67 results about "Cattle herd" patented technology

The invention discloses a long-chain non-coding RNA molecular marker related to bovine semen quality and application of the long-chain non-coding RNA molecular marker, long-chain non-coding RNA comprises an LNC68393 promoter sequence and an LNC68393 gene sequence, a molecular marker SNP1 is located on the promoter sequence, and a molecular marker SNP2-5 is located on the gene sequence. Different polymorphisms of the molecular marker are significantly related to the bull semen quality, and the molecular marker can be applied to detection of the bull semen quality, further early evaluation of the bull reproductive performance, cultivation of excellent bulls, shortening of the breeding time, improvement of the efficiency and reduction of the cost, and has important application value in improvement of the reproductive performance of the whole bull herd.

The invention discloses an automatic cow dung degradation device for cattle herd breeding, and relates to the technical field of degradation treatment.The automatic cow dung degradation device comprises a degradation treatment bin with the top open, a communicating cavity is formed in the lower end of the degradation treatment bin, a plurality of filtering holes are formed in the inner bottom wall of the degradation treatment bin, and the filtering holes communicate with the communicating cavity; the lifting mechanism is installed on the degradation treatment bin, an extrusion plate is connected to the lifting mechanism in a driving mode, the extrusion plate is driven by the lifting mechanism to penetrate into the degradation treatment bin, and at least one earthworm throwing mechanism is arranged on the extrusion plate. According to the device, the lifting mechanism drives the extrusion plate to move downwards, so that the extrusion plate extrudes a cow dung and soil mixture in the degradation treatment bin, and in the extrusion process, liquid dung can be quickly filtered out from the filter holes, so that the liquid dung content in the cow dung and soil mixture is reduced; the influence on the growth and reproduction of the earthworms in the mixture of the cow dung and the soil is small.

The invention relates to a cattle face image dynamic detection and tracking method based on ViT-YOLOX-Dynamic Head, and the method comprises the steps: obtaining a cattle herd face video, and carrying out the data preprocessing; constructing a cattle face image dynamic detection and tracking model based on a YOLOX model; performing training to obtain a trained cattle face image dynamic detection and tracking model; and obtaining a to-be-detected cattle face image, performing preprocessing, inputting the preprocessed to-be-detected cattle face image into the trained cattle face image dynamic detection and tracking model, and obtaining a cattle face image detection result. According to the method, the capability of capturing context information of the model is enhanced, the parameter efficiency of the model is fully utilized, global information in the image can be better captured, and the method has higher recognition capability for cow face targets with complex backgrounds and different scales; a dynamic head method is adopted to perform multi-scale feature fusion and adaptively adjust feature levels by associating spatio-temporal features and facial features, so that the cow face detection and tracking capability of the model in different scales and complex backgrounds is improved.

The invention discloses a cattle oestrus monitoring method based on multi-camera data fusion, and relates to the technical field of cattle oestrus monitoring. According to the cattle oestrus monitoring method based on multi-camera data fusion, cattle behaviors under complete shielding are visualized through multi-camera dynamic cooperation and skeleton movement deduction; a space-time slice attention mechanism is combined with joint dynamics calculation, target actions are reversely deduced from adjacent cattle body movements, the problem of climbing misjudgment caused by shielding of a traditional visual system is thoroughly solved, and the monitoring reliability in dense cattle herds is remarkably improved; the method comprises the following steps: establishing a differential filtering model of limp gaits and oestrus behaviors; based on acceleration signal time-frequency characteristics and duration determination, a false alarm signal is dynamically suppressed, the inherent defects of a contact sensor in a special physiological state are overcome, and the manual re-checking cost is reduced.

The invention discloses application of an NPFFR2 gene SNP site in judgment of dairy cow hysteritis resistance, and belongs to the technical field of livestock and poultry molecular biology, the SNP site is rs110326785, and the site generates Ggt; the metritis resistance of a dairy cow individual with the genotype of GG at the site is obviously higher than that of dairy cow individuals with the genotypes of GA and AA. The mutation of the SNP site rs110326785 is missense mutation, so that glutamic acid at the 406th site of an amino acid sequence coded by NPFFR2 mutates into lysine, when the genotype of the site is GG, the dairy cow metritis resistance is the highest, and the SNP site can be used for screening and identifying dairy cows with high metritis resistance, so that dairy cow individuals with high metritis resistance are selected for cattle herd optimization and auxiliary breeding.

The invention 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 steps of collecting meteorological data and dairy cow breeding basic data in real time; key meteorological factors influencing cow breeding are extracted; defining a meteorological appropriate threshold value corresponding to each breeding stage; cattle herd screening adaptive to weather is realized; selecting a time period with proper temperature to carry out hybridization operation; formulating meteorological guarantee schemes according to pregnancy stages; and quantifying the influence of meteorological conditions on the breeding core indexes, and optimizing a breeding plan and resource allocation based on an evaluation result. Through a perfect dairy cow breeding management process, the breeding resource utilization efficiency is improved, a traceable and iterable analysis framework is provided for breeding plan optimization, the precise and efficient development of ecological pasture breeding management is promoted, the cost of a pasture is reduced, and meanwhile, the population quality and economic benefits are improved.

The invention relates to the technical field of bovine viral diarrhea virus detection, in particular to a bovine viral diarrhea virus multi-epitope fusion protein and application thereof, a coding gene of the bovine viral diarrhea virus multi-epitope fusion protein is a nucleotide sequence as shown in SEQ ID NO.5 and corresponds to an amino acid sequence as shown in SEQ ID NO.9, and the coding gene of the bovine viral diarrhea virus multi-epitope fusion protein is an amino acid sequence as shown in SEQ ID NO.9. The recombinant plasmid comprises a coding gene of the bovine viral diarrhea virus multi-epitope fusion protein. The bovine viral diarrhea virus monoclonal antibody is used as a coating antibody, and the bovine viral diarrhea virus multi-epitope fusion protein is used as a marker antigen, so that early infection cases can be found, and a detection result can be provided for health management of cattle herds in time, so that corresponding prevention and control or treatment measures can be taken in time, and the detection efficiency is improved. Different subtypes of BVDVs can be detected more widely, and the applicability to detection of different popular subtypes of BVDVs in different regions is improved.

The invention belongs to the technical field of image processing, and provides a cattle herd density abnormity early warning method based on multi-camera data fusion, which utilizes a multi-camera data fusion technology to convert cattle herd pixel data into two-dimensional coordinates in a unified coordinate system to form a beef cattle global movement track, and meanwhile, divides a field area according to grid units to form a beef cattle density abnormity early warning system. Calculating the density of each grid, delimiting the degree of congestion according to the density, calculating the characteristic values of the grids, introducing a logistic regression model, monitoring and labeling the grids with high characteristic values, combining the grid data and the global motion track, calculating the risk probability, making early warning arrangement according to the level of the risk probability, and counting the false alarm and missing alarm conditions. And retraining the model to complete closed-loop iteration.

The invention relates to the technical field of multi-modal interaction, in particular to a vision, language and behavior linkage grassland robot inspection and driving integrated method, which comprises the following steps: acquiring a cattle herd image annotation coordinate attitude acquisition distance density input model to generate an inspection target sequence, driving a robot to acquire physical signs, judging abnormity and generating an abnormal individual identifier set, screening a monitoring target, inputting visual questions and answers, outputting a next inspection position coordinate, calculating an inspection path motion instruction set by fusing topographic semantics, completing detection and calculation of deviation, adjusting acousto-optic output, and generating a driving control instruction set. A semantic inspection sequence is generated in combination with text vision, target adaptive updating and real-time response are achieved, sign abnormity is recognized through infrared depth comparison, paths are optimized through image semantic matching, obstacle avoidance and adaptability are improved by fusing terrain semantics and motion parameters, and task continuity and recognition reliability are ensured.

The invention relates to the technical field of forage grass drying evaluation, and particularly discloses a forage grass drying evaluation method and system based on multi-modal fusion. According to the method, a quality file containing indexes such as the moisture content, the dry matter content and the dryness grade is established for each batch of forage grass, the feed intake, the feed intake behavior and the production performance data of cattle herds are synchronously collected in the feeding period, and a multi-modal association data set is established with batch identifiers and timestamps as association keys; and obtaining response results of the ingestion performance and the production performance corresponding to different drying characteristics by adopting correlation analysis, regression analysis and statistical significance test, and dynamically correcting the forage grass drying evaluation standard according to the response results of the ingestion performance and the production performance. According to the method, the forage grass drying characteristic data is associated with the cattle herd feed intake, the feed intake behavior and the production performance data according to batches and time, the multi-mode associated data set is constructed, and the direct corresponding relation between the forage grass drying state and the actual feed intake performance and the growth effect of the cattle herd is achieved.

The invention discloses a large-scale breeding method for dairy and meat dual-purpose cattle, and relates to the technical field of livestock breeding, and the breeding steps comprise: S1, selecting a breeding site, obtaining optimal breeding environment data of the dairy and meat dual-purpose cattle based on network big data, according to the obtained breeding environment data, locally screening an optimal breeding environment site as the breeding site, and carrying out site construction, building a cattle farm for both dairy and meat; s2, selecting healthy and healthy milk and meat dual-purpose cattle with regular limbs and good breast development as cattle. According to the method, the occurrence and development trend of epidemic diseases is predicted and the breeding site is managed and controlled by screening out proper feed collocation selection and establishing an epidemic disease monitoring database and an early warning platform, so that cattle herds can be effectively prevented from being infected with epidemic diseases in a large-scale breeding process and spreading the epidemic diseases to other cattle, the epidemic disease prevention and control difficulty and cost are reduced, and the breeding efficiency is improved. And large-scale feeding can be carried out more conveniently.

The utility model discloses a cattle driving device and a pneumatic system thereof. The pneumatic system of the cow driving device comprises an air source assembly, an air control assembly, a reversing valve, a three-way air control valve, at least one air cylinder and a pneumatic motor. A first air outlet of the reversing valve is communicated with a forward rotation port of the pneumatic motor; a second air outlet of the reversing valve is communicated with a reversing port of the pneumatic motor; an air outlet of the three-way pneumatic control valve is communicated with a working port of each air cylinder; the pneumatic motor can be in transmission connection with a frame of the cattle driving device; each cylinder can be in transmission connection with an overhead door of the cattle driving device; and the pneumatic control assembly can control the actuating mechanism of the reversing valve and the actuating mechanism of the three-way pneumatic control valve to act so as to open or close the first passage or the second passage of the reversing valve and open or close the first passage or the second passage of the three-way reversing valve. According to the pneumatic system of the cattle driving device, pure pneumatic control of the cattle driving device is achieved, and the cattle herd safety problem caused by power failure, electric leakage and the like can be effectively avoided.

The invention relates to the technical field of intelligent livestock management, in particular to an intelligent monitoring method and system for rumination behaviors of cattle individuals, and solves the technical problem of low monitoring accuracy in the prior art. The method comprises the following steps: acquiring cattle herd monitoring video data, and performing cattle mouth part identification on image frames in the cattle herd monitoring video data through a target identification model to obtain a cattle mouth area image in each image frame; performing shielding detection on the cattle mouth area image in each image frame, and screening out a target cattle mouth area image from the cattle mouth area images in each image frame according to an obtained shielding proportion; processing the screened target cattle mouth area image through an optical flow algorithm, and generating an optical flow field sequence representing cattle mouth movement; and inputting the optical flow field sequence into a preset classifier, judging whether the cattle is in a rumination behavior, and outputting a monitoring result of the rumination behavior.

The invention belongs to the technical field of grazing intensity evaluation, and discloses a household pasture grazing intensity evaluation method and system based on unmanned aerial vehicle aerial photography and the Internet of Things technology, and the method comprises the steps: obtaining information, such as the spatial distribution position of cattle herds, the number and distribution of livestock herds, and the distance to a livestock pen, in a pasture based on the unmanned aerial vehicle aerial photography technology; based on a GPS Internet of Things tracking technology, obtaining a time sequence cattle herd activity track data set; inverting the spatio-temporal dynamic change condition of the pasture grazing intensity by combining the activity rule of the cattle herd in the pasture and the cattle herd activity track obtained by the unmanned aerial vehicle; and based on the time sequence grazing intensity change condition, calculating the pasture accumulative grazing intensity spatial differentiation condition. Results of the method show that the spatio-temporal dynamic change condition of the pasture scale livestock grazing intensity can be effectively monitored by combining the unmanned aerial vehicle aerial photography technology and the GPS Internet of Things tracking technology, and the research result can provide theoretical basis and scientific support for pasture livestock balance and grassland resource sustainable development.

The present application provides a DC-SMKD-based lightweight cattle herd detection method and device. The present application uses deep separable convolution to reduce the model size of the classic model to obtain a student model. The features of each layer output by the student model and the teacher model are subjected to knowledge distillation through SmoothL1Loss, so that the student model learns the multi-layer feature information of the teacher model YOLOv5x, which makes up for the feature loss after the separable convolution, and is conducive to obtaining relatively complete cattle body features in the teacher model, thereby improving the accuracy of cattle herd detection.

The utility model belongs to the technical field of agricultural machinery, and particularly relates to a cow pregnancy period feed feeding amount adjusting device which comprises a feeding box. A conveying belt is mounted at the bottom of the feeding box; a feeding opening is formed in the side wall of the feeding box; a rotating rod is rotationally connected to the middle part of the feeding opening; the end part of the rotating rod is fixedly connected with a limiting piece; an inner toothed belt is installed on the inner wall of the limiting piece, and the other end of the inner toothed belt is installed on the conveying belt output shaft. The middle part of the rotating rod is fixedly connected with a plurality of groups of connecting pieces, and the plurality of groups of connecting pieces are positioned in the feeding opening; by arranging the inner toothed belt on the conveying belt, the working synchronism of the feeding port and the conveying belt can be improved, and the problem that the blanking amount of different cattle herds is difficult to flexibly change due to the fact that the size of a hole of an original feeding port is manually adjusted is solved; and the distribution uniformity of the feed transferred on the conveying belt can be improved.

The invention belongs to the technical field of biology, and particularly relates to a bovine viral diarrhea virus NS2 truncated protein and application thereof in BVDV antibody detection. The invention firstly provides a truncated protein of a BVDV NS2 protein, the truncated protein is subjected to soluble expression after being fused with glutathione S transferase (GST) and horse radish peroxidase (HRP) respectively, has better reactogenicity with positive serum of a BVDV antibody, does not react with negative serum of the BVDV antibody, and can be used for detecting the BVDV antibody; secondly, a fusion protein of GST and the truncated protein is taken as a coating antigen, a fusion protein of HRP and the truncated protein is taken as a detection antigen, a double-antigen sandwich ELISA method for BVDV antibody detection is constructed, and the method has the technical advantages of high sensitivity, good specificity, simplicity and convenience in operation, easiness in popularization, low cost and the like, and can be applied to screening of BVDV antibodies in cattle.

This invention belongs to the field of animal breeding technology, specifically relating to a molecular marker, primer pair, detection reagent, and application closely linked to the beef meat color brightness trait. The nucleotide sequence of the molecular marker is shown in SEQ ID NO.1, and the nucleotide sequence shown in SEQ ID NO.1 exhibits a G / T polymorphism at position 217 bp. This molecular marker can be used to select cattle herds with high meat color brightness traits.

The invention discloses a bezoar quality improving method based on natural pasture environment optimization. According to the method, the internal quality of the calculus bovis is remarkably improved through multi-dimensional cooperative regulation and control. A natural feed basis with balanced nutrition is provided for cattle from soil environment baseline investigation to precise pasture proportioning, and by combining directional cultivation and implantation of genetic engineering strains, the metabolic activity of rumen microorganisms is effectively enhanced, and accumulation of key components for synthesis of calculus bovis is promoted. The linkage application of the intelligent monitoring system and the environment regulation and control device optimizes the living environment of cattle in real time, and cooperates with innovative intervention means such as lavender essential oil and music therapy, so that the stress reaction of cattle herds is remarkably reduced, and the efficient operation of liver metabolic pathways is guaranteed. The directional feeding of the functional lick bricks further enhances the conversion efficiency of the calculus bovis precursor substance, the whole-process data tracing ensures the controllability of the quality formation process, and finally the improvement of the content of effective active ingredients in the calculus bovis and the enhancement of the quality stability are realized.

This invention belongs to the field of animal breeding technology, specifically relating to an SNP molecular marker, primer pair, kit, and application closely linked to the drip loss trait in beef. The nucleotide sequence of the molecular marker is shown in SEQ ID NO.1, where a mutation occurs at position 76 from base C to base T. This molecular marker can be used to select cattle herds with low drip loss traits.

The utility model belongs to the technical field of animal husbandry tool cars, and relates to an animal feeding scattering car which comprises a car body, a baffle, a pulley, a lever and a pull rope, a car hopper is arranged on the car body, a discharge port is formed in the car hopper, the baffle is installed at the discharge port in a lifting opening and closing mode, and the pull rope is connected with the pulley. The pulley is rotationally installed at the upper end of the baffle, a fulcrum of the lever is arranged on the car hopper, one end of the pull rope is connected with the car hopper, and the other end of the pull rope bypasses the pulley and then is connected with the lever. According to the baffle opening and closing mechanism, complex electrical elements such as a hydraulic cylinder and an air cylinder are abandoned, the manufacturing cost is reduced, the reliability and durability of equipment are enhanced, the maintenance cost and the downtime caused by faults of the electrical elements are reduced, and a more economical, efficient and stable feed scattering solution is provided for cattle raising work.

The utility model relates to the technical field of cattle farm environment control equipment, and discloses a cattle farm ventilation cooling device which comprises a shell, an air outlet is formed in one side of the shell, a plurality of rotating shafts are rotatably connected to the inner wall, located at the air outlet, of the shell, and air deflectors are fixedly connected to the outer walls of the rotating shafts; the outer wall of the top of the shell is provided with a wind direction adjusting mechanism for driving the multiple wind deflectors to synchronously rotate, the wind direction adjusting mechanism can drive the multiple wind deflectors to synchronously swing in a reciprocating mode, the swing of the multiple wind deflectors can change the wind inlet direction and angle, air can be more evenly distributed in the cowshed, and the wind inlet efficiency is improved. The problems of unsmooth ventilation and high temperature of partial areas are effectively solved, and a comprehensive and uniform ventilation environment is provided for cattle herds.

The invention discloses a cattle herd raw material ratio measuring and calculating method and platform based on big data, and relates to the technical field of big data analysis. According to the method, firstly, physiological, production and ingestion data, raw material information and environmental parameters of cattle are collected through the Internet of Things, multi-dimensional analysis is carried out after standardization processing, a matching optimization model is constructed in combination with an MEMP algorithm, and a preliminary scheme giving consideration to nutrition balance and productivity is output; then inputting real-time data of the cattle herds, calculating to obtain initial proportioning parameters, and synchronously simulating proportioning combinations and effects under different targets; finally, consistency verification is conducted according to the goodness of fit between the productivity predicted value of each scheme and the productivity of the same type of historical cattle herds, the optimal scheme is screened, collaborative optimization of precise measurement and calculation, dynamic adjustment and production benefit improvement of the cattle herd raw material ratio is achieved, and then the problems that in the prior art, dynamic fluctuation of raw material nutritional ingredients is difficult to accurately capture, and the production efficiency is improved are effectively solved. Therefore, the problem of insufficient adaptability between the matching scheme and the actual production scene is solved.

The invention discloses an intelligent cattle health condition analysis method and system based on feature recognition, and relates to the technical field of intelligent analysis, and the intelligent analysis method comprises the following steps: obtaining cattle health data based on a camera and a sensor which are deployed in advance, and carrying out the preprocessing of the cattle health data; feature recognition is carried out on the preprocessed cattle health data by using an SIFT algorithm, cattle health feature elements are confirmed, and a cattle health assessment feature set is constructed; based on the cattle health assessment feature set and the cattle health data, utilizing an isolated forest algorithm to construct and train a cattle health analysis model, and determining an abnormal score; and the trained cattle health analysis model is utilized to analyze the cattle health data in combination with the abnormal score, and the cattle health state is analyzed and evaluated. The intelligent level of cattle herd health management is greatly improved, and technical support and economic guarantee are provided for development of modern animal husbandry.

This invention discloses a method and system for cattle detection and counting based on unmanned aerial vehicles (UAVs), belonging to the field of smart ranch monitoring technology. The core of this invention lies in constructing a lightweight C2Net deep neural network. This network uses an improved DLA-34 as its backbone and embeds two types of receptive field reconstruction convolutional modules guided by fixed priors to enhance cattle contours and suppress background noise, respectively. During the feature upsampling stage, a Converse2D deconvolution operator based on closed-form solutions is introduced to improve reconstruction quality. Furthermore, it innovatively uses a focal inverse distance transform map as a supervision signal, transforming sparse point annotations into response maps with strictly non-overlapping peaks for training. This invention can achieve high-precision detection and stable counting of dense cattle herds while significantly reducing annotation costs, and has the advantages of strong robustness, high computational efficiency, and ease of deployment.

To provide a method for estimating a composition ratio by somatic cell count in a cow group, enabling more accurate monitoring than monitoring individual cows, and thereby ensuring stable supply of raw milk.SOLUTION: A method for estimating a composition ratio by somatic cell count in a cow group, including: obtaining partial regression coefficients using a multiple regression model based on a data group, in which at least one of a cow group health factor derived from milk components of milk produced by the cow group, a cow group milk yield factor indicating a ratio of the cow group's milk yield during a specified period before milking to a representative value reflecting an expected milk yield of the cow group, and a cow group environmental factor during rearing of the cow group, is used as an explanatory variable, and a ratio of the number of cows indicating somatic cell counts within the specified range to the number of cows belonging to the cow group is used as an objective variable; and determining the ratio of cows indicating somatic cell counts within the specified range of the estimated cow group, based on the explanatory variable of the estimated cow group and the partial regression coefficients. The method allows estimating the ratio of cows indicating somatic cell counts within the specified range.SELECTED DRAWING: Figure 1

The present invention provides an intelligent control method and system for an electric cattle rumen brush, which relates to the field of agricultural breeding technology. The method comprises deploying an electric rumen brush at a target vibration position inside the cattle rumen, wherein a pH sensor is integrated in the electric rumen brush; collecting historical cattle physiological data, constructing an offset prediction model, and determining a pH target offset; constructing a personalized activation threshold prediction model, and determining a pH personalized activation threshold based on the pH target offset; obtaining a pH measurement value of the pH sensor, constructing a rumen brush vibration frequency adjustment model, and determining a target rumen brush vibration frequency based on the pH personalized activation threshold and the pH measurement value; and remotely controlling the operating state of the electric rumen brush based on the target rumen brush vibration frequency, thereby accurately improving the digestion and absorption rate of the cattle herd, reducing the disease incidence rate of the cattle herd, reducing the frequency of antibiotic use, and improving the operating efficiency and economic benefits of the ranch.

Aiming at the problem of difficult cattle identity recognition caused by problems such as cattle herd occlusion, dirty cattle faces, and the diversity of the activity states and postures of cattle in a complex cattle farm environment. The present invention discloses a cattle face recognition algorithm for a complex cattle farm environment based on Vision-Transformer. The present invention designs a brand-new feature fusion method for the complex cattle farm environment on the basis of the VIT model. A patch-shift network layer proposed by the present invention is added to the VIT model. The shift module in the patch-shift network layer fuses the information between features, not only using local features but also fusing the information between local features, alleviating the impact of dirt on recognition in the cattle farm environment. A learnable Mask matrix is added to enable the model to suppress the image patches without cattle face information, suppressing the interference of the image background, making the model pay more attention to the cattle face features in the image, and learning more robust cattle face features.

The utility model relates to the technical field of beef cattle breeding equipment, and discloses an automatic water drinking device for beef cattle breeding, which comprises a base, a mounting seat is arranged at the top of the base, and a water drinking box positioned on the right side of the mounting seat is arranged at the top of the base. According to the automatic water drinking device for beef cattle breeding, by arranging the water outlet assembly, when the water level in a water drinking box drops, as a hollow floating plate floats on the water surface, the height of the hollow floating plate is lowered, meanwhile, the height of an extension shaft connected with the hollow floating plate is lowered, and at the moment, a water adding hole in the right side of an L-shaped drainage pipe is in an open state; according to the device, a water pump does not need to be used for water injection, so that noise cannot be generated to disturb cattle herds, the influence on water drinking of the cattle herds is avoided, the practicability of the device is improved, and the device is convenient to use by workers.

The invention relates to the field of consumption cattle health analysis, and discloses a consumption cattle health index analysis method based on artificial intelligence, and the method comprises the steps: firstly collecting the medical record information of consumption cattle, classifying the consumption cattle, and binding a label to establish a consumption cattle illness condition portrait; the method comprises the following steps: performing regional monitoring on a consumption cattle herd, tracking and recording the motion trail of the consumption cattle, and establishing a consumption cattle herd-motion state active curve with different labels; the method comprises the following steps: monitoring a consumption cattle herd in different periods, and establishing a consumption cattle physical state score curve; monitoring the sleep condition of the consumption cattle to obtain rest indexes of consumption cattle herds with different labels; identifying the stress state and the early symptom of the disease of the cattle herd, and generating a disease pre-estimation map of the cattle herd; integrating the data to obtain a consumption cattle health index analysis model, and performing real-time analysis on the health state of the consumption cattle; the problems that an existing livestock health supervision technology cannot be suitable for the cattle herd, and an existing health analysis technology does not consider cattle characteristics, so that health analysis is inaccurate and analysis is not systematic are solved.