Early Detection of Lameness in Dairy Cattle Using Activity Data, Image Analysis, AI and ML - An Approach for Improved Animal Welfare and Economic Impact

Abstract

The economic burden of lameness in dairy cattle is a significant challenge facing the worldwide dairy industry. Studies suggest that it can cost the industry billions of dollars annually, with the exact cost varying by region. In the United States, the cost of lameness is estimated to be approximately $2 billion per year, while in the United Kingdom, it is around £200 million per year. These costs include lost milk production, decreased fertility, and treatment expenses. The impact of lameness on dairy cattle is far-reaching, posing a significant economic burden on farmers and countries and affecting animal welfare, milk production, and farm profitability. It is particularly concerning for small and marginal farmers, who are vulnerable to economic and financial sustainability concerns. Early detection and prevention of lameness are crucial to reducing these costs and improving the overall health and productivity of dairy herds. Prevalence rates vary globally, ranging from 17% to 35% in dairy herds, underscoring the urgent need for innovative solutions. Our proposed paper offers a novel approach to addressing this challenge. By combining activity data captured by Cow Necklace IoT Sensor and image analysis with Computer Vision, alongside expert veterinarian input, we provide a comprehensive and data-driven solution for early lameness detection in dairy cattle. This approach has the potential to significantly improve animal welfare, farm management practices, and overall herd productivity, leading to substantial economic benefits for farmers and the agricultural sector as a whole.