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Using artificial intelligence to monitor wildlife

Camera traps (motion-triggered cameras) are used for monitoring a range of wildlife species in Aotearoa New Zealand, including native and invasive animals. These cameras provide essential information on animal abundance, distribution, and behaviour, but they have one major drawback: they can produce thousands of images, many of which are empty, and which are time-consuming and costly to process.

With funding from Predator Free 2050 and the Ministry of Business, Innovation and Employment (MBIE)’s Kiwi Rescue programme, Manaaki Whenua researchers Dr Brent Martin and Dr Al Glen have developed a free online tool, CamTrapNZ, which allows users to manage their images quickly and easily.

The tool uses artificial intelligence (AI) to identify images of 15 taxa commonly detected by camera traps in AoNZ: kiwi, other birds, cats, deer, dogs, ferrets, goats, stoats/weasels, possums, rodents, hedgehogs, rabbits/hares, wallabies, pigs, and livestock. The model could be trained to recognise more taxa in the future. The software is hosted on TrapNZ , a free online platform widely used for recording pest control, monitoring, and biodiversity outcome data in AoNZ.


Camera trap images showing that accurate species identification can be difficult.

The accuracy of species identification depends on the species, and also whether the image is colour (daytime) or black and white (night), says Al. “For example, the AI will detect wallabies around 98 percent of the time, but has much lower accuracy for mice. This is mainly because mice are so small that they often appear as little more than a dot in the images. Accuracy is generally higher with colour images than with black and white ones.”

Some species are grouped together because the images captured by camera traps don’t always show distinguishing features. Rats and mice are particularly difficult to separate. The online tool allows users to produce maps, graphs, and other reports of their results. Further improvements to CamTrapNZ are planned, including improved accuracy of species identification, more species, and new software that runs on the user’s own computer, without the need to upload images to a server.

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