Intelligent sampling for colombian soundscapes using an artificial neural network

Luis Quiroz; Jairo Gómez; Oscar Agudelo; Luis Tobón

doi:10.1007/978-3-319-66963-2_17

Intelligent sampling for colombian soundscapes using an artificial neural network

Luis Quiroz, Jairo Gómez, Oscar Agudelo, Luis Tobón

Universidad Javeriana

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Information extracted from environmental sounds has been of great importance to the analysis of ecological complexity in natural ecosystems. However, the study of these sounds does not have a universal protocol for the sampling and reduction of large quantities of data that it produces. This paper proposes to use a neural network to optimize the sampling of soundscapes of three Colombian ecosystems. The neural network is trained to identify meaningful temporal windows for audio recording from previously gathered data. This method simplifies the acoustic complexity analysis.

Original language	English
Title of host publication	Applied Computer Sciences in Engineering - 4th Workshop on Engineering Applications, WEA 2017, Proceedings
Editors	Juan Carlos Figueroa-Garcia, Eduyn Ramiro Lopez-Santana, Roberto Ferro-Escobar, Jose Luis Villa-Ramirez
Publisher	Springer Verlag
Pages	179-188
Number of pages	10
ISBN (Print)	9783319669625
DOIs	https://doi.org/10.1007/978-3-319-66963-2_17
State	Published - 2017
Event	4th Workshop on Engineering Applications, WEA 2017 - Cartagena, Colombia Duration: 27 Sep 2017 → 29 Sep 2017

Publication series

Name	Communications in Computer and Information Science
Volume	742
ISSN (Print)	1865-0929

Conference

Conference	4th Workshop on Engineering Applications, WEA 2017
Country/Territory	Colombia
City	Cartagena
Period	27/09/17 → 29/09/17

Keywords

Artificial neural network
Bioacoustics monitoring
Environmental monitoring
Intelligent sampling
Soundscape ecology

Access to Document

10.1007/978-3-319-66963-2_17

Cite this

Quiroz, L., Gómez, J., Agudelo, O., & Tobón, L. (2017). Intelligent sampling for colombian soundscapes using an artificial neural network. In J. C. Figueroa-Garcia, E. R. Lopez-Santana, R. Ferro-Escobar, & J. L. Villa-Ramirez (Eds.), Applied Computer Sciences in Engineering - 4th Workshop on Engineering Applications, WEA 2017, Proceedings (pp. 179-188). (Communications in Computer and Information Science; Vol. 742). Springer Verlag. https://doi.org/10.1007/978-3-319-66963-2_17

Quiroz, Luis ; Gómez, Jairo ; Agudelo, Oscar et al. / Intelligent sampling for colombian soundscapes using an artificial neural network. Applied Computer Sciences in Engineering - 4th Workshop on Engineering Applications, WEA 2017, Proceedings. editor / Juan Carlos Figueroa-Garcia ; Eduyn Ramiro Lopez-Santana ; Roberto Ferro-Escobar ; Jose Luis Villa-Ramirez. Springer Verlag, 2017. pp. 179-188 (Communications in Computer and Information Science).

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title = "Intelligent sampling for colombian soundscapes using an artificial neural network",

abstract = "Information extracted from environmental sounds has been of great importance to the analysis of ecological complexity in natural ecosystems. However, the study of these sounds does not have a universal protocol for the sampling and reduction of large quantities of data that it produces. This paper proposes to use a neural network to optimize the sampling of soundscapes of three Colombian ecosystems. The neural network is trained to identify meaningful temporal windows for audio recording from previously gathered data. This method simplifies the acoustic complexity analysis.",

keywords = "Artificial neural network, Bioacoustics monitoring, Environmental monitoring, Intelligent sampling, Soundscape ecology",

author = "Luis Quiroz and Jairo G{\'o}mez and Oscar Agudelo and Luis Tob{\'o}n",

note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 4th Workshop on Engineering Applications, WEA 2017 ; Conference date: 27-09-2017 Through 29-09-2017",

year = "2017",

doi = "10.1007/978-3-319-66963-2_17",

language = "English",

isbn = "9783319669625",

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editor = "Figueroa-Garcia, {Juan Carlos} and Lopez-Santana, {Eduyn Ramiro} and Roberto Ferro-Escobar and Villa-Ramirez, {Jose Luis}",

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Quiroz, L, Gómez, J, Agudelo, O & Tobón, L 2017, Intelligent sampling for colombian soundscapes using an artificial neural network. in JC Figueroa-Garcia, ER Lopez-Santana, R Ferro-Escobar & JL Villa-Ramirez (eds), Applied Computer Sciences in Engineering - 4th Workshop on Engineering Applications, WEA 2017, Proceedings. Communications in Computer and Information Science, vol. 742, Springer Verlag, pp. 179-188, 4th Workshop on Engineering Applications, WEA 2017, Cartagena, Colombia, 27/09/17. https://doi.org/10.1007/978-3-319-66963-2_17

Intelligent sampling for colombian soundscapes using an artificial neural network. / Quiroz, Luis; Gómez, Jairo; Agudelo, Oscar et al.
Applied Computer Sciences in Engineering - 4th Workshop on Engineering Applications, WEA 2017, Proceedings. ed. / Juan Carlos Figueroa-Garcia; Eduyn Ramiro Lopez-Santana; Roberto Ferro-Escobar; Jose Luis Villa-Ramirez. Springer Verlag, 2017. p. 179-188 (Communications in Computer and Information Science; Vol. 742).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Intelligent sampling for colombian soundscapes using an artificial neural network

AU - Quiroz, Luis

AU - Gómez, Jairo

AU - Agudelo, Oscar

AU - Tobón, Luis

PY - 2017

Y1 - 2017

N2 - Information extracted from environmental sounds has been of great importance to the analysis of ecological complexity in natural ecosystems. However, the study of these sounds does not have a universal protocol for the sampling and reduction of large quantities of data that it produces. This paper proposes to use a neural network to optimize the sampling of soundscapes of three Colombian ecosystems. The neural network is trained to identify meaningful temporal windows for audio recording from previously gathered data. This method simplifies the acoustic complexity analysis.

AB - Information extracted from environmental sounds has been of great importance to the analysis of ecological complexity in natural ecosystems. However, the study of these sounds does not have a universal protocol for the sampling and reduction of large quantities of data that it produces. This paper proposes to use a neural network to optimize the sampling of soundscapes of three Colombian ecosystems. The neural network is trained to identify meaningful temporal windows for audio recording from previously gathered data. This method simplifies the acoustic complexity analysis.

KW - Artificial neural network

KW - Bioacoustics monitoring

KW - Environmental monitoring

KW - Intelligent sampling

KW - Soundscape ecology

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U2 - 10.1007/978-3-319-66963-2_17

DO - 10.1007/978-3-319-66963-2_17

M3 - Conference contribution

AN - SCOPUS:85030027724

SN - 9783319669625

T3 - Communications in Computer and Information Science

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EP - 188

BT - Applied Computer Sciences in Engineering - 4th Workshop on Engineering Applications, WEA 2017, Proceedings

A2 - Figueroa-Garcia, Juan Carlos

A2 - Lopez-Santana, Eduyn Ramiro

A2 - Ferro-Escobar, Roberto

A2 - Villa-Ramirez, Jose Luis

PB - Springer Verlag

T2 - 4th Workshop on Engineering Applications, WEA 2017

Y2 - 27 September 2017 through 29 September 2017

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Quiroz L, Gómez J, Agudelo O, Tobón L. Intelligent sampling for colombian soundscapes using an artificial neural network. In Figueroa-Garcia JC, Lopez-Santana ER, Ferro-Escobar R, Villa-Ramirez JL, editors, Applied Computer Sciences in Engineering - 4th Workshop on Engineering Applications, WEA 2017, Proceedings. Springer Verlag. 2017. p. 179-188. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-66963-2_17

Intelligent sampling for colombian soundscapes using an artificial neural network

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