The importance of sleep: using AI (video-based motion capture systems) to improve the health, resilience and productivity of dairy cows
Lead Research Organisation:
Aberystwyth University
Department Name: IBERS
Abstract
This project focuses on sleep in dairy cows. Sleep is one of most critical and often overlooked factors affecting farm animal health and production. It is fundamental to animal well-being and chronically disrupted sleep leads to a number of issues such changes in brain function, changes in physiology and reduced resilience to stress. Optimal sleep is, therefore, critical to the well-being of animals and, in the context of farm animals, has the potential to greatly impact the animal's level of sustainability and production. Understanding and being able to improve farm animal sleep is, thus, both an ethical and economic priority. There are three main stages of the project which are:
1.
To collect video footage of wake and sleep states of 10 cows within a commercial indoor dairy system alongside EEG and actigraphy data;
2.
To use artificial intelligence techniques to train computer vision technology to identify different sleep, wake and eating states from the videos footage by cross-referencing the behavioural, EEG and actigraphy data;
3.
To validate the automated sleep video analysis system by running a sleep disturbance trial through small changes in the animal's husbandry (light and bedding).
1.
To collect video footage of wake and sleep states of 10 cows within a commercial indoor dairy system alongside EEG and actigraphy data;
2.
To use artificial intelligence techniques to train computer vision technology to identify different sleep, wake and eating states from the videos footage by cross-referencing the behavioural, EEG and actigraphy data;
3.
To validate the automated sleep video analysis system by running a sleep disturbance trial through small changes in the animal's husbandry (light and bedding).
Organisations
People |
ORCID iD |
| Lok Ka (Jacky) Kuo (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| BB/T008776/1 | 30/09/2020 | 29/09/2028 | |||
| 2938804 | Studentship | BB/T008776/1 | 20/01/2025 | 19/01/2029 | Lok Ka (Jacky) Kuo |