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The Future of Artificial Intelligence in Monitoring Animal Identification, Health, and Behaviour
SIMPLE SUMMARY: Due to climate change and human interference, many species are now without habitats and on the brink of extinction. Zoos and other conservation spaces allow for non-human animal preservation and public education about endangered species and ecosystems. Monitoring the health and well-...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9265132/ https://www.ncbi.nlm.nih.gov/pubmed/35804610 http://dx.doi.org/10.3390/ani12131711 |
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author | Congdon, Jenna V. Hosseini, Mina Gading, Ezekiel F. Masousi, Mahdi Franke, Maria MacDonald, Suzanne E. |
author_facet | Congdon, Jenna V. Hosseini, Mina Gading, Ezekiel F. Masousi, Mahdi Franke, Maria MacDonald, Suzanne E. |
author_sort | Congdon, Jenna V. |
collection | PubMed |
description | SIMPLE SUMMARY: Due to climate change and human interference, many species are now without habitats and on the brink of extinction. Zoos and other conservation spaces allow for non-human animal preservation and public education about endangered species and ecosystems. Monitoring the health and well-being of animals in care, while providing species-specific environments, is critical for zoo and conservation staff. In order to best provide such care, keepers and researchers need to gather as much information as possible about individual animals and species as a whole. This paper focuses on existing technology to monitor animals, providing a review on the history of technology, including recent technological advancements and current limitations. Subsequently, we provide a brief introduction to our proposed novel computer software: an artificial intelligence software capable of unobtrusively and non-invasively tracking individuals’ location, estimating position, and analyzing behaviour. This innovative technology is currently being trained with orangutans at the Toronto Zoo and will allow for mass data collection, permitting keepers and researchers to closely monitor individual animal welfare, learn about the variables impacting behaviour and provide additional enrichment or interventions accordingly. ABSTRACT: With many advancements, technologies are now capable of recording non-human animals’ location, heart rate, and movement, often using a device that is physically attached to the monitored animals. However, to our knowledge, there is currently no technology that is able to do this unobtrusively and non-invasively. Here, we review the history of technology for use with animals, recent technological advancements, current limitations, and a brief introduction to our proposed novel software. Canadian tech mogul EAIGLE Inc. has developed an artificial intelligence (AI) software solution capable of determining where people and assets are within public places or attractions for operational intelligence, security, and health and safety applications. The solution also monitors individual temperatures to reduce the potential spread of COVID-19. This technology has been adapted for use at the Toronto Zoo, initiated with a focus on Sumatran orangutans (Pongo abelii) given the close physical similarity between orangutans and humans as great ape species. This technology will be capable of mass data collection, individual identification, pose estimation, behaviour monitoring and tracking orangutans’ locations, in real time on a 24/7 basis, benefitting both zookeepers and researchers looking to review this information. |
format | Online Article Text |
id | pubmed-9265132 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92651322022-07-09 The Future of Artificial Intelligence in Monitoring Animal Identification, Health, and Behaviour Congdon, Jenna V. Hosseini, Mina Gading, Ezekiel F. Masousi, Mahdi Franke, Maria MacDonald, Suzanne E. Animals (Basel) Communication SIMPLE SUMMARY: Due to climate change and human interference, many species are now without habitats and on the brink of extinction. Zoos and other conservation spaces allow for non-human animal preservation and public education about endangered species and ecosystems. Monitoring the health and well-being of animals in care, while providing species-specific environments, is critical for zoo and conservation staff. In order to best provide such care, keepers and researchers need to gather as much information as possible about individual animals and species as a whole. This paper focuses on existing technology to monitor animals, providing a review on the history of technology, including recent technological advancements and current limitations. Subsequently, we provide a brief introduction to our proposed novel computer software: an artificial intelligence software capable of unobtrusively and non-invasively tracking individuals’ location, estimating position, and analyzing behaviour. This innovative technology is currently being trained with orangutans at the Toronto Zoo and will allow for mass data collection, permitting keepers and researchers to closely monitor individual animal welfare, learn about the variables impacting behaviour and provide additional enrichment or interventions accordingly. ABSTRACT: With many advancements, technologies are now capable of recording non-human animals’ location, heart rate, and movement, often using a device that is physically attached to the monitored animals. However, to our knowledge, there is currently no technology that is able to do this unobtrusively and non-invasively. Here, we review the history of technology for use with animals, recent technological advancements, current limitations, and a brief introduction to our proposed novel software. Canadian tech mogul EAIGLE Inc. has developed an artificial intelligence (AI) software solution capable of determining where people and assets are within public places or attractions for operational intelligence, security, and health and safety applications. The solution also monitors individual temperatures to reduce the potential spread of COVID-19. This technology has been adapted for use at the Toronto Zoo, initiated with a focus on Sumatran orangutans (Pongo abelii) given the close physical similarity between orangutans and humans as great ape species. This technology will be capable of mass data collection, individual identification, pose estimation, behaviour monitoring and tracking orangutans’ locations, in real time on a 24/7 basis, benefitting both zookeepers and researchers looking to review this information. MDPI 2022-07-01 /pmc/articles/PMC9265132/ /pubmed/35804610 http://dx.doi.org/10.3390/ani12131711 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Communication Congdon, Jenna V. Hosseini, Mina Gading, Ezekiel F. Masousi, Mahdi Franke, Maria MacDonald, Suzanne E. The Future of Artificial Intelligence in Monitoring Animal Identification, Health, and Behaviour |
title | The Future of Artificial Intelligence in Monitoring Animal Identification, Health, and Behaviour |
title_full | The Future of Artificial Intelligence in Monitoring Animal Identification, Health, and Behaviour |
title_fullStr | The Future of Artificial Intelligence in Monitoring Animal Identification, Health, and Behaviour |
title_full_unstemmed | The Future of Artificial Intelligence in Monitoring Animal Identification, Health, and Behaviour |
title_short | The Future of Artificial Intelligence in Monitoring Animal Identification, Health, and Behaviour |
title_sort | future of artificial intelligence in monitoring animal identification, health, and behaviour |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9265132/ https://www.ncbi.nlm.nih.gov/pubmed/35804610 http://dx.doi.org/10.3390/ani12131711 |
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