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Improving the Quality of User Generated Data Sets for Activity Recognition

  • Chris NugentEmail author
  • Jonathan Synnott
  • Celeste Gabrielli
  • Shuai Zhang
  • Macarena Espinilla
  • Alberto Calzada
  • Jens Lundstrom
  • Ian Cleland
  • Kare Synnes
  • Josef Hallberg
  • Susanna Spinsante
  • Miguel Angel Ortiz Barrios
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10070)

Abstract

It is fully appreciated that progress in the development of data driven approaches to activity recognition are being hampered due to the lack of large scale, high quality, annotated data sets. In an effort to address this the Open Data Initiative (ODI) was conceived as a potential solution for the creation of shared resources for the collection and sharing of open data sets. As part of this process, an analysis was undertaken of datasets collected using a smart environment simulation tool. A noticeable difference was found in the first 1–2 cycles of users generating data. Further analysis demonstrated the effects that this had on the development of activity recognition models with a decrease of performance for both support vector machine and decision tree based classifiers. The outcome of the study has led to the production of a strategy to ensure an initial training phase is considered prior to full scale collection of the data.

Keywords

Activity recognition Open data sets Data validation Data driven classification 

Notes

Acknowledgments

Invest Northern Ireland partially supported this project under the Competence Centre Program Grant RD0513853 – Connected Health Innovation Centre.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Chris Nugent
    • 1
    • 4
    Email author
  • Jonathan Synnott
    • 1
  • Celeste Gabrielli
    • 2
  • Shuai Zhang
    • 1
  • Macarena Espinilla
    • 3
  • Alberto Calzada
    • 1
  • Jens Lundstrom
    • 4
  • Ian Cleland
    • 1
  • Kare Synnes
    • 5
  • Josef Hallberg
    • 5
  • Susanna Spinsante
    • 2
  • Miguel Angel Ortiz Barrios
    • 6
  1. 1.School of Computing and MathematicsUlster UniversityJordanstownNorthern Ireland, UK
  2. 2.Dipartimento dell’ingegneria dell’informazioneUniversita Politecnica Delle MarcheAnconaItaly
  3. 3.Department of Computer SciencesUniversity of JaenJaenSpain
  4. 4.School of Information TechnologyHalmstad UniversityHalmstadSweden
  5. 5.Department of Computer Science, Electrical and Space EngineeringLulea Technical UniversityLuleåSweden
  6. 6.Industrial Engineering DepartmentUniversidad de La Costa CUCBarranquillaColombia

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