1647 results about "Identity recognition" patented technology

To solve the problems of fractured identity across multiple blockchains, these methods and systems allow for a single unified identity to be managed and resolved across multiple chains within an interop network. By leveraging message passing, identity records can exist securely across different chains. The system incorporates counterfactual blockchains, enabling trust-minimized name registration that reduces costs while maintaining decentralization and security. ENS name resolution is supported across both onchain and offchain environments, with verifiable proofs ensuring efficient resolution. By structuring message passing and utilizing decentralized indexers, these methods and systems provide a scalable and reliable framework for cross-chain identity.

The invention discloses a physical fitness evaluation method based on human skeleton trajectory tracking, which comprises the following steps: S1, acquiring whole-process video data of a physical fitness test through video acquisition equipment, and generating a video frame according to an acquisition frequency; s2, processing the video frame by using a skeleton dynamic analysis algorithm, and extracting human skeleton key points; s3, extracting identity features of the testee through a motion map identity recognition network, and tracking and confirming the identity features; s4, performing action recognition, fragment segmentation and compliance judgment on the skeleton key point time sequence track; s5, aiming at the abnormal skeleton key points, performing complementation and time sequence smoothing by adopting an inverse kinematics inference method; s6, inputting the complete skeleton key point time sequence data into the human body action evaluation model for processing, and quantizing and outputting a physical ability evaluation index; and S7, generating a physical ability evaluation report and giving action feedback and optimization suggestions. According to the invention, objectivity, accuracy and intelligent level of physical ability evaluation are effectively improved.

The invention relates to the technical field of security and protection management, in particular to a campus security and protection management system based on deep learning, which improves the accuracy and robustness of identity recognition by acquiring access control card numbers, face images or fingerprint features and generating standardized identity authentication data. And on the basis of a comparison result of the identity authentication data and the campus database, a behavior chain initialization identifier is generated, and accurate identity binding of the school entering personnel is realized. Furthermore, by collecting multi-camera image stream data, pedestrian re-identification and similarity calculation are executed by using a deep feature matching network, and a cross-camera continuous trajectory data set is generated. And matching the behavior track data set with the conventional path template to generate a behavior offset feature vector. And carrying out joint modeling on the behavior offset characteristics and the identity information through a graph neural network model containing an attention mechanism, and outputting a behavior purpose label and a risk grade score. And a graded security response instruction is generated based on the risk score, so that the missing report rate and the false report rate are effectively reduced.

The invention discloses an automatic fare collection method and system based on multi-modal identity recognition, and relates to the technical field of rail transit automatic fare collection systems and multi-modal biological recognition fusion, and the method comprises the following steps: 1, enabling a user to approach a recognition area, carrying out the multi-modal data collection, and carrying out the quality detection and preprocessing; 2, feature extraction and credibility preliminary calculation are carried out; 3, environment data are collected and subjected to standardization processing; step 4, adaptively predicting a weight through machine learning, and constructing weight smoothing and time domain constraints; step 5, carrying out D-S evidence step-by-step fusion, and calculating comprehensive credibility; and step 6, comparing the comprehensive credibility with a preset threshold value, if the comprehensive credibility is greater than or equal to the preset threshold value, determining that the identification is successful and the gate is opened for passing, otherwise, determining that the credibility is insufficient, and performing alternative / manual processing. The system comprises a front-end identification terminal, a read-write industrial control all-in-one machine and a cloud management platform.

The invention relates to the technical field of artificial intelligence, and discloses an intelligent rationing system for pig house feed supply, which comprises the following steps: performing identity recognition on pigs in a feeding area through radio frequency identification tags, and extracting weight, growth cycle and behavior characteristics; based on historical ingestion records, health data and environmental factors, a dynamic nutritional requirement model of the pigs is constructed, and the current feed requirement is predicted in combination with a multi-factor regression algorithm; according to the feed demand result, the feeding amount and the feeding frequency of the corresponding trough are adjusted in real time; dynamically adjusting the power of a conveying motor and the pressure difference of a pipeline section by utilizing a variable-frequency driving control technology; and collecting the ingestion response and the feeding execution state of the pigs, and outputting an updated pig allocation result in combination with online feedback and historical data differences. The feeding device has the advantage that the feeding stability is improved.

The invention discloses a multi-mode emotion continuous recognition method for medical treatment, belongs to the technical field of artificial intelligence and medical treatment information, and mainly aims to simulate the dynamic change process of emotion by establishing a Neural ODEs framework and overcome the static property and discreteness of emotion modeling in a traditional method. Through a causal inference technology, emotional features are separated from individual-independent physiological differences, and the generalization ability across individuals is improved. A self-supervised learning method is utilized, the synergistic effect between the EEG and the eye movement signal is improved through cross-modal contrast learning, and the emotion recognition precision is enhanced. The calculation complexity is reduced through a dynamic sparse attention mechanism, and meanwhile, focusing is performed on a key time slice in emotion recognition. Through multi-task joint learning, the model learns multiple tasks such as emotion intensity regression and tested identity recognition during emotion classification, and the personalized emotion recognition capability is improved.

The invention discloses an electric power artificial intelligence model security protection method and system based on a zero-trust architecture, and belongs to the technical field of power grid security protection. The method comprises the following steps: constructing an encryption service request according to identity recognition information and environment information of an access user; verifying the request by adopting a multi-factor identity verification method, and generating an authentication credible score; performing weighted calculation by combining the user historical behavior score, the equipment safety score and the environmental factor score to obtain a dynamic comprehensive credibility score; and generating a permission configuration strategy based on the score to realize fine-grained access control. The system comprises a user request access module, an information collection module, a credibility evaluation module and an access control module, and through continuous verification and dynamic permission adjustment, safe access of the electric power artificial intelligence model is ensured. The defect that a traditional security technology depends on static authentication and boundary protection is overcome, data leakage, model tampering and illegal access are effectively prevented, and the overall security and stability of a power system are improved.

The invention relates to the technical field of data acquisition and information security, and discloses a block chain tamper-proof data acquisition method and device, and the device comprises a control chip, an identity recognition module, a local tamper-proof module, a time sequence processing module (including a parallel uploading unit), a clock calibration module, a storage monitoring module and the like. The method comprises the steps of hardware-level identity verification, operator verification, generation of a data packet containing metadata, encryption and tamper prevention, networking / offline uplink evidence storage, association uplink approval and hash comparison verification. By applying the method and the system, the tamper-proofing of the data in the whole process can be realized, the offline scene is adapted, and the high-credibility data acquisition requirement is met.

Methods and apparatus for biometric data maintenance, access and distribution across two or more experiential and / or network domains. In one embodiment, a 5G NR-based network architecture is provided which allows ultra-low latency and effectively user-imperceptible biometric data use for e.g., authentication and maintenance of user state across multiple domains via multiple constituent user devices (e.g., UEs). The network architecture includes both (i) a distributed biometric database (BDB) model wherein relevant biometric data for individuals / UEs is intelligently cached in various portions of the distributed database, and (ii) centralized and local BAEs (biometric analytics entities) which manage the aforementioned intelligent caching, as well as network configuration using one or both of 5G NR network “slicing” and CU / DU split options to optimize end-user biometric-related applications such as those providing identification / authentication, AR functions, VR functions or yet others.

The invention discloses a traffic checkpoint holographic recognition method and system based on multi-mode perception and a medium, and relates to the technical field of traffic management, and the method comprises the steps: collecting an original perception data set in real time through a multi-mode sensor array disposed at a target traffic checkpoint; performing time-space synchronization processing on the original sensing data set to generate a multi-modal data frame sequence; performing fusion processing on the multi-modal data frame sequence by using a deep learning model to generate a holographic feature vector of the target vehicle; and based on the holographic feature vector, target identity recognition and behavior analysis of the target vehicle are carried out, a recognition result is output, and abnormal event early warning is carried out. The technical problems of low traffic recognition precision and insufficient real-time performance caused by the fact that an existing traffic monitoring system cannot efficiently fuse various sensor data for holographic recognition are solved, and the technical effect of improving traffic management efficiency and safety through multi-modal data space-time synchronization and deep feature fusion is achieved.

The invention provides a multi-head gun-type camera multi-angle intelligent tracking method and system, and the method comprises the steps: obtaining image flow data through a multi-head gun-type camera, building a D-NeRF model through combining with an improved multi-layer perception mechanism, outputting a virtual viewpoint image, a scene depth image, a shielding relation image and a motion vector field according to the D-NeRF model, obtaining a volume density field, and carrying out the multi-head gun-type camera multi-angle intelligent tracking. Analyzing the volume density field, acquiring a continuous aggregation area and performing cutting operation, generating a target instance, acquiring a bounding box and a centroid coordinate in combination with a scene depth map, acquiring appearance characteristics and morphological characteristics and performing matching, generating an identity recognition result, performing trajectory prediction through physical constraint, generating a probability space-time trajectory and performing evaluation, and performing identification on the probability space-time trajectory. According to the method, the uncertain area is obtained, the motion of the camera is subjected to joint optimization in combination with the probability space-time trajectory, the intelligent control instruction is generated, and multi-angle intelligent tracking is performed according to the intelligent control instruction, so that the intelligent level of multi-camera monitoring and tracking in a complex scene is improved.

The embodiment of the invention discloses a cross-modal biological feature generation type enhancement method and system. The method comprises the following steps of: constructing a cross-modal biological feature recognition model, respectively acquiring long-distance modal data and short-distance modal data of a user, extracting feature vectors, pre-recognizing the user based on the long-distance feature vectors, finely recognizing the user based on the short-distance feature vectors, and carrying out mutual complementation and fusion on various modal features, so as to improve the recognition accuracy of the user. According to the method, the limitation that a single mode is low in recognition accuracy and prone to being interfered under different distance scenes is overcome, the identity recognition safety is improved, and through a secondary recognition mechanism combining pre-recognition and fine recognition, the efficiency and precision of identity recognition are improved while the system load is reduced.

The invention discloses a door lock collaborative identity recognition method and system, and the method comprises the steps: obtaining a locally stored MAC-face binding relation table according to face recognition verification completed by a resident through an intelligent door lock; according to the moving path of the resident from the floor entrance to the home door lock, identity recognition is completed through cooperation of multicast communication and the home door lock, an identity confirmation result is obtained, and a directional multicast network is constructed; according to a leaving event that a resident opens a door lock from a room, triggering a passing door lock to collect leaving person information, and obtaining a leaving person identity confirmation result; and selecting to send a unicast or multicast confirmation message by the own door lock according to the completion degree of identity confirmation of the leaving person, and triggering the passing door lock to send an IGMP leaving message to the router to obtain a simplified multicast forwarding table. According to the embodiment of the invention, seamless identity cooperation of the whole process from home returning to home leaving can be realized, and the automation degree of home security and protection and the user experience are improved.

The invention discloses a violation person identity recognition method for gas turbine power plant on-site safety supervision, relates to the technical field of person identity recognition, and aims at recognizing specific violation behaviors, positioning the occurrence time and space of the violation behaviors and marking corresponding behavior subjects. The method comprises the following steps: acquiring operation image data, extracting behavior subject image features and equipment acquisition data, generating fusion identity information, matching violation identities, outputting structured records, evaluating violation risk levels, verifying the identities of persons in charge and filing violation records, and automatically identifying dangerous behaviors in a gas turbine power plant through the operation image data acquisition and violation behavior identification model. And in combination with the dynamic attitude vector sequence and equipment acquisition data, generating identity feature fusion data, performing map matching, identifying the identity of a violation person, labeling through a risk level label, pushing to a responsible person terminal, completing identity confirmation and violation behavior recording and archiving, and realizing whole-process supervision and closed-loop management.

The invention discloses a two-dimensional code full-life-cycle tracking management system based on dynamic encryption, relates to the technical field of two-dimensional code tracking management, and is characterized in that a target object life cycle state sequence diagram is constructed, and a two-dimensional code coding index is dynamically generated based on a current state, an equipment environment and a time factor; and dynamic generation and secure binding of two-dimensional code content are realized in combination with a multi-factor asymmetric encryption mode. Meanwhile, through path consistency verification and state chain continuity judgment, validity verification is carried out on a two-dimensional code access behavior, and the validity of the two-dimensional code is judged in combination with an environment deviation detection mechanism; compared with the prior art, the method can effectively prevent the two-dimensional code from being counterfeited, replayed and visited unauthorized, improves the uniqueness, verifiability and safety of the two-dimensional code in the whole life cycle, and is suitable for high-safety product tracking, anti-counterfeiting authentication, multi-stage identity recognition and other scenes.

The invention relates to the technical field of face recognition, and discloses a face recognition method and system suitable for an outdoor electronic instrument to solve the problem of low recognition precision under complex illumination, posture change and shielding conditions in the prior art, and the method comprises the steps: S1, collecting image data, and carrying out the preprocessing; s2, performing face region detection and face key point positioning on the illumination enhanced image; s3, performing affine transformation based on the face detection result set to perform face alignment; s4, extracting a face feature vector based on a ResNet100 structure; s5, performing attitude-guided feature reconstruction processing on the face feature vector to obtain an attitude-enhanced face feature vector; s6, performing feature normalization and identity classification on the posture-enhanced face feature vector, and outputting a face recognition result; and S7, outputting a final identity recognition result and confidence. According to the method, an efficient and scientific optimization scheme can be provided in outdoor face recognition, and remarkable technical values and economic benefits are brought to practical application.

The invention discloses an authority management method and system for an access control system of a building hall, and relates to the technical field of authority management, and the authority management method comprises the following steps: associatively storing personnel identity information and corresponding authority levels to form an authority database, and adjusting the authority in real time according to time, events and personnel demands; the access control terminal reads the personnel identity recognition information, dynamically evaluates the credibility of the personnel identity recognition information, and judges whether the personnel are allowed to pass the access control according to the credibility; the permission verification server performs matching in a permission database according to the received identity recognition information to search a corresponding permission level; and according to the searched authority level, monitoring the number of times of accessing areas and floors exceeding the authority level of the person, and the access time of the person, and timely giving an alarm for abnormal behaviors according to a monitoring result. According to the invention, by integrating multiple security authentication means, the problems of single identity authentication form and low security are solved, and the security protection capability of the system is improved.

The invention provides a driving authority management method and device based on biological feature verification and a medium, and belongs to the technical field of vehicles. The method comprises the steps of collecting facial features, voiceprint data and driving behavior data by detecting a starting operation of a current driver; the identity of the current driver is recognized by using a multi-modal biological recognition algorithm, and the accuracy and anti-counterfeiting capability of identity verification are improved by adopting a bimodal fusion scheme of face recognition and voiceprint recognition; when it is determined that identity recognition of the current driver succeeds, a driving account is determined to judge whether the driver has the use permission or not, a binding relation of driver identity-account-function permission is established, and accurate matching of the intelligent driving permission and the driver qualification is achieved; the open state of the intelligent driving function is dynamically controlled based on a permission verification result, if the permission exists, the intelligent driving function is automatically prepared, if the permission does not exist, the function is locked, a clear prompt is given, and the safety risk that the intelligent driving function is used before being learned is avoided from the source.

The invention relates to the technical field of gateway management, in particular to a Modbus gateway management system and method based on an active identification carrier, and the system comprises a priority field identification module, an instruction field association module, an authority state judgment module, an access judgment module and an exception classification module. According to the method, dynamic structured sorting is executed according to priorities, functional fields are dynamically coupled with instruction sequences according to a mapping relation, equipment authority is synchronously judged based on a validity period and an operation state label to realize packet switching, and a communication process is subjected to full-process identification according to an access state and a data association feature; identity consistency and response sequence differences in interaction events are automatically classified into exclusive abnormal tags, links of equipment access, permission change, communication judgment and abnormal collection are driven by real-time parameter linkage, attribute distinguishing and behavior judgment capabilities in a multi-equipment environment are improved, and the method is suitable for the multi-equipment environment. And full-process management of multi-dimensional identity recognition, dynamic permission allocation, communication judgment and abnormity tracing is supported.

The invention belongs to the technical field of gait recognition, and particularly relates to a human gait recognition method and system in a complex scene. And sequentially performing illumination correction, human body posture angle alignment and shielding processing on the extracted human body gait data, and performing human body gait recognition based on the gait data obtained after illumination correction, human body posture angle alignment and shielding processing. According to the occlusion processing, a comprehensive and reliable occlusion area judgment standard is set based on the connection relation between skeleton nodes, the human anatomy reference distance, kinematics constraint and the time continuity requirement, and then a missing human body area is reconstructed through optical flow compensation or bilinear interpolation based on information of visible pixels around the occlusion area. The accuracy of gait recognition in a complex scene is improved, the problem of adaptability of the complex scene is solved in a breakthrough mode, high-precision gait identity recognition is achieved, and the security and protection monitoring requirement of a real scene is met.

The invention discloses a sports equipment management personnel identification method, system and equipment, and the method comprises the steps: starting and initializing a camera through detecting a sports equipment use trigger signal, and stopping automatic focusing; and shooting multiple frames of images at different focal lengths according to a preset interval, determining a clear area by using a gradient magnitude algorithm, and performing image registration and fusion to form a composite image. And if the whole area is not covered, shooting and splicing are carried out again. And through composite image splicing, distortion cutting, noise reduction and normalization processing, a final image is output for determining the identity of a person. According to the invention, through multi-frame shooting and accurate image processing, a high-quality image is obtained, and information limitation and quality defects of a single image are effectively avoided. Various algorithms are fused to ensure that the image is clear, complete and standardized, the accuracy and reliability of personnel identity recognition are remarkably improved, an accurate image basis is provided for sports equipment management, the normalization and safety of equipment use are guaranteed, meanwhile, the image collecting and processing efficiency is improved, and the management cost is reduced.

The invention discloses a console identity recognition method based on a block chain, relates to the technical field of computer security and human-computer interaction, and realizes non-sensibility and precision of console identity recognition through fusion of behavior feature modeling and a block chain technology. In a multi-person alternate scene, an operator does not need to actively execute a biological verification action, and the system converts behavior characteristics into encrypted operation fingerprints by continuously capturing physical operation actions and graphic interaction logic and carries out uplink storage on the encrypted operation fingerprints; the block chain smart contract compares the time sequence difference between the current operation and the historical fingerprint in real time, and only when the behavior is abnormal, the biological auxiliary verification is triggered, so that the operation interruption caused by the factors such as gloves and light in the industrial environment is remarkably reduced; a dynamic permission label generation mechanism breaks through static authorization limitation; by analyzing the semantic intention of the control instruction and combining a preset equipment permission topological graph, the minimum equipment operation range is automatically delimited, and the tag validity period is set according to the instruction risk level.

The invention discloses a long-distance identity recognition method for a large area, which belongs to the technical field of computer vision and comprises the following steps: S1, initializing a system; s2, collecting video data; s3, pedestrian detection and segmentation; s4, performing gait recognition; s5, multi-target cross-camera tracking is carried out; and S6, result output and application service. According to the invention, an effective solution is provided for large-scene video intelligent security and protection in a complex environment of a park, the accuracy and traceability of personnel identity recognition in a high-risk area are ensured, and the safety production level of the park is improved; a long-distance multi-target identity recognition scheme is provided, real-time monitoring and early warning of illegal person invasion in key protection areas are achieved, and reliable safety guarantee is provided for public places.

The invention relates to the field of voiceprint recognition and voice transfer, and discloses a real-time voiceprint recognition method and system for multi-user overlapped voices. The method comprises the following steps: acquiring a multi-source audio stream, and carrying out standardization and framing processing to generate a streaming audio frame sequence; based on the sequence, through circular buffering, noise reduction, endpoint detection and overlap detection model processing, obtaining an overlap interval label; task assembly, speaker separation, track numbering, voiceprint feature extraction and identity judgment are carried out, and a track identity binding structure is generated; and finally, voice transcription, fragment splicing and conflict cutting are executed, and the voiceprint template library is updated. According to the method, real-time separation and identity recognition of overlapped voices of multiple persons are realized, and the accuracy and robustness of voiceprint recognition in a complex scene are effectively improved.

The invention provides an automatic production station working hour statistical system and method based on near field communication, the system comprises five layers of architectures including an identity recognition layer, a data acquisition layer, an edge computing layer, a cloud service layer and a terminal interaction layer, and the method completes the steps of initialization, NFC interaction triggering, multi-mode mistaken touch prevention verification and the like by means of the system. NFC, a sensor and a face recognition technology are fused, core modules such as task intelligent matching, energy consumption-man-hour linkage accounting and cross-station collaborative man-hour splitting are designed, and the system further has the functions of offline intelligent caching and multi-dimensional man-hour analysis. According to the invention, automation and precision of man-hour statistics are realized, single-station standardization and multi-station collaborative production scenes are adapted, data are ensured to be reliable and free of loss, deep fusion of production data is realized, enterprise hardware and management costs are reduced, and the intelligent manufacturing fine management level is improved.

The invention provides a three-dimensional tracking scanner with a face recognition safety system and a control method. The three-dimensional tracking type scanner comprises a scanner body; the face recognition module is connected with the scanner body and comprises a binocular camera assembly which is used for responding to the situation that an object approaches the three-dimensional tracking type scanner and synchronously collecting left and right images of the object; the binocular reconstruction unit is used for establishing a three-dimensional grid model of a human face according to the left and right images when the detected object is the human face; the living body detection unit is used for carrying out living body detection on the human face by adopting a multiple detection mechanism based on the three-dimensional grid model; the face recognition unit is used for performing identity recognition on the user corresponding to the face under the condition that the living body detection is passed; and the control management system is connected with the face recognition module, and the control management system is used for allowing the user to execute an operation matched with the permission of the target identity on the scanner body under the condition that the identity of the user is the target identity.

The invention relates to the technical field of magnetic attraction control, and discloses a multi-head shaver linkage control method and system based on magnetic attraction contacts.The method is based on at least two single-head shavers with controllers, shaving modules and energy storage modules, and electric connection is achieved through the magnetic attraction contacts; the first controller sends an identity recognition instruction after detecting the contact connection state, receives and matches identity information of the second controller, and establishes a control link if matching succeeds; the working state is synchronized when the link is established, the abnormal state is unified as the running state, any subsequent controller sends a cooperation instruction through the link after obtaining an operation instruction, and the other controllers execute synchronously. According to the method, the problems that a traditional single shaver is insufficient in scene adaptation and a multi-shaver-head product is tedious in operation are solved, flexible combination and separation of single-head units are achieved, the requirements for portable storage and efficient shaving are met, and the operation convenience and the intelligent level are improved.

The embodiment of the invention discloses a chemical early warning interception method and device, electronic equipment and a medium. A specific embodiment of the method comprises the following steps: carrying out identity recognition on a target chemical detection terminal set to obtain a detection terminal identity recognition information set; performing state information extraction on the multi-modal target chemical information set to obtain a chemical multi-modal state information set; performing data deduplication on the multi-modal state information set of the chemicals and then performing association identification to obtain a multi-modal association information set; performing chemical risk identification on the de-duplicated multi-modal chemical information set to obtain a to-be-tracked chemical information set; and performing trajectory tracking early warning on the to-be-tracked chemical article information set to obtain a chemical article trajectory early warning information set, and performing early warning interception on the to-be-tracked chemical article information set. According to the embodiment, a data barrier can be broken, data sharing and safety are improved, and the accuracy of accurate interception and risk early warning of target chemicals is improved.

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.

The invention discloses a sheep weight and size measuring system and method, and relates to the technical field of animal husbandry breeding intelligent management. Firstly, the invention discloses a sheep weight and body size measuring system, which comprises a PLC (Programmable Logic Controller), a computer, a channel module, a blocking module, an identity recognition module, an entrance module, an image acquisition module, a weighing module and a grouping module, wherein the PLC is in communication connection with the computer. Secondly, the invention discloses a method for measuring the weight and the body size of the sheep, and the method comprises the following steps: S1, driving the sheep into a guide channel at the entrance of the system, and arranging a queue; and S2, a worker starts a blocking module to communicate the recognition channel with the guide channel, and after the first sheep enters the recognition channel, the blocking module is started again to block the space between the recognition channel and the guide channel and block the next sheep. The device has the advantages of automation, high precision and non-contact, so that personal errors and sheep stress are reduced, and the working efficiency is improved.