Animal-borne soundscape logger as a system for edge classification of sound sources and data transmission for monitoring near-real-time underwater soundscape
Abstract The underwater environment is filled with various sounds, with its soundscape composed of biological, geographical, and anthropological sounds. Our work focused on developing a novel method to observe and classify these sounds, enriching our understanding of the underwater ecosystem. We con...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-03-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-56439-x |
| _version_ | 1827316151747608576 |
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| author | Takuji Noda Takuya Koizumi Naoto Yukitake Daisuke Yamamoto Tetsuro Nakaizumi Kotaro Tanaka Junichi Okuyama Kotaro Ichikawa Takeshi Hara |
| author_facet | Takuji Noda Takuya Koizumi Naoto Yukitake Daisuke Yamamoto Tetsuro Nakaizumi Kotaro Tanaka Junichi Okuyama Kotaro Ichikawa Takeshi Hara |
| author_sort | Takuji Noda |
| collection | DOAJ |
| description | Abstract The underwater environment is filled with various sounds, with its soundscape composed of biological, geographical, and anthropological sounds. Our work focused on developing a novel method to observe and classify these sounds, enriching our understanding of the underwater ecosystem. We constructed a biologging system allowing near-real-time observation of underwater soundscapes. Utilizing deep-learning-based edge processing, this system classifies the sources of sounds, and upon the tagged animal surfacing, it transmits positional data, results of sound source classification, and sensor readings such as depth and temperature. To test the system, we attached the logger to sea turtles (Chelonia mydas) and collected data through a cellular network. The data provided information on the location-specific sounds detected by the sea turtles, suggesting the possibility to infer the distribution of specific species of organisms over time. The data showed that not only biological sounds but also geographical and anthropological sounds can be classified, highlighting the potential for conducting multi-point and long-term observations to monitor the distribution patterns of various sound sources. This system, which can be considered an autonomous mobile platform for oceanographic observations, including soundscapes, has significant potential to enhance our understanding of acoustic diversity. |
| first_indexed | 2024-04-24T23:08:44Z |
| format | Article |
| id | doaj.art-f3951aa1203d4c7f9b15b18bcddc75ce |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-24T23:08:44Z |
| publishDate | 2024-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-f3951aa1203d4c7f9b15b18bcddc75ce2024-03-17T12:21:23ZengNature PortfolioScientific Reports2045-23222024-03-0114111510.1038/s41598-024-56439-xAnimal-borne soundscape logger as a system for edge classification of sound sources and data transmission for monitoring near-real-time underwater soundscapeTakuji Noda0Takuya Koizumi1Naoto Yukitake2Daisuke Yamamoto3Tetsuro Nakaizumi4Kotaro Tanaka5Junichi Okuyama6Kotaro Ichikawa7Takeshi Hara8Biologging Solutions Inc.Biologging Solutions Inc.Biologging Solutions Inc.Biologging Solutions Inc.Biologging Solutions Inc.Japan Fisheries Science and Technology AssociationFisheries Technology Institute, Japan Fisheries Research and Education AgencyField Science Education and Research Center, Kyoto UniversityJapan Fisheries Science and Technology AssociationAbstract The underwater environment is filled with various sounds, with its soundscape composed of biological, geographical, and anthropological sounds. Our work focused on developing a novel method to observe and classify these sounds, enriching our understanding of the underwater ecosystem. We constructed a biologging system allowing near-real-time observation of underwater soundscapes. Utilizing deep-learning-based edge processing, this system classifies the sources of sounds, and upon the tagged animal surfacing, it transmits positional data, results of sound source classification, and sensor readings such as depth and temperature. To test the system, we attached the logger to sea turtles (Chelonia mydas) and collected data through a cellular network. The data provided information on the location-specific sounds detected by the sea turtles, suggesting the possibility to infer the distribution of specific species of organisms over time. The data showed that not only biological sounds but also geographical and anthropological sounds can be classified, highlighting the potential for conducting multi-point and long-term observations to monitor the distribution patterns of various sound sources. This system, which can be considered an autonomous mobile platform for oceanographic observations, including soundscapes, has significant potential to enhance our understanding of acoustic diversity.https://doi.org/10.1038/s41598-024-56439-xSoundscapeBiologgingEdge classificationDeep learningOcean noise |
| spellingShingle | Takuji Noda Takuya Koizumi Naoto Yukitake Daisuke Yamamoto Tetsuro Nakaizumi Kotaro Tanaka Junichi Okuyama Kotaro Ichikawa Takeshi Hara Animal-borne soundscape logger as a system for edge classification of sound sources and data transmission for monitoring near-real-time underwater soundscape Scientific Reports Soundscape Biologging Edge classification Deep learning Ocean noise |
| title | Animal-borne soundscape logger as a system for edge classification of sound sources and data transmission for monitoring near-real-time underwater soundscape |
| title_full | Animal-borne soundscape logger as a system for edge classification of sound sources and data transmission for monitoring near-real-time underwater soundscape |
| title_fullStr | Animal-borne soundscape logger as a system for edge classification of sound sources and data transmission for monitoring near-real-time underwater soundscape |
| title_full_unstemmed | Animal-borne soundscape logger as a system for edge classification of sound sources and data transmission for monitoring near-real-time underwater soundscape |
| title_short | Animal-borne soundscape logger as a system for edge classification of sound sources and data transmission for monitoring near-real-time underwater soundscape |
| title_sort | animal borne soundscape logger as a system for edge classification of sound sources and data transmission for monitoring near real time underwater soundscape |
| topic | Soundscape Biologging Edge classification Deep learning Ocean noise |
| url | https://doi.org/10.1038/s41598-024-56439-x |
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