127 results about "Herd" patented technology

A feeding system for feeding individual animals of a herd feed, supplements, and combinations thereof. The feeding system includes one-to-many feed bin assemblies or feeding stations such that the system is able to dispense a specified mass of feed to specific animals at user-defined intervals. In this way, each animal of a herd is provided with optimal, individualized amounts of feed or feed material. Multiple feed bin assemblies in a single pasture, for example, can automatically form a network of feeders so that regardless of the specific feed bin assembly or feeding station within the feeding system that an animal visits, the specified amount and type of feed or feed material is delivered. Each feed bin assembly or feeding station can also be equipped with an access control mechanism to ensure each animal of a herd receives its individualized amounts of feed or feed material.

A method for predicting body mass of herd animal that comprises the steps of: collecting data from the livestock environment; detect and select the animal; determining geometric characteristics of each RGB-D depth image; and obtaining the prediction of herd animal body mass. Furthermore, the present invention relates to a system for predicting body mass of herd, comprising: at least one RGB-D capture set including at least one RGB-D imaging sensor; at least one storage module; and at least one remote monitoring module; wherein the storage module stores a set of instructions that, when executed by a processor, carries out the method for predicting body mass of herd animal.

Monitoring of animals in a herd has various challenges. A method and a system for monitoring and measuring the behavior of a plurality of animals in a herd chamber is provided. The disclosure provides a method to develop a model to identify the animal interactions between a given set of herds of two or more animals. The system uses image, RFID sensors, animal phenotyping information such as species, breed, age and reproduction cycle information to generate an animal profile. This profile is used to quantify the interaction into an aggression score to the animals in the given herd. The aggression score over a given duration can help herd manager to put the animals with similar aggression score together. This will also help analyze the temporal aspects of the aggression score for a given animal and take preventive measures.

An autonomous system and method thereof for mass individual treatment such as injection of livestock or wild animals from a herd or group for precise delivery of a technical treatment or substance to an animal by intramuscular (IM) injection, subcutaneous (SQ) injection, or any transdermal injection, spraying, pouring-on, tagging, cooling, pinning, gluing or saddling, is described. The system comprises an ecological and ergonomically-designed smart grooming passageway for a single animal to move into and be calm while safely and snugly embraced for injection, and then motivated to move forward, allowing the next animal to amble in, after injection. The system has an adjustable autonomous device carrying an injection assembly with a number of injectors for delivery of injectable substances, as well as pre-injection desensitization and disinfection, and comprising a temperature control means for maintaining optimal and constant temperature of injectable substances. A camera and sensor array send various data to a controller and processor to determine the optimal individualized treatment. The system then instructs the injection assembly to inject injectable substances into a predefined injection target triangle of the animal's triangular mass of muscle on the side of the neck or any other injection target, thus achieving the highest efficiency and least amount of damage and stress to the animal, without risk to humans.

The invention discloses a zero-perception dairy cow behavior observation system based on AI vision, and the system comprises a data collection module which is used for collecting a video image through a monitoring camera; the image preprocessing module is used for generating a standardized image frame sequence; the visual Transform feature extraction module is used for outputting a space-time feature vector; the deep forest behavior classification module is used for behavior classification and label output; the behavior analysis module is used for generating a behavior track and group distribution; the model adaptive training module is used for periodic incremental training; and the abnormity early warning module is used for judging and outputting abnormal behaviors. According to the invention, cow behavior automatic identification and abnormity intelligent early warning based on AI vision are realized, and the management efficiency of a farm and the cow health guarantee level are improved.

The invention discloses a future pork pig group weight estimation method and system based on multi-model fusion, and the method comprises the steps: obtaining a historical structural data set of a pork pig breeding complete period, and employing a multi-modal fusion evaluation method of field priori knowledge weighted evaluation, data-driven feature importance calculation and an automatic code analysis tool. Extracting a key factor set influencing the weight of the pork pig, then based on the historical structured data set and the key factor set, respectively constructing an expert rule reasoning model, a data-driven prediction model and a code generation type dynamic model to predict the weight of the pork pig, inputting each model based on real-time data, and outputting a prediction value; weights are dynamically distributed according to historical errors, results are fused, abnormal values are removed in combination with discrete degree detection, and a final fusion prediction value is generated. The technical problem of improving the weight estimation accuracy of the pork pig group in the prior art is solved.

The invention relates to the technical field of cattle and sheep anti-lost, and discloses a free-ranging cattle and sheep anti-lost early warning system based on Internet of Things, which comprises a cattle and sheep positioning collar, a cattle and sheep positioning data receiving unit, a cattle and sheep electronic fence setting unit, a cattle and sheep position analysis unit and a lost early warning unit. According to the free-range cattle and sheep anti-lost early warning system based on the Internet of Things, real-time coordinates of a large cattle and sheep group serve as a center point of an electronic fence, the range of the electronic fence is manually set, the electronic fence is continuously moved along with feeding of the cattle and sheep group, and the electronic fence can be driven to move along with feeding of the cattle and sheep group; the individual does not move along with the cattle and sheep flock, and when the individual exceeds or approaches the boundary of the electronic fence, early warning is given out in time, so that the situation that the individual is in the static electronic fence but does not move along with the large flock when the cattle and sheep flock enters or moves due to the static electronic fence, and the situation cannot be effectively early warned is avoided, and when the cattle and sheep flock enters or moves, the individual does not move along with the large flock. And missing individuals need to be retrieved manually.

The present invention relates miRNA biomarkers and in particular to a combination of miRNA biomarkers, e.g. exosome-derived microRNA, as indicators of welfare in bovines. In particular, the present invention relates to the identification of heat stress in bovines allowing to propose management actions to improve productive animal welfare at the individual or the herd levels.

To provide a behavior prediction system capable of predicting the behavior of a herd of livestock, which is a group of livestock, in a form that reflects the differences between individuals. [Solution] The movement prediction system comprises a memory unit 211 that stores livestock herd information including individual information of livestock that make up a livestock herd, which is a flock of livestock, the number of individuals that make up the livestock herd, health condition information of the individuals that make up the livestock herd, and life cycle information of the livestock, and a movement prediction unit 212 that predicts the movement of the livestock herd including changes in the number of individuals based on the livestock herd information stored in the memory unit 211, and at least a part of the individual number and health condition information is managed based on data obtained by sensors around the livestock.

The invention discloses a wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging, a sensing system carries out thermal imaging processing and camera shooting monitoring on wild boars in corresponding areas in the air through thermal imaging and camera shooting functions of an unmanned aerial vehicle, and a ground infrared camera array carries out infrared imaging processing on the wild boars around the ground; the sound sensor recognizes the sound of the wild boars, and the ground vibration sensor detects the running of the wild boars and the digging of the ground, and relates to the technical field of early warning, prevention and control of the activities of the wild boars. According to the wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging, a sensing module is arranged in a system, and an unmanned aerial vehicle module, a ground infrared imaging module, a sound recognition processing module and a ground vibration sensing module are matched with one another to perform thermal imaging processing on wild boars so as to obtain specific information of a wild boar group; subsequent driving and marking operations are facilitated while continuous monitoring is carried out, and the danger level of the wild boar herd is analyzed through the analysis module.

An autonomous herding system using a fleet of vehicles to manage and retrieve stray animals, combining technologies from U.S. Patents US 12102060 and US 12153451. The system employs autonomous vehicles equipped with optical-LiDAR sensors, GPS, and machine-learning image recognition to detect and guide strays back to the herd. Vehicles operate in two modes: roundup, for gathering scattered animals, and herding, for maintaining cohesion and directing movement. Positioned in traditional formations (point, swing, flank, drag), they use strategic movements, visual cues, and audio signals to influence herd behavior based on flight zone and point-of-balance principles. A trail boss module coordinates vehicle actions, ensuring efficient herd control. The system includes a battery replacement station for continuous operation, automatically swapping depleted batteries. This integration streamlines livestock management, reducing labor costs while improving animal and handler safety.

According to the livestock positioning control device based on GNSS and Bluetooth Mesh networking, the manual dependence is greatly reduced, the informatization level is high, and long-time low-cost grazing is achieved. The Bluetooth tag converts the communication signal intensity with the surrounding wearable driving necklace into the distance with the surrounding necklace, completes the calculation of the position information of the Bluetooth tag according to the GNSS positioning information of the necklace, and transmits the position information to the nearest necklace through the Mesh network; after receiving the position information of the surrounding labels, the necklace transmits the self positioning information and the information of each label to a monitoring platform through a 4G communication technology, and the position of the livestock is monitored in real time through the monitoring platform; the necklace judges whether the livestock exceeds the buffer zone or leaves the boundary or not according to the position information of the necklace and the vertex coordinates of the virtual fence, if the livestock exceeds the buffer zone, sound stimulation is conducted on the livestock, if the livestock exceeds the boundary of the fence, electric shock stimulation is conducted on the livestock, and the aim of controlling the whole livestock group is achieved in the mode that the livestock with the leading force is controlled in the fence.

The present invention relates miRNA biomarkers from milk. e.g. exosome-derived microRNA from milk, as indicators of welfare in bovines. In particular, the present invention relates to the identification of heat stress in bovines allowing to propose management actions to improve productive animal welfare at the individual or the herd levels.

The present disclosure discloses an intelligent management method and management system of a natural pasture using multi-machine collaboration of UAVs, which belongs to the technical field of UAVs. The method includes: by a UAV group, obtaining pasture environment information, automatically planning a global grazing path, and performing automatic driving and grazing according to a user-defined grazing time, a starting point and an end point; during the process, collecting and analyzing herd activity images, and planning local grazing paths to assist in the automatic driving; and meanwhile, collecting vegetation coverage image data of a grazing area to further assist in the grazing.

Techniques and mechanisms for preventing resource starvation and service throttling during container orchestration system operations are provided. In a Kubernetes-based container orchestration system, pluggable mechanisms are applied to pod and / or associated container creation and operation at the direction of a cluster controller to prevent resource overloading and service throttling during thundering herd problems encountered by components of a Kubernetes cluster. A special-purpose plugin may be provided that causes creation of a pod and / or associated container according to a prescribed order to prevent caching overload and resulting thundering herd problems during pod and / or associated container creation and startup.

The application provides an ecological pasture cow breeding and health management method and system based on meteorological data, and relates to the technical field of cow breeding and health management. The method comprises the following steps: collecting meteorological data and cow breeding basic data in real time; extracting key meteorological factors affecting cow breeding; dividing meteorological suitable threshold corresponding to each breeding stage; realizing weather adaptation of cow herd screening; selecting temperature suitable period for mating operation; formulating meteorological guarantee scheme according to pregnancy stage; quantifying the influence of meteorological conditions on breeding core indicators, and optimizing breeding plan and resource allocation based on the evaluation results. Through the improved cow breeding management process, the application improves the utilization efficiency of breeding resources, provides a traceable and iterative analysis framework for breeding plan optimization, promotes the development of ecological pasture breeding management towards precision and high efficiency, and helps the pasture to reduce costs while realizing the double improvement of population quality and economic benefits.

The invention discloses a speed control optimization method for a sweeping robot, which belongs to the field of PID control technology. The method comprises the following steps: S1, constructing a sweeping robot speed control system; S2, improving a border collie optimization algorithm, which comprises two improvements: D1, using a dynamic acceleration adjustment strategy to improve the position movement acceleration of a sheepdog and a flock of sheep during the optimization process of a standard border collie optimization algorithm; D2, using a mobile strategy integrating a winning pool to improve a mathematical model for updating the position of a flock of sheep; S3, using an improved border collie optimization algorithm to optimize three parameters of a PID controller Kp, Ki and Kd of the sweeping robot speed control system; and S4, applying the searched optimal PID parameters Kp, Ki and Kd to the sweeping robot speed control system to optimize the control effect of the system.

This invention discloses the application of SNP molecular markers based on the STPG1 gene promoter in assessing bull semen quality. The SNP molecular markers include SNP2: g.-1220 T>C, where bulls with the CT genotype have significantly higher sperm motility and a significantly lower sperm abnormality rate than those with the CC genotype. In addition to SNP2, the invention also includes SNP1: g.-1234 G>A and SNP3: g.-1211 C>T. There are six haplotypes among SNPs 1-3. Compared to other haplotype combinations, bulls with H5H2 exhibit the highest sperm motility, while bulls with H3H2 exhibit the lowest sperm abnormality rate. These SNP molecular markers can serve as potential genetic markers for early identification of bull semen quality, which can not only improve breeding efficiency and reduce costs but also significantly enhance the overall reproductive performance of the herd.

Provided, according to one aspect of the present invention, is a method for analyzing incidents in a herd including a plurality of individual animals, the method comprising the steps of: grouping a plurality of individual animals on the basis of at least one criterion and extracting a reference behavior pattern for each group; generating information related to whether a current behavior is abnormal for each group with reference to the reference behavior pattern; and generating information related to an incident on the basis of the information related to whether the current behavior of each group is abnormal.

The invention relates to the field of molecular biology, and discloses a haplotype marker for dairy cow milk production butter-fat percentage character breeding and application of the haplotype marker, the haplotype marker is composed of three SNP sites in a strong linkage imbalance state, and the three SNP sites are located in a Block1 haplotype block region of a 10 # chromosome NC037337.1 of a dairy cow ARS-UCD1.2 genome; the three SNP sites are as follows: SNP1: g.59680573 A > C, SNP2: g.59743173 G > C, and SNP3: g.59743414 C > T; the dominant haplotype of the haplotype marker is H2, and the allele combination of the haplotype marker is SNP1-A, SNP2-G and SNP3-C; the homozygous H2H2 of the dominant haplotype H2 is significantly related to the high milk fat percentage character of milk production of dairy cows. The bottleneck of the traditional technology is solved, and the breeding accuracy is remarkably improved; the screening detection technical scheme is stable and reliable and has a wide application range; the milk production quality of groups is improved, and the industrial economic value is enhanced.

Techniques for measuring greenhouse gas emissions of ruminants after administration of a feed additive include receiving, by a server computer and within a reference period of time during which a cattle farm operates, feed ingredient usage data for each cattle type. The feed ingredient usage data includes an amount of feed provided for each cattle type and an identification of feed additives included in the feed. The feed additive is configured to reduce the emissions of greenhouse gases produced by each cattle in a herd that consumes the feed. The server computer also determines an estimated total amount of controllable greenhouse gas emissions of the cattle farm operation using a total controllable greenhouse gas emission model for the reference time period of the cattle farm operation with the feed ingredient usage data as an input to the model, which can be used to request carbon credits.

In particular, the present invention relates to a method for determining whether an animal and / or a progeny thereof is likely to have an increased heat resistance, an increased resistance to a wall lice, and / or a desired fur texture. It also provides methods for selecting or excluding an animal, one or more cells or embryos; estimating the value of the animal; producing an animal having a desired genotype / phenotype; cloning and breeding animals; and a method of forming a population.

This invention belongs to the field of black pig breeding technology, specifically relating to a method for breeding large-sized, high-quality black pigs. The method involves crossing purebred Songliao black pigs with purebred Berkshire pigs to obtain F1 generation hybrid pigs. The F1 generation hybrid pigs are backcrossed twice with purebred Songliao black pigs to obtain B2 generation hybrid pigs. The B2 generation hybrid pigs are then crossbred to obtain a basic breeding herd of black pigs. This basic breeding herd is then subjected to closed breeding and successive selection for at least six generations to obtain large-sized, high-quality black pigs. The large-sized, high-quality black pigs of this invention have a Berkshire bloodline content of 12.5%, retaining the high fertility and excellent meat quality of Songliao black pigs, while effectively introducing the growth rate and intramuscular fat deposition advantages of Berkshire pigs. The large-sized, high-quality black pigs of this invention have all-black coats, reach 100kg at ≤175 days of age, have a live intramuscular fat content ≥3.5%, and a litter size ≥10.5 piglets, and can be self-breeding.

The invention belongs to the technical field of cow herd optimization, and particularly relates to a cow herd optimization method and system based on cow production performance determination (DHI) data. According to the method, production performance, health, reproduction and other indexes influencing the benefits of the dairy cows are integrated, different weights are given according to the importance of each index, first-birth cows and multiparous cows are evaluated and scored respectively, ranking is performed according to scores, the dairy cows with higher scores are reserved preferentially, and individuals with lower scores are eliminated according to a plan. The method solves the problem of single and inaccurate evaluation basis of the cow individuals, can comprehensively and accurately evaluate the cow individuals, and completes high-efficiency cow herd optimization.

A feeding system for feeding individual animals of a herd feed, supplements, and combinations thereof. The feeding system includes one-to-many feed bin assemblies or feeding stations such that the system is able to dispense a specified mass of feed to specific animals at user-defined intervals. In this way, each animal of a herd is provided with optimal, individualized amounts of feed or feed material. Multiple feed bin assemblies in a single pasture, for example, can automatically form a network of feeders so that regardless of the specific feed bin assembly or feeding station within the feeding system that an animal visits, the specified amount and type of feed or feed material is delivered. Each feed bin assembly or feeding station can also be equipped to download, archive / store, and / or synthesize data into an individual animal record and / or to transmit data from additional onboard animal sensors such as activity and rumination sensors.

A livestock management system for detecting, tracking, and responding to livestock location and physical parameters, and for determining livestock behavior and physical conditions correlated thereto. The system generally includes a plurality of tags and sensors attached to and implanted in a plurality of livestock, one or more local sensors, a management platform, and a remote computer system. Each tag receives, processes and maintains data regarding the location, activity and physical parameters of a livestock to which it is attached and locally determines the behavior and physical conditions of the livestock. The tags communicate with other nearby tags and sensors locally via dynamic mesh networks and with the management platform and remote computer system via longer range wireless networks. The management platform processes the tag data and produces herd-related data. The remote computer uses the tag data to generate and update livestock behavior and condition models for download to the tags.

This invention discloses an industrial park optimization scheduling method based on the wild horse herd algorithm, comprising: establishing a multi-energy resource model of the park and an objective function oriented towards minimizing the overall expected operating cost of the industrial park; constructing a multivariate joint probability distribution model of wind power, photovoltaic power, and load using the R-Teng Copula method to quantify source-load uncertainty and generate multiple typical scenarios; establishing a two-layer optimization model, with the upper layer taking the minimization of the overall expected operating cost of the industrial park as the global optimization objective, and the lower layer dividing the park into several aggregation units with the minimization of the operating cost of each unit as the local optimization objective; performing sub-problem optimization for each aggregation unit based on the wild horse herd algorithm and ADMM; and achieving optimized scheduling based on the charging and discharging power of energy storage units, the demand response reduction power of flexible units, and the output value of distributed units in each aggregation unit obtained through optimization.

The invention discloses a grass and livestock integrated intelligent management system and method with cooperation of grass original ecology protection and production. The system integrates a space-air-ground integrated monitoring network, a hybrid communication network, a cloud platform and an intelligent analysis model, and realizes comprehensive acquisition, transmission, analysis and decision of grassland environment, pasture growth and livestock behavior data; a scientific grazing scheme and graded early warning are generated through dynamic grassland bearing capacity evaluation, a livestock group optimization grazing strategy and a grass and livestock balance early warning model, and decision making, feedback collection and continuous model optimization are performed by means of an intelligent mobile terminal and an intelligent electronic fence system; according to the invention, the problems of disjunction of monitoring and execution, imbalance of grass and livestock and the like in traditional grassland management are solved, and intelligent cooperation and dynamic balance of ecological protection and animal husbandry production are realized.

The invention discloses a system for calculating the number of calves and the total value of calves in different sperm freezing schemes in a dairy farm, and relates to the technical field of animal husbandry production cost control, and the system comprises an input module, a calculation module and a display module. The input module is used for inputting group indexes, price indexes and different semen freezing schemes of a target dairy farm; the calculation module is used for respectively calculating the calf income except the surplus milk female calf quantity and the sperm freezing cost of the target dairy farm under different sperm freezing schemes based on the group index, the price index and the different sperm freezing schemes of the target dairy farm; wherein the calf income except for the frozen semen cost does not contain the calf income of the milk female calf; and the display module is used for displaying the calf income except the excessive milk female calf quantity and the sperm freezing cost of the target dairy farm under different sperm freezing schemes. The accuracy and the calculation efficiency of calculation of the calf number and the calf total value of different sperm freezing schemes are improved.