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Energy-Efficient Data Collection for Context Recognition
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DOI：10.1145/3123024.3124430.png)
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Detection of the user's context with mobile sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems is often making continuous detection impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near optimal sensor settings. It uses Markov chains to simulate the behaviour of the system in different configurations, and multi-objective genetic algorithm to find a set of good non dominated configurations.
Keyword:
Context recognition
energy efficiency
wearable sensors
smartphone
Markov chains
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