to a data life-cycle. We demonstrate the proposed framework using an application in smart transit.
Iris type:
01.01 Articolo in rivista
Keywords:
Internet of Things; Computational Platforms; Machine Learning
List of contributors:
Renso, Chiara; Carlini, Emanuele
Authors of the University:
CARLINI EMANUELE
RENSO CHIARA
Handle:
https://iris.cnr.it/handle/20.500.14243/369817
Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/369817/39915/prod_415403-doc_146516.pdf
Published in:
IEEE ACCESS
Journal
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URL

https://ieeexplore.ieee.org/document/8723480
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