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

Date Added: Aug 2010
Format: PDF

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.