Goal Oriented Sensing in Pervasive Computing

نویسندگان

  • Gerold Hölzl
  • Anind K. Dey
چکیده

PROBLEM STATEMENT AND RESEARCH QUESTION Today’s dominating design principles to build context aware systems are based on bottom-up philosophies. The design process begins with selecting the sensors that deliver the necessary data and the associated in-line processing steps. These processing steps, encapsulated in the so called Activity Recognition Chain, allow to interpret the delivered raw sensor data towards semantic meaningful labels (e.g., Walk, Stand, Sit, etc.) using machine learning and reasoning techniques. The major drawback and the Achilles’ Heel of systems based on this design metaphor is their static and predefined nature. Systems of that kind are not able to adapt to changes in the sensing ecosystem as sensors may fail, or to integrate newly, unforeseen available ones. Complete system failure can be caused by just the failure of one single sensor. The march goes on towards highly miniaturised sensor platforms that are more and more integrated into various gadgets of daily living. Up until today, these platforms were mostly used in laboratory settings, but recent developments start reaching the global consumer market. Manifested in all forms of Smart-X-Devices like smart-watches, smartglasses, smart-shoes, and of course smart-phones, they will be an essential element for a globe spanning, always on, sensor network. The complexity of this globe spanning distributed, cyper-physical system will reach the limits of today’s dominating, bottom-up design principles for pervasive Activityand Context recognition systems. New methods have to be developed to overcome this complexity crises.

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تاریخ انتشار 2014