Novel Real-Time Heat Detection System for Dairy Cows Based on Supervised Techniques and Smart Collars

Abstract

[Abstract] In precision animal husbandry, behavioral monitoring collars have become widely used tools for individualized and real-time herd management. These devices allow for the collection of individual animal activity data to be analyzed to identify behavioral patterns or specific events of interest. One of the most relevant events that can be detected by analyzing behavioral changes is estrus. In this context, the present paper analyzes and compares the performance of several supervised classification techniques combined with feature engineering for early estrus detection in dairy cows from intensive farms using behavioral data obtained from a commercial smart collar. For this purpose, twelve dairy cows were monitored in a Galician intensive farm, and customized models were developed for each animal. Several configurations of both the models and the input data used were evaluated. The results obtained were excellent, reaching, in some cases, F1-Score values of up to 1 in specific configurations and techniques. In addition, this research demonstrates a high variability in model performance between cows, highlighting the need to develop individualized animal models. It is also concluded that to obtain good results, it is essential to provide the model with a temporal context that includes the animal’s previous behavior.