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This paper proposes a logical correlation-based sleep scheduling mechanism (LCSSM) to implement energy-efficient wireless sensor networks (WSNs) in ambient-assisted homes (AAHs). LCSSM analyzes sensory data generated by different human behaviors to detect the logical correlations between sensor nodes in an AAH. By utilizing the particular logical correlations of an AAH to predict its usage status,...
Rapid increase of elderly population in the world is motivating innovative technologies for healthcare services that are both high-quality and cost-effective. Wireless sensor networks (WSNs) based smart home for assisted living is one of the most prosperous solutions to this area, since it removes the requirement of deploying wired devices and is easy to be implemented in existing home environments...
Energy efficiency is a key problem in wireless sensor networks. Keeping only a portion of nodes active and putting the others into sleep mode can conserve energy. In order to maintain satisfactory data quality, we recover the would-be sensed data for sleeping nodes. In this paper, we exploit spatial correlation among densely deployed nodes and use such correlation for data recovery. Loss in data quality...
Data samples sensed from a densely deployed sensor network often exhibit strong spatial and temporal correlation. Sampling and transmitting these highly correlated data through wireless channel would result in excessive energy consumption. One way to conserve energy is to set a portion of sensors into sleep mode provided their missing data can be well recovered by sensors that remain active. Different...
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