Physical Sciences and Mathematics Commons^™

A Data-Driven Approach For Processing Heterogeneous Categorical Sensor Signals, Randy Paffenroth, Christopher Calderon, Austin Jones, Scott Lundberg

Randy C. Paffenroth

False alarms generated by sensors pose a substantial problem to a variety of fusion applications. We focus on situations where the frequency of a genuine alarm is "rare" but the false alarm rate is high. The goal is to mitigate the false alarms while retaining power to detect true events. We propose to utilize data streams contaminated by false alarms (generated in the field) to compute statistics on a single sensor's misclassification rate. The nominal misclassification rate of a deployed sensor is often suspect because it is unlikely that these rates were tuned to the specific environmental conditions in which …