307 results about "Animal behavior" patented technology

Systems, methods, and computer code products for monitoring the behavior, health, and/or characteristics of an animal are disclosed herein. In one implementation, the animal is positioned inside a waste container placed on a system that is adapted to determine, record and communicate over a network various animal health parameters. These parameters can be processed to determine trends, statistics and changes of animal physiological functions. The results can be used to access animal health conditions and issue warnings, alarms, messages, and other notifications to designated caretakers. These notifications may be displayed using various means such as computers and/or mobile devices. Data retrieval and review capability can provide improved understanding of an animal's health conditions and facilitate early illness detection.

A highly automated non-confining system to continuously, or at selected time intervals identify, measure, monitor and manage the consumption behavior, substance intake, body weight and growth of individual animals in their usual production environment including range, pasture, feedlot, dairy and farm without disruption to typical behaviors in order to determine, analyze, model and predict a variety of conditions relating to animal health, productivity, efficiency and quality. A transmitter generally attached to the animal identifies the individual animal by a unique individual code. A weighing device measures animal weight while an animal is consuming substances. An antenna receives the unique signal from the transmitter and a transmitting and receiving device sends acquired signals to a computer and receives instructions from a computer. A computer acquires signals and modification factors incorporated in the computer generate an event or interval measurement of an animal's weight and gain, growth rate and substance consumption, and the animal behavior affecting the measurement. A visual identification mechanism marks cattle that the computer system has determined require intervention. The system models and predicts animal health and growth, performance, carcass characteristics, feed utilization, manure and methane output.

A robotic architecture for capturing the autonomous performance advantages the animal models enjoy in the natural environment is disclosed. A biomimesis process is employed to allow selective utilization of basic physical components and adaptation of a common control paradigm for each of different vehicle types. The biomimetic architecture involves five functional elements: a basic biomorphic plant for capturing the biomechanical advantages of the model organism; a neural circuit-based controller consisting of a finite state machine; myomorphic actuators producing linear graded force in response to trains of current pulses for mediating movements; labeled line code output by neuromorphic sensors; and a reactive behavioral sequencer executing command sequences defined within a behavioral library.

The device and method for remotely monitoring animal behavior consists of a sensor unit mounted on an animal. The sensor unit utilizes motion sensors to monitor the specific behavioral patterns of the animal. Power management is controlled to turn the system on when specific types of motion are detected. Motion data is wirelessly transmitted to a base station for analysis. Data analysis functions are used to detect and identify the occurrence of characteristic motions. Network decision algorithms analyze the characteristic motions and compute weighted indicators and weighted counter-indicators which are combined into a final diagnostic score. When the final diagnostic score exceeds a threshold value, a specific behavioral pattern is confirmed which may indicate the animal is in a distress situation or experiencing another type of behavior that requires intervention. If distress is detected, the system sends a communication to notify the appropriate personnel that a distress condition exists.

The invention relates to a fruit fly behavior researching system, belonging to the animal behavior field. The system comprises a fruit fly moving container, an image acquiring device, a stimulating device and a center device; the fruit fly moving container is used for supplying a moving space to the fruit fly with the specific protein; the image acquiring device is used for acquiring the fruit fly behavior image; the stimulating device is used for applying the external stimulation to the fruit fly; and the center device is connected with the image acquiring device and the stimulating device, used for controlling the image acquiring device and the stimulating device, recording the fruit fly behavior image and analyzing the fruit fly behavior. In addition, the invention also relates to a fruit fly behavior researching method. The method comprises the following steps of: applying the external stimulation to the fruit fly with the specific protein; acquiring the fruit fly moving image; and analyzing the fruit fly behavior according to the fruit fly moving image. In the system, the stimulation to the fruit fly, the behavior recording and analysis in the fruit fly behavior research are automatically carried out, so that the deviation brought by the experience or fatigue factors of the artificial observation and statistic can be eliminated. The system carries out the stimulation to the fruit fly with the specific points particularly, and improves the precision and efficiency of the analysis on the fruit fly behavior.

The present invention enables testing the effect of one or more test agent(s) on one or more animal(s) of a group of animals, preferably insects, to identify agents that affect behavioral properties of the animals. The invention is comprised of the steps of providing animals suitable for testing, bringing those animals into contact with the test agent(s), moving the animals from a growth container to isolate them, prepare and separate the animals for singulation, relocated the animals to a behavior arena, subject the animals to behavioral tracking to assess their behavioral state, and removing the animals from the behavioral tracking to facilitate iterative analysis of further groups. The invention enables a method for preparing a therapeutic compound for the treatment of an animal disease.

A system, apparatus, and/or method of determining a health condition of an animal is provided. First data may be received from a first sensor device. The first data may be indicative of an animal event of an animal. Second data may be received from a second sensor device. The second sensor may be separate and/or distinct from the first sensor device. The second data may confirm an occurrence of the animal event. The animal event may be a discharge event and/or a feeding event. The occurrence of the animal event may be identified based on the first data and the second data. The occurrence of the animal event may be displayed via a display device. A health condition of the animal may be determined based on the animal event. The determination of the health condition may be based on a quantity and/or a duration of the animal event.

An animal behavior modification device is provided. The device includes a sound, vibration or motion sensor that is configured to generate electrical signals in response to an occurrence. The device may include a filter, which is tuned to recognize a dog barking event, and generate an electrical signal in response to recognizing an input signal indicative of a dog's bark. The device further includes a canister that holds a deterrent fluid under pressure. The device additionally comprises a motor module configured to rotate a shaft in response to the electrical signal from the filter. The canister has a spray nozzle for releasing fluid that affects the dog's senses. In response to rotating the shaft, the spray nozzle is depressed. A method of modifying the behavior of an animal using the device is also provided herein.

The invention provides an animal behavior identification method and apparatus based on transfer learning (TL), i.e., the training sample in a training data set comprises one or more than one from the group composed of a human behavior sample, a non object animal behavior sample and an object animal behavior sample, and a test data set is an object animal behavior sample. The method comprises: step 101, extracting original characteristics for each training sample in the training data set and each test sample in the test data set; step 102, employing a domain adaptation learning (DAL) method in TL to map the original characteristics onto a common space to obtain new characteristics; step 103, utilizing the new characteristics to train a support vector machine (SVM) classifier, obtaining a behavior identification model, and meanwhile testing an object animal behavior identification model; and step 104, utilizing the animal behavior identification model to identify object animal behavior to be identified. The animal behavior identification method based on TL can effectively identify animal behaviors.

Systems and methods for monitoring and controlling animal behavior are disclosed. According to an aspect, a system comprises a computing device comprising at least one processor and memory. The system includes a detection electrode and an animal signaling device. The computing device is configured to detect a change of an electrical capacitance at a detection electrode. The computing device is also configured to determine a position of an animal based on the change in the electrical charge. Further, the computing device is configured to control the animal signaling device to communicate a signal in response to determining the position of the animal.

The invention relates to an earthquake prediction auxiliary system based on a technology of Internet of things. The system comprises omnidirectional vision-based biological earthquake predictors placed on all observation points and an earthquake prediction server which is used for performing comprehensive analysis on monitoring results of the omnidirectional vision-based biological earthquake predictors on all the observation points, wherein all the omnidirectional vision-based biological earthquake predictors are communicated and connected, and all the omnidirectional vision-based biologicalearthquake predictors are communicated and connected with the earthquake prediction server; and the earthquake prediction auxiliary system can improve the credibility of earthquake early warning and simultaneously provide a certain reference basis for future judgment of earthquake occurrence times and earthquake occurrence areas by combining omnidirectional vision, computer vision, a database andother technologies for analyzing activities, postures, actions, behaviors and the like of animals, enabling the behaviors of the animals distributed on monitoring points of all places to speak and adopting comprehensive analysis means including time sequence of speaking, spatial positions, speaking sequence of the animals in different species and the like.