Activity Recognition for Personal Time Management

  • Zoltán Prekopcsák
  • Sugárka Soha
  • Tamás Henk
  • Csaba Gáspár-Papanek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5859)


We describe an accelerometer based activity recognition system for mobile phones with a special focus on personal time management. We compare several data mining algorithms for the automatic recognition task in the case of single user and multiuser scenario, and improve accuracy with heuristics and advanced data mining methods. The results show that daily activities can be recognized with high accuracy and the integration with the RescueTime software can give good insights for personal time management.


Support Vector Machine Mobile Phone Activity Recognition Data Mining Algorithm Smart Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Zoltán Prekopcsák
    • 1
  • Sugárka Soha
    • 1
  • Tamás Henk
    • 1
  • Csaba Gáspár-Papanek
    • 1
  1. 1.Budapest University of Technology and EconomicsHungary

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