1031 results about "Tracking system" patented technology

The invention provides a mine abnormal event real-time identification method and system based on time sequence characteristics, and relates to the technical field of mode identification, and the method comprises the steps: carrying out the time-space alignment and semantic annotation of multi-modal monitoring data, and constructing a time sequence knowledge graph; calculating a dynamic association weight between entities, and analyzing a risk propagation path; predicting a risk situation based on a historical evolution rule; and dynamically generating a differential early warning strategy and establishing a closed-loop tracking system. According to the invention, early identification, accurate prediction and efficient disposal of mine safety risks can be realized, and the mine safety management level is improved.

The invention provides a pipeline welding all-position welding seam identifying and tracking system and method, and belongs to the technical field of pipeline welding automation. In order to solve the problems of strong arc light interference, low tracking precision, slow response speed and insufficient robustness in the existing pipeline all-position welding tracking technology, the system comprises a sensing layer, a processing layer, a decision-making layer and an execution layer. The welding seam identifying and tracking method comprises the following steps: S1, calibrating the welding seam identifying and tracking system; s2, all-position welding tracking is carried out; and S3, performing adaptive adjustment on different scenes. According to the method, dynamic weighted fusion and fuzzy PID control are adopted, multi-posture welding such as flat welding, vertical position welding, horizontal position welding and overhead position welding can be automatically adapted, parameters do not need to be manually adjusted, and the operation threshold is lowered.

The invention relates to the technical field of computer vision and multi-sensor data fusion, in particular to a multi-sensor image fusion obstacle real-time detection and tracking system, which comprises the following steps of: firstly, fusing data of a camera, a millimeter wave radar and a laser radar, and extracting and fusing multi-modal features; performing multi-target tracking based on a recurrent neural network: generating a target state through space-time modeling, associating a target with a historical track by using an attention mechanism, and maintaining track consistency; and the system performs semantic classification and interaction analysis on the obstacle, predicts the movement track of the obstacle, realizes deep semantic understanding, and finally outputs the identity label and the complete historical track of the obstacle.

The invention discloses a block chain-based blood full-process traceability tracking and safety management system and method, and relates to the technical field of blood management, and the method comprises the steps: distributing an encrypted digital identifier with a timestamp for each blood unit; collecting physical characteristic data of the blood storage environment in real time; dynamically adjusting the state mark of the blood product based on a preset plasma quality evaluation model; a threshold signature technology is adopted to ensure that multiple medical institutions complete blood information verification and sharing on the premise of protecting privacy; when it is monitored that the blood environment parameters exceed a safety threshold value, graded early warning is generated, and an emergency processing flow is started; and establishing a blood circulation whole process auditing tracking system. The system has the advantages that the blood whole-process traceability system based on the block chain is constructed, transparent credible management of the whole life cycle of blood products from collection to use is achieved, the trust and privacy protection problem in multi-mechanism cooperation is solved, and the blood safety management level and the emergency processing efficiency are comprehensively improved.

The invention provides a patient rehabilitation tracking system, a rehabilitation training regulation and control method based on active perception and environment self-adaption, equipment and a medium, and the method comprises the steps: determining a cooperative motion state of a nerve-muscle-bone system according to a multi-modal physiological data flow of rehabilitation training tracking of a target patient; performing intention-muscle force cooperative identification based on the cooperative motion state to obtain motion intention and muscle force contribution distribution of the target patient; determining a dynamic risk map of the target patient during rehabilitation training; variable universe fuzzy reasoning is carried out on the motion intention, the muscle force contribution distribution and the dynamic risk map, and then a rehabilitation adjustment instruction matched with the rehabilitation state of the target patient is obtained; the rehabilitation progress of the target patient is continuously tracked, and the rehabilitation training robot is controlled to execute self-adaptive power-assisted compensation according to the rehabilitation adjustment instruction. By means of the scheme, motion intention decoding and muscle force contribution analysis can be conducted on rehabilitation training of the patient, and rehabilitation training regulation and control are conducted in combination with the dynamic environment risk.

The invention relates to an acquisition equipment parameter determination method and equipment for improving welding seam image quality, and the method comprises the steps: determining the current parameters of acquisition equipment, and obtaining a welding seam region image under the current parameter condition; high-brightness pixel points and low-brightness pixel points in the welding seam area image are extracted to determine the high-brightness pixel proportion, the low-brightness pixel proportion and the high-brightness pixel distribution divergence; according to the high-brightness pixel proportion, the low-brightness pixel proportion and the high-brightness pixel distribution divergence, whether the welding seam area image is qualified or not is judged; if yes, taking the current parameter as a determined parameter of the acquisition equipment; and if not, correcting the current parameter to obtain the updated current parameter, and returning to determine the current parameter until the determined parameter of the acquisition equipment is obtained. The problems that in the prior art, under the complex illumination working condition, proper collection equipment parameters cannot be determined to ensure clear presentation and stable extraction of a welding seam feature area, then the robustness and positioning precision of a welding seam tracking system are affected, and the technical adaptability is reduced are solved.

The invention provides an acoustic coalescence elimination method for hydrogen bubbles in molten aluminum, and belongs to the technical field of molten aluminum bubble elimination. According to the method, sound field collaborative focusing is achieved by arranging a phase control array transducer set in a molten aluminum smelting furnace, primary gathered sound waves and efficient coalescence sound waves are applied in stages according to bubble size evolution in a double-frequency scanning mode, and the hydrogen bubbles in the molten aluminum are eliminated. A target frequency is dynamically adjusted in combination with a bubble resonance frequency optimization model to match the inherent frequency of a bubble, a sound-bubble coupling dynamic tracking system is used for monitoring bubble evolution triggering stage switching in real time, and a sound field focus point dynamically scans and covers a three-dimensional space area through phase delay control. A delay detection method is adopted to eliminate cavitation bubble interference and accurately measure the hydrogen content, sound intensity and frequency parameters are optimized according to a sound field parameter self-adaptive regulation and control model, and the technical problem that hydrogen bubbles in a molten aluminum deep area are difficult to be effectively driven by sound waves and cannot be fully coalesced and eliminated is solved.

The invention relates to the technical field of fire fighting, in particular to a fire fighting safety technical-connection early warning and task trajectory tracking system, which comprises a safety technical-connection early warning subsystem and a task trajectory tracking subsystem, and is characterized in that the safety technical-connection early warning subsystem and the task trajectory tracking subsystem realize bidirectional linkage through a data middle table; through bidirectional linkage of the safety technical linkage early warning subsystem and the task trajectory tracking subsystem, an intelligent cooperative closed loop of early warning and rescue is constructed, millisecond-level data interaction between the multi-mode monitoring unit and the multi-mode tracking unit is achieved through the data middle platform, and when the early warning system recognizes fire point coordinates and a three-level risk level, the safety technical linkage early warning subsystem and the task trajectory tracking subsystem are combined to achieve early warning and rescue. An optimal internal attack path can be pushed to a trajectory tracking system in real time; on the contrary, when the vital signs of the rescuers are abnormal, emergency equipment such as a smoke exhaust fan can be reversely triggered to be started, and a full-link response mechanism of risk pre-judgment, path planning and dynamic intervention is formed.

A system and method for 3D anomaly detection and tracking are provided that uses multimodal fusion, reduced training data, recursive segmentation and histogram statistic distance. The anomaly may be a defect or a configuration error.

A method for transferring seed during a planting operation includes receiving, by a theft detection system, a first equipment identity of first equipment, receiving the seed into a seed bin of second equipment from the first equipment, determining, using a sensing device disposed on the second equipment and communicatively coupled to the theft detection system, a first weight value indicative of weight of the seed received into the seed bin from the first equipment, and at least one of transmitting, by the theft detection system using a satellite data communication protocol, the first weight value and the first equipment identity to a tracking system, and determining, by the theft detection system, whether any of the seed was stolen based on the first weight value and the first equipment identity and selectively generating and transmitting a notification to the tracking system indicating that the seed was stolen.

Examples relate to systems and methods for enhancing generative AI outputs using eye tracking data. An eye tracking system accesses eye gaze information associated with a field of view of a head-wearable apparatus and generates contextual information associated with the field of view of the head-wearable apparatus based on the eye gaze information. The eye tracking system processes, by a generative machine learning model, the contextual information and at least one image of the field of view of the head-wearable apparatus to generate an output and presents on a display of the head-wearable apparatus the output generated by the generative machine learning model.

Systems and methods for object tracking are described. One or more aspects of the systems and methods include receiving a video depicting an object; generating object tracking information for the object using a student network, wherein the student network is trained in a second training phase based on a teacher network using an object tracking training set and a knowledge distillation loss that is based on an output of the student network and the teacher network, and wherein the teacher network is trained in a first training phase using an object detection training set that is augmented with object tracking supervision data; and transmitting the object tracking information in response to receiving the video.

The invention discloses a fusion detection and iron tower photoelectric tracking system and a fusion detection and iron tower photoelectric tracking method for a low-speed small target. The system comprises a multi-source detection module, a data fusion module and a photoelectric tracking module, and various heterogeneous data of a target are obtained through a radar detection unit, a frequency spectrum detection unit and a protocol cracking unit; after data preprocessing, performing multi-source data fusion by adopting a dynamic weight fusion algorithm and Kalman filtering to generate comprehensive target information; and based on the equipment space calibration parameters, calculating an optoelectronic equipment pointing instruction through a coordinate conversion model, and driving the optoelectronic equipment to accurately track a target. The system is further provided with a feedback optimization module which dynamically corrects the pointing instruction according to the tracking deviation. According to the invention, deep fusion and intelligent cooperation of multi-source detection data are realized, and the detection precision, tracking stability and system response speed of a low-speed small target are effectively improved.

The invention relates to the technical field of block chain data storage and traceability tracking, in particular to a document printing and traceability tracking system based on a block chain. Comprising an off-line certificate generation unit used for generating an off-line cryptographic certificate based on technical parameters analyzed from an external printing request; the dynamic anchoring control unit is used for monitoring system state parameters and carrying out dynamic anchoring strategy calculation based on the system state parameters so as to generate an anchoring triggering decision; the aggregation anchoring unit is used for responding to the anchoring triggering decision, aggregating a plurality of offline cryptographic certificates to generate an aggregation root certificate, and broadcasting a block chain transaction containing the aggregation root certificate; and the verification traceability unit is used for acquiring the aggregation root certification on the block chain and executing cryptographic verification in combination with the offline data to obtain a final verification result. According to the invention, the core pain point that the system is unavailable due to the performance bottleneck of the block chain in a high-concurrency scene in the prior art is solved, and the continuity and reliability of services are ensured.

The invention provides a multi-modal fusion real-time tracking system and method for a low-speed small target in a complex low-altitude environment. The method comprises the steps that S1, sensor data of a radar, a visible light camera and an infrared camera are collected and preprocessed; the sensor data comprises a visible light image, an infrared image and a radar echo signal; s2, fusing the visible light image and the infrared image to obtain a fused image; generating a joint region of interest as a target recognition region according to the radar echo signal; s3, based on the target identification area and the fusion image, fusion is carried out, and an information fusion grid is obtained; and S4, matching a target based on the information fusion grid, and updating the trajectory of the target. According to the method, the detectability and the tracking stability of the target under complicated conditions such as shielding, severe weather and night are remarkably improved.

The invention provides a camera focusing method and device for video transparent transmission equipment. Gaze information from the gaze tracking subsystem and depth information from the depth tracking system may be utilized to determine a depth to focus. A combination of depth information and gaze information is used.

The invention discloses an all-terrain maneuvering target tracking system and an all-terrain maneuvering target tracking method, belongs to the technical field of all-terrain moving target tracking, and aims to solve the problems of poor target tracking trajectory adaptability and large vibration interference in a complex terrain. During operation, the target orientation is positioned, the advancing direction is updated in real time, after the collection range is dynamically delimited, multiple frames of images are collected, and a topographic map is constructed through cutting, splicing and distortion correction; preprocessing the topographic map, extracting landform features, and dividing passable areas; generating a tracking trajectory in the passable area, and optimizing the trajectory through the position change of the target; and adaptively adjusting parameters of the balance component according to the track area, and fusing a vibration signal to judge whether to trigger track updating so as to ensure that the track dynamically adapts to terrain and target movement. According to the invention, through enhancing image processing and multi-source data fusion, the continuity, accuracy and environmental adaptability of target tracking in a complex terrain are significantly improved, and the reliability and efficiency of operation are effectively enhanced.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a search and chat generative interfaces, which may be used to produce generative answers, identify relevant content, and take actions within a respective content collaboration platform.

The invention, which relates to the technical field of printing production management, discloses a production processing tracking system and tracking method for a printing industry, and the method specifically comprises the steps: creating a corresponding production order in a preset printing production management system based on customer demand information, generating a unique identification code for each production order according to a dynamic random number algorithm, and associating and binding the unique identification code with each production order; obtaining a process node of each production order associated with the unique identification code to construct a process dependency graph of each production order; calculating the remaining delivery time of each production order associated with the unique identification code, and sorting each production order in real time to construct a self-adaptively updated priority scheduling queue; obtaining a current process node of each production order, and obtaining a state attribute of each process node of each production order and a corresponding execution progress; and carrying out full-link visual display on the state attribute of each process node of each production order and the corresponding execution progress, and inputting a unique identification code through a client to carry out query.

The invention relates to the technical field of target tracking, in particular to an infrared target tracking system in a complex scene, which comprises a radiation analysis module, a phase analysis module, a trajectory extraction module, a state evaluation module and a region optimization module. According to the method, smooth estimation and stability judgment of thermal signal time sequence change are realized by performing frequency domain and phase feature analysis on continuous frame thermal radiation signals, establishing a temperature difference signal sequence of a target and a background, and extracting a phase disturbance amplitude and a curvature change trend; target motion features are identified in combination with a trajectory direction angle and a curvature change rate, response to thermal phase mutation and maintenance of trajectory continuity are enhanced in a dynamic background, background disturbance and a real moving target can be effectively distinguished, the accuracy of target positioning and trajectory extraction is improved, and the target positioning and trajectory extraction efficiency is improved. The stability and continuity of a target tracking area in a complex infrared scene are kept, and accurate recognition and area adaptive optimization of a target state are realized.

A blockchain-verified data tracking system provides enhanced data privacy management through selective masking of blockchain ledger fields. Data transactions associated with a data set are detected and recorded in a blockchain ledger, with certain data fields masked based on a blockchain permission scheme. Network nodes can store and transmit blockchain updates, generating a distributed and secure record of data transactions. The selective masking enables different levels of access to sensitive information based on user roles, permissions, or other criteria, facilitating compliance with data protection regulations while supporting data operations and analytics.

The invention provides an unmanned aerial vehicle tracking system and method based on state space modeling and scale searching, and belongs to the technical field of artificial intelligence. The invention aims to solve the problems of low recognition rate and high false alarm rate when a traditional unmanned aerial vehicle tracking method is used for processing low-altitude complex backgrounds, illumination changes and multi-shielding scenes. The tracking system comprises a target detection module, a target tracking module and a dual-threshold closed-loop control module. The tracking method comprises the following steps: performing feature extraction and candidate target identification on an input video stream or image sequence through a target detection module, and outputting a detection result in the form of a coordinate frame and confidence; the target tracking module performs continuous frame association and real-time position updating on candidate unmanned aerial vehicle targets through a multi-scale twin convolutional network; and the double-threshold closed-loop control module receives an output result, automatically judges a current task state according to a detection confidence threshold and a tracking frame number threshold, and intelligently switches a tracking mode and a detection mode.

The invention discloses a material tracking system for battery production, and particularly relates to the technical field of production data traceability, a process topology constraint model is constructed based on a production process, and a material flow expected path is generated; collecting behaviors of the materials in each station to form a material circulation time sequence track; matching the time sequence track with the process topology constraint model to generate a process legality state; controlling association establishment of process data and material identifiers according to a process legality state, and isolating and re-checking data which do not meet constraints; a source identifier is introduced into the process data and is bound with the process legality state, and finally a material production resume record is generated; according to the invention, through process topology constraint and behavior time sequence matching, accurate tracking of material circulation in a dynamic production scene is realized; abnormal path data is prevented from entering associative storage through legality judgment and associative gating; through source identification and resume integration, the traceability and the rechecking reliability capability of the material production process are improved.

The invention discloses a high-speed target continuous tracking system and method based on inter-satellite cooperative computing. The system comprises a distributed architecture management module, an inter-satellite communication module, a double-satellite cooperative tracking module and a distributed computing coordination module. The system provided by the invention adopts a distributed hierarchical management structure, and through a hierarchical management mechanism of intra-cluster local management and inter-cluster global coordination, not only are the quick response and autonomy of a distributed system reserved, but also the global management capability of a centralized layer is introduced, and the communication overhead is effectively reduced. In addition, a multi-type missile trajectory prediction method based on deep learning is designed, a prediction-driven tracking switching mechanism is achieved, the next round of prediction task is triggered through an adaptive threshold value, and missing of a visibility window is avoided. In the aspect of computing resource scheduling, the time delay of task scheduling can be reduced, the communication overhead is remarkably reduced while the tracking precision is ensured, the high timeliness of the tracked target is ensured, and the global continuous tracking of the target is realized.

The invention discloses an unmanned aerial vehicle relay tracking system and method for cloud side-end cooperation in an urban scene, and belongs to the technical field of intelligent traffic and unmanned aerial vehicle cooperative control. In order to solve the problems of insufficient endurance and limited sight distance of existing single-machine tracking in an urban large-range scene, a physically distributed and logically unified cloud-side-end three-level architecture is constructed, wherein a cloud end is responsible for natural language instruction analysis and global road network monitoring; the edge end serves as a regional scheduling hub and is responsible for operating a high-precision detection model, extracting a target Re-ID feature fingerprint and calculating a cross-machine relay time window; and the terminal unmanned aerial vehicle only operates a lightweight tracking model and a visual servo control law. According to the method, the urban area is divided into a plurality of honeycomb grids, seamless locking and relay of a target among unmanned aerial vehicles in different grid responsibility areas are realized by using a cross-view feature relay protocol and a collaborative finite-state machine, and the engineering problem of long-time-sequence and large-range vehicle tracking is effectively solved.

The invention relates to the technical field of automatic identification and data acquisition, discloses a control method and system for positioning a scanning gun based on an RFID electronic chip, and aims to solve the problems of remnant detection failure and misjudgment caused by shielding and deformation of existing video monitoring. A unique identification RFID chip is arranged on the surface of an object, a multi-protocol scanning gun terminal is combined to capture label signals in real time, a space coordinate mapping module is used for achieving three-dimensional positioning, a track generation engine restores a moving path, and a retention judgment unit recognizes abnormal retention according to a time threshold value and a behavior mode and triggers an alarm linkage mechanism. According to the method, an active identity binding and trajectory tracking system is constructed, so that the dependence on a visual environment is eliminated, the remnant identification precision, the anti-interference capability and the response speed in a security scene are remarkably improved, and all-weather stable operation and large-scale convenient deployment are supported.

The invention discloses a video target tracking system and method combined with deep learning, and relates to the technical field of computer vision, and the method comprises the following steps: obtaining video frame sequence data of each monitoring device; performing segmentation processing on the time coding sequence of the video frame sequence data to obtain track fragments of corresponding monitoring equipment; and extracting a time coding subsequence of a track fragment pair formed by any two track fragments, and carrying out feature analysis on the time coding subsequence to obtain a multi-dimensional matching confidence score of each track fragment pair. According to the scheme, a shielding time window detection mechanism is introduced, shielding influences are actively recognized and quantified, the problem of time coding distortion caused by shielding in a multi-monitoring-device environment is solved, a similarity calculation result can be dynamically corrected, mismatching caused by local shielding is avoided, and the accuracy of time coding is improved by combining motion continuity constraint and a nonlinear fusion strategy. The track matching robustness in a complex shielding scene is effectively improved, and a high-confidence matching reference is provided for subsequent time axis unification.

The invention discloses an eye movement tracking stability enhancing method, system and device and a storage medium, and belongs to the field of human-computer interaction and computer vision. The method comprises the following steps: acquiring an eye image and an original sight fixation point coordinate; performing quantitative evaluation on the image from five dimensions of definition, contrast and the like to generate an eye image quality evaluation grade; calculating the moving speed and acceleration of the current point based on the historical sight fixation point sequence; fusing, and judging and correcting the original coordinates. Through multi-modal information fusion and hierarchical adaptive correction, noise jump caused by poor image quality can be accurately distinguished and filtered out, meanwhile, the real eye movement dynamic state is effectively reserved, and the output stability and reliability of an eye movement tracking system are remarkably improved.

The invention discloses a moving target identification and tracking system based on an analog micromirror array (AMA), belongs to the technical field of photoelectric tracking and machine vision, and aims to solve the technical problems of slow response, large inertia and complex structure of a traditional mechanical tracking system. According to the technical scheme, an AMA composed of a plurality of MEMS micromirror units which can be independently controlled and have the static or quasi-static two-dimensional deflection capacity is adopted as a non-mechanical light beam deflection actuator, the AMA can be composed of micromirror arrays in various forms, digital image data are analyzed in real time to solve the target offset, and the non-mechanical light beam deflection actuator is obtained. And an instruction is generated to drive the AMA to deflect at a high speed so as to compensate the deflection, so that continuous and stable locking and tracking imaging of the moving target are realized. The system has the advantages of being high in response speed, high in tracking precision, free of mechanical inertia and compact in structure, supports flexible switching of various working modes such as wide-area scanning and long-distance tracking, and is high in application flexibility.

A computer-implemented method for defining and creating a request intake flow for an issue tracking system is described. Embodiments described herein include systems and techniques for creating custom portal intake flows for an issue tracking system. The systems may include a user interface that allows portal intake flows to be generated and the user to select the information and workflow for an intake flow during the generation process. Embodiments are also directed to system and methods for creating dynamic summaries for issues managed by an issue tracking system. The dynamic summaries may be generated using a generative output model, as described herein, and provide information to a user about a current status, history or other events associated with an issue. Embodiments are directed to systems and methods for using a generative output engine to provide suggestions for creating a project management interface for an issue tracking system.