1487 results about "Draft animals" patented technology

The invention discloses a livestock health state real-time monitoring method and system based on the Internet of Things, and the method comprises the steps: collecting livestock biological data and environment parameters through a biological chip ear tag and an environment sensor, and carrying out the preprocessing, and obtaining a standardized multi-dimensional livestock data flow; in combination with image data provided by a video monitoring system, identifying livestock individuals and analyzing behavior features, and fusing biological data and visual data to generate livestock individualized feature vectors; constructing an individualized health baseline model in combination with historical health records; comparing the deviation degree between the current state and the health baseline through an anomaly detection algorithm, and identifying a potential health problem; early warning is performed according to the abnormity severity level, intervention suggestions are generated, early warning information is pushed to the breeding personnel through multiple channels, and response measures and results are recorded to form closed-loop management. According to the invention, accurate real-time monitoring of the health state of the livestock is realized, the accuracy and timeliness of anomaly detection are improved, the breeding risk is reduced, and the production efficiency of animal husbandry is improved.

The invention discloses an intelligent livestock breeding traceability method and system, and the method comprises the steps: building an overall framework of the intelligent livestock breeding traceability system based on a micro-service architecture, and employing Spring Cloud Al ibaaba as a micro-service technology stack; livestock physiological data and environmental parameters are collected through Internet of Things equipment, and a livestock electronic file is established; an AI intelligent analysis engine is constructed, and livestock health state evaluation, oestrus prediction and abnormal behavior recognition are achieved; the whole life cycle data of livestock from breeding to selling is recorded based on the block chain technology, and a full-chain traceability system is constructed. The method further comprises the functions of integrating a financial service interface, designing a multi-terminal collaborative application platform, constructing a matchmaking transaction platform and the like. According to the invention, the problems of data islanding, incomplete traceability system, low intelligent level, insufficient system expandability and the like in the prior art are solved, and the accuracy, traceability and system stability of livestock breeding are improved.

The invention relates to the technical field of Internet of Things and artificial intelligence, in particular to a livestock disease prevention, control, monitoring and early warning system based on Internet of Things, which comprises a data acquisition module, a data preprocessing module, a self-adaptive data analysis module, an early warning generation module and a user interface module, wherein the data acquisition module is used for acquiring physiological data, behavior data and environment data of livestock; the data preprocessing module is used for cleaning and processing the data to eliminate noise and interference; the self-adaptive data analysis module is used for dynamically adjusting monitoring parameters and early warning threshold values and identifying potential disease risks; and the early warning generation module is used for generating early warning information of different levels and sending early warning. According to the invention, by combining the Internet of Things, machine learning and deep learning technologies, real-time monitoring of livestock health, accurate identification of disease risks and dynamic adjustment of monitoring parameters and early warning thresholds are realized, and the accuracy and timeliness of disease prevention and control are significantly improved.

The invention relates to the technical field of livestock breeding instruments, and discloses an auxiliary fixing device for animal husbandry veterinary examination, which comprises a fixing cage, fences are arranged on the periphery of the fixing cage, a fixing cage base is used as a horizontal plane, for two oppositely arranged fences in the X-axis direction of the fixing cage base, a neck clamping device is arranged in one of the fences, and the neck clamping device is arranged in the other of the fences. One fence is of a movable structure and moves towards the neck clamping device under the action of a driving mechanism, a cage door is formed in the fence, and a lower fixing device is arranged on the lower portion of the fixing cage and used for limiting and supporting the abdomen and four limbs of the livestock. Lifting frames are arranged on the two sides of the outer portion of the fixing cage in the Y-axis direction. The lower fixing device and the upper fixing device are matched with each other, the abdomen, the four limbs and the back of the livestock are limited, supported and clamped in all directions, so that the livestock is difficult to struggle off and keeps a relatively stable posture, and a safe and reliable foundation is provided for subsequent inspection operation.

The invention discloses a livestock health state monitoring method, apparatus and device, and a storage medium. The livestock health state monitoring method comprises the steps of obtaining sensor monitoring data in a livestock factory; constructing a sample data set according to the sensor monitoring data; and performing model pre-training and model tuning training on a pre-constructed monitoring network model by adopting the sensor sample data until a preset model training ending condition is met, and taking the trained monitoring network model as a livestock health monitoring model. By means of the technical scheme, the model performance of the livestock health monitoring model applied to different livestock factory areas is improved, and meanwhile the training efficiency of model training is improved.

Livestock may be managed by a variety of systems, processes, and techniques. In particular implementations, the properties of water may be monitored by automated techniques and treated water may be provided to animals. In certain implementations, sick, or potentially sick, livestock may be provided with treated water to improve their health. The automated techniques may include monitoring the movements and / or water consumption of the livestock and predicting which ones may be sick based on their movements and / or water consumption. In some implementations, a water trough may contain multiple segments. The water properties in the segments may be maintained at different states.

The invention relates to a livestock health early warning and intelligent driving mechanical auxiliary system based on bio-electricity signal monitoring, and belongs to the technical field of animal husbandry intelligent management. Aiming at the problems of single parameter, strong driving irritability and low efficiency of a traditional monitoring method, the system is used for generating a health score in real time by adopting a CNN-LSTM hybrid model through data fusion of a bio-electricity signal acquisition module (electrocardio, myoelectricity and respiratory frequency) and an environment sensor, and driving an intelligent driving machine in combination with a deep reinforcement learning algorithm, so that the driving effect is improved. The abnormal livestock is guided to be isolated in a non-intrusive mode through ultrasonic directional wave beams and low-intensity laser. The monitoring accuracy is larger than or equal to 95%, the driving efficiency is improved by 60%, all-weather stable operation (availability is larger than or equal to 98%) is achieved, the epidemic disease risk and animal stress are effectively reduced, and an efficient intelligent solution is provided for large-scale breeding.

The embodiment of the invention provides a livestock state monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of intelligent breeding. Acquiring a plurality of physiological indexes respectively corresponding to the livestock to be monitored in a plurality of preset time periods, wherein each preset time period corresponds to one or more physiological indexes; and determining at least one first target physiological state of the to-be-monitored livestock according to the plurality of physiological indexes corresponding to the plurality of preset time periods. By adopting the above technical scheme, the at least one first target physiological state of the to-be-monitored livestock can be determined according to the plurality of physiological indexes corresponding to the plurality of preset time periods, the conditions of oestrus, illness, scare and the like of the livestock can be automatically and accurately predicted, intervention measures can be conveniently taken in time, the livestock breeding cost is reduced, and the livestock breeding efficiency is improved. The livestock breeding yield is improved.

The invention discloses an automatic feeding device for livestock feeding, and belongs to the technical field of livestock breeding, the automatic feeding device comprises a bottom plate, a feeding trough is fixed on the side surface of the top end of the bottom plate, a material containing cylinder is arranged right above the feeding trough, and a moving assembly in transmission connection with a servo motor is arranged at the top end of the bottom plate; a discharging barrel communicating with the interior of the material containing barrel is fixed to the bottom end of the material containing barrel, a cleaning assembly is arranged outside the discharging barrel, and a material mixing assembly is arranged inside the material containing barrel; fodder in the material containing barrel falls into the feeding trough at a constant speed through the moving assembly, so that uniform feeding is conducted on the interior of the feeding trough, the utilization rate of the fodder is increased, the feeding cost is reduced, and the overall feeding efficiency is improved; feed is uniformly mixed through the material mixing assembly, auxiliary feed conveying and auxiliary discharging are carried out through the material mixing assembly, the problem of discharging blockage is avoided, the discharging speed of plastic is effectively increased, and it is ensured that good feeding can be conducted all the time.

The present disclosure generally relates to a monitoring device (100) for remotely monitoring health of a young livestock animal (10), the device (100) comprising: an elongated body (110) within predefined dimensional limits; and a set of electronic components housed within the elongated body (110), the electronic components comprising: a temperature sensor for measuring body temperature of the young livestock animal (10); a computer processor for processing the measured temperature into temperature data; and a wireless communications component for transmitting the temperature data to a remote computer device (210) for processing to monitor the health of the young livestock animal (10), wherein the predefined dimensional limits of the elongated body (110) enable the monitoring device (100) to be orally administrable into the young livestock animal (10) and to remain inside its stomach (12) without being excreted.

The utility model relates to the technical field of isolation cages, in particular to an isolation cage for animal husbandry and veterinary medicine. Comprising a supporting part and an isolation cage body, the supporting part is detachably connected with the isolation cage body, the middle of the isolation cage body is connected with an operation part, the operation part is slidably connected with the isolation cage body, and a limiting assembly is arranged on the outer side of the isolation cage body and used for limiting the operation part; the supporting part comprises a limiting base and a supporting disc, the supporting disc is rotationally connected with the limiting base, and the supporting disc is detachably connected with the isolation cage body. When livestock enter the isolation cage body, the isolation cage body can be driven to rotate through the supporting part, the livestock rotates along with the isolation cage body, and the illness state of the livestock can be conveniently detected; when the livestock is treated, the operation part can be fixed, the posture of the livestock is adjusted, and examination and treatment are facilitated.

In general, one aspect disclosed features an anchoring system for anchoring an at least partially floorless mobile livestock enclosure to the ground. The anchoring system comprising: a securing flange configured to mechanically couple the anchoring system to the enclosure; an anchor; and a drive configured to place the anchor into contact with the ground, and to retract the anchor from contact with the ground.

The invention relates to the technical field of computers, and discloses a livestock three-dimensional measurement-based attitude detection method, which comprises the following steps: acquiring three-dimensional point cloud data of a to-be-detected livestock by using a multi-view depth camera system, and extracting livestock contour point cloud data; inputting the livestock contour point cloud data into a preliminary identification model for screening, determining potential livestock attitude data, and identifying the potential livestock attitude data to obtain target livestock attitude data; the target livestock attitude data is compared with the standard attitude data, a body size three-dimensional model corresponding to the livestock is constructed based on the livestock contour point cloud data to judge whether the to-be-detected livestock is in a normal state, body size parameters of the body size three-dimensional model mainly comprise the height of a cross part, the inclined length of the body, the chest circumference and the abdominal circumference, and the body size parameters of the body size three-dimensional model comprise the height of the cross part. And if the posture of the to-be-detected livestock is abnormal, generating alarm data containing the posture abnormity, and sending the alarm data to a user terminal in real time. The accuracy and the real-time performance of livestock health condition monitoring can be improved.

In a headlock system having a plurality of n headlock cells, each of the n cells being adapted to enclose at least one animal; n is an integer greater than 1; a system for locating the position of at least one animal, the system comprising: at least one identification means adapted to transmit at least one identification signal associated with said at least one animal; at least one locating means adapted to generate at least one location signal associated with said at least one animal; and, a data processing system in communication with said at least one identification means and said at least one locating means, adapted to analyze said signals, said analyzed signals comprising the position within a predetermined region in said headlock system of each of said at least one animals as a function of time.

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.

The invention discloses intelligent pasture livestock health monitoring equipment. The equipment comprises a vital sign monitoring mechanism worn on the legs of livestock, a behavior monitoring mechanism worn on the neck of the livestock and an environment monitoring mechanism vertically extending and arranged on the pasture ground; the vital sign monitoring mechanism comprises a vital sign monitoring fixing ring, a vital sign monitoring supporting shell with an upward opening is connected to the vital sign monitoring fixing ring, and a plurality of body temperature monitoring sensors are connected into the vital sign monitoring supporting shell; a pulse monitoring through hole penetrating in the radial direction of the physical sign monitoring fixing ring is formed in the side face of the physical sign monitoring fixing ring, and a pulse monitor is arranged at the pulse monitoring through hole; the behavior monitoring mechanism comprises a conventional monitoring camera, a high-speed monitoring camera and an infrared monitoring camera; the equipment can accurately collect various physiological data of livestock, such as body temperature, heart rate, respiratory rate and the like, as well as behavior data, such as activity amount, ingestion time, rumination times and the like, so that the accuracy and reliability of the data are ensured, and an accurate basis is provided for evaluating the health condition of the livestock.

The invention provides a GIS-based intelligent livestock breeding full-chain visualization method and system, and the method comprises the steps: collecting the basic information of a farm, livestock information, production process data and other multi-source data through a standardized data interface, and carrying out the correlation mapping of business data and GIS spatial data based on a geographic coordinate system; constructing a three-dimensional data model containing spatial information, attribute information and relation information; three-dimensional scene rendering is realized by utilizing a WebGL technology, a macroscopic visual engine, a mesoscopic visual engine and a microcosmic visual engine are constructed, and multi-scale visual display is realized; constructing a full-life-cycle data model of the livestock products, and realizing visual display of full-chain traceability of the livestock products; based on a visual data analysis method, a decision support system for industrial layout analysis, breeding scale prediction, epidemic disease risk assessment and market supply and demand analysis is constructed. Visual management of the whole industry chain of livestock breeding is achieved, the industry management efficiency is improved, the epidemic disease risk prevention and control capacity is enhanced, and data support is provided for decision making of the livestock industry.

The invention discloses an intelligent animal husbandry and veterinary diagnosis system based on machine learning, and particularly relates to the technical field of intelligent animal husbandry diagnosis. The livestock body surface temperature, the livestock chewing data and the livestock movement data are processed to obtain the real body temperature, the rumination time, the movement state and the movement speed of the livestock, and the livestock heart rate, the respiratory rate, the real body temperature, the rumination time and the movement speed are input into a livestock sign abnormity recognition model for abnormity recognition. The behavior data of the livestock is obtained through the multi-angle camera, the abnormal image data set is marked after a series of processing, the received livestock sign abnormal data set and the received livestock behavior abnormal image data set are input into the livestock health intelligent diagnosis model for health diagnosis, and the livestock illness state diagnosis efficiency and accuracy can be effectively improved.

The invention belongs to the technical field of animal husbandry veterinarians and discloses a cub heat preservation device for animal husbandry veterinarians, which comprises a box body, a box cover detachably connected to the top of the box body, a feeding mechanism arranged on one side of the box body, a water inlet mechanism arranged on one side, away from the feeding mechanism, of the box body, a temperature sensor arranged on the inner bottom surface of the box cover, and a heating mechanism arranged on the top of the box cover. The heating mechanism comprises a heating part fixedly connected to the top face of the box cover, the heating part is communicated with a heating pipe, the heating pipe is communicated with the interior of the box body, limiting mechanisms are symmetrically arranged between the box body and the box cover, and exhaust outlets are symmetrically formed in the two sides of the box body. A cub is placed in the box body, the box cover is covered, the temperature in the box body is sensed through the temperature sensor, when temperature rise is needed, hot air is conveyed into the box body through the heating part, the temperature in the box body is kept constant, and meanwhile the feeding mechanism and the water inlet mechanism are arranged on the two sides of the box body respectively to provide food and water for the cub in the box body. According to the method, various environmental factors are adjusted, so that the survival rate of the livestock cubs is greatly improved.

The invention relates to the technical field of animal husbandry monitoring, in particular to a livestock physiological behavior monitoring method and system. The method comprises the following steps: acquiring a three-area pressure matrix through a pressure sensing pad; performing dynamic path identification and camera adjustment according to the three-region pressure matrix to obtain dynamic path tracking data; performing livestock mechanical gait analysis according to the dynamic path tracking data to obtain a gait mechanical characteristic spectrum; acquiring basic information of livestock; performing individual gait time sequence segmentation according to the gait mechanics characteristic spectrum to obtain segmented aligned gait data; according to the basic information of the livestock and the segmented alignment gait data, self-adaptive gait threshold calculation is carried out, and an individualized abnormal threshold set is obtained; and performing abnormal gait pattern recognition according to the individualized abnormal threshold set to obtain a gait deviation index matrix. The scientificity and reliability of livestock management and animal husbandry production efficiency are remarkably improved through the regional pressure sensing technology and the biological tracking camera shooting technology.

The invention discloses a feed feeding control system and method based on data analysis, and relates to the technical field of feed feeding, and the method comprises the steps: obtaining feed feeding data and corresponding livestock growth data according to a historical feed feeding cycle; analyzing the feed feeding data, and extracting a matching sequence of historical feed feeding data; combining the corresponding livestock growth data to establish an associated data group; constructing a feed ratio prediction model based on a support vector regression method; performing feed preparation and feeding according to the real-time matching sequence; analyzing an adaptive value of the real-time matching sequence of the current feed feeding period according to the real-time monitoring data set, and judging the continuous condition of the current feed feeding period according to the adaptive value; and constructing an update cycle matching model based on the update cycle matching set, and analyzing the total number of days of the subsequent feed feeding cycle according to the update cycle matching model. The rationality of feed feeding is improved, and intelligent and reasonable feeding is realized.

The invention belongs to the technical field of livestock feeding management, and particularly relates to a livestock breeding feeding precise management method and system based on an AI technology. A fixed feeding mode based on a growth stage and a self-adaptive dynamic correction algorithm based on environment deviation and activity fluctuation are fused; a multi-dimensional data-driven feeding amount decision model is constructed, dependence of a single parameter is broken through, accurate feeding can be performed according to real-time monitoring data by adopting a self-adaptive feeding mode when the environment or activity amount fluctuates and deviates, the nutritional requirements of livestock are better met, and the feeding efficiency is improved. When data acquisition is abnormal or the environment and activity amount are stable and appropriate, a fixed feeding mode is adopted, and the fixed feeding mode can be periodically updated according to a self-adaptive feeding mode, so that the feeding accuracy and efficiency are improved, the feed waste is reduced, the stability of feed feeding is guaranteed, and the feeding efficiency is improved. And the feeding effect can be brought into an optimal state.

The invention discloses a livestock identity recognition method and system based on an unmanned aerial vehicle, and relates to the technical field of livestock identity recognition, and the method comprises the steps: constructing an identity information database which comprises the electronic ear tag IDs of all target livestock individuals in a pasture, a visible light feature image, an infrared thermal imaging contour template and a historical motion behavior sequence in a cloud server; initialization of an unmanned aerial vehicle system carrying a visible light camera, an infrared thermal imager, an RFID reader and an edge calculation module is completed, and communication connection between the unmanned aerial vehicle system and a ground control station and between the unmanned aerial vehicle system and a cloud server is established; controlling the unmanned aerial vehicle to enter an inspection area, monitoring a ground target through a visible light camera, synchronously acquiring a visible light image, an infrared thermal image and a radio frequency response signal of a target individual when the livestock is detected to enter an effective identification range, and performing timestamp alignment on the three types of data; a first visual feature vector is extracted from the visible light image and a visual confidence score is generated.

A device for calculating a feed conversion ratio of livestock includes a memory storing a program for calculating the feed conversion ratio of the livestock, and a processor configured to execute the program for calculating the feed conversion ratio of the livestock, wherein the program for calculating the feed conversion ratio of the livestock receives image data from at least one camera capturing images of an inside of a livestock shed, recognizes livestock from the image data, calculates a movement distance and a weight of the livestock, calculates a meal amount of the livestock based on a time period in which the livestock stays in a preset eating region, calculates the feed conversion ratio based on the weight and meal amount of the livestock, and provides the calculated feed conversion ratio to a user terminal.

The invention relates to the field of animal husbandry feeding control, in particular to an automatic feeding method and system based on electromagnetic valve flowmeter data, and the method comprises the steps: collecting a historical water pressure time sequence of a drinking water pipeline; static characteristics and dynamic characteristics of all water pressure characteristics of the water pressure time sequence are calculated, and a feeding error is calculated according to the target feeding water quantity and the actual feeding water quantity collected during feeding every time; the water pressure features are clustered, corresponding initial weights are distributed to the static features and the dynamic features in the clustering process, an evaluation function is constructed according to the difference of feeding errors in each cluster after clustering is completed, and when the evaluation function value reaches the minimum value, an optimal clustering result is obtained; according to the optimal clustering result, the water volume during real-time feeding is adjusted so as to complete water drinking management of the livestock. According to the method, the water quantity during real-time feeding is adjusted according to the optimal clustering result, and a more accurate feeding strategy can be formulated according to different conditions.

The livestock industry must be able to easily calculate the amount of emissions reduction required to utilize the carbon credit system, so that livestock breeders who raise livestock to reduce greenhouse gases emitted from their manure and waste can do so. [Solution] The number of livestock raised in each unit period is obtained, the operating status of the treatment tank that performs excrement treatment in each unit period is received, and the number of livestock and the operating status in the corresponding unit period are used to calculate a second emission amount when the livestock excrement is treated using a second excrement treatment method.

The invention relates to the technical field of material conveying equipment, in particular to a livestock slaughtering automatic feeding device and a feeding method thereof.The livestock slaughtering automatic feeding device comprises a feeding table, the feeding table is provided with a conveying belt with a cutting gap, side plates and limiting frames are arranged on the two sides of the feeding table, and a cutting knife is arranged between the limiting frames; gravity detection assemblies (including pressure detection tables, detection supporting plates and the like) are symmetrically arranged in the feeding table, limiting assemblies (including clamping frames, driving shafts, auxiliary driving belts and the like) are arranged on the inner sides of the side plates, and driving assemblies (including driving equipment, pressure sensors and the like) electrically connected with the gravity detection assemblies are arranged on the outer sides of the side plates; a flow dividing box with a spray head and a cleaning rod is arranged below the feeding table, cleaning of the conveying belt, intermittent discharging of materials to the conveying belt, triggering and limiting when the materials are conveyed to a detection area, starting of weight detection after a pressure sensor reaches the standard, adjustment of the positions of the materials through a driving assembly to guarantee equal-weight cutting, and resetting of a system after completion are achieved. Accurate slitting is achieved, weight deviation is reduced, and production efficiency and product standardization are improved.

The high-fence type livestock transfer trolley comprises an engineering van, the engineering van comprises a cab and a rear chassis, and a transfer carriage is installed on the rear chassis; the transfer carriage comprises a first bottom plate and a second bottom plate. A left front stand column, a right front stand column, a left rear stand column and a right rear stand column are arranged at the four corners of the first bottom plate correspondingly. A handrail assembly is arranged between the left front stand column and the right front stand column, a rear vehicle door is arranged between the left rear stand column and the right rear stand column, and fence door assemblies are arranged between the left front stand column and the left rear stand column and between the right front stand column and the right rear stand column. Cleaning mechanisms are arranged above the first bottom plate and the second bottom plate, each cleaning mechanism comprises a left slide way, a right slide way and a cleaning water spraying assembly, the left slide ways are horizontally arranged between the left front stand column and the left rear stand column in the front-back direction, and the right slide ways are horizontally arranged between the right front stand column and the right rear stand column in the front-back direction. The technical problem that the livestock transfer requirement cannot be met due to the fact that excrement of an existing transfer vehicle is difficult to clean is effectively solved.

The invention provides a six-axis inertial data behavior identification universal platform method for cattle, pigs, sheep and other livestock, and is suitable for behavior monitoring and management scenes of various livestock and poultry animals. The method comprises the steps of animal identity and species recognition, corresponding behavior recognition template loading, six-axis data feature extraction, behavior judgment and state recognition, recognition result output, platform interface butt joint and the like. Uniform adaptation and efficient processing of different animal types and sampling strategies (including fixed frequency, intermittent sampling, event triggering and the like) are achieved through a modular structure and a parameterized configuration mode. The platform supports continuous expansion of newly added species and behavior templates, can be deployed on edge equipment or a cloud server, has low power consumption, high compatibility and cross-scene applicability, and is suitable for intelligent management requirements of health monitoring, oestrus recognition, abnormity early warning and the like of livestock such as dairy cattle, beef cattle, live pigs, sheep, goats and the like in a farm.

The invention provides a livestock number identification method and system combining AI vision and multi-target tracking, and the method comprises the steps: collecting a continuous video stream of a livestock activity region, generating a video frame sequence with a timestamp mark, carrying out the dynamic background modeling operation, extracting a contour feature set of a livestock object in each frame image, generating a multi-dimensional motion representation vector, and carrying out the recognition of the number of livestock. The method comprises the following steps: performing adaptive multi-scale feature enhancement on a livestock cluster region, decoupling pixel-level features of the livestock cluster region, outputting a form-motion joint coding sequence of each independent livestock individual, constructing a space-time incidence matrix based on the form-motion joint coding sequence, and extracting topological features of a livestock motion track through a lightweight feature extraction network. And generating a global ID mapping table containing the unique identifier of the individual, carrying out real-time statistics on the number of the livestock based on the global ID mapping table, and carrying out behavior tracing analysis on the individual livestock corresponding to the abnormal movement track to obtain a number statistics result and an abnormal behavior identification result. The precision of livestock quantity statistics can be improved.