An AI-operated smart gate system for increasing the permeability of conservation fences

Context Wildlife management in the Anthropocene is a complex and challenging task, that involves balancing the needs of different species and ecosystems. There is now broad consensus that a network of large, feral predator-free fenced areas must form part of any strategy to prevent further extinctions of Australian mammals. However, fencing to protect threatened species from introduced predators can have drawbacks such as restricting natural migration and dispersal, and creating barriers to gene flow or ecological processes. Therefore, developing innovative solutions to optimise the use of fencing and minimise negative effects is an important goal for Australian conservation practitioners. Aims We aimed to develop a method for allowing target species to move from one side of a conservation fence to another, while maintaining the fence as a barrier for all other species. Methods We designed and built a prototype artificial intelligence (AI)-operated Smart Gate system to allow target species to move through a fence while preventing non-target species from doing so. We conducted two rounds of field-testing at Karakamia Wildlife Sanctuary to train the AI species classifier to recognise brush-tailed bettongs (woylies, Bettongia penicillata) and to test the AI-operated Smart Gate system. Key results The field-trials provided a convincing proof of concept, with 42 successful and safe woylie transits and zero non-target species transits through the Smart Gate system from 73 events when an animal entered the system. Conclusions The AI-operated Smart Gate has the potential to be used as a management tool to allow transit of target species across conservation fences. Implications There are many potential future applications for this technology, including allowing target species to enter or exit a fenced area, improving connectivity between a fenced area and the surrounding landscape by allowing some species to pass through the fence in either direction, or acting as a trap for a highly targeted monitoring or management purpose. Although further refinement is needed before a real-world application, devices such as this Smart Gate are likely to become part of the toolkit for managing conservation fences in Australia and beyond.

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Publication Details

Journal
Wildlife Research
Published
2026-06-25
DOI
https://doi.org/10.1071/wr26033
Primary Topic
Wildlife-Road Interactions and Conservation
Type
article
Field-Weighted Citation Impact
0.00
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article

An AI-operated smart gate system for increasing the permeability of conservation fences

Bryony Palmer, Amanda R. Bourne, Phil Scully, John Corey et al.
Wildlife Research
Wildlife-Road Interactions and Conservation
article

An AI-operated smart gate system for increasing the permeability of conservation fences

Bryony Palmer, Amanda R. Bourne, Phil Scully, John Corey, Damien Kerr, Yezmin Assad, Quan Tran
article en

Abstract

Context Wildlife management in the Anthropocene is a complex and challenging task, that involves balancing the needs of different species and ecosystems. There is now broad consensus that a network of large, feral predator-free fenced areas must form part of any strategy to prevent further extinctions of Australian mammals. However, fencing to protect threatened species from introduced predators can have drawbacks such as restricting natural migration and dispersal, and creating barriers to gene flow or ecological processes. Therefore, developing innovative solutions to optimise the use of fencing and minimise negative effects is an important goal for Australian conservation practitioners. Aims We aimed to develop a method for allowing target species to move from one side of a conservation fence to another, while maintaining the fence as a barrier for all other species. Methods We designed and built a prototype artificial intelligence (AI)-operated Smart Gate system to allow target species to move through a fence while preventing non-target species from doing so. We conducted two rounds of field-testing at Karakamia Wildlife Sanctuary to train the AI species classifier to recognise brush-tailed bettongs (woylies, Bettongia penicillata) and to test the AI-operated Smart Gate system. Key results The field-trials provided a convincing proof of concept, with 42 successful and safe woylie transits and zero non-target species transits through the Smart Gate system from 73 events when an animal entered the system. Conclusions The AI-operated Smart Gate has the potential to be used as a management tool to allow transit of target species across conservation fences. Implications There are many potential future applications for this technology, including allowing target species to enter or exit a fenced area, improving connectivity between a fenced area and the surrounding landscape by allowing some species to pass through the fence in either direction, or acting as a trap for a highly targeted monitoring or management purpose. Although further refinement is needed before a real-world application, devices such as this Smart Gate are likely to become part of the toolkit for managing conservation fences in Australia and beyond.

Wildlife ResearchVol. 53(6)
Australian Wildlife Conservancy (AU)
Life in Land
Openalex Percentile: Top 7%
Wildlife-Road Interactions and Conservation
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