WildTracker + Stickybeak AI

We used AI in the Tasmanian Land Conservancy’s (TLC) citizen science project to save thousands of volunteer-hours.

We’ve been collaborating with the TLC since 2019 on WildTracker – a citizen-science program whose online platform enables private landholders to upload, tag, and share camera trap images of Tasmania’s exceptional wildlife.

The program leverages the passion of private landholders — from farmers to suburban homeowners — to gather wildlife data through camera traps placed on their properties across Tasmania.

The aim is to contribute records of Tasmania’s unique wildlife to help scientists at the Tasmanian Land Conservancy answer important ecological questions, gain insights into how our natural environment is changing, and better protect our native species.

Inspired by the curious currawong, Stickybeak is WildTracker’s AI-powered tool designed to streamline your wildlife monitoring.

WildTracker now has over 450 Tasmanian landholders participating who have collectively contributed more than 700,000 images to conservation science. We're thrilled with the stats, but it created a new challenge – efficiently processing this wealth of data.

Luckily, machine learning and AI techniques have been improving rapidly of late, and we've partnered with UTAS researcher Barry Brooks and the TLC team to build a sophisticated machine learning pipeline that's tailored specifically to Tasmania's unique wildlife.

Stickybeak sifts through your camera trap photos, filtering out empty shots triggered by plants or shadows – and any pesky humans – and helps you classify the species captured.

Our AI solution has proven remarkably effective, automatically identifying around 30% of uploads as blank images. This automatic filtering has already saved an estimated 900+ hours of volunteer time. Those are precious hours our conservation community can now dedicate to analysis and action rather than wading through empty frames.

What next?

Looking ahead, we're excited to see the research breakthroughs that emerge from this rich new data source.

We're also keenly tracking how the system's species identification accuracy performs. With AI now integrated into our platform, we're positioned to enhance species detection algorithms further. This technology-conservation partnership represents just the beginning of what's possible when we combine passionate citizen scientists, expert ecologists, and cutting-edge AI.

Up next