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

Martín Rodríguez, Henar; Iglesias Alvarez, Josué; Cano García, Jesús; Bernardos Barbolla, Ana M. y Casar Corredera, Jose Ramon (2012). Towards a fuzzy-based multi-classifier selection module for activity recognition applications. En: "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.

Descripción

Título: Towards a fuzzy-based multi-classifier selection module for activity recognition applications
Autor/es:
  • Martín Rodríguez, Henar
  • Iglesias Alvarez, Josué
  • Cano García, Jesús
  • Bernardos Barbolla, Ana M.
  • Casar Corredera, Jose Ramon
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 4th International Workshop on Sensor Networks and Ambient Intelligence 2012
Fechas del Evento: 23/03/2012 - 23/03/2012
Lugar del Evento: Lugano
Título del Libro: 4th International Workshop on Sensor Networks and Ambient Intelligence 2012
Fecha: Marzo 2012
ISBN: 978-1-4244-9529-0
Materias:
Palabras Clave Informales: activity recognition, mobile technologies, context awareness, personal health applications, fuzzy inference.
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 19814
Identificador DC: http://oa.upm.es/19814/
Identificador OAI: oai:oa.upm.es:19814
Identificador DOI: 10.1109/PerComW.2012.6197634
URL Oficial: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06197634
Depositado por: Memoria Investigacion
Depositado el: 21 Sep 2013 07:59
Ultima Modificación: 21 Abr 2016 21:22
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