Adaptable data models for scalable Ambient Intelligence scenarios

Research output: Contribution to conferenceOther

7 Citations (Scopus)


In most real-life scenarios for Ambient Intelligence, the need arises for scalable simulations that provide reliable sensory data to be used in the preliminary design and test phases. This works present an approach to modeling data generated by a hybrid simulator for wireless sensor networks, where virtual nodes coexist with real ones. We apply our method to real data available from a public repository and show that we can compute reliable models for the quantities measured at a given reference site, and that such models are portable to different environments, so as to obtain a complete, scalable and reliable testing environment.
Original languageEnglish
Number of pages6
Publication statusPublished - 2011

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

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