The FishID project aims to transform environmental monitoring of aquatic ecosystems in Australia through automated detection and identification of animals in underwater imagery.
The FishID platform will overcome the cost associated with manually processing and extracting data from underwater cameras by creating a user-friendly, public-facing end-to-end pipeline for deep learning detection and automated identification of animals. FishID will deliver a robust and intuitive system for researchers to annotate imagery, train and evaluate deep learning models to accurately detect, identify and count species of interest across coastal and marine ecosystems.
Who is this project for?
- Federal and state government
- Environmental educators
- Tourism operators
What does this project enable?
This project fills a critical infrastructure gap between the collection of underwater imagery and the resulting data made available in national repositories.
The project will enable a step-change in monitoring efficiency that will improve outcomes across multiple sectors such as marine environmental monitoring (e.g. environmental assessments, State of Environment reporting); river health monitoring (e.g. Murray-Darling Basin Authority); fisheries assessments (e.g. State Fisheries departments); aquatic habitat restoration (e.g. NGOs investing $130 million in reef restoration over 5 years), some already with streaming cameras suitable for automated image analysis; education (e.g. Moreton Bay Live streaming cameras by QLD Environmental Education Centre); and tourism (e.g. Great Barrier Reef live streaming cameras with Cairns Aquarium).
- FishID: Automated analysis of underwater video footage
- Microsoft AI grant sharpens PhD’s eye on fish monitoring
- Automated fish identification and abundance using Artificial Intelligence
- Automated fish tracking for aquatic conservation
- Reference: https://doi.org/10.47486/PL071
- Full title: Transforming Australian aquatic ecosystem monitoring using AI