AI methods for the early detection of equine diseases

For the development of non-invasive detection of behaviors and activities in horses, we are utilizing cutting-edge AI methods, specifically from the field of computer vision. This expertise is applied under real-world conditions, incorporating domain experts from our collaboration partner, the State Stud of Redefin, to validate our solution for the early detection of diseases and discomfort in horses under practical conditions. The goal is to detect issues such as general stress and colic.

For private horse owners, the developed solution offers the possibility of 24-hour monitoring of their mostly unsupervised animals, allowing them to intervene either immediately in acute conditions or gradually in case of long-term behavioral abnormalities, ultimately improving horse care in a sustainable way and promoting animal welfare.

The collected data and developed models are specifically designed and optimized with a focus on B2C applications for private horse owners. The results of the research will later be offered to this target group in the form of a product for condition monitoring of horses in the stall, adding value to their care.