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Embedded sensors of a Body Sensor Network need to efficiently utilize their energy resources to operate for an extended amount of time. A Markov Decision Process (MDP) framework has been used to obtain a globally optimal policy that coordinated the sampling of multiple sensors to achieve high efficiency in such sensor networks. However, storing the coordinated sampling policy table requires a large...
Sensor webs for environmental monitoring integrate data from a large number of fixed and mobile sensors. The spatial and temporal distribution of these sensors varies with time when the network controllers adapt the operation of the sensors to detected events. The paper describes an approach for online visualization of data from such sensor webs. The visualization approach explicitly takes into account...
The paper has shown how the Markov decision process framework can be used for sensor coordination. This method is suitable for networks of relatively few sensors and where the computational capabilities and energy reserves at each node are limited.
The paper describes the use of model predictive control (MPC) as a framework for optimal resource management in environmental monitoring sensor networks. The MPC formulation adapts sensor and network parameters (such as sensor sampling rates, and routing of data) that impact the utilization of the system resources (such as energy reserves at off-shore in-situ sensors, and wireless bandwidth). The...
This study describes the functioning of a novel sensor that measures the alcohol concentration in the interstitial fluid (ISF) of a human subject. ISF is extracted using vacuum pressure from micropores on the stratum corneum layer of the skin. The pores are created by focusing a near infrared laser on a layer of black die attached to the skin. This poration procedure is essentially painless. Clinical...
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