14 results about "Animal identification" patented technology

This invention relates to the field of animal management technology and discloses an AI-based animal identification and management method based on unmanned aerial vehicles (UAVs). The method includes: responding to the generation of a heat map of suspected animal locations, a second UAV cluster performs a pinpoint confirmation task on the heat map area, collecting detailed image data of the animals; inputting the detailed image data into an animal identification model; based on species category and behavioral state, calling the corresponding animal movement prediction model from a model library and combining it with real-time environmental data to predict the animal's movement trajectory within a future time window; and controlling a third UAV cluster to generate a virtual electronic fence according to the predicted movement trajectory and a user-defined range. The method in this invention not only enables rapid animal species identification and population statistics but also generates a virtual electronic fence based on the predicted animal movement trajectory and a user-defined range, comprehensively considering both animal activity trends and human management needs.

This application relates to a vehicle risk avoidance method and electronic device, belonging to the field of vehicle technology. The vehicle risk avoidance method includes: when the vehicle is parked and an animal recognition event is detected, acquiring animal status information and personnel location information, wherein the animal recognition event indicates the presence of a dangerous animal target within a preset area around the vehicle, and the animal status information is determined based on the state of the dangerous animal target; the personnel location information is used to represent the relative position between the personnel associated with the vehicle and the vehicle; determining a target risk avoidance strategy based on the animal status information and personnel location information; and controlling the vehicle to execute the target risk avoidance strategy. This application establishes a complete risk avoidance process from risk perception to targeted risk avoidance strategy formulation, and then to automatic execution of the risk avoidance strategy, enabling vehicles to provide users with proactive warnings and risk avoidance assistance in outdoor scenarios such as camping, thereby reducing the safety risks posed by dangerous animals in outdoor environments.

A milking system (100) is designed to extract milk from an animal (101). The system (100) includes several components for efficient milk sampling and biomarker detection. It is characterized by a feed cassette (140) holding multiple vials (150), at least one of which is prepared for biomarker detection. During milking, a milk sampler (300) transfers some milk into the selected vial (150). The system also has an animal identification device (116) for identifying the animal (101) and an information tagging device (370) for tagging the vials with relevant details. A controller (120) is connected to the identification device (116), the milk sampler (300), and the information tagging device (370). The system identifies the animal, determines whether biomarker detection is required, and, if necessary, signals the milk sampler to transfer milk into the appropriate vial and signals the information tagging device to tag the vial with the animal's identity. The system streamlines the process of collecting and analyzing milk samples.

This invention discloses a low-power analog front-end circuit and control method for animal tags. The circuit includes: a radio frequency (RF) unit, a power management unit, and an antenna. The power management unit includes a rectifier and a low-power power management circuit. The rectifier is connected to the antenna. The low-power power management circuit supplies power to the RF unit and digital circuits. The RF unit includes a load modulation and limiting circuit, a demodulation circuit, and a clock generation circuit. The demodulation circuit receives the demodulated envelope signal sent by the rectifier and outputs digital demodulated data to the digital circuits. The clock generation circuit extracts a clock signal from the antenna signal generated by the antenna and outputs the clock signal to the digital circuits. The load modulation and limiting circuit receives the limiting reference voltage sent by the rectifier and the uplink data output by the digital circuits. In this embodiment, an animal identification tag adapted for wireless communication achieves a balance between low power consumption and small area while ensuring communication reliability.

A first database (130) stores visual characteristics that designates each member (m) in a group (H) of dairy animals. A camera (120) registers image data (Dimg) representing at least one member (m) of the group (H) of dairy animals that passes in connection with a milking process. A second database (140) contains relationship data (DCL, DO) describing interrelations between the members (m). The relationship data (DCL, DO) are based on an analysis of historic data (HD) acquired at earlier passages of the members (m). In connection with a milking process, a controller (110) obtains the relationship data (DCL, DO) to derive at least one candidate identity (ID(a1), …, ID(ai)) for the at least one member (m), which at least one candidate identity (ID(a1), …, ID(ai)) is a respective at least one identity of said members (m) of the group (H). The controller (110) performs a recognition procedure, which recognition procedure seeks to find a match between the obtained register image data (Dimg) representing at least one member (m) of the group (H) and the obtained stored visual characteristics of the at least one candidate identity (ID(a1), …, ID(ai)).

The application belongs to the technical field of pest control, and discloses an animal recognition system for laser pest control, which comprises an animal recognition system, wherein the animal recognition system comprises an intelligent screening module, a target determination module, a fixed-point locking module, a trajectory prediction module, an energy regulation module, a laser emission module, an infrared camera capturing module, an infrared recognition module, an infrared imaging module, an infrared environment sensing module, an infrared safety warning module and a data storage and updating module. The application is constructed based on the function of distinguishing the obvious features of animals and plants by infrared rays of the animal recognition system, is specially applied to farmland scenes, can realize efficient pest control and guarantee the safety of humans and large domestic animals in the operation area, can intelligently, accurately and safely complete the laser pest control task in the complex environment of farmland through the close cooperation and efficient operation of each module, provides strong technical support for pest control in agricultural production, and is favorable for actual application and operation.

A first database (130) stores a respective identity uniquely designating each member (m) in a group of dairy animals. A primary identification station (115) extracts information (INFO) representing the respective identities of the members (m) that pass through a first detection zone (Z1). A second database (140) contains relationship data (DCL, DO) describing interrelations between the members (m). The relationship data (DCL, DO) are based on an analysis of historic data (HD) acquired at earlier passages of the members (m) through the first detection zone (Z1). In connection with a milking process, a controller (110) checks the information (INFO) from the primary identification station (115) to determine if at least one of the members (m) is unidentified (x, y), and if so, obtains the relationship data (DCL, DO) to derive at least one candidate identity (ID(a1), …, ID(ai)) for the at least one unidentified member (x, y), which at least one candidate identity (ID(a1), …, ID(ai)) is a respective at least one identity of said members (m). The controller (110) performs a recognition procedure for the at least one unidentified member (x, y) seeking to find a match between the at least one unidentified member (x, y) and the at least one candidate identity (ID(a1), …, ID(ai)).

An applicator for animal identification tags includes a tag magazine configured to hold a plurality of animal identification tags that are connected together in a strip and arranged in a row between a first end and a second end of the tag magazine. A pair of jaws receives one of the plurality of animal identification tags dispensed from the tag magazine and are operable to affix the received animal identification tag to an animal's ear by engaging a male portion and female portion of the animal identification tag through the animal's ear. The tag magazine is movable relative to the jaws to sequentially align each one of the plurality of tags in the magazine with a tag receiving portion of the jaws. The applicator includes a dispensing mechanism to dispense the one of the plurality of animal identification tags that is aligned with the tag receiving portion of the jaws.

A milking system (100) designed to extract milk from animals (101). The system (100) comprises several components for efficient milk sampling and biomarker detection. It is characterized by a magazine (140) holding a plurality of vials (150). During milking, a milk sampler (300) transfers some milk to a selected vial (150). The system also has an animal identification device (116) for identifying the animal (101) and an information marking device (370) for marking the vials with relevant details. A controller (120) is connected to the identification device (116), the milk sampler (300) and the information marking device (370). The animal is identified, it is decided whether biomarker detection is needed, and, if so, the milk sampler is signaled to transfer milk to the appropriate vial and the information marking device is signaled to mark the vial with the identity of the animal and which type of biomarker detection is to be performed. The system streamlines the process of collecting and analyzing milk samples.

The presently disclosed subject matter aims to a system and method for animal identification. The system and method involve the use of global and local dictionaries, such that each local dictionary is associated with a set of matrix code markers derived from a plurality of matrix code markers associated with a global dictionary. The local dictionaries may be associated with respective geographical areas, where their group of matrix code markers can be used to mark a group of animals for identification purposes. In addition, the presently disclosed subject matter aims to an animal tag including a matrix code marker placed thereon. The matrix code marker of the animal tag possesses attributes enabling it to be read at different lighting conditions.

Disclosed is a method for managing animals by surveying eating behavior of the animals in a livestock area, including monitoring the animals over a time period subsequent to distributing feed at a feed table in the livestock area, identifying animal behavior that fails to meet a criteria, and performing an such as regrouping the animals or conducting a health check on the animals.

The present invention relates to an animal monitoring system (100) for an animal cage, the animal monitoring system (100) comprising: a physical platform divided into a grid of cells (106), each cell (106) including at least one load cell (108); an animal identification system; and a processing unit configured to identify at least one animal on the physical platform using the animal identification system, to continuously acquire load signals from the load cell (108), and to track the position and / or change in position of the identified at least one animal on the physical platform based on the load signals from the load cell (108). The disclosure further relates to a method for inspecting animals in an animal cage.

A system for offline-capable, multimodal animal identification and secure data management, consisting of: one or more Internet of Things (IoT) collar devices configured for attachment to livestock. Each device incorporates a variety of physiological sensors and a Bluetooth Low Energy (BLE) communication interface configured to capture and transmit physiological parameters of the livestock via the Bluetooth Low Energy communication interface; a mobile computing device configured to receive multimodal livestock data from one or more IoT collar devices, the captured multimodal livestock data including images of the livestock, images of the muzzle pattern, acoustic vocalization samples, and GPS location data;an artificial intelligence processing module within the mobile computer device, configured to process the multimodal livestock data offline locally, identify breed characteristics of the livestock based on the multimodal livestock data and assess the health status of the livestock based on the multimodal livestock data and physiological parameters, generating a unique livestock identification number (ULID) for each individual animal;a blockchain-based distributed ledger within the mobile device, connected to artificial intelligence processing and configured to store the unique animal identification number, owner information and health data of each individual farm animal, and ensuring tamper-proof verification of the stored information, wherein the blockchain-based distributed ledger enables the creation of a digital twin profile for each individual farm animal, with this digital twin profile being dynamically updated based on incoming multimodal farm animal data and physiological parameters;and an analytics dashboard interface connected to the artificial intelligence module and a blockchain-based distributed ledger, configured to display predictive insights into the health, milk productivity, disease risk, and reproductive cycles of farm animals.