Early Detection of Cattle Hoof Disease using Internet of Things(IoT) based Sensory Data

Abstract

The monitoring of the health of dairy cattle is an extremely important component in the process of growing the supply of dairy products around the globe. Farmers these days are displaying less interest in the dairy industry since animals are suffering from a wide variety of debilitating health difficulties, unpredictability in the form of fatal illnesses, and advanced breeding expenses. The idea of "Smart Dairy Farming" is no longer only a notion for the distant future; rather, it has begun to materialise as numerous areas, such as machine learning, have found practical applications in this sector. In the dairy business, the timely diagnosis of lameness is a significant challenge that farmers are not yet able to tackle in an effective manner. Lameness may be brought on by a wide variety of foot and limb disorders, each of which can be brought on by a different illness, management practise, or environmental element. The importance of lameness prevention, early identification, and treatment in dairy cows cannot be overstated in light of the many detrimental impacts that may result from lameness. The early discovery of illness provides farmers with the opportunity to take preventative measures sooner, which may result in the reduction or elimination of the use of antibiotics, an increase in milk production, and cost savings on veterinary care for their herd. This finding reveals the possibility of using classification algorithms to differentiate between the behaviours.