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In this work we present a framework for automatic acoustic detection of chainsaw sounds to detect illegal wood extraction in the Amazon Rainforest. Our approach was developed to be embedded into the sensor nodes of a Wireless Acoustic Sensor Network (WASN) to monitor the environment. First, we represent each sound by a set of Mel-Frequency Cepstral Coefficients (MFCCs) and, after that, we fit a Probability...
A bioacoustical animal recognition system is composed of two parts: (1) the segmenter, responsible for detecting syllables (animal vocalization) in the audio; and (2) the classifier, which determines the species/animal whose the syllables belong to. In this work, we first present a novel technique for automatic segmentation of anuran calls in real time; then, we present a method to assess the performance...
Anurans (frogs or toads) are commonly used by biologists as early indicators of ecological stress. The reason is that anurans are closely related to the ecosystem. Although several sources of data may be used for monitoring these animals, anuran calls lead to a non-intrusive data acquisition strategy. Moreover, wireless sensor networks (WSNs) may be used for such a task, resulting in more accurate...
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