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Three Methods for Energy-Efficient Context Recognition
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DOI：10.31449/inf.v45i2.3509.png)
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Abstract
En 中文
Context recognition is a process where (usually wearable) sensors are used to determine the context (location, activity, etc.) of users wearing them. A major problems of such context- recognition systems is the high energy cost of collecting and processing sensor data. This paper summarizes a doctoral thesis that focuses on solving this problem by proposing a general methodology for increasing the energyefficiency of context-recognition systems. The thesis proposes and combines three different methods that can adapt a system's sensing settings based on the last recognized context and last seen sensor readings.
Keywords:
context recognition
optimization
energy efficiency
Markov chains
duty-cycling
decision trees
Journal
IF:
1.7
Papers:
250
Citations:
62
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