Identification of Cow Hoof Disease in Early Stage using Internet of Things (IoT) and Machine Learning
Keywords:
Cow Hoof Health, CSHMoS, Machine Learning, Health Monitoring, Animal Behaviour, IoT in Animal MonitoringAbstract
Monitoring the health of dairy cattle is critical in increasing the global supply of dairy products. Farmers are losing interest in the dairy industry because their animals are suffering from a wide range of debilitating health issues, unpredictability in the form of fatal illnesses and advanced breeding costs. The concept of "Smart Dairy Farming" is no longer just a pipe dream; it has begun to take shape as numerous fields, such as machine learning and IoT, have found practical applications in this sector. The hoof holds immense significance within the anatomy of an animal. The main focus to identify the injured cow's hoof in a early stage. In the dairy industry, timely lameness diagnosis is a significant challenge that farmers must address effectively. Lameness can be caused by several foot and limb disorders, each caused by a different illness, management practice, or environmental factor. The significance of lameness prevention, early detection, and treatment in dairy cows cannot be overstated, given the numerous negative consequences of lameness. Early detection of illness allows farmers to take preventative measures sooner, which may result in reduced or eliminated antibiotic use, increased milk production, and cost savings on veterinary care for their herd. This discovery suggests that classification algorithms could be used to distinguish between the behaviors. The proposed CHHMoS(Cow Hoof Health Monitoring System) device equipped with accelerometer, ESP Node32 Microprocessor and temperature sensor helps to monitor the continuous activity of the cow to predict the Cow Hoof Disease in early manner.
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