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Seabird surveillanc...
Seabird surveillance: combining CCTV and artificial intelligence for monitoring and research
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- Hentati-Sundberg, Jonas (author)
- Sveriges lantbruksuniversitet (SLU),Swedish University of Agricultural Sciences (SLU)
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- Olin, Agnes (author)
- Stockholms universitet,Institutionen för ekologi, miljö och botanik,Swedish University of Agricultural Sciences, Sweden,Sveriges lantbruksuniversitet (SLU),Swedish University of Agricultural Sciences (SLU),Stockholm University
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- Reddy, Sheetal (author)
- Volvo
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Berglund, Per Arvid (author)
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Svensson, Erik (author)
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- Reddy, Mareddy, 1993 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Kasarareni, Siddharta (author)
- Stiftelsen Chalmers Industriteknik
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- Carlsen, Astrid A. (author)
- Sveriges lantbruksuniversitet (SLU),Swedish University of Agricultural Sciences (SLU)
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- Hanes, Matilda (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Kad, Shreyash (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Olsson, Olof, 1961- (author)
- Stockholms universitet,Stockholm Resilience Centre
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(creator_code:org_t)
- 2023-03-07
- 2023
- English.
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In: Remote Sensing in Ecology and Conservation. - : Wiley. - 2056-3485. ; 9:4, s. 568-581
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https://doi.org/10.1...
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Abstract
Subject headings
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- Ecological research and monitoring need to be able to rapidly convey information that can form the basis of scientifically sound management. Automated sensor systems, especially if combined with artificial intelligence, can contribute to such rapid high-resolution data retrieval. Here, we explore the prospects of automated methods to generate insights for seabirds, which are often monitored for their high conservation value and for being sentinels for marine ecosystem changes. We have developed a system of video surveillance combined with automated image processing, which we apply to common murres Uria aalge. The system uses a deep learning algorithm for object detection (YOLOv5) that has been trained on annotated images of adult birds, chicks and eggs, and outputs time, location, size and confidence level of all detections, frame-by-frame, in the supplied video material. A total of 144 million bird detections were generated from a breeding cliff over three complete breeding seasons (2019–2021). We demonstrate how object detection can be used to accurately monitor breeding phenology and chick growth. Our automated monitoring approach can also identify and quantify rare events that are easily missed in traditional monitoring, such as disturbances from predators. Further, combining automated video analysis with continuous measurements from a temperature logger allows us to study impacts of heat waves on nest attendance in high detail. Our automated system thus produces comparable, and in several cases significantly more detailed, data than those generated from observational field studies. By running in real time on the camera streams, it has the potential to supply researchers and managers with high-resolution up-to-date information on seabird population status. We describe how the system can be modified to fit various types of ecological research and monitoring goals and thereby provide up-to-date support for conservation and ecosystem management.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Annan teknik -- Övrig annan teknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Other Engineering and Technologies -- Other Engineering and Technologies not elsewhere specified (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
- NATURVETENSKAP -- Biologi -- Ekologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Ecology (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Naturresursteknik -- Fjärranalysteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Environmental Engineering -- Remote Sensing (hsv//eng)
Keyword
- machine learning
- monitoring
- object detection
- Artificial intelligence
- seabirds
Publication and Content Type
- art (subject category)
- ref (subject category)
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- By the author/editor
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Hentati-Sundberg ...
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Olin, Agnes
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Reddy, Sheetal
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Berglund, Per Ar ...
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Svensson, Erik
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Reddy, Mareddy, ...
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show more...
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Kasarareni, Sidd ...
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Carlsen, Astrid ...
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Hanes, Matilda
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Kad, Shreyash
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Olsson, Olof, 19 ...
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- About the subject
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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and Other Computer a ...
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- ENGINEERING AND TECHNOLOGY
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ENGINEERING AND ...
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and Other Engineerin ...
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and Other Engineerin ...
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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and Computer Vision ...
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Biological Scien ...
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and Ecology
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- ENGINEERING AND TECHNOLOGY
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ENGINEERING AND ...
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and Environmental En ...
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and Remote Sensing
- Articles in the publication
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Remote Sensing i ...
- By the university
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Chalmers University of Technology
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Stockholm University