Relevant framework for social applications of IoT by means of Machine Learning techniques

Zheng, Xiaochen and Ordieres-Meré, Joaquín (2016). Relevant framework for social applications of IoT by means of Machine Learning techniques. In: "Industriales Research Meeting 2016", 20 abril 2016, Escuela Técnica Superior Ingenieros Industriales - UPM - Madrid. ISBN 978-84-16397-31-0. p. 171.

Description

Title: Relevant framework for social applications of IoT by means of Machine Learning techniques
Author/s:
  • Zheng, Xiaochen
  • Ordieres-Meré, Joaquín
Item Type: Presentation at Congress or Conference (Poster)
Event Title: Industriales Research Meeting 2016
Event Dates: 20 abril 2016
Event Location: Escuela Técnica Superior Ingenieros Industriales - UPM - Madrid
Title of Book: Industriales Research Meeting 2016
Date: 2016
ISBN: 978-84-16397-31-0
Subjects:
Freetext Keywords: Internet of Things
Faculty: E.T.S.I. Industriales (UPM)
Department: Ingeniería de Organización, Administración de Empresas y Estadística
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

With the rapid development of Internet of Things (IoT) technology, billions of smart devices are being connected into a whole network and streaming out a huge amount of data every moment. Unimaginable potential value can be mined from these data with the help of "Cloud Computing" and "Machine Learning" techniques. The target of our research is to address the benefits of IoT in social applications, especially in healthcare area, by developing a multilayer framework. Low cost data collection, efficient data transfer, flexible data management and accurate data analysis mechanisms will be included in the framework. A Smart Decision Support System is supposed to be developed on the basis of this framework.

More information

Item ID: 46154
DC Identifier: http://oa.upm.es/46154/
OAI Identifier: oai:oa.upm.es:46154
Official URL: http://www.industriales.upm.es/investigacion/irm16/index.es.htm
Deposited by: Memoria Investigacion
Deposited on: 30 May 2017 08:10
Last Modified: 23 Apr 2018 07:41
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