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Three Methods for Energy-Efficient Context Recognition
DOI:10.31449/inf.v45i2.3509.png)
摘要
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.
Keyword:
context recognition
optimization
energy efficiency
Markov chains
duty-cycling
decision trees
期刊
IF:
1.7
论文数:
250
被引数:
62
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