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A Multi-view CNN-based Acoustic Classification System for Automatic Animal Species Identification

Weitao Xu, Xiang Zhang, Lina Yao, Wanli Xue, Bo Wei
2020 Ad hoc networks  
In this paper, we propose a deep learning based acoustic classification framework for Wireless Acoustic Sensor Network (WASN).  ...  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.  ...  Acknowledgement The work described in this paper was fully supported by a grant from City University of Hong Kong (Project No.7200642)  ... 
doi:10.1016/j.adhoc.2020.102115 fatcat:jpetzrvcuvcmnkhbux7nrvmp6a

Domain Adaptation of Deep Neural Networks for Automatic Speech Recognition via Wireless Sensors

Gábor Gosztolya, Tamás Grósz
2016 Journal of Electrical Engineering  
In this study, we experimented with adapting Deep Neural Network-based acoustic models trained on noise-free speech data to perform speech recognition on utterances recorded by wireless sensors.  ...  Wireless sensors are recent, portable, low-powered devices, designed to record and transmit observations of their environment such as speech.  ...  Acknowledgment The Titan X graphics card used for this research was donated by the NVIDIA Corporation.  ... 
doi:10.1515/jee-2016-0017 fatcat:oia44cit5bhyxbttvlyw36y2ai

Wireless acoustic sensor networks and edge computing for rapid acoustic monitoring

Zhengguo Sheng, Saskia Pfersich, Alice Eldridge, Jianshan Zhou, Daxin Tian, Victor C. M. Leung
2019 IEEE/CAA Journal of Automatica Sinica  
Rather than transmitting heavy audio data, in this paper, we propose a low-cost and energy efficient wireless acoustic sensor network integrated with edge computing structure for remote acoustic monitoring  ...  Recording and transmitting large quantities of audio data is power intensive, hampering long-term deployment in remote, off-grid locations of key ecological interest.  ...  In this paper, we propose a low cost solution for an audio recorder with onboard audio processing, embedded in a wireless sensor network based on a ZigBee protocol.  ... 
doi:10.1109/jas.2019.1911324 fatcat:7faeldm44zdxncbyhoxvovvthu

The Implementation of Low-cost Urban Acoustic Monitoring Devices [article]

Charlie Mydlarz and Justin Salamon and Juan Pablo Bello
2016 arXiv   pre-print
To monitor and ultimately understand these sonic environments, a process of long-term acoustic measurement and analysis is required.  ...  This paper details the sensors' design, development and potential future applications, with a focus on the calibration of the devices' Microelectromechanical systems (MEMS) microphone in order to generate  ...  Labs for their equipment loan and support, The Cooper Union for the use of their acoustic laboratory, the Department of Environmental Protection (DEP) for their input on the NYC noise code and Deckard Audio  ... 
arXiv:1605.08450v1 fatcat:rorvkcoq3nhizpc2c5r4jxol4i

Wireless Sensor Networks for Long-Term Monitoring of Urban Noise

Courtney Peckens, Cédric Porter, Taylor Rink
2018 Sensors  
Wireless sensor networks offer a method for achieving this with a higher level of granularity than traditional handheld devices.  ...  Strategies are also employed to ensure real-time functionality is maintained on the sensing unit, with a focus on preventing bottlenecks between data acquisition, data processing, and wireless transmission  ...  Sensors 2018, 18, 3161  ... 
doi:10.3390/s18093161 pmid:30235854 pmcid:PMC6165576 fatcat:rbkpunkkxvfebaievgbjtc6pqe

Long-range wireless sensor networks with transmit-only nodes and software-defined receivers

Christof Huebner, Rachel Cardell-Oliver, Stefan Hanelt, Tino Wagenknecht, Alvaro Monsalve
2011 Wireless Communications and Mobile Computing  
Wireless sensor networks for environmental monitoring and agricultural applications often face long-range requirements at low bit-rates together with large numbers of nodes.  ...  This paper presents the design and test of a novel wireless sensor network that combines a large radio range with very low power consumption and cost.  ...  Acknowledgments This work was supported by a grant from the DAAD Go8 AustraliaGermany Joint Research Co-operation Scheme.  ... 
doi:10.1002/wcm.1198 fatcat:3bj65b6hynadln4g3fvysi5zpe

Low-Cost Sensors for Urban Noise Monitoring Networks—A Literature Review

Judicaël Picaut, Arnaud Can, Nicolas Fortin, Jeremy Ardouin, Mathieu Lagrange
2020 Sensors  
networks for the assessment of sound environments.  ...  To implement strategies to improve sound environments, experts need information on existing noise.  ...  Later, the sensor network was successfully deployed for long-term measurements in a school yard, showing a good agreement by comparison with a Class-2 sound level meter [53] .  ... 
doi:10.3390/s20082256 pmid:32316202 pmcid:PMC7218845 fatcat:nnzmuplkpzcwjplvbezf5enlyu

On the Application of the Raspberry Pi as an Advanced Acoustic Sensor Network for Noise Monitoring

Juan Noriega-Linares, Juan Navarro Ruiz
2016 Electronics  
The use of wireless sensor networks with acoustic sensor has been studied in several works [12] [13] [14] [15] . Recently, there has emerged a new concept of computers.  ...  With the use of long-term measurements, changes on the levels can be observed from the data, and more advanced studies can be performed in order to assess the noise annoyance.  ...  Acknowledgments: The work presented in this paper have been funded by project PMAFI-02-14 by the UCAM Catholic University of Murcia, Spain.  ... 
doi:10.3390/electronics5040074 fatcat:3fukmmnx3fdyxc5truoui37ojy

Smart sensors for small rodent observation

Johannes Thiele, Okuary Osechas, Jo Bitsch, Klaus Wehrle
2008 2008 IEEE Sensors  
Working towards the observation of rats (and other small rodents) in the wild we have developed tools that will enable us to study their behavior using a wireless network of wearable sensor nodes.  ...  by stationary data sinks.  ...  The long term goal is to attach, or even implant, the sensor nodes to wild rats.  ... 
doi:10.1109/icsens.2008.4716540 fatcat:stjqznmacngjldeklnoc6zwnfu

Real-Time Remote Sensing of the Lobesia botrana Moth Using a Wireless Acoustic Detection Sensor

Gabriel Hermosilla, Francisco Pizarro, Sebastián Fingerhuth, Francisco Lazcano, Francisco Santibanez, Nelson Baker, David Castro, Carolina Yáñez
2021 Applied Sciences  
The wireless sensor consists of an acoustic-based detection of the sound generated by a flying Lobesia botrana moth.  ...  This article presents a wireless sensor for pest detection, specifically the Lobesia botrana moth or vineyard moth.  ...  It started with a project call by Telefonica I + D Chile, where a first prototype was developed.  ... 
doi:10.3390/app112411889 fatcat:y2genlp5gbdcbd76c4p3ebed5e

Paper titles

2020 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)  
Wireless Rechargeable Sensor Networks Based on Charging Curve Color Filter Array Demosaicking Algorithm Based on Convolutional Neural Network Comparative Analysis of Maximum Power Point Tracking Algorithm  ...  Markov Transition Field and Convolutional Long Short-Term Memory Neural Network for Manufacturing Quality Prediction Modeling of malware diffusion with the FLIPIT game Modified YOLOv3-Tiny Using Dilated  ... 
doi:10.1109/icce-taiwan49838.2020.9258179 fatcat:2eheaztzhncixhbvp7nrbzml4m

Search and discovery in an uncertain networked world

E.B. Ermis, M. Alanyali, V. Saligrama
2006 IEEE Signal Processing Magazine  
We consider the example of a sensor network for  ...  In this work we also focus on the architecture that performs in-network data processing.  ...  Acknowledgements This work was supported by PECASE grant no. N00014-02-100362, NSF grants CCF 0430983, CCF 0530572, ANI 0238397, and ECS 0449194.  ... 
doi:10.1109/msp.2006.1657821 fatcat:ld4l5vrno5h6vpuqcjyijndvjm

Multi-target tracking through opportunistic camera control in a resource constrained multimodal sensor network

Jayanth Nayak, Luis Gonzalez-Argueta, Bi Song, Amit Roy-Chowdhury, Ertem Tuncel
2008 2008 Second ACM/IEEE International Conference on Distributed Smart Cameras  
For obtaining good surveillance results in a sparse camera networks requires that they be complemented by additional sensors with different modalities, their intelligent assignment in a dynamic environment  ...  Correspondences between the audio and video sensor observations are obtained through a learned homography between the image plane and ground plane.  ...  A multimodal network, where audio sensors direct the cameras to focus on the most interesting parts of the scene, is one such strategy.  ... 
doi:10.1109/icdsc.2008.4635682 dblp:conf/icdsc/NayakGSCT08 fatcat:2f52dksxdjgurkuql537y6b4qe

Evaluation of MPEG-7-Based Audio Descriptors for Animal Voice Recognition over Wireless Acoustic Sensor Networks

Joaquín Luque, Diego Larios, Enrique Personal, Julio Barbancho, Carlos León
2016 Sensors  
Therefore, we propose the use of a Wireless Acoustic Sensor Network (WASN) to monitor animals' voices.  ...  To overcome these limitations, this paper proposes an environmental Wireless Acoustic Sensor Network architecture focused on use of generic descriptors based on an MPEG-7 standard.  ...  Figure 1 . 1 Architecture of the proposed Wireless Acoustic Sensor Network. Figure 1 . 1 Architecture of the proposed Wireless Acoustic Sensor Network.  ... 
doi:10.3390/s16050717 pmid:27213375 pmcid:PMC4883408 fatcat:jqginacqlfcbnni7tk6tgdg7wy

Detecting Context in Distributed Sensor Networks by Using Smart Context-Aware Packets [chapter]

Florian Michahelles, Michael Samulowitz, Bernt Schiele
2002 Lecture Notes in Computer Science  
In this approach, sCAP's are injected into the sensor network by the context inquirer.  ...  The paper concentrates on the routing concepts which allow to deal with breakdowns of sensor nodes and continuous changes of the network topology.  ...  Acknowledgements The Smart-Its project is funded in part by the Commission of the European Union under contract IST-2000-25428, and by the Swiss Federal Office for Education and Science (BBW 00.0281).  ... 
doi:10.1007/3-540-45997-9_5 fatcat:6ilyg73b75gz3kmkljbo6mz3ci
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