Abstract
The study of data processing for wireless sensor networks has an interest in filtering, aggregation, and data fusion, and additionally has tended to focus on power reduction in the network. To access the data in a real context at the higher level, the network should consist of heterogeneous multi-sensors, and should converge for the multi-sensors data, which has been sent from the heterogeneous sensors. In this paper, a weighting method based on the sensors has been proposed dependent on the fusion of the multi-sensor data of wireless sensor network. This is based on Dempster-Shafer’s evidence theory.
At this point, the valid entropy weighting method has been introduced as a rational weighting method, assuming the circumstances to be identified have been influenced by multiple factors. The data has been fused after weighing on the basic probability assignment function for each sensor, following the weighing method. The contexts have been induced after weighting, and compared to the contexts prior to weighting.
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Suh, D., Yoon, S., Jeon, S., Ryu, K. (2011). Weighting Method Based on Entropy Analysis for Multi-sensor Data Fusion in Wireless Sensor Networks. In: Kim, Th., et al. Database Theory and Application, Bio-Science and Bio-Technology. BSBT DTA 2011 2011. Communications in Computer and Information Science, vol 258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27157-1_5
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DOI: https://doi.org/10.1007/978-3-642-27157-1_5
Publisher Name: Springer, Berlin, Heidelberg
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