Inferring Complex Human Behavior Using a Non-obtrusive Mobile Sensing Platform

  • Bruce DeBruhl
  • Michele Cossalter
  • Roy Want
  • Ole Mengshoel
  • Pei Zhang
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 76)


Thanks to the decreasing cost, increasing mobility, and wider use of sensors, a great number of possible applications have recently emerged, including applications that may impact the high-level goals in people’s lives. Applications can be found in many areas ranging from medical devices to consumer devices. Information about activity and context can be inferred from sensors and be used to provide automated recommendations.


Activity Recognition Acceleration Data Light Sensor Wearable Sensor Triaxial Accelerometer 
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

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2012

Authors and Affiliations

  • Bruce DeBruhl
    • 1
  • Michele Cossalter
    • 1
  • Roy Want
    • 2
  • Ole Mengshoel
    • 1
  • Pei Zhang
    • 1
  1. 1.Carnegie Mellon UniversityUSA
  2. 2.Intel LabsUSA

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