Devices, systems and methods for animal training, animal feeding, animal management, animal fitness, monitoring and managing animal food intake, remote animal engagement, behavioral training and animal entertainment are disclosed. Embodiments of the present invention provide devices, systems and methods for measuring a dog’s energy expenditures and/or movements, and providing signals to the dog to engage in activities or games to earn food. In one aspect, one or more of the dog’s activity level, age, weight, body mass, and/or other health information is utilized to determine an appropriate food intake level for the dog. By measuring the dog’s activity, the amount of calories the dog needs and/or has utilized may be determined. By encouraging activity by the dog, the dog’s health may improve, even if the dog’s weight remains unchanged. Among other embodiments disclosed herein, various mechanisms capable of moderating animal noise and/or behavior are disclosed.

An agricultural data collection framework is provided in a system and method for tracking and managing livestock, and for analyzing animal conditions such as health, growth, nutrition, and behavior. The framework uses ultra-high frequency interrogation of RFID tags to collect individual animal data across multiple geographical locations, and incorporates artificial intelligence techniques to develop machine learning base models for statistical process controls around each animal for evaluating the animal condition. The framework provides a determination of normality at an individual animal basis or for a specific location, and generates alerts, predictions, and a targeted processing or application schedule for prioritizing and delivering resources when intervention is needed.

An orientation indicator device that includes a band having an interior side, an exterior side, and a length to wrap around a neck of an animal. The orientation indicator device includes at least one fiducial marker attached to the band that is visible from the exterior side of the band to denote an orientation of the animal. The orientation indicator device includes a tag coupled to the band to hang by gravity from under the neck. The band is in the form of a collar with fasteners to fasten the collar around the neck. A system is also disclosed that includes a walk-in analysis zone. The orientation indicator device and a computer vision system, in the walk-in analysis zone, identify an orientation of an animal in the zone by capturing the orientation indicator device and dimensions of a body of the animal.

A system that includes a persuasion delivery device to deliver a persuasion to an animal to persuade the animal into a walk-in analysis zone for conducting an examination session. The system includes a set of sensors to sense in real-time at least one biological parameter to create real-time biological data. Each sensor has a sample collector in the walk-in analysis zone to capture a respective biological parameter. The system includes at least one processor to analyze the real-time biological data and at least one of: recommending animal feed nutrients based on the analyzed real-time biological data; identifying the at least one biological parameter on a user interface; and causing a feed making machine to make animal feed based on the recommended animal feed nutrients.

A method of feeding a group of animals at a feeding location includes automatically determining an expected feed demand for the group of animals to be fed using a computer; automatically harvesting feed crop in a crop field using an autonomous, unmanned device; automatically loading the harvested feed crop into a storage space provided on the autonomous, unmanned device; automatically transporting the feed crop from the crop field to the feeding location by means of the autonomous, unmanned device; and automatically dosing harvested feed from the storage space of the autonomous; unmanned device to the animals at the feeding location. A completely automated method for determining a feed demand and then harvesting, transporting and dosing the harvested feed to the animals is thus realized. A system for performing the method of feeding a group of animals at a feeding location is also disclosed.

A smart feeding device for cats, comprises a feeder body and a food discharge mechanism provided on the feeder body; the food discharge mechanism comprises a food bowl and a weighing tray; the food bowl is fixed to the weighing tray; a tray fixing member is fixed at the bottom of the weighing tray; and a weighing sensor is arranged in the tray fixing member. The device also comprises a device for recognizing multiple cats and a food scattering device. The food scattering device is arranged in a food storage bin of the feeder body and comprises silica gel blades, food discharge blades and a food discharge impeller box which are sequentially arranged from top to bottom. Cat food in the food bowl is weighed by means of the weighing sensor, and the weight of the cat food eaten each time by the cats may be known.

A system is described including a scale device for measuring weight of a food container, wherein one or more applications run on at least one processor of the scale device and are configured to detect weight of the food container and its contents using the scale device. The one of more applications are configured to detect a first weight measurement of the food container, wherein the first weight measurement includes weight of the food container and a first amount of food, to detect a second weight measurement of the food container, wherein the second weight measurement includes the weight of the food container, the first amount of food, and a second amount of food, wherein the second weight measurement is an updated weight measurement of the food container, to subsequently log weight measurements of the food container at time intervals, and to intermittently adjust and monitor the updated weight measurement.

An agricultural data collection framework is provided in a system and method for tracking and managing livestock, and for analyzing animal conditions such as health, growth, nutrition, and behavior. The framework uses ultra-high frequency interrogation of RFID tags to collect individual animal data across multiple geographical locations, and incorporates artificial intelligence techniques to develop machine learning base models for statistical process controls around each animal for evaluating the animal condition. The framework provides a determination of normality at an individual animal basis or for a specific location, and generates alerts, predictions, and a targeted processing or application schedule for prioritizing and delivering resources when intervention is needed.

An apparatus for farming animals, with a trough, a distributing system, an identifying system, a database and a control unit that allows, once an animal has been identified, the time passed ‘t’ since the time T.sub.0 corresponding to the last feed of said animal to be measured, a new value of the credit feed weight MC to be computed with the formula

[00001]$\mathrm{MC}\left(t\right)=\frac{MP}{\Delta T}*\left(t-T_0\right)+M{C}_0$

and a succession of feed portions to be distributed to the trough until the animal is sated or until a zero or negative credit feed weight MC is obtained.

A feed-mixing device for receiving, mixing and dispensing animal feed includes a frame with a mixing bin for receiving and mixing the animal feed therein and dispensing it therefrom, at least one mixing device rotatably drivable in the mixing bin using a drive, in particular a vertical mixing auger, for mixing the received animal feed, and a weighing device for determining the weight of the animal feed received in the mixing bin, comprising N weighing elements, with N≥2, each of which emits a weighing signal, and a control system for controlling the feed-mixing device and for processing the weighing signals from the weighing elements to produce the determined weight. The control system is configured to perform an, in particular fully automatic, calibration action of the weighing elements. The calibration action includes driving the at least one mixing device, reading out the respective weighing signal of each of the N weighing elements in each of M different positions of the mixing device, with M≥N, calibrating the weighing elements on the basis of the read-out weighing signals, wherein the calibrating at least includes determining a respective correction factor for the weighing signal of each weighing element by analysing the read-out weighing signals of all weighing elements. Thus, all weighing elements may be calibrated without having to detach the weighing elements, which provides very reliable weight measurements in a very simple manner.