Partial DCT-based energy efficient compression algorithm for wireless multimedia sensor network

Banerjee, Rajib; Mohammad, Mobashir; Bit, Sipra Das

doi:10.1109/conecct.2014.6740356

Cited by 6 publications

(2 citation statements)

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“…There are a large volume of audio monitoring systems in the literature [4,6,7,8,9,10,11,12,13,14]. In the early stage, biologists have traditionally deployed audio recording systems over the natural environment where their research projects were developed [6,7].…”

Section: Introductionmentioning

confidence: 99%

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A multi-view CNN-based acoustic classification system for automatic animal species identification

Zhang

Yao

et al. 2020

Ad Hoc Networks

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Automatic identification of animal species by their vocalization is an important and challenging task. Although many kinds of audio monitoring system have been proposed in the literature, they suffer from several disadvantages such as non-trivial feature selection, accuracy degradation because of environmental noise or intensive local computation. In this paper, we propose a deep learning based acoustic classification framework for Wireless Acoustic Sensor Network (WASN). The proposed framework is based on cloud architecture which relaxes the computational burden on the wireless sensor node. To improve the recognition accuracy, we design a multi-view Convolution Neural Network (CNN) to extract the short-, middle-, and long-term dependencies in parallel. The evaluation on two real datasets shows that the proposed architecture can achieve high accuracy and outperforms traditional classification systems significantly when the environmental noise dominate the audio signal (low SNR). Moreover, we implement and deploy the proposed system on a testbed and analyse the system performance in real-world environments. Both simulation and real-world evaluation demonstrate the accuracy and robustness of the proposed acoustic classification system in distinguishing species of animals.

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Section: Introductionmentioning

confidence: 99%

“…However this procedure requires human presence in the area of interest at certain moments. In recent years, with the development of WSN, some researchers have proposed remotely accessible systems in order to minimize the impact of the presence of human beings in the habitat of interest [4,12,13,14].…”

Section: Introductionmentioning

confidence: 99%