AI-empowered visual recognition system for dairy cow identification, health and behaviour monitoring
Project overview
Project title
AI-empowered visual recognition system for dairy cow identification, health and behaviour monitoring and detection
Project description
This project develops an AI-driven system to identify individual cows, and monitor and detect their health and behaviour, through the use of facial recognition, posture analysis, and thermal imaging. The expected outcome is early detection of illness and abnormal activity of cows. This project will support productivity, reduce losses, and improve animal welfare in the dairy industry.
Supervisory team
University
| Name of university supervisor | Associate Professor Hai Wang |
| Name of university | Murdoch University |
| Email address | hai.wang@murdoch.edu.au |
| Faculty | College of Science, Technology, Engineering and Mathematics |
CSIRO
| Name of CSIRO supervisor | Dr Quanxi Shao |
| Email address | Quanxi.Shao@data61.csiro.au |
| CSIRO Research Unit | Data61 |
Industry
| Name of industry supervisor | Dr Mark McHenry |
| Name of business/organisation | Peninsula Downs Pty Ltd |
| Email address | mpmchenry@gmail.com |
Further details
| Primary location of student | Murdoch University, 90 South Street, Murdoch WA 6150, Australia |
| Industry engagement component location | Peninsula Downs Pty Ltd, 1713 Warner Glen Road, Warner Glen WA 6288, Australia |
| Other locations | CSIRO Kensington, 26 Dick Perry Avenue, Kensington WA 6151, Australia |
| Ideal student skillset | A background in computer science, machine learning, AI engineering, or a related discipline, with strong skills in computer vision and programming (e.g., Python, PyTorch, or TensorFlow). Experience with image/video analysis or thermal data processing is desirable. Familiarity with animal behaviour, agricultural systems, or human/animal posture recognition is a plus. Strong communication skills and the ability to work collaboratively across academic and industry settings. |
| Application close date | Open until position filled |
| Apply | Contact Associate Professor Hai Wang |