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CADSI
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Our impact areas
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Nature
- AutoWeed: AI Sport Spraying for Smarter Weed Control
- Automated Detection and Counting of Flying-Foxes from Thermal Imagery
- Smart Detection of Marine Invasive Species for Biosecurity
- 3D LiDAR Mapping of Coral Restoration Gardens and Mangrove Ecosystems in Bali and Lombok, Indonesia
- Hyperspectral Satellite Monitoring of Post-Cyclone Water Quality in the Great Barrier Reef
- Automated Estimation of Snail Shell Volume and Morphology
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- Smart Sugarcane Health Monitoring Platform with Satellite Remote Sensing and Machine Learning
- AutoFish: AI Phenotyping for Tropical Aquaculture
- Detecting Variety Contamination in Sugarcane Plots
- Automating South Sea Pearl Phenotyping Through Masking and Deep Learning Algorithms
- Non-Destructive, High-throughput Phenotyping for Aquaculture: NIR Spectroscopy for the “Forensic” Chemical Analysis of Akoya Oyster and Red Algae
- Remote Sensing and Hydrodynamic Modelling for Flood-Driven Soil Erosion in Northern Queensland
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- Beyond the Text: Exploring student engagement and perceptions of AI generated podcasts and infographics in higher education
- Guardrails or Handbrakes? How Australian Universities Frame AI in Policy, and the Dominance of Misconduct Narratives
- Equitable GenAI Co-Pilot for Engineering Education
- VEtheRBlocks: Teaching the Internet with AR and Toy Bricks
- Corrugation Control in Unsealed Roads: Mechanisms and Sustainable Solutions
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We protect and restore tropical environments by combining remote sensing, geospatial analytics and on-ground knowledge to map ecosystems, monitor biodiversity, and support climate resilience. Outcomes include earlier detection of threats, smarter conservation planning, and better stewardship of land and sea Country.
AutoWeed: AI Spot Spraying for Smarter Weed Control
AutoWeed is a collaboration between James Cook University, AutoWeed Pty Ltd, and Sugar Research Australia using AI and robotics to detect and target weeds in sugarcane systems, reducing herbicide use and improving efficiency.
Learn more about this project here
Automated Detection and Counting of Flying-Foxes from Thermal Imagery
The project uses AI and computer vision to monitor endangered spectacled flying-foxes in the Wet Tropics of Queensland using drone-based thermal imaging. It enables faster, scalable population counts to support conservation and ecosystem management.
Learn more about this project here
Automated Estimation of Snail Shell Volume and Morphology
This project uses AI and image segmentation to estimate shell volume and extract morphological traits from gastropod and crustacean specimens. By analysing specimen images, it supports faster, automated measurement for ecological and evolutionary research.<
Learn more about this project here
3D LiDAR Mapping of Coral Restoration Gardens and Mangrove Ecosystems in Bali and Lombok, Indonesia
This project uses AI and 3D laser scanning to monitor coral reef and mangrove restoration in Indonesia. By analysing drone-collected data, it enables faster, scalable tracking of ecosystem recovery and conservation outcomes
Learn more about this project here
This project uses AI and hyperspectral satellite imagery to monitor post-cyclone water quality in the Great Barrier Reef. It improves detection of sediment and water quality changes to support reef conservation and management.
This project uses AI and hyperspectral satellite imagery to monitor post-cyclone water quality in the Great Barrier Reef. It improves detection of sediment and water quality changes to support reef conservation and management.
Learn more about this project here
Smart Detection of Marine Invasive Species for Biosecurity
This project uses AI and image segmentation to estimate shell volume and extract morphological traits from gastropod and crustacean specimens. It enables scalable, automated analysis to support ecological and evolutionary research.
Learn more about this project here