Role Title: Project Intern: Using AI to Identify Northern Quolls from Camera Trap Images
Organisation: Department of Biodiversity, Conservation and Attractions
Internship Period: Summer (November - December)
Location: Woodvale
The Department of Biodiversity, Conservation and Attractions is exploring the use of artificial intelligence (AI) software to identify individual quolls from camera trap images based on their unique spot patterns. This project will support wildlife monitoring and conservation research by investigating how AI-assisted image analysis can help identify individual animals and improve the efficiency of processing camera trap data.
The intern will work with the project team to review and organise camera trap images, assist with AI-assisted identification, and undertake manual verification of results. Where feasible, the placement may also include an introduction to fieldwork, including demonstrating how camera traps are installed and used for wildlife monitoring.
Key Activities
Review, sort and organise camera trap images of quolls.
Use AI software and digital tools to assist with identifying individual quolls from images.
Manually examine and verify image classifications and identification results.
Record, organise and maintain accurate data relating to individual quoll sightings and identifications.
Assist with checking data quality and documenting identification outcomes.
Work with the project team to explore opportunities to improve the efficiency and accuracy of AI-assisted wildlife identification.
Where practical and appropriate, participate in or observe fieldwork activities, including learning how camera traps are set up to monitor wildlife.
The Department of Biodiversity, Conservation and Attractions (DBCA) brings together the Parks and Wildlife Service, Botanic Gardens and Parks Authority, Zoological Parks Authority (Perth Zoo), Rottnest Island Authority, Conservation and Parks Commission, Swan River Trust (Swan Canning Riverpark) and Biodiversity and Conservation Science.