Dynamic Deployment of Sensing Experiments in the Wild Using Smartphones

  • Nicolas Haderer
  • Romain Rouvoy
  • Lionel Seinturier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7891)


While scientific communities extensively exploit simulations to validate their theories, the relevance of their results strongly depends on the realism of the dataset they use as an input. This statement is particularly true when considering human activity traces, which tend to be highly unpredictable. In this paper, we therefore introduce APISENSE, a distributed crowdsensing platform for collecting realistic activity traces. In particular, APISENSE provides to scientists a participative platform to help them to easily deploy their sensing experiments in the wild. Beyond the scientific contributions of this platform, the technical originality of APISENSE lies in its Cloud orientation and the dynamic deployment of scripts within the mobile devices of the participants.We validate this platform by reporting on various crowdsensing experiments we deployed using Android smartphones and comparing our solution to existing crowdsensing platforms.


Mobile Phone Mobile Device Cloud Computing Mobile Node Activity Trace 
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

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  • Nicolas Haderer
    • 1
  • Romain Rouvoy
    • 1
  • Lionel Seinturier
    • 1
  1. 1.Inria Lille – Nord Europe, LIFL - CNRS UMR 8022University Lille 1France

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