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Distributed inference schemes for detection, estimation and learning comprise an attractive approach to Wireless Sensor Networks (WSNs), because of properties such as asynchronous operation and robustness in the face of failures. Belief Propagation (BP) is a method for distributed inference which provides accurate results with rapid convergence properties. However, applying a BP algorithm to...
Clustering is an important mechanism in large multi-hop wireless sensor networks for obtaining scalability, reducing energy consumption and achieving better network performance. Most of the research in this area has focused on energy-efficient solutions, but has not thoroughly analyzed the network performance, e.g. in terms of data collection rate and time. The main objective of this paper...
Indoor positioning systems based on Received Signal Strength Indicator (RSSI) in Wireless Sensor Networks (WSNs) are commonly used. The position accuracy in these systems is highly affected by the wireless medium variability, and therefore, a precise calibration is necessary to translate the power measurements to corresponding distance between each pair of nodes. In this paper, we propose a calibration...
In this paper we develop a continuous high-precision tracking system based on Received Signal Strength Indicator(RSSI) measurements for small ranges. The proposed system uses minimal number of sensor nodes with RSSI capabilities to track a moving object in close-proximity and high transmission rate. The close-proximity enables conversion of RSSI measurements to range estimates and the high transmission...
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