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In this paper, asynchronous sampling is proposed as a novel approach to improve the information quality of sensory data through shifting the sampling moments of sensors from each other. The exponential correlation model and the entropy model for the sensory data are introduced to quantify their information quality. An asynchronous sampling strategy, EASS, is presented accordingly to assign equal time...
Ubiquitous (or smart) healthcare applications envision sensor rich computing and networking environments that can capture various types of contexts of patients (or inhabitants of the environment), such as their location, activities and vital signs. Such context information is useful in providing health related and wellness management services in an intelligent way so as to promote independent living...
Intensive research has focused on redundance reduction in wireless sensor networks among sensory data due to the spatial and temporal correlation embedded therein. In this paper, we propose a novel approach termed asynchronous sampling that complements existing study. The key idea of asynchronous sampling is to spread the sampling times of the sensor nodes over the time line instead of performing...
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