Sequential Classifier Combination for Pattern Recognition in Wireless Sensor Networks

In the current paper we consider the task of object classification in wireless sensor networks. Due to restricted battery capacity, minimizing the energy consumption is a main concern in wireless sensor networks. Assuming that each feature needed for classification is acquired by a sensor, a sequential classifier combination approach is proposed that aims at minimizing the number of features used for classification while maintaining a given correct classification rate. In experiments with data from the UCI repository, the feasibility of this approach is demonstrated.

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