16 results about "Estrus Detection" patented technology

The invention provides an ewe oestrus detection method and device based on multi-modal feature fusion, and relates to the technical field of livestock behavior monitoring, the method comprises the following steps: acquiring behavior data and audio data of an ewe to obtain a first behavior data set and a first audio data set; inputting the first behavior data set into an ewe behavior recognition model to obtain a second behavior data set, and inputting the first audio data set into an ewe sound detection model to obtain a second audio data set; performing feature extraction on the second behavior data set and the second audio data set to obtain a multi-modal feature fusion data set; and inputting the multi-modal feature fusion data set into an ewe oestrus discrimination model to obtain an ewe oestrus detection result. According to the ewe oestrus detection method based on multi-modal feature fusion, on the basis of fully learning the multi-modal features of the ewe, whether the ewe is oestrus or not is intelligently judged through the ewe oestrus judgment model, and the accuracy and efficiency of ewe oestrus detection are improved.

The invention relates to a cattle behavior classification and oestrus detection method based on deep learning, and the method comprises the steps: S1) building an acceleration and sound data set for representing cattle behaviors, which comprises the steps: carrying out the collection and marking of acceleration data and sound data representing the daily behaviors and oestrus behaviors of cattle, forming acceleration data and sound data with annotation information; step S2), constructing a CLAT-MMNet model; s3) training the CLAT-MMNet model to an expected result by using a data set of acceleration data and sound data with annotation information; and S4) inputting the collected acceleration data and sound data representing cattle behaviors into the trained CLAT-MMNet model, and outputting a detection result of the cattle behaviors.

Accurate estrus detection of sows is critical to achieving a high farrowing rate and maintaining good reproductive performance. However, the conventional method of estrus detection uses a back pressure test by farmers, which is time-consuming and labor-intensive with a significant degree of error. This disclosure is of an automated estrus detection method by monitoring the change in vulva swelling around the estrus using a three-dimensional measurement device, e.g., LiDAR camera, which includes an RGB camera and a depth camera. This sow estrus detection improves accuracy and efficiency, reduces labor and cost, and improves the sustainability of swine production using a data-driven decision-making system based on a robotic cyber-physical system (CPS) that can utilize deep learning detection based on a deep learning model.

The invention discloses an estrus detection method based on sow video motion information, and belongs to the field of motion information detection.The estrus detection method comprises the steps that videos are collected through a camera at the top of a pig house, the continuous track of each sow is obtained through improved YOLOv11 and ByteTrack, and daily average speed, acceleration and motion distance time sequence data are extracted; the continuous rising trend is recognized through sliding window linear regression, oestrus early warning is given out in combination with a dynamic threshold value, the boars are automatically guided to approach, and the oestrus state is confirmed according to an interactive video. The system gets rid of dependence on external stimulation and specific actions, all-weather non-contact monitoring is achieved, tiny behavior changes in the early estrus stage can be found in advance, and the large-scale pig farm breeding management efficiency is remarkably improved.

The application discloses an intelligent bionic estrus induction and estrus detection robot system and a working method thereof, and the system comprises: an autonomous mobile inspection platform serving as a physical carrier of the estrus induction and estrus detection robot; an anti-habituation bionic excitation subsystem for generating a modulation control sequence and dynamically modulating a pre-recorded pig audio sample to output an anti-habituation bionic estrus induction audio, and combining a smell pulse to trigger a bionic estrus induction mechanism; a multi-modal perception and feature extraction subsystem for perceiving physiological data and behavioral reaction data of sows after being induced by the bionic estrus induction mechanism, and converting the data into multi-dimensional response features; and a large model diagnosis subsystem based on cross attention, for cross attention fusion of the multi-dimensional response features, obtaining an estrus diagnosis result according to the fused features, and driving the system to perform a closed-loop execution stage. The application effectively replaces a test estrus boar, and significantly reduces non-production days of breeding.

The present application relates to a ewe estrus detection method based on a patrol robot, comprising: collecting video streams of a sheep shed in real time by using a patrol robot; analyzing the video streams in real time by a target detection model deployed on the patrol robot, identifying and preliminarily positioning the target area where the climbing behavior occurs; navigating the patrol robot to move to the target area according to the spatial coordinates of the target area; within the target area, continuously tracking the individual ram based on the target detection and target tracking model; when detecting that the ram and the ewe have climbing interaction, collecting the climbing behavior video clip of the climbing process; determining whether there is an estrus ewe based on the climbing behavior video clip; if so, positioning and indicating the estrus ewe. The present application realizes high-precision, non-invasive intelligent identification of ewe estrus behavior based on a patrol robot, organically integrates autonomous navigation, visual analysis and physical marking, and significantly improves the accuracy and patrol efficiency of estrus detection in a complex shed environment.

The invention discloses a sow oestrus detection method based on improved YOLOv5s, and the method comprises the steps: S1, obtaining time sequence pudendum image sequence data and auxiliary sensing data of a target sow, and generating multi-modal input data; s2, inputting the multi-modal input data into an improved YOLOv5s target detection model, extracting spatial features, and then performing sequential network processing to generate an estrus feature vector; and S3, applying a classifier and a time sequence smoothing algorithm to the oestrus feature vector, and outputting an oestrus state detection result of the target sow. By improving a YOLOv5s target detection algorithm, the accuracy of sow oestrus detection is remarkably improved.

The invention provides a dairy cow oestrus and basic motion detection method, device, equipment and medium, and the method comprises the steps: S1, collecting a dairy cow activity video, extracting an image in a framing manner, and carrying out the image enhancement processing according to the illumination weather condition and the camera shooting condition; s2, constructing a positive sample and a negative sample; the positive samples are different artificially selected climbing oestrus behavior images, and the negative samples are different artificially selected non-oestrus behavior images of standing, lying, drinking, eating and walking; randomly extracting samples from the positive samples and the negative samples to construct a training set, a verification set and a test set; s3, performing cow oestrus detection model training; s4, putting the trained dairy cow oestrus detection model into a real environment for testing to obtain an optimal model of the dairy cow oestrus detection model, and generating a standard data set; the method solves the problems that an existing detection model is not easy to extract cow behavior characteristics, the detection efficiency is low, and the effect is poor.

The invention provides a sheep oestrus identification colloidal gold kit, which relates to the technical field of animal breeding detection and comprises test paper and a kit body, the test paper comprises a sample pad, a colloidal gold combination pad, a chromatography membrane and water absorption filter paper; a detection line and a quality control line are arranged on the chromatography membrane; the detection line is coated with a luteinizing hormone monoclonal antibody 5F3G4C6, and the quality control line is coated with goat anti-mouse IgG. The sheep oestrus identification colloidal gold kit is used for ewe oestrus identification, the oestrus identification accuracy and detection efficiency are improved, and the labor cost is reduced. By improving the accuracy and efficiency of oestrus identification, the kit provided by the invention not only can improve the reproductive performance of livestock, but also can reduce the breeding cost and improve the economic benefit.

The invention relates to a sow estrus checking and inducing system and a linkage control method of the sow estrus checking and inducing system. The rail robot is arranged above the pigsty in a suspended manner; the visual estrus checking device is mounted on the rail robot and used for obtaining three-dimensional posture information of the sows in the pigsties and recognizing the standing reflex behaviors of the sows in the estrus period based on the three-dimensional posture information, and then estrus checking is achieved; the estrus inducing boar vehicle is used for carrying boars and generating contact stimulation with the sows in the specified fences; the control unit is in communication connection with the track robot, the visual estrus checking device and the estrus inducing boar vehicle, and the track robot, the visual estrus checking device and the estrus inducing boar vehicle are controlled by applying the steps of the linkage control method of the sow estrus checking and inducing system. The method can improve the oestrus detection rate, reduce the conditions of omission and omission of oestrus induction, reduce the empty running distance of the boar vehicle, shorten the cruise time of a single vehicle, realize zero contact of people and pigs, and meet the biological safety requirements of a pig farm.

This invention relates to a method for predicting sow estrus based on low-cost electronic ear tags, belonging to the field of smart animal husbandry technology. Addressing the problems of high cost and model overfitting in automated sow estrus detection in large-scale farming, this invention uses low-power electronic ear tags worn on the sow's ear to collect ear temperature data in real time, and performs multiple calibrations to ensure data stability. Its core components include: employing an hourly average body temperature resampling strategy to construct a 48-hour regularized time-series feature sample set to enhance the model's generalization ability; constructing a classification model based on a lightweight gradient boosting machine (LightGBM); and innovatively designing a "Forced Offspring Iteration" (FOI) mechanism to improve the genetic algorithm for global optimization of model hyperparameters. This mechanism improves convergence efficiency while maintaining search capability by cutting off parental gene transmission. This invention can achieve reliable automatic identification of sow estrus using low-cost sensing data.

The invention provides a data processing method and device in cow oestrus detection, equipment and a medium, and relates to the technical field of livestock breeding. According to the method, initial head posture data of a dairy cow is acquired and preprocessed, characteristic parameters and difference parameters are determined based on target posture data, time window division and data screening are performed on data streams corresponding to the parameters, and on the basis, effective data in a preset period are extracted as reference data; and determining a target judgment parameter combination and a corresponding reference behavior index according to the target judgment parameter combination, and in a real-time detection process, comparing a real-time behavior index based on non-reference data with the corresponding reference behavior index to determine a head-up behavior offset. When the head raising behavior offset exceeds a preset oestrus judgment threshold value, it is judged that the dairy cow is in an oestrus state. According to the method, the head raising posture characteristics of the cow in the oestrus are comprehensively considered, the accuracy and specificity of cow oestrus detection are improved, and the false alarm rate and the missing report rate are reduced.

The invention provides a method for identifying cow oestrus based on a positioning track and an intelligent ear tag system thereof, and aims to realize high-accuracy, real-time and automatic identification of cow oestrus. According to the method, based on intelligent ear tags worn on ears of dairy cows, positioning coordinates are periodically uploaded, and individuals with abnormal behaviors are identified through track point string construction, space thermodynamic mapping, motion deviation indexes, a group comparison algorithm and the like. The system comprehensively analyzes track distribution, path form, activity range and group deviation of the dairy cow in a given time period, and accurately judges whether the dairy cow is in an oestrus state or not. Compared with the existing necklace equipment, the estrus uncovering rate is obviously improved, remote monitoring and AI linkage scheduling are supported, and the system can be widely applied to large-scale dairy cattle farms.

The presently disclosed subject matter is directed to a system and method for determining an estrus or estrus of one or more female animals located in proximity to a male animal, the system comprising processing circuitry configured to: (a) receive information indicative of a degree of proximity between the one or more female animals and the male animal; and (b) determining, for each given one of the one or more female animals, whether the given female animal is in oestrus based on the received information. Further, systems and methods for determining estrus or estrus may be used to determine a source of conception for one or more pregnant female animals or suspected pregnant female animals, and to determine a distance between the secondary tag and the primary tag.