Real-time bioacoustics monitoring and automated species identification
Identifieur interne : 000646 ( Pmc/Curation ); précédent : 000645; suivant : 000647Real-time bioacoustics monitoring and automated species identification
Auteurs : T. Mitchell Aide [États-Unis] ; Carlos Corrada-Bravo [États-Unis] ; Marconi Campos-Cerqueira [États-Unis] ; Carlos Milan [États-Unis] ; Giovany Vega [États-Unis] ; Rafael Alvarez [États-Unis]Source :
- PeerJ [ 2167-8359 ] ; 2013.
Abstract
Traditionally, animal species diversity and abundance is assessed using a variety of methods that are generally costly, limited in space and time, and most importantly, they rarely include a permanent record. Given the urgency of climate change and the loss of habitat, it is vital that we use new technologies to improve and expand global biodiversity monitoring to thousands of sites around the world. In this article, we describe the acoustical component of the Automated Remote Biodiversity Monitoring Network (ARBIMON), a novel combination of hardware and software for automating data acquisition, data management, and species identification based on audio recordings. The major components of the cyberinfrastructure include: a solar powered remote monitoring station that sends 1-min recordings every 10 min to a base station, which relays the recordings in real-time to the project server, where the recordings are processed and uploaded to the project website (
Url:
DOI: 10.7717/peerj.103
PubMed: 23882441
PubMed Central: 3719130
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PMC:3719130Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>Traditionally, animal species diversity and abundance is assessed using a variety of methods that are generally costly, limited in space and time, and most importantly, they rarely include a permanent record. Given the urgency of climate change and the loss of habitat, it is vital that we use new technologies to improve and expand global biodiversity monitoring to thousands of sites around the world. In this article, we describe the acoustical component of the Automated Remote Biodiversity Monitoring Network (ARBIMON), a novel combination of hardware and software for automating data acquisition, data management, and species identification based on audio recordings. The major components of the cyberinfrastructure include: a solar powered remote monitoring station that sends 1-min recordings every 10 min to a base station, which relays the recordings in real-time to the project server, where the recordings are processed and uploaded to the project website (<uri xlink:href="http://arbimon.net/arbimon/">arbimon.net</uri>
). Along with a module for viewing, listening, and annotating recordings, the website includes a species identification interface to help users create machine learning algorithms to automate species identification. To demonstrate the system we present data on the vocal activity patterns of birds, frogs, insects, and mammals from Puerto Rico and Costa Rica.</p>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">PeerJ</journal-id>
<journal-id journal-id-type="iso-abbrev">PeerJ</journal-id>
<journal-id journal-id-type="pmc">PeerJ</journal-id>
<journal-id journal-id-type="publisher-id">PeerJ</journal-id>
<journal-title-group><journal-title>PeerJ</journal-title>
</journal-title-group>
<issn pub-type="epub">2167-8359</issn>
<publisher><publisher-name>PeerJ Inc.</publisher-name>
<publisher-loc>San Francisco, USA</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">23882441</article-id>
<article-id pub-id-type="pmc">3719130</article-id>
<article-id pub-id-type="publisher-id">103</article-id>
<article-id pub-id-type="doi">10.7717/peerj.103</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Animal Behavior</subject>
</subj-group>
<subj-group subj-group-type="heading"><subject>Biodiversity</subject>
</subj-group>
<subj-group subj-group-type="heading"><subject>Conservation Biology</subject>
</subj-group>
<subj-group subj-group-type="heading"><subject>Human-Computer Interaction</subject>
</subj-group>
</article-categories>
<title-group><article-title>Real-time bioacoustics monitoring and automated species identification</article-title>
</title-group>
<contrib-group><contrib id="author-1" contrib-type="author" corresp="yes"><name><surname>Aide</surname>
<given-names>T. Mitchell</given-names>
</name>
<xref ref-type="aff" rid="aff-1">1</xref>
<email>tmaide@yahoo.com</email>
</contrib>
<contrib id="author-2" contrib-type="author"><name><surname>Corrada-Bravo</surname>
<given-names>Carlos</given-names>
</name>
<xref ref-type="aff" rid="aff-2">2</xref>
</contrib>
<contrib id="author-3" contrib-type="author"><name><surname>Campos-Cerqueira</surname>
<given-names>Marconi</given-names>
</name>
<xref ref-type="aff" rid="aff-1">1</xref>
</contrib>
<contrib id="author-4" contrib-type="author"><name><surname>Milan</surname>
<given-names>Carlos</given-names>
</name>
<xref ref-type="aff" rid="aff-1">1</xref>
</contrib>
<contrib id="author-5" contrib-type="author"><name><surname>Vega</surname>
<given-names>Giovany</given-names>
</name>
<xref ref-type="aff" rid="aff-2">2</xref>
</contrib>
<contrib id="author-6" contrib-type="author"><name><surname>Alvarez</surname>
<given-names>Rafael</given-names>
</name>
<xref ref-type="aff" rid="aff-2">2</xref>
</contrib>
<aff id="aff-1"><label>1</label>
<institution>Department of Biology, University of Puerto Rico-Rio Piedras</institution>
,<addr-line>San Juan, Puerto Rico</addr-line>
,<country>United States</country>
</aff>
<aff id="aff-2"><label>2</label>
<institution>Department of Computer Science, University of Puerto Rico - Rio Piedras</institution>
,<addr-line>San Juan, Puerto Rico</addr-line>
,<country>United States</country>
</aff>
</contrib-group>
<contrib-group><contrib id="editor-1" contrib-type="editor"><name><surname>Huang</surname>
<given-names>Xiaolei</given-names>
</name>
</contrib>
</contrib-group>
<pub-date pub-type="epub" date-type="pub" iso-8601-date="2013-07-16"><day>16</day>
<month>7</month>
<year iso-8601-date="2013">2013</year>
</pub-date>
<pub-date pub-type="collection"><year>2013</year>
</pub-date>
<volume>1</volume>
<elocation-id>e103</elocation-id>
<history><date date-type="received" iso-8601-date="2013-05-07"><day>7</day>
<month>5</month>
<year iso-8601-date="2013">2013</year>
</date>
<date date-type="accepted" iso-8601-date="2013-06-22"><day>22</day>
<month>6</month>
<year iso-8601-date="2013">2013</year>
</date>
</history>
<permissions><copyright-statement>© 2013 Aide et al.</copyright-statement>
<copyright-year>2013</copyright-year>
<copyright-holder>Aide et al.</copyright-holder>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/3.0/"><license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">Creative Commons Attribution License</ext-link>
, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<self-uri xlink:href="https://peerj.com/articles/103"></self-uri>
<abstract><p>Traditionally, animal species diversity and abundance is assessed using a variety of methods that are generally costly, limited in space and time, and most importantly, they rarely include a permanent record. Given the urgency of climate change and the loss of habitat, it is vital that we use new technologies to improve and expand global biodiversity monitoring to thousands of sites around the world. In this article, we describe the acoustical component of the Automated Remote Biodiversity Monitoring Network (ARBIMON), a novel combination of hardware and software for automating data acquisition, data management, and species identification based on audio recordings. The major components of the cyberinfrastructure include: a solar powered remote monitoring station that sends 1-min recordings every 10 min to a base station, which relays the recordings in real-time to the project server, where the recordings are processed and uploaded to the project website (<uri xlink:href="http://arbimon.net/arbimon/">arbimon.net</uri>
). Along with a module for viewing, listening, and annotating recordings, the website includes a species identification interface to help users create machine learning algorithms to automate species identification. To demonstrate the system we present data on the vocal activity patterns of birds, frogs, insects, and mammals from Puerto Rico and Costa Rica.</p>
</abstract>
<kwd-group kwd-group-type="author"><kwd>Acoustic monitoring</kwd>
<kwd>Machine learning</kwd>
<kwd>Animal vocalization</kwd>
<kwd>Long-term monitoring</kwd>
<kwd>Species-specific algorithms</kwd>
</kwd-group>
<funding-group><award-group id="fund-1"><funding-source>DOD Legacy program</funding-source>
<award-id>W912DY-07-2-0006- P00001, P00002, P0003</award-id>
</award-group>
<award-group id="fund-2"><funding-source>National Science Foundation</funding-source>
<award-id>0640143</award-id>
</award-group>
<award-group id="fund-3"><funding-source>University of Puerto Rico-Rio Piedras</funding-source>
<award-id>FIPI</award-id>
</award-group>
<funding-statement>Funds for this research were provided by the DOD Legacy program (W912DY-07-2-0006- P00001, P00002, P0003), National Science Foundation (0640143), and the University of Puerto Rico-Rio Piedras (FIPI). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement>
</funding-group>
</article-meta>
</front>
</pmc>
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