39results about How to "Reduce bandwidth usage" patented technology

The invention discloses an image transmission method, device and equipment of a remote operation system and a medium, the method is applied to a local operation end, the remote operation system comprises the local operation end and a remote operation end, and the method comprises the following steps: acquiring an initial ultrasonic image corresponding to a target object at the local operation end, performing feature extraction on the initial ultrasonic image to obtain a target ultrasonic image; determining an ultrasonic sub-image corresponding to the target ultrasonic image based on the knowledge graph, and determining an image value of the ultrasonic sub-image according to the ultrasonic image evaluation dimension; and transmitting the ultrasonic sub-image to a remote operation end according to the image value. Based on the technical scheme, the image is divided into the sub-images of different areas, the image values of the sub-images are determined, and the transmission methods corresponding to the sub-images are determined according to the image values, so that the preferential transmission of the high-value image is ensured, the overall bandwidth occupation and the system load are reduced, and the transmission efficiency is improved. And a key technical support is provided for the accuracy and safety of a remote operation.

The invention relates to image processing and video monitoring, in particular to a real-time target tracking method and system based on double-camera linkage, and the method comprises the steps: initializing the system and defining a coordinate system; when the target enters the high-definition picture of the high-definition zoom camera, judging whether the target enters the field of view of the wide-angle fixed-focus camera or not in real time; if the target enters the view field of the wide-angle fixed-focus camera, guiding the high-definition zoom camera to turn to the target by using the large view field advantage of the wide angle, and carrying out picture fusion and asymmetric weight ROI video coding; if the target does not enter the field of view of the wide-angle fixed-focus camera, starting an independent closed-loop PID tracking mode for the high-definition zoom camera, and gradually switching the high-definition zoom camera from the wide-angle end to the long-focus end to realize stable locking of the target in a full-focus range; according to the technical scheme provided by the invention, the defect that the moving target is difficult to accurately track in the prior art can be effectively overcome.

The invention relates to the technical field of Internet of Things communication, discloses an Internet of Things multi-Android client state synchronization method, and solves the problems of poor state consistency, high back-end dependence, large delay and insufficient compatibility in the prior art. According to the scheme, the method comprises the steps that after a client completes initialization, MQTT connection with a rear end is established, an MQTT state message pushed by the rear end is monitored, after the message is received, equipment state information is obtained through analysis, local state cache and a UI interface are updated, meanwhile, the client serves as a distribution node, a UDP synchronization message containing the equipment state and the IP of the distribution node is established, and the UDP synchronization message is sent to the client. The UDP synchronization message is broadcasted to the local area network, other clients in the local area network receive the UDP synchronization message and then verify whether the distribution node IP is the client in the local area network, if the verification is passed, the message is analyzed, the state updating timestamp and the local cache timestamp are compared, and the local state cache and the UI interface are updated only when the state updating timestamp is larger.

The invention discloses a data generation method of a photoetching pattern, an electron beam exposure system, a medium and a product, which are applied to the technical field of photoetching. The method is applied to an electron beam exposure system comprising an upper computer and a lower computer. The method comprises the following steps: receiving first original coordinate data and second original coordinate data of a layout transmitted by the upper computer; performing linear interpolation based on the first original coordinate data and the second original coordinate data to obtain a plurality of pieces of original intermediate coordinate data; respectively mapping the first original coordinate data, the second original coordinate data and each piece of original intermediate coordinate data into first mapping coordinate data, second mapping coordinate data and each piece of mapping intermediate coordinate data of a lower computer; and performing exposure operation based on the first mapping coordinate data, the second mapping coordinate data and the mapping intermediate coordinate data. The data transmission quantity between the upper computer and the lower computer can be reduced, the bandwidth occupation and delay of data transmission are reduced, and the exposure efficiency is improved while the exposure precision is guaranteed.

The invention belongs to the technical field of Internet of Vehicles communication, and discloses a heavy diesel vehicle remote monitoring method and system based on edge computing, and the method comprises the steps: constructing a rule engine according to a predefined transmission rule, and deploying the rule engine to an edge computing node; the data stream of the heavy diesel vehicle is transmitted to an edge computing node, a rule engine is used for evaluating each data field in the data stream, a corresponding transmission level is distributed, and the transmission level comprises a first-level field, a second-level field and a third-level field; and matching a preset transmission strategy according to the data field with the allocated transmission level, executing differentiated data processing, and transmitting a processing result to an enterprise cloud platform through a network transmission layer. According to the method, low-value data is filtered in real time through edge calculation, the invalid data uploading amount is reduced, and data transmission is reduced; in addition, through a high compression ratio and a delay transmission technology, the bandwidth occupation of low-value data is reduced, and the utilization efficiency of network resources is optimized.

The invention discloses a global nerve drawing method and system based on a programmable rasterization engine, and belongs to the technical field of computer graphics, and the method comprises the steps: at the programmable rasterization engine, analyzing a rasterization descriptor according to a rasterization instruction, and extracting vector microoperation and control parameters; maintaining a task state machine according to the parameters and distributing a control signal, selecting an execution entry from a vector kernel table according to the control signal, and instantiating an operation into a parallel vector thread; in a vector thread execution process, tracking data dependence of a vector register and a synchronization state of a direct memory access unit, executing vector loading / storage operation so as to carry data between the register and an on-chip shared memory according to the data dependence and the synchronization state, and dynamically scheduling vector micro-operation to an execution component so as to complete rasterization calculation; and outputting a result to the neural rendering network to complete global neural rendering. According to the method, the multi-representation neural rendering load can be uniformly and efficiently supported on the AI accelerator, the memory access overhead is remarkably reduced, and the calculation efficiency is improved.

The application relates to the technical field of Internet of Things data processing, and discloses a local reasoning and abnormality detection method for a wireless sensor network, which comprises the following steps: constructing a hypergraph model according to a sensor node set in the sensor network and corresponding association relations, and defining an energy function; applying a sensitivity constraint to the potential function, so that the potential function satisfies a bounded difference condition; determining a constraint range of coupling strength and a truncation order m; performing local deterministic approximate reasoning to obtain a conditional edge probability of a target sensor node; calculating an abnormality score of the target sensor node, and performing abnormality detection. In the wireless sensor network, a hypergraph Gibbs model with a sensitivity constraint is constructed, and based on strong spatial mixing ensured by theory, the application realizes the probability reasoning of a deterministic error bound only by relying on a limited-step local communication, so that the explainable abnormality detection and positioning are completed on a resource-limited edge device.

The present application belongs to the technical field of remote control of robots, and particularly relates to a 5G cross-domain low-latency remote control system and method for an explosion-proof humanoid robot. The system comprises a master end teleoperation intelligent cockpit and a slave end remote explosion-proof humanoid robot, and the two are connected through a 5G network for information interaction. The system transmits video streams through H.264 encoding and WebRTC protocol, packs sensor data through JSON, and independently processes information for humanoid control and chassis control. The present application can realize accurate remote force feedback and control, with a humanoid control latency within 100 ms and a chassis control latency within 150 ms, effectively solving the stability and latency problems of remote cross-domain control and ensuring the personal safety of operators in dangerous operating environments.

The application provides a network test transmission optimization method and a test system, and belongs to the technical field of network testing.The network test transmission optimization method of the application transmits only the 4-layer header and load description information, compared with transmitting complete data packets, the data transmission amount of the PCIe bus is greatly reduced, and the bandwidth occupation of the PCIe bus is significantly reduced;the FPGA intelligent network card locally completes load generation, assembly and detection, does not need to rely on the CPU processing of the mainboard, reduces the data interaction delay, and improves the concurrent test capability of the test instrument.

This application relates to the field of natural language processing, and more particularly to a method for ultra-long context tensor parallel incremental attention and differential compression transmission. It employs a multi-level precision sliding window attention mechanism, dynamically allocating precision levels such as fp16 / int8 / int4 based on the distance between the window and the current computation position, and the information entropy of the window content. A tensor parallel incremental attention engine enables cross-GPU / node incremental attention computation and asynchronous All-Reduce synchronization, improving computational efficiency. Semantic differential compression transmission technology is used, transmitting only the differential data based on similarity detection, significantly reducing cross-node transmission overhead. Combined with an extreme performance optimization and security control strategy, a balance between performance and security is achieved through hardware monitoring and dynamic power consumption / frequency adjustment. This invention can significantly reduce memory usage and transmission overhead in ultra-long context processing, improve computational efficiency and hardware utilization, enhance the understanding ability of large models for long texts, adapt to heterogeneous hardware environments, and is suitable for large model inference and training scenarios.

The application discloses a satellite image on-orbit change detection method and device, a storage medium and an electronic device, and relates to the technical field of information. The method comprises the following steps: searching for reference images matched with the to-be-detected images, and performing block processing on the to-be-detected images; extracting multi-scale semantic feature maps of each block image in the plurality of block images and the reference images; determining semantic probability distribution vectors corresponding to each block image and the reference images according to the multi-scale semantic feature maps of each block image and the reference images; determining a change mask corresponding to each block image based on the multi-scale semantic feature maps and the semantic probability distribution vectors corresponding to each block image and the reference images, and simultaneously evaluating the change detection uncertainty of each block image; and based on the change mask and the change detection uncertainty, transmitting part of data under a sparsification back transmission strategy to complete on-orbit change detection. The application can meet the real-time response requirement of satellite image change detection.

The invention discloses a method for realizing a centerless multicast conference, which comprises the following steps: S1, conference members adopt a multicast centerless mode to communicate and join in a centerless multicast conference group; s2, collecting voice data of conference members, performing energy detection, and sending the voice data when a speech is detected; and S3, after receiving the voice data, other conference members decode, cache, mix and play the voice data. According to the invention, the problem of user offline does not exist, and the service is available if the network is available: no conference server exists, so that the conference does not have a control center, and the fault of any member does not affect the group conference; the members can speak and receive voice at any time when the network is connected when entering the conference, the use of other users is not influenced when the network is not connected, and the users can listen to and speak in the conference immediately once the network communication is recovered.

Embodiments of the present application provide a request processing method and device, electronic equipment and computer readable storage medium, and relate to the technical field of computers. The method comprises: determining a response end for responding to the display request according to the number of target electronic labels requested in the display request and / or the estimated response time of the central cloud server responding to the display request; and responding to the display request based on the response end. In this way, the display requirement of the electronic labels in the actual scene and the data processing capability of the central cloud server can be flexibly determined to respond to the display request by the central cloud server and / or the edge cloud server, thereby relieving the processing pressure of the central cloud server, reducing the network bandwidth occupation, and reducing the calculation delay.

The application discloses a kind of multi-modal event primitive extraction, coding and collaborative generation method and system for smart engineering construction scene, the system includes multi-modal data acquisition module, edge preprocessing module, event candidate extraction module, time-space alignment module, subject association module, event primitive coding module, multi-source fusion generation module and primitive output module. Through edge pre-processing, candidate event extraction, time alignment, space mapping, subject association, unified coding and multi-source fusion to video, environmental parameters, device status, positioning information, wearable terminal data and job log data and other multi-modal raw data, generate standardized event primitives, and output to risk identification, knowledge graph and early warning module. The present application can reduce the transmission pressure of raw data, improve the unified semantic expression ability of multi-source heterogeneous data, the fusion accuracy and the subsequent risk analysis efficiency, suitable for hoisting, high altitude, closed space and warehousing logistics and other smart engineering construction scenes.

The invention provides a federated learning-driven cross-mine intelligent risk identification method. Comprising the steps of mine multi-source operation image collection and mine risk event data set construction, mine intelligent risk perception and event recognition model construction, federated learning-based distributed mine risk model training and parameter optimization, model deployment and mine intelligent risk recognition. According to the method, through multi-layer feature coding and cross-scale collaborative modeling, the risk events of the key working area of the mine are accurately positioned and classified, and comprehensive identification of the risk events of the mine can be realized; federated learning and an adaptive sparse parameter communication method are adopted, cross-mine model training can be completed without concentrating original image data, and mine data privacy and distributed training efficiency are guaranteed; meanwhile, the comprehensive risk level of the whole image is generated in real time in combination with multi-event features and a global risk comprehensive evaluation mechanism, a direct quantitative decision basis is provided for mine safety management and instant early warning, and accuracy and operability are improved.

The invention relates to the field of acquisition and transmission data analysis, in particular to an acquisition and transmission data comparative analysis method based on parameter real-time monitoring. The technical problems that in the prior art, most of collected and transmitted data comparative analysis methods depend on manual data analysis, lack intelligent data processing and exception recognition capabilities, lack advanced algorithm support, incomplete data models and limitation of system architecture, and consequently complex data analysis and processing tasks are difficult to complete automatically are solved; according to the technical scheme, the acquisition and transmission data comparative analysis method based on parameter real-time monitoring comprises the steps that a parameter threshold value and a standard range are set, comparative analysis is conducted on real-time data and historical data, and abnormal points and trend changes in the data are recognized; according to the method, the data is sorted and sorted according to the time sequence, the real-time data and the historical data are compared and analyzed, the influence of interference factors on the data is eliminated through an algorithm model, and the identified abnormal data and trend are analyzed to realize automatic analysis of the data.

The invention discloses an unmanned aerial vehicle airborne ground multi-target online positioning method and system and a storage medium, an unmanned aerial vehicle is in communication connection with a vehicle end, the unmanned aerial vehicle carries out preliminary positioning on multiple ground targets and sends a preliminary geographic positioning result of the multiple ground targets to the vehicle end, and the method is executed by the vehicle end. Comprising the following steps: carrying out secondary correction on a ground multi-target preliminary geographic positioning result sent by an unmanned aerial vehicle, and projecting the corrected ground multi-target positioning result to a vehicle BEV space; target risk values of the multiple ground targets are calculated respectively, the multiple ground targets in the first data set are sorted according to the risk values from high to low, and a second data set is obtained; and the data set 2 is used for the vehicle end to carry out multi-target online positioning on the ground. According to the method, the preliminary positioning of the unmanned aerial vehicle is combined with the vehicle end correction, so that the multi-target high-precision online positioning of the road surface is realized, the vehicle end positioning calculation complexity is reduced, and the method has the characteristics of high positioning precision, strong real-time performance and the like.

This invention discloses a data transmission method, system, device, and storage medium for a unidirectional optical gate, relating to the field of data transmission technology. The method includes: a transmitting end acquiring the raw data to be transmitted, extracting the corresponding first integrity check value, performing deep binding and splicing, and generating a combined data stream; the transmitting end performing redundant encoding on the combined data stream and sending it to the receiving end through a physical unidirectional isolation channel; the receiving end using symmetric decoding logic to perform packet loss self-healing calculation, restoring the combined data stream, and disassembling the restored combined data stream to separate the raw data and the corresponding first integrity check value; the receiving end performing a second integrity check on the disassembled raw data locally, comparing the check result with the disassembled first integrity check value, and outputting the raw data when the checks match. The method described in this invention improves data transmission integrity and reliability, enhances system flexibility and ease of use, and optimizes the real-time performance of data transmission.

The present application relates to the technical field of address translation request scheduling, and particularly relates to an address translation request aggregation scheduling method and system. The present application maintains a pending request filter table, each table entry corresponding to a 4KB address range, recording address translation requests that have been sent but have not received responses. When a new request is received, the 4KB base address to which the virtual address belongs is calculated and the filter table is queried: if there is a corresponding table entry, the request is added to the associated waiting queue, and the new request is not sent; if there is no corresponding table entry, the new request is sent and a new table entry is created. Thus, during the waiting response period, subsequent requests in the same address range are aggregated, the number of repeated requests is reduced from N times to 1 time, the root complex load is significantly reduced, redundant transactions are reduced, and the hardware overhead is extremely low.

This invention relates to the fields of medical informatics and data communication technology, specifically a CRRT online acquisition and intelligent monitoring system based on HL7. The system includes: a protocol cleaning and state mapping step: parsing the private protocol binary stream based on a virtual device state machine model to extract the device operating status and monitoring value vectors; a differential semantic analysis step: calculating the rate of change and deviation vector of the monitoring value vector relative to the historical time window; an adaptive message encoding step: selectively generating incremental maintenance messages or full semantic messages based on the comparison results of the rate of change and semantic fluctuation threshold; and a hybrid channel transmission step: dynamically allocating transmission channels and error correction coding strategies according to the message type to execute transmission. This invention solves the transmission contradiction between the real-time nature of high-frequency vital sign data and the redundancy of standardized protocols, balancing standard compatibility and real-time alarm capabilities under limited network conditions.

This invention provides a three-dimensional force data management method and system, relating to the management and communication of three-dimensional force data from tactile sensors. The method quantizes and compresses the X / Y / Z axis amplitudes of each three-dimensional force vector to 10 bits, and separately encodes the X and Y sign bits into 2 bits, forming a compact 32-bit representation of 10+10+10+2 bits. At the transmitting end, continuous three-dimensional force vector arrays are batch-packed into multiple 64-byte communication frames with 32-bit alignment and zero-copy, and then sent. At the receiving end, the three-axis force and direction information is quickly recovered through bitmasking and shifting. Simultaneously, addressing the bus contention problem caused by multiple nodes powering on in parallel, this invention utilizes a unique chip identifier and a hardware counter to generate multi-level random startup delays, enabling staggered initialization and transmission by multiple devices, thereby reducing frame loss and congestion. This invention has the advantages of data compression, fast parsing, low memory and bandwidth consumption, and high stability across multiple nodes, making it suitable for mass production deployment of tactile sensor products using real-time buses such as CAN / CAN-FD.

The application discloses a multi-region power system event-triggered load frequency safety control method and system, and the technical scheme points are as follows: in view of the problem that the existing load frequency control method generally assumes that the communication link is continuously available and is difficult to maintain stable operation under the condition of DoS attack, the system is modeled as a switching system when the DoS attack exists, and the control mode is switched in real time according to whether the link is subjected to the DoS attack: the conventional learning control is executed to optimize the frequency regulation performance when the communication is normal; the anti-attack control mode is switched to when the attack occurs, so that the closed-loop stability can be maintained and the frequency deviation and the tie-line power fluctuation can be inhibited under the condition that the communication is blocked, and the system safety is significantly improved; in addition, based on the RL method, the control strategy is obtained by online learning through interaction with the environment under the condition that the system model is unknown or the parameters are uncertain, so that the control energy minimization and the operation economy are realized without depending on the accurate system dynamics.

The application discloses a kind of distributed concurrent download method, system, electronic equipment and storage medium, it is related to computer technical field, the application will authentication business and file data transmission split, business server only completes user permission verification and the work of the issue of pre-signature list, whole course does not participate in entity file forwarding, can greatly reduce server bandwidth occupancy and power consumption;Through front-end loading webpage assembly binary module to form sandbox running instance, use concurrent download coroutine to bypass business server and directly interface cloud storage edge node fragment to obtain data, overcome the concurrent performance short board brought by traditional front-end single-thread operation, improve the speed of fragment download;While data is written into local disk, not in sandbox memory and browser buffer stores fragment data, avoid out-of-order fragment accumulation to occupy memory, effectively eliminate the memory crash hidden danger in the process of large file download, on the basis of optimizing server resource overhead, improve client download stability and transmission efficiency.

The invention relates to an intelligent pressure bra and a control method thereof. Comprising a bra main body, a pressure sensing module, a posture sensing module, a pressure adjusting module and a central control module, the pressure sensing module, the posture sensing module and the pressure adjusting module are fixedly connected to the bra main body; the pressure sensing module is used for collecting original chest pressure signals of a patient; the posture sensing module is used for collecting an original posture signal of a patient; the pressure adjusting module and the pressure sensing module are correspondingly arranged; the central control module is connected with the pressure sensing module, the posture sensing module and the pressure adjusting module and used for processing data, communicating with remote terminal equipment and controlling the pressure adjusting module. Compared with the prior art, the method has the advantages that real-time closed-loop adjustment is realized; the compression strategy is dynamically optimized in combination with the posture of the patient, and the safety and accuracy of postoperative rehabilitation are improved.

This invention discloses a computing power optimization method based on an industrial control gateway, characterized by the following steps: collecting computing power index data of each node through the industrial control gateway and calculating the comprehensive computing power score of each node; setting the number of grids and setting the upper limit of the total comprehensive computing power score for each grid; dividing all nodes into corresponding grids using the K-means algorithm; calculating the comprehensive performance evaluation value of each grid based on the computing task completion time, resource utilization, and communication latency; allocating computing tasks to the grid with the lowest comprehensive performance evaluation value; and executing computing tasks through the nodes in the grid. This invention, through grid partitioning, achieves refined management of computing resources and a high degree of matching between computing task execution and performance, improving production efficiency and reducing operation and maintenance costs.

This invention relates to the field of cloud-edge collaboration technology, specifically disclosing a scene-adaptive urban management platform based on cloud-edge collaboration, comprising: an image acquisition module: commanding a drone to fly along a preset route and capture images along the way, preprocessing and recognizing the video stream data, and extracting keyframes; a keyframe cropping module: acquiring the three primary color values ​​of pixels, marking target pixels based on the three primary color channels, constructing a planar coordinate system, and cropping frames based on the maximum and minimum values ​​of the horizontal and vertical coordinates; and an analysis and processing module: dividing the cropped frames into groups, acquiring the maximum proportion of cropped frames in the same group, determining the target event corresponding to the urban management problem, and distributing the data to various drone terminals. By lightweighting the data, the bandwidth pressure during upload is reduced, transmission resources are saved, the efficiency from problem discovery to handling is improved, management resources are targeted, and the transformation of urban management from passive response to proactive prediction is supported.

The application discloses a kind of based on digital ray technology's transmission line strain clamp nondestructive testing method, it is related to transmission line strain clamp detection field, method includes: collection strain clamp radiographic image and geometric dimension, stress and so on multidimensional parameter, data fusion is carried out by hypergraph structure, multidimensional heterogeneous strain clamp analysis model is calculated and analyzed in edge side using optimized hypergraph neural network and edge computing gateway, to visualize presentation detection result in the form of double screen linkage, while realizing intelligent diagnosis and defect early warning;The application provides an efficient, accurate and reliable solution for the intelligent operation and maintenance of transmission line strain clamp, effectively improves the safe operation level and operation and maintenance efficiency of power grid.

The application provides an end-cloud cooperative target perception method and system and a storage medium. The method comprises: obtaining video data to be processed and task semantic information under a target monitoring task on an end-side device; generating a target attention heat map of each video frame to be processed based on the task semantic information; determining a set of attention regions of each video frame to be processed based on the target attention heat map of each video frame to be processed; determining a set of key frames from the video data to be processed based on the set of attention regions of each video frame to be processed; determining a cloud-side data packet to be processed based on the attention region indication data of each key frame in the set of key frames; uploading the cloud-side data packet to be processed to the cloud side to perform target perception based on the cloud-side data packet to be processed on the cloud side, and obtaining a target attention region perception result. The embodiment of the application can improve the accuracy of target perception while ensuring low latency.

This invention relates to the field of power system distribution network operation monitoring technology, and discloses a method and system for predicting electricity meter faults based on edge computing. The method includes: an end node receiving a reverse intervention token issued by an edge gateway, performing phase-locked loop secondary capture based on environmental verification, acquiring a micro-window data sequence and performing dimensionality reduction and compression, and reporting supplementary message frames; the edge gateway retrieving and matching suspended deterministic finite state automata instances, injecting the decoded character sequence into ambiguous intermediate state nodes to continue state transition; evaluating the final state set of the finally residing state node to output closed-loop control commands; and using historical decision records to train the model through a lightweight temporal convolutional network, dynamically correcting the state transition rules. This invention solves the technical problems of easy stagnation in state transitions and false alarms under complex load environments, and realizes end-edge collaborative breakpoint continuation deduction and closed-loop iteration of state transition rules.

This disclosure provides a data transmission method and an on-chip network system applied to PCIe point-to-point communication. The on-chip network includes a requesting node and a home node. The method includes: the requesting node sending a write request to the home node, the write request containing indication information indicating the total amount of write data corresponding to this data transmission; the home node returning at least one write request receive response message to the requesting node based on the current receiving resource status, the write request receive response message indicating the amount of data allowed to be sent by the home node; and the requesting node sending corresponding write data to the home node based on the received write request receive response message and the amount of data allowed to be sent by the home node. This disclosure avoids breaking down a large data transmission task into multiple independent small write requests for separate sending, thereby significantly reducing the number of request messages generated in the on-chip network and reducing bandwidth consumption for requests.