Abstract: The present disclosure provides systems and methods for animal health monitoring. Load data can be obtained from an animal monitoring device including three or more load sensors associated with a platform carrying contained litter thereabove, wherein individual load sensors of the three or more load sensors are separated from one another and receive pressure input from the platform independent of one another, wherein the three or more load sensors individually sample loads at from 2.5 Hz to 110 Hz. An animal behavior property associated with the animal can be recognized if it is determined based on load data that the interaction with the contained litter was due to the animal interaction with the contained litter. The animal behavior property can be classified into an animal classified event using a machine learning classifier.

Abstract: The present disclosure provides systems and methods for animal health monitoring. Load data can be obtained from an animal monitoring device including three or more load sensors associated with a platform carrying contained litter thereabove, wherein individual load sensors of the three or more load sensors are separated from one another and receive pressure input from the platform independent of one another, wherein the three or more load sensors individually sample loads at from 2.5 Hz to 110 Hz. An animal behavior property associated with the animal can be recognized if it is determined based on load data that the interaction with the contained litter was due to the animal interaction with the contained litter. The animal behavior property can be classified into an animal classified event using a machine learning classifier.

Abstract: The present disclosure provides systems and methods for animal health monitoring. Load data can be obtained from an animal monitoring device including three or more load sensors associated with a platform carrying contained litter thereabove, wherein individual load sensors of the three or more load sensors are separated from one another and receive pressure input from the platform independent of one another, wherein the three or more load sensors individually sample loads at from 2.5 Hz to 110 Hz. An animal behavior property associated with the animal can be recognized if it is determined based on load data that the interaction with the contained litter was due to the animal interaction with the contained litter. The animal behavior property can be classified into an animal classified event using a machine learning classifier.

Abstract: The present disclosure provides systems and methods for animal health monitoring. Load data can be obtained from a plurality of load sensors associated with a platform carrying contained litter thereabove, wherein individual load sensors of the plurality of load sensors are separated from one another and receive pressure input from the platform independent of one another. If the load data is determined or not to be from an animal interaction with the contained litter, an animal behavior property associated with an animal is recognized if a determination is made based on load data that the interaction with the contained litter was due to the animal interaction. The animal behavior property is classified into an animal classified event using a machine learning classifier. A change in the animal classified event is identified as compared to a previously recorded event associated with the animal.