Classificação distribuída de anuros usando rede de sensores sem fio

Abstract

Wireless Sensor Networks (WSNs) can be used in environmental conservation applications and studies due to its wireless communication, sensing, and monitoring capabilities. In the Ecology context, amphibians are used as bioindicators of ecosystemic changes of a region and can early indicate environmental problems. Thus, biologists monitor the anuran (frogs and toads) population in order to establish environmental conservational strategies. Anuran were chosen because the sounds they emit allow classification by using microphones and signal processing. In this work we propose and evaluate some distributed algorithms for anuran classification based on their calls (vocalizations) in the habit using WSNs. This method is interesting because it is not intrusive and it allows remote monitoring. Our solution builds cluster of nodes whose acoustic collected measurements are correlated. The nodes of the same group are combined to generate local classification decisions. Then, these decisions are combined to generate a global decision. We use k-means algorithm for clustering nodes with correlated measurements, which groups instances by similarity. Experiments show that, in comparison with other literature algorithms, the error rate of our solution were 26 pp (percentage points) lower.