An electronic monitor can monitor experimental animals in a cage. The cage has one or more walls that enclose a living space for the experimental animals. The electronic monitor is coupled to the cage. The electronic monitor may include a housing adapted to be mechanically coupled to the cage in a predefined position relative to the cage. A substantially sterile barrier is provided between the living space and the external environment in this coupled state. The walls of the cage may include a signal-interface section. An electromagnetic detector may be coupled to the housing to have a line-of-sight through the signal-interface section and into the living space of the cage. The electromagnetic detector is adapted to detect electromagnetic radiation that is transmitted through the signal-interface section. A controller processes a signal received from the electromagnetic detector to determine a status of the experimental animals or the living space.

A system for noninvasively monitoring physiological data of non-human animals, said system includes a sensor module having a transmit antenna, a receive antenna and a microprocessor. The transmit antenna being configured to wirelessly transmit electromagnetic waves to an area in the vicinity of an animal. The receive antenna being configured to receive modulated signals back from the animal that have been modulated as a function of physiological characteristics of animal. A hub having a processor and configured to receive signals from the sensor module. The processor in the hub being further configured to compare the signals from the sensor module with previously obtained data and generate an alert to a user if the comparison indicates an abnormal physiological characteristic of the animal.

Various examples are directed to livestock management systems and methods. A first user computing device may display a GUI comprising a first animal visual element. The first animal visual element may correspond to the first animal and indicate a first colostrum feeding of the first animal. When a user selects the first animal visual element, the user computing device may display a first colostrum input screen for receiving first colostrum data. The user computing device may also modify the first animal visual element to indicate the time status of the first testing action for the first animal.

Smart livestock management method and system based on Internet of things. The smart livestock management system may include a gate. The gate may include a frame forming a moving path of an animal, an external device disposed in the frame and configured to radiate electromagnetic waves toward the moving path and to receive identification information and bio information of the animal from an implant device inserted into the body of the animal passing through the moving path, and a camera configured to obtain image data of the animal passing through the moving path.

There is provided a computer implemented method of training a machine learning model, comprising: computing at least one in-colony feature indicative of an internal state of a sample honeybee colony positioned for pollination of at least one crop in a geographical area, from output of at least one internal sensor monitoring the honeybee colony, computing at least one out-colony feature indicative of an external environment of the sample honeybee colony, from output of at least one external sensor monitoring the environment of the honeybee colony, creating a multi-record training dataset, wherein a record comprises: a combination of at least one in-colony feature and at least one out-colony feature, and a ground truth label indicating pollination effectiveness of the sample honeybee colony, and training a machine learning model on the multi-record training dataset.

A detector for detecting a signal from one or more feeders. A processor is in communication with the can be configured with an artificial intelligence module and a library of pre-recorded action events and for comparing the signal with the library of pre-recorded action events and determining a likely action event. A warring device can be in communication with the processor for providing an output in response to the likely action event. At least one false positive sensor in communication with either the processor or the warning device or both of the processor and the warning device can be used for stopping the output from the warning device upon a predetermined condition.

A method for measuring and analyzing the productivity of Angora rabbit is provided. Firstly, the Angora rabbit to be tested are simultaneously sheared at the age of 18 weeks, and are reared in a single cage to the age of 29 weeks according to standard conditions for test, and the individual consumption of Angora rabbit during the test period is recorded; secondly, the wool samples were sheared from the middle and upper part of the body side of the Angora rabbit with an electric wool clippers. The weight of the Angora rabbit, the weight of the wool sample, and the length of the wool fiber were measured and bagged for recording; in the third step, the wool fiber diameter of each wool sample was measured by fiber projection method; in the fourth step, the measured values were substituted into the given estimation formula.

One variation of a method includes: accessing a video feed recorded at a training apparatus configured to dispense primary reinforcer units; dispensing a first primary reinforcer unit toward a first location; in response to detecting the animal at the first location, dispensing a second primary reinforcer unit toward a second location intersecting a pathway extending from the first location; in response to detecting movement of the animal along the pathway, collecting a timeseries of position data representing changes in position of a set of anatomical features of the animal; based on the timeseries of position data, deriving a movement profile representing movement of the animal along the pathway; based on a difference between the movement profile and a baseline movement profile defined for the animal, interpreting an abnormality and predicting a causal pathway for the abnormality; and selecting a mitigation protocol based on the causal pathway.

A system for virtual management of livestock includes a server computer, a primary collar, and a plurality of secondary collars. The server computer receives virtual boundary data, as a user input, which establishes a virtual boundary. The primary collar is worn by and associated with a primary livestock animal and communicates with the server computer via a remote wireless gateway. The plurality of secondary collars communicate wirelessly with one another and with the primary collar via an ad hoc wireless mesh network. Each of the secondary collars is worn by and associated with an individual secondary livestock animal of a plurality of secondary livestock animals. The primary collar receives the virtual boundary data from the server computer, transmits it to the plurality of secondary collars via the wireless mesh network, and provides directional stimulation to the primary livestock animal to encourage it to refrain from crossing the virtual boundary.

An artificial and/or simulated environment is used to raise a domestic or commercially raised animal to promote a positive health feedback and to minimize stress on the animal. The simulated environment is used to create the façade of a free range or cage free environment, while also minimizing the exposure to inclement weather, potential predators, and other unknown or stress-inducing situations. The results include animals that have higher resistance to diseases and have a lower stress. The artificial environment can be created by projecting or otherwise showing images and/or videos depicting simulation of environments, climate, and/or other unknown situations to normalize the animals to the same.