Towards a fuzzy-based multi-classifier selection module for activity recognition applications

Martín Rodríguez, Henar and Iglesias Alvarez, Josué and Cano García, Jesús and Bernardos Barbolla, Ana M. and Casar Corredera, Jose Ramon (2012). Towards a fuzzy-based multi-classifier selection module for activity recognition applications. In: "4th International Workshop on Sensor Networks and Ambient Intelligence 2012", 23/03/2012 - 23/03/2012, Lugano. ISBN 978-1-4244-9529-0. pp. 871-876. https://doi.org/10.1109/PerComW.2012.6197634.

Description

Title: Towards a fuzzy-based multi-classifier selection module for activity recognition applications
Author/s:
  • Martín Rodríguez, Henar
  • Iglesias Alvarez, Josué
  • Cano García, Jesús
  • Bernardos Barbolla, Ana M.
  • Casar Corredera, Jose Ramon
Item Type: Presentation at Congress or Conference (Article)
Event Title: 4th International Workshop on Sensor Networks and Ambient Intelligence 2012
Event Dates: 23/03/2012 - 23/03/2012
Event Location: Lugano
Title of Book: 4th International Workshop on Sensor Networks and Ambient Intelligence 2012
Date: March 2012
ISBN: 978-1-4244-9529-0
Subjects:
Freetext Keywords: activity recognition, mobile technologies, context awareness, personal health applications, fuzzy inference.
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Performing activity recognition using the information provided by the different sensors embedded in a smartphone face limitations due to the capabilities of those devices when the computations are carried out in the terminal. In this work a fuzzy inference module is implemented in order to decide which classifier is the most appropriate to be used at a specific moment regarding the application requirements and the device context characterized by its battery level, available memory and CPU load. The set of classifiers that is considered is composed of Decision Tables and Trees that have been trained using different number of sensors and features. In addition, some classifiers perform activity recognition regardless of the on-body device position and others rely on the previous recognition of that position to use a classifier that is trained with measurements gathered with the mobile placed on that specific position. The modules implemented show that an evaluation of the classifiers allows sorting them so the fuzzy inference module can choose periodically the one that best suits the device context and application requirements.

More information

Item ID: 19814
DC Identifier: http://oa.upm.es/19814/
OAI Identifier: oai:oa.upm.es:19814
DOI: 10.1109/PerComW.2012.6197634
Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06197634
Deposited by: Memoria Investigacion
Deposited on: 21 Sep 2013 07:59
Last Modified: 21 Apr 2016 21:22
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