Pattern recognition in wireless sensor networks in presence of sensor failures
János Csirik, Peter Bertholet, Horst Bunke · 2011
In the current paper we consider the task of object classification in wireless sensor networks. Assuming that each feature needed for classification is acquired by a sensor, a new approach is proposed that aims at minimizing the number of features used for classification while maintaining a given correct classification rate. In particular, we address the case where a sensor may have a failure before its battery is exhausted. In experiments with data from the UCI repository, the feasibility of this approach is demonstrated.