A Social Network for Dairy Cattle
The analysis of animals’ behavior is an essential part for understanding their state of health, in many senses. A body condition score (BCS) can be used as a part of such analysis: such a score is based on estimates of fat on the animals’ upper hind quarters, coat condition, visibility of bone structure, and other indicators. When coupled with other metrics, such as biometric data, milk quantity and quality data, etc, we arrive at a data set that can be used as an input for predicting reproductive performance and productivity, and even effectiveness of nutrition, heat stress, and other health factors. Images / video footage of dairy cattle can serve as input in the task of classifying the health situation of that individual. More specifically, by extracting features from pixels, a deep learning model can learn the underlying correlation between the input pictures and the overall BCS of those cattle. These results would then be utilized for constructing a network of social networks of cattle. This social network can visualize all important indicators for the health of the individual cattle and the herd and become a powerful tool for the animal experts and digital farms.
