Ontological Sensor Selection for Wearable Activity Recognition

  • Claudia Villalonga
  • Oresti Banos
  • Hector Pomares
  • Ignacio Rojas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9095)

Abstract

Wearable activity recognition has attracted very much attention in the recent years. Although many contributions have been provided so far, most solutions are developed to operate on predefined settings and fixed sensor setups. Real-world activity recognition applications and users demand more flexible sensor configurations, which may deal with potential adverse situations such as defective or missing sensors. A novel method to intelligently select the best replacement for an anomalous or nonrecoverable sensor is presented in this work. The proposed method builds on an ontology defined to neatly describe wearable sensors and their main properties, such as measured magnitude, location and internal characteristics. SPARQL queries are used to retrieve the ontological sensor descriptions for the selection of the best sensor replacement. The on-body location proximity of the sensors is considered during the sensor search process to determine the most adequate alternative.

Keywords

Ontologies Activity recognition Wearable sensors Sensor selection Sensor placement Human anatomy 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Claudia Villalonga
    • 1
  • Oresti Banos
    • 2
  • Hector Pomares
    • 1
  • Ignacio Rojas
    • 1
  1. 1.Research Center for Information and Communications Technologies of the University of GranadaGranadaSpain
  2. 2.Department of Computer EngineeringKyung Hee UniversitySeoulKorea

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