A system and computerized method for monitoring and analyzing animal related data. In one embodiment, the system includes a processor and memory operable to identify a parameter related to animal management for species in a biological environment, aggregate animal related data from different sources about the parameter of the species, identify a baseline for the parameter, correlate the animal related data against the baseline to obtain correlated data, and analyze said correlated data to assess said animal management.

A pet monitoring device is disclosed that's wearable by a pet for recording and communicating the pet's movements within an environment in which radio frequency identifier (RFID) tags have been strategically placed. The device includes: a transmitter configured to send a radio signal to an area surrounding a pet's location; a receiver configured to receive a reflected radio signal from an RFID tag within the area; a processor configured to identify the RFID tag of the reflected radio signal; and a database in which the processor stores times and locations of identified RFID tags in the environment such that the times and locations are indicative of behavior of the pet in the environment. The device can be used for behavioral analysis, tracking key indicators related to the well-being of the pet, such as when a pet eats and drinks water, and how the pet behaves during recovery from an injury.

An unmanned aerial vehicle for determining geolocation exclusion zones of animals. The unmanned aerial vehicle includes a processor-based monitoring device to track geolocation information associated with an animal from the unmanned aerial vehicle, an identification device mounted on the unmanned aerial vehicle to identify the animal and to track a position of the animal over time, and a mapping device coupled to the monitoring device to determine locations where the animal has traversed and to identify where an encounter with the animal is reduced.

An unmanned aerial vehicle for determining geolocation exclusion zones of animals. The unmanned aerial vehicle includes a processor-based monitoring device to track geolocation information associated with an animal from the unmanned aerial vehicle, an identification device mounted on the unmanned aerial vehicle to identify the animal and to track a position of the animal over time, and a mapping device coupled to the monitoring device to determine locations where the animal has traversed and to identify where an encounter with the animal is reduced.

A system for managing a group of dairy animals includes a dwelling space, such as an animal shed, in which the dairy animals can roam. A dairy animal-related device for performing a dairy animal-related operation is arranged in the dwelling space. The dairy animals in the dwelling space can walk to the dairy animal-related device through the dwelling space. A luring system includes luring devices, each of which is attached to in each case one of the dairy animals. The luring device of each dairy animal is activatable in order to give said dairy animal a luring signal so as to lure said dairy animal to the dairy animal-related device. A detection system is configured for detecting the position of each individual dairy animal in the dwelling space. The luring system is connected to the detection system for receiving the positions of the dairy animals in the dwelling space detected by the detection system. On the basis of the received detected positions of the dairy animals in the dwelling space, the number of dairy animals is determined which are situated in a predetermined area of the dwelling space adjacent to the dairy animal-related device. The luring system activates the luring device of one of the other dairy animals depending on said number of dairy animals situated in said area.

A bovine monitoring system may include a rumination sensor, a motion sensor, a posture sensor. The rumination sensor may detect chewing by sensing jaw motion. The motion sensor may detect motion. The posture sensor may detect orientation of the bovine asset through detection of gravitational acceleration, detection of gyroscopic rotation, or a combination of gravitational acceleration and gyroscopic rotation. Using the recorded rumination, motion, and posture sensors, the bovine asset monitoring system may identify aberrations in the estrous cycle or physical or mental health of the bovine assets. A bovine monitoring system may include a thermal scanning device to detect localized heating of the vulva area of the bovine asset, which may be used to identify aberrations in the estrous cycle or physical or mental health of the bovine assets.

A method of monitoring the physiological condition, and/or suitability of animal feed, of ruminant animals, comprising: a. sensing the occurrence of at least a first predetermined type of activity of the animal; b. determining a length of a time period of a first type during which in step a. a sensed first predetermined type of activity has taken place; c. transmitting information about the length of a time period of the first type determined in step b. wherein preferably the transmission starts on a moment in time which depends on the moment in time on which the time period of the first type has ended; d. repeating steps a.-c. for next sensed occurrences of activities of the first predetermined type.

Methods and apparatuses are shown for selectively capturing a targeted animal that are directed to capturing an animal in a capture module having a one way capture mechanism and, using instructions executing in a controller, sensing the animal in an identification module and, responsive thereto, capturing an image of the animal, analyzing the captured image to identify whether the animal is a targeted animal, if the animal is the targeted animal, processing the animal, and releasing the animal. Additional examples involve performing chromatic or pattern analysis on the captured image, using the chromatic or patent analysis results, searching a database for machine recognized animal colors or patterns, generating a probabilistic assessment based on color or pattern of whether the animal in the identification module is the targeted animal, and generating a target determination indication based on the probabilistic assessment based on color or pattern. Processing the animal may include injecting the animal using a syringe.

A system for remote care of an animal includes a smart bowl that includes an open-faced container for holding a substance, a microprocessor, and a proximity sensor configured to detect the presence of a proximity tag attached to an animal.

This invention relates to a feed system for delivering liquid feed to animals. The system includes a feed apparatus having at least one liquid feed source, and at least one at least common supply line connected to the liquid feed source. A plurality of animal feeding stalls are connected to the at least one common supply line along its length.