Mining Wireless Sensor Network Data: An Adaptive Approach Based on Artificial Neural Networks Algorithm

This paper proposes a layered modular architecture to adaptively perform data mining tasks in large sensor networks. The architecture consists in a lower layer which performs data aggregation in a modular fashion and in an upper layer which employs an adaptive local learning technique to extract a prediction model from the aggregated information. The rationale of the approach is that a modular aggregation of sensor data can serve jointly two purposes: first, the organization of sensors in clusters, then reducing the communication effort, and second, the dimensionality reduction of the data mining task, then improving the accuracy of the sensing task.

Provided by: Interscience Open Access Journals Topic: Mobility Date Added: Aug 2010 Format: PDF

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