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Elephants and algorithms: a review of the current and future role of AI in elephant monitoring
Artificial intelligence (AI) and machine learning (ML) present revolutionary opportunities to enhance our understanding of animal behaviour and conservation strategies. Using elephants, a crucial species in Africa and Asia’s protected areas, as our focal point, we delve into the role of AI and ML in...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10645515/ https://www.ncbi.nlm.nih.gov/pubmed/37963556 http://dx.doi.org/10.1098/rsif.2023.0367 |
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author | Brickson, Leandra Zhang, Libby Vollrath, Fritz Douglas-Hamilton, Iain Titus, Alexander J. |
author_facet | Brickson, Leandra Zhang, Libby Vollrath, Fritz Douglas-Hamilton, Iain Titus, Alexander J. |
author_sort | Brickson, Leandra |
collection | PubMed |
description | Artificial intelligence (AI) and machine learning (ML) present revolutionary opportunities to enhance our understanding of animal behaviour and conservation strategies. Using elephants, a crucial species in Africa and Asia’s protected areas, as our focal point, we delve into the role of AI and ML in their conservation. Given the increasing amounts of data gathered from a variety of sensors like cameras, microphones, geophones, drones and satellites, the challenge lies in managing and interpreting this vast data. New AI and ML techniques offer solutions to streamline this process, helping us extract vital information that might otherwise be overlooked. This paper focuses on the different AI-driven monitoring methods and their potential for improving elephant conservation. Collaborative efforts between AI experts and ecological researchers are essential in leveraging these innovative technologies for enhanced wildlife conservation, setting a precedent for numerous other species. |
format | Online Article Text |
id | pubmed-10645515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-106455152023-11-15 Elephants and algorithms: a review of the current and future role of AI in elephant monitoring Brickson, Leandra Zhang, Libby Vollrath, Fritz Douglas-Hamilton, Iain Titus, Alexander J. J R Soc Interface Review Articles Artificial intelligence (AI) and machine learning (ML) present revolutionary opportunities to enhance our understanding of animal behaviour and conservation strategies. Using elephants, a crucial species in Africa and Asia’s protected areas, as our focal point, we delve into the role of AI and ML in their conservation. Given the increasing amounts of data gathered from a variety of sensors like cameras, microphones, geophones, drones and satellites, the challenge lies in managing and interpreting this vast data. New AI and ML techniques offer solutions to streamline this process, helping us extract vital information that might otherwise be overlooked. This paper focuses on the different AI-driven monitoring methods and their potential for improving elephant conservation. Collaborative efforts between AI experts and ecological researchers are essential in leveraging these innovative technologies for enhanced wildlife conservation, setting a precedent for numerous other species. The Royal Society 2023-11-15 /pmc/articles/PMC10645515/ /pubmed/37963556 http://dx.doi.org/10.1098/rsif.2023.0367 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Review Articles Brickson, Leandra Zhang, Libby Vollrath, Fritz Douglas-Hamilton, Iain Titus, Alexander J. Elephants and algorithms: a review of the current and future role of AI in elephant monitoring |
title | Elephants and algorithms: a review of the current and future role of AI in elephant monitoring |
title_full | Elephants and algorithms: a review of the current and future role of AI in elephant monitoring |
title_fullStr | Elephants and algorithms: a review of the current and future role of AI in elephant monitoring |
title_full_unstemmed | Elephants and algorithms: a review of the current and future role of AI in elephant monitoring |
title_short | Elephants and algorithms: a review of the current and future role of AI in elephant monitoring |
title_sort | elephants and algorithms: a review of the current and future role of ai in elephant monitoring |
topic | Review Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10645515/ https://www.ncbi.nlm.nih.gov/pubmed/37963556 http://dx.doi.org/10.1098/rsif.2023.0367 |
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