# AI-Based Intelligent Monitoring System for Estrus Prediction in the Livestock Industry
### The Livestock Activity Monitoring  
In the case of animals, they all have similar shapes in appearance, and because they behave according to their self-awareness as living individuals, it is difficult to predict their behavioral characteristics. The data for analysis of animals' behavioral characteristics are mostly collected through real-time observation using cameras. When acquiring the activity images of animals, the observer is excluded as much as possible to avoid influencing the natural behaviors of the animals.  
In the image acquisition process, the activities of the animals can be detected using various sensors, such as infrared sensors, and the acquired image information and the detected patterns from the sensors are used as information for observing the detailed behavioral characteristics of the target animal. This image acquisition process must minimize factors that may influence the animal's behavior and secure the target animals' rights.  
In terms of industrial applications, the method can be applied for observation and monitoring of health conditions of livestock resources, specific, abnormal, or unusual behavior of the livestock, such as estrus, and efficient management of livestock and their environment. The animals' behavioral characteristics are analyzed by experts' visual checks with the acquired images later, and the meanings of the behavioral characteristics are investigated [5].  
The method of observing livestock is also very similar to the environment of animal observation. In the case study of Hanwoo, the estrus manifestation timing of Hanwoo appears between 6:00 p.m. and 6:00 a.m. with a 55.9% probability [6]. It has been found through the research of various conditions and visual methods to check estrus that close observation in intervals of 4 to 5 h per day in the early morning and late evening is most effective [7]. Estrus often begins at inconvenient times, such as at night when it is difficult to detect estrus through direct observation. In large-scale livestock environments, the probability of detecting estrus manifestation is quite low because it is difficult for the worker to directly distinguish and specify the target Hanwoo that has manifested estrus because most Hanwoo have similar appearances [8].  
A number of studies have been conducted in relation to the detection or prediction of estrus manifestation, and the methods of attaching accelerometers to the neck and ankles of Hanwoo to detect the mounting motion or temperature sensors to the tail to detect the change in body temperature were used for the prediction of estrus manifestation sign. However, because these methods may interfere with cattle behavior and cause problems in animal welfare, we used AI technology, which is image-based object classification. Related to the reasons, instead of attaching various electronic devices and sensors to animals and collecting information from them, the method using AI based on image information is more appropriate in terms of securing healthy livestock resources as well as animal rights, contributing to the establishment of safe livestock farms.  
For the safe management of livestock resources and the establishment of an effective breeding environment, information that can determine and verify the objective state of animal objects needs to be properly defined, collected, and shared with livestock professionals, field workers, and executives.