A new lameness detection device designed to daily visualise changes to hoof health, provide early detection of any potential issues and, in turn, enable dairy farmers to make the earliest treatment, has been launched by Hoofcount.

Called Pedivue, the system’s launch marks the completion of a two-year project with £250,000 funding from UK Research and Innovation (UKRI) – part of Defra’s Farming Innovation Programme.

The system, which was designed utilising computer vision and machine learning, was developed by Hoofcount with the UK Agri-Tech Centre at the South West Dairy Development Centre in collaboration with farmers, and the Centre for Machine Vision (CMV) at the University of the West of England, Bristol.

Camera in the footbath is able to identify lesions in the hooves of cattleCamera in the footbath is able to identify lesions in the hooves of cattle

Anthony Marsh of Hoofcount explained: “Digital dermatitis affects well over 90% of dairy herds in the UK contributing to lameness, which continues to be one of the main, if not biggest, issues within the sector costing an estimated £300 per incident.”

He added that while the company’s automatic footbath system is helping reduce and control lameness, particularly digital dermatitis on numerous dairy units, it was agreed that a device to detect these issues as early as possible in order to enable prompt effective treatment was also required. After designing and trialling various options, it becam clear that machine learning and AI was the way forward for the best results.

“With both financial and technical support, together with guidance and direction, we have been able to develop Pedivue. The system’s results, clarity and accuracy, even in its early stages of development, have already gained interest and support from vets and hoof trimmers.”

CMV’s Wenhao Zhang continued: “Hoofcount, together with CMV’s help, developed Pedivue’s computer vision and machine learning algorithm by retrofitting a single camera and an AI system to an existing Hoofcount footbath.

The high-speed camera captured crucial moments of moving hooves, enabling an intelligent filtering algorithm to capture clear, square-on views of hoof soles for AI assessment. By ‘learning’ from extensive hoof data from four farms alongside veterinary expertise, the AI-powered system initially achieved over 80% accuracy in detecting active digital dermatitis lesions.”

Early detection combined with prompt effective treatment (EDPET) is a critical part of managing digital dermatitis on farm – it not only helps cows to recover quicker, but also reduces the risk of further spread, commented Herd Health Consultancy’s Nick Bell, who together with the company’s James Wilson has offered advice and guidance to the project’s development.

“Cows with visible digital dermatitis lesions are the major source of new infections within a herd and the incubation period is very long. However, these lesions are difficult to spot, even with the trained eye,” he said.

“Regular foot bathing is just preventative not a treatment, and occasional hosing of feet will help make lesions visible. However, Pedivue is offering a promising future, enabling farmers to easily identify lesions at the M2 active stage, before they reach the M4 chronic stage, and treat accordingly.”

UK Agri-Tech Centre’s Rob Morrison added: “Pedivue is set to revolutionise hoof health in dairy farms with automated detection using advanced vision and AI, ensuring early intervention, improved animal welfare, and reduced costs. Proven at the UK Agri-Tech Centre’s Dairy Development Centre, this Innovate UK funded project could change the way we monitor hoof health.”

Pedivue – how the device works

  • Pedivue’s high-speed camera takes footage of the moving hooves each time the cow steps away from the footbath.
  • The recordings featuring any images of digital dermatitis – either at the M2 active or M4 chronic stages – are collected in a centrally-located, cloud-based database.
  • The information is downloaded to a farmer-friendly dashboard for viewing on the farm’s PC web browser or phone app.
  • An email alerts the farmer to the information and offers a treatment protocol.
  • A follow up email is issued up to one week later reminding to retreat if necessary, and with an accompanying protocol.