Advanced Video Processing to Optimise Feeding of Livestock in Farms
Dr Paul Murray, University of Strathclyde; Prof Ilias Kyriazakis, Queen’s University Belfast; Anthony McMahon Peacock Technology (Industry Supervisor)
Interview date
Tuesday 12th March, between 2pm and 5pm, via Zoom
Apply for this studentship
See our Application Page.
Research Aims
A key contributor to the GHG footprint of milk production is associated with animal feedstock, which, if not optimised for each animal, can lead to increases in CH4. This PhD project will introduce new video processing tools to interpret animal eating and feeding- behaviours before, during and after eating with the aim of personalising and optimising the feedstock for individual farm animals. To achieve this, the successful candidate will design state-of-the-art image and video processing analytics using AI (artificial intelligence) and machine learning (ML), potentially in combination with traditional signal processing techniques.
The successful candidate will be based predominantly within the Technology and Innovation Centre at the University of Strathclyde where they will work alongside existing PhD students, postdoctoral researchers and the academic supervisor who will provide support, guidance and training. Specifically, the successful student will learn about the theory, application and ways in which to conduct research in the areas of AI and ML based image and video processing. The student will also be supported by a second supervisor based at Queen’s University Belfast who will provide expertise in assessing and quantifying the environmental impact of the proposed approach for reducing GHG emissions in the farming industry. Finally, the successful candidate will spend time on a weekly basis (1-2 days a week) at Peacock Technology where they will work and function as part of the company to conduct and deliver the research alongside a team of Peacock Technology engineers with expertise in designing and deploying innovative robotics and sensor platforms with embedded signal, image and video processing solutions.
The successful candidate will have access to state-of-the-art computing facilities, large volumes of data and all of the tools and training required to successfully complete their PhD studies with us. There will also be opportunities to publish work in leading international conferences and journals.