117results about How to "Reduce transfer volume" patented technology

The invention discloses an intelligent advertisement putting processing method and system based on user data, and relates to the technical field of data processing, and the method comprises the steps: putting an advertisement in an advertisement pool based on an edge device, collecting the video information during the advertisement playing period through the edge device, analyzing the stored video information, extracting the user feature information, and storing the user feature information in the advertisement pool; the user feature information is integrated into user feature vectors, the user feature vectors stored in the edge devices are uploaded to the cloud platform, the cloud platform analyzes the user feature vectors uploaded by the edge devices to generate user portrait information, and the user portrait information is displayed on the basis of the user portrait information generated by the cloud platform. And putting corresponding advertisements to the user groups with similar user portrait information, collecting feedback data, and dynamically optimizing the advertisements put by the edge devices and the user groups based on the feedback data. The method has the advantages that the data transmission delay and the cloud computing pressure are reduced through the cloud edge collaboration method.

The invention relates to the technical field of sensor upgrading, in particular to a remote upgrading method and system for a tire pressure sensor. The method comprises the following steps: acquiring real-time state data of a tire pressure sensor; carrying out outlier parameter elimination on the real-time state data of the tire pressure sensor, and carrying out state diagnosis mining, so as to generate a state diagnosis report of the tire pressure sensor; performing upgrade demand prediction based on the tire pressure sensor state diagnosis report, and performing priority upgrade analysis to extract a plurality of upgradable sensors; performing byte-by-byte difference identification on the plurality of upgradable sensors based on preset latest version information, and performing incremental data encapsulation to generate a plurality of incremental upgrading data blocks; acquiring a historical running log of the vehicle; performing dynamic vehicle using behavior analysis and vehicle idle time period prediction on the vehicle historical operation log to generate a plurality of idle prediction time periods; the upgrading efficiency and the safety performance of the tire pressure sensor are improved.

The invention discloses a loom data monitoring method and system, computer equipment and a storage medium. The method comprises the following steps of S10, collecting operation data of a loom through a distributed sensor network; s20, optimizing the operation data of the weaving machine by utilizing edge computing equipment to obtain optimized operation data of the weaving machine; s30, the edge computing device transmits the optimized operation data of the weaving machine to a cloud server; s40, the cloud server analyzes the optimized operation data of the weaving machine based on a weaving machine operation state evaluation model to obtain an operation state evaluation result of the weaving machine; and S50, the cloud server performs predictive maintenance on the weaving machine based on the operation state evaluation result of the weaving machine. The technical problems of poor real-time performance, low maintenance efficiency and weak prediction performance of loom monitoring in the prior art can be solved.

The invention provides a digital office data synchronization and sharing method and system based on cloud computing, and relates to the technical field of cloud computing, and the method comprises the steps: building a distributed data synchronization system on a cloud computing platform, and detecting the change of digital office data on each terminal device through a real-time monitoring mechanism; when data change is detected, triggering an incremental synchronization algorithm, and only synchronizing the changed data part; historical version information of each data change is recorded by using a block chain-based distributed account book technology, and data version tracking and backtracking are realized; constructing a role-based access control system, and allocating data access permissions to different users; a real-time collaborative editing function is realized, and multiple users are allowed to edit the same digital office data at the same time; establishing a data sharing log system, and recording data access and operation behaviors of each user; and a machine learning algorithm is utilized to analyze a user behavior mode, and related digital office data is automatically recommended.

The invention provides a universal audio quality analysis method and system, and belongs to the technical field of audio, and the method comprises the steps: determining a standard audio quality index corresponding to a target scene; feature extraction is carried out on the target audio, multiple pieces of audio feature data are obtained, and the target audio is the audio in the target scene; and determining a target repair mode corresponding to the target scene based on the standard audio quality index and the multiple pieces of audio feature data, and repairing the to-be-transmitted audio based on the target repair mode. According to the universal audio quality analysis method and system provided by the invention, the accuracy of audio quality analysis can be improved.

The invention relates to an incremental data synchronization method based on primary key combination. The method comprises the steps that a mapping relation is established, keys of the mapping relation are formed by combining table names and main key values, and the values of the mapping relation are corresponding DML records; dML records are collected from the source library, whether main keys of the DML records exist in the mapping or not is checked, and if not, the DML records are directly added into the mapping; if yes, taking out the record of the same primary key from the mapping as an original record, and taking the DML record as a new record; if the type of the DML record is deelete, adding the original record and the new record into a sending queue; if the record is update, the original record and the new record are merged; if so, adding the original record into a sending queue, and adding the new record into mapping; and when the transaction is submitted, traversing all residual DML records in the mapping, writing the DML records into a sending queue, and sending the DML records to a downstream system for processing. According to the method, by optimizing the processing flow of the DML records related to incremental migration, rapid merging and efficient synchronization of incremental data are achieved, and the efficiency and accuracy of data synchronization are improved.

The invention provides a video coding method and device, electronic equipment, a chip and a medium, and relates to the field of video coding, and the method comprises the steps: determining a plurality of initial regions in each frame of picture for a plurality of frames of pictures in an original video; determining the change rate of each initial region based on the pixel points in the plurality of initial regions; determining at least one coding region and a coding strategy corresponding to each coding region based on the change rate; and performing video coding on each coding region by using the coding region corresponding to each coding region to obtain target data. According to the coding method provided by the invention, the change frequencies of different regions are identified, the regions needing to be coded are determined, and different coding modes are adopted according to the change frequencies of the coding regions, so that efficient and flexible dynamic regional coding is realized, the coding efficiency is improved, the calculation amount and the transmission amount are reduced, and the network bandwidth requirement is reduced.

The invention discloses a cross-platform file incremental synchronization method, a computer device, a medium and a product. The method comprises the following steps: monitoring a determined to-be-monitored file in real time, obtaining file change information, dynamically obtaining a target coding algorithm and a target compression ratio, processing the file change information, obtaining intermediate file information, distributing a unique identifier and unique verification information for the intermediate file information, and obtaining target file data; detecting and acquiring a plurality of target network paths; and according to the network delay information, the bandwidth information and the reliability information, determining an optimal transmission path in the plurality of target network paths, and then transmitting the target file data on the path. The method is suitable for different operating systems and platforms, the optimal network path can be detected and selected for file transmission, and it is ensured that cross-platform file synchronization can be efficiently, stably and safely carried out under different network conditions.

The invention discloses a block chain node consensus method and system based on block chain fragments, and the method comprises the steps: enabling a block chain node added into a committee fragment to be called as a committee node, collecting transaction data through the committee node, and carrying out the Hash processing of the transaction data, and obtaining a Hash value; the committee node configures itself to a committee Merkel tree according to the Hash value; the committee Merkel tree is realized by adopting an improved Merkel compressed prefix tree structure; meanwhile, the block chain node added into the global fragment is called as a global node, and the global node receives the root hash of each committee fragment; configuring the global node into a global Merkel tree according to the root hash; the global Merkel tree is also realized by adopting an improved Merkel compressed prefix tree structure; consensus operation is completed on the committee nodes of the committee fragments; and completing a consensus operation on the global node of the global fragment.

The invention provides an asynchronous federal learning system and method for a turnout switch machine fault diagnosis model. The system comprises the following steps: acquiring mechanical vibration signals at three positions of a speed reducer shell, a contact seat and an actuating rod of a switch machine by using a mechanical vibration sensor; information fusion of the vibration signals of the three point locations is carried out; a lightweight dual-scale neural network model; an asynchronous federated learning process resistant to time delay and packet loss; and an asynchronous federated learning system structure. An asynchronous federal learning process resistant to time delay and packet loss is adopted, communication delay and the remaining receiving time of single uploading of an edge computing unit are fully utilized, and the extra computing time for fusion after all units are uploaded is shortened; the asynchronous federated learning system structure clarifies the hierarchical relationship and specification of federated learning of point switch fault diagnosis in a railway system. Distributed training of the switch machine fault diagnosis model is realized, and reliable guarantee is provided for railway transportation safety.

The invention discloses a road detection system and method based on an expressway intelligent gateway system, and relates to the technical field of intelligent traffic control, and the system comprises a road detection module and the expressway intelligent gateway system. Wherein the road detection module is used for executing a road information detection task of an expressway; the expressway intelligent gateway system is used for carrying out dynamic resource configuration on a road information detection task; the resource allocation unit is used for allocating first edge end resources of a plurality of network edge nodes to the simple charging task in real time; determining a first complex charging task from the complex charging tasks according to the allocation condition of the first side end resources, and allocating second side end resources of a plurality of network edge nodes to the first complex charging task in real time; a second complex charging task except the first complex charging task in the complex charging tasks is sent to the cloud module; and the cloud module is used for allocating cloud resources to the second complex charging task in real time to obtain a third processing result.

The invention discloses a holder control method and device, a storage medium and electronic equipment. The method comprises the following steps: in response to a cradle head control start instruction, controlling a cradle head to execute a target action corresponding to the cradle head control start instruction, and obtaining a time delay and a frame rate corresponding to the cradle head, the cradle head control start instruction is sent by a target terminal, and the time delay represents a transmission time delay between the target terminal and the cradle head; the frame rate represents the frame rate used by the holder to transmit data; and determining the number of target frames based on the number of frames which are sent to the target terminal by the cradle head and are not determined to be received by the target terminal, the time delay and the frame rate, clearing non-key frame data corresponding to the number of the target frames in the first cache data, and controlling the cradle head to stop executing a target action in response to a cradle head control ending instruction. The technical problems that a holder and a video picture are not synchronous enough and the video picture is delayed in the prior art are solved.

The invention discloses a face image data distributed storage method, belongs to the field of artificial intelligence, and aims to realize accurate identity verification and state monitoring of a driver by capturing and processing a face image of the driver in real time in a distributed manner. The method comprises the following steps: capturing a driver face image in real time through front-end acquisition equipment; an edge computing node is used for judging the illumination condition of the captured face image, dynamic normalization processing is carried out according to the illumination condition, adaptive graying is carried out on the face image based on the illumination condition, the processed face image is uploaded to a data center after zooming and cutting, then feature extraction is carried out, and a feature set is constructed; performing primary processing based on the feature set, and then creating redundant backup and establishing an index in a data center through distributed storage; and the personalized processing unit compares the current driver feature set with the feature set stored in the data center, and judges whether the face image of the driver is matched so as to determine the control authority of the vehicle.

The invention relates to the technical field of AI big data processing, and discloses an AI big data real-time processing and analysis method, which comprises the following steps: step 1, data acquisition and preprocessing; step 2, feature extraction and intelligent adaptation; step 3, feature association and data screening; step 4, data analysis; 5, system architecture and technical support; and step 6, edge calculation support. For different types of data, such as images, texts, sensor data and the like, the edge device firstly performs standardization processing, converts the data into a general format, facilitates subsequent unified processing, converts the images into a specific resolution or color format, and converts the texts into a unified coding format; and the sensor data is converted into a specific data unit or range, so that the beneficial effect of uniformly processing different data types to improve the data processing efficiency is achieved.

The invention provides a power distribution network grounding fault line selection method based on characteristic frequency band optimization, and the method comprises the following steps: obtaining a transient zero sequence signal of each line, the transient zero sequence signal comprising a normalized transient zero sequence current and a transient zero sequence voltage derivative; decomposing the transient zero-sequence signal by adopting a wavelet packet transformation method; a historical data set is constructed, and frequency bands capable of effectively representing fault features in the historical data set are extracted in an off-line self-adaptive mode through a genetic algorithm; collecting data after the fault, and analyzing and extracting a characteristic frequency band in the fault data by utilizing wavelet packet energy entropy; performing intersection extraction processing on the characteristic frequency bands extracted by the genetic algorithm and the wavelet packet energy entropy to obtain a final optimized characteristic frequency band result; and for a real-time fault, carrying out fault research and judgment by utilizing the transient zero-sequence signal in the optimal characteristic frequency band. According to the invention, waveform data collected by all detection nodes does not need to be uploaded to a power distribution master station, and the position of the single-phase earth fault can be researched and judged on site.

The invention discloses a modular multilevel converter valve control device and a wave recording method thereof, which are suitable for various modular multilevel converter valve control devices. The integrated wave recording function of the valve control device plays an important role in observing the operation state of the converter and analyzing the fault transient process of the sub-module. The valve control device is a core control device of the whole valve control system and interactively communicates with each sub-module. The sub-modules upload capacitor voltage, IGBT switching state and fault information to the valve control device, the valve control device needs to gather mass data sent by the sub-modules, and the original recording data is gathered through the programmable logic array FPGA, so that the processing time consumption of the control CPU is effectively reduced, and the output data transmission quantity of the control CPU is reduced. The wave recording method for the modular multilevel converter valve control device has the advantages of being universal in architecture, flexible in configuration, convenient to transplant and the like, and can be suitable for various modular multilevel converter valve control systems.

The invention relates to a narrow-band system differential upgrading method of a wide-narrow band fusion terminal. When version upgrading is needed, the wide-narrow band fusion terminal firstly reports an original narrow-band system version number to the upgrading management server, the upgrading management server finds a target software version, the original narrow-band system version and the target software version are compared, and a differential upgrading package is made; and the differential upgrade package is sent to a broadband system in the broadband and narrowband fusion terminal, the broadband system sends the differential upgrade package to a narrowband system, and the narrowband system carries out an upgrade process. According to the method, differential upgrade package transmission optimization is used, only the part needing to be upgraded is transmitted, the data transmission amount is reduced, and the transmission efficiency is improved; the upgrade management server monitors the upgrade process in real time and provides a feedback mechanism to ensure smooth upgrade; and the broadband system and the upgrade management server are connected through a 5G / WIFI network, and the broadband system and the narrowband system are connected through a UART, so that the stability of data transmission is ensured.

The invention relates to the technical field of tunnel deformation monitoring, in particular to a tunnel primary support surrounding rock deformation monitoring system and method, and the method comprises the steps: data collection, data transmission, data preprocessing, model training and verification, real-time analysis, feature extraction and early warning and response. Data acquisition equipment and an edge server are installed and deployed on the inner side wall of tunnel primary support surrounding rock, the data acquisition equipment acquires original data, it is ensured that data coverage is comprehensive and not excessive redundancy exists, the original data are timely transmitted to the edge server in a wireless mode of the low-delay Internet of Things, the data transmission process is combined with an MQTT protocol, and the data transmission efficiency is improved. The method comprises the following steps: preprocessing data, selecting a trained convolutional neural network model CNN, carrying out online analysis on the data transmitted in real time, predicting the deformation trend of the tunnel primary support surrounding rock, and immediately sending an early warning to a monitoring and early warning module when the deformation trend exceeds a set deformation threshold value, so that the system can monitor the deformation of the tunnel primary support surrounding rock in real time and ensure the accuracy and reliability of the data.

The invention discloses a satellite remote sensing image transmission and storage method and system for tobacco planting analysis, and relates to the technical field of image data processing. Comprising the following steps: identifying and marking abnormal images in multiple frames of collected tobacco satellite remote sensing images, and performing fuzzy processing on all images except the abnormal images in the tobacco satellite remote sensing images; according to the method, the abnormal images such as the vegetation density, the growth state and the lesion position in the tobacco satellite remote sensing image are identified and marked, and then the abnormal images are taken as boundaries to perform fuzzy processing on the non-abnormal image segments in the tobacco satellite remote sensing image, so that key details are prevented from being lost, and the accuracy of the tobacco satellite remote sensing image is improved. The transmission quantity of redundant data of the tobacco satellite remote sensing image is reduced, so that the subsequent processing of the tobacco satellite remote sensing image can be analyzed based on the abnormal image, the subsequent analysis speed of the tobacco satellite remote sensing image is improved to a certain extent, and the analysis and processing accuracy of the subsequent tobacco satellite remote sensing image is improved.

The invention relates to the technical field of remote sensing image on-orbit real-time processing, in particular to a low-redundancy-rate image segmentation method and system based on an FPGA, and the method comprises the steps: determining the maximum physical size of a target object; calculating a first maximum pixel value occupied by the target type object in the remote sensing image according to the maximum physical size of the target type object; performing correction calculation on the maximum physical size according to the side-sway angle during satellite imaging to obtain the maximum physical size of the target object after side-sway distortion is considered; calculating a second maximum pixel value occupied by the target type object in the remote sensing image according to the maximum physical size of the target type object after side-sway distortion is considered; taking the maximum value from the first maximum pixel value and the second maximum pixel value as an overlapping region setting value; setting an overlapping region setting value as a sliding window segmentation step length; and carrying out sliding window segmentation on the segmented sub-graphs according to the sliding window segmentation step length. According to the method and the device, the minimization of the overlapped region of the segmented sub-images is realized, the segmentation redundancy rate is reduced, and the data storage and transmission quantity is reduced.

The invention discloses a processing method and system for power supply data transmission of an electric power system, relates to the technical field of data transmission, and solves the technical problems of transmission resource waste and low efficiency caused by the fact that a processing mode for repeated data is relatively single and data characteristics cannot be fully utilized for compression transmission. The packet loss rate in the network environment is monitored in real time, when the packet loss rate exceeds a normal value, the environment switching information can be generated in time, a user is prompted to switch to a more suitable network environment, reliable transmission of power supply data is ensured, repeated data in the parallel transmission process is analyzed and processed, and the data transmission efficiency is improved. According to the method, data transmission and transfer are reasonably performed according to the type of the repeated data and the transmission rate of the transmission channel, the data is further compressed and transmitted under the condition that transmission and transfer cannot be performed, and the processing mode for the repeated data not only reduces the data transmission quantity, but also improves the transmission efficiency and the resource utilization rate.

The invention provides a real-time monitoring device and monitoring method for partial discharge ultrasonic signals of power equipment, and relates to the technical field of power equipment monitoring. The real-time monitoring device for the partial discharge ultrasonic signal of the power equipment comprises a distributed monitoring system based on a block chain, intelligent monitoring based on edge computing, a positioning module based on an acoustic phased array, an environment monitoring module, a safety and protection module and a power management module. The integrity and security of partial discharge ultrasonic signal data are ensured and the data are prevented from being tampered or lost by using the decentralization and tampering-free characteristics of the block chain, the monitoring data are stored on a plurality of nodes in a distributed manner, the single-point fault is avoided, the reliability and fault tolerance of the data are improved, all data operations are recorded on the block chain, and the data operation efficiency is improved. The transparency and traceability of data are ensured, auditing and fault traceability are facilitated, real-time data processing and analysis are performed near a data source based on intelligent monitoring of edge calculation, and data transmission delay is reduced.

The invention relates to the technical field of over-the-horizon remote control mobile robots, in particular to an over-the-horizon remote control mobile robot low-delay double-view-angle control system and method, and the system comprises a mobile robot end and a remote control end, and the mobile robot end comprises a fisheye lens group and an image fusion processing module; the fisheye lens group captures a 360-degree panoramic image, the image fusion processing module preprocesses image data, generates a panoramic video stream in real time through an image fusion algorithm, and transmits the panoramic video stream to the remote control end through the communication module; and the remote control end performs selective double-view-angle display, and adjusts the observation view angle in real time based on the head action of the user or a manual instruction. The data transmission quantity is reduced, the video quality is ensured, the transmission efficiency is improved, the stable transmission of the panoramic video stream is ensured, the delay and packet loss phenomena are reduced, the time delay problem is solved, and the real-time performance and comfort of control are better.

The invention discloses a remote management method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the following steps: acquiring real-time bandwidth information of the server; determining a compression strategy for the to-be-transmitted data according to the format of the to-be-transmitted data, and compressing the to-be-transmitted data by using the compression strategy to obtain compressed data; performing differential analysis on the compressed data and the transmitted data, and screening out incremental data from the compressed data according to the difference between the compressed data and the transmitted data; determining the transmission frequency of the data to be transmitted according to the real-time bandwidth information and the type of the data to be transmitted; and sending the incremental data corresponding to the to-be-transmitted data to a client according to the transmission frequency, so that the client remotely manages the server. The data transmission quantity can be reduced, the bandwidth occupation is reduced, the remote management real-time performance is improved, and the system resource consumption is optimized.

The invention relates to the technical field of big data processing, and discloses a cloud computing and edge computing-based big data co-processing method and a cloud server, which are applied to a co-processing system consisting of an edge node cluster and the cloud server. And obtaining target data through a preprocessing strategy consisting of data filtering, format conversion, increment extraction and lightweight compression. According to the method, the compression ratio larger than or equal to 62% is achieved in combination with the improved LZ4 algorithm, only differential data with service value is transmitted, the invalid data transmission amount is greatly reduced, and the network bandwidth occupation pressure is remarkably reduced; and a dynamic task scheduling link, which is fused with a genetic-reinforcement learning hybrid algorithm of bidirectional LSTM load prediction, can accurately predict edge node computing power fluctuation, dynamically divide task types, match optimal processing nodes, control real-time task response delay within a reasonable range, and realize maximization of computing power resource utilization rate at the same time.

The invention relates to the technical field of data transmission, and discloses a data transmission method, a robot and a storage medium. The method comprises the steps of obtaining first health data; preprocessing the first health data to obtain second health data; the second health data are dynamically marked, the priority of the second health data is determined, third health data are obtained, and the third health data comprise the data type and the data priority; sorting the third health data according to the data priority, and packaging the sorted third health data to obtain fourth health data; performing grading processing on the fourth health data to obtain target health data; and uploading the target health data. In this way, the data processing and reporting efficiency is improved.

The embodiment of the invention discloses a data backup method and device, equipment and a storage medium, which are applied to a data backup system comprising a plurality of source ends and a backup end, and comprise the following steps: segmenting a target data stream into a plurality of target data blocks, and determining a target hash index value corresponding to each target data block; querying each target hash index value in a target source end hash index database matched with the target data stream in the target source end; if the first type of target Hash index values are stored in the target source end Hash index database, only sending the first type of target Hash index values to a standby end; if the second type of target Hash index values are not stored in the target source end Hash index database, querying each second type of target Hash index value in a standby end Hash index database in a standby end, and selecting only the second type of target Hash index values according to a query result; or the second type of target hash index values and the matched target data blocks are sent to the standby end, so that the data backup efficiency is improved.

The invention discloses a battery energy storage system and a remote upgrading method of the battery energy storage system. The upgrading method comprises the following steps: a WiFi module broadcasts and issues a CODE array to a centralized master control BCCU and each slave master control BCU, and the centralized master control BCCU and each slave master control BCU respond and confirm one by one in sequence in a token relay mode according to preset parameters; and the centralized master control BCCU successfully confirms that the sequence is detained at the last, expresses that all master control responses are finished, and uploads a confirmation response to the WiFi module. According to the remote upgrading method, the upgrading time is shortened, and the code transmission quantity is reduced. The semi-broadcast upgrading method provided by the invention is not only suitable for a multi-battery-cluster high-voltage parallel energy storage system, but also suitable for a low-voltage parallel energy storage system, and is more suitable for a system with a three-level architecture of an M-BMS, a C-BMS and an A-BMS.

The invention discloses a cloud edge hierarchical collaborative information system integrated resource scheduling system. The system comprises an acquisition module. Data preliminary cleaning and feature extraction are locally executed through the edge end, only key feature data are uploaded, network transmission quantity is reduced, cloud computing pressure is relieved, real-time tasks can respond quickly, task timeout caused by transmission delay is avoided, feature vectors of the edge end and the cloud end are dynamically analyzed based on a scheduling decision model of reinforcement learning, and the real-time performance of the edge end is improved. Task requirements and resource states are intelligently matched, the scheduling accuracy is improved, model parameters are dynamically updated through task execution state data (such as duration and resource utilization rate deviation), the model is adaptively optimized along with environment changes (such as edge end hardware aging and cloud load fluctuation), the efficient scheduling capacity is kept for a long time, and the scheduling efficiency is improved. Layered processing and intelligent scheduling avoid edge end overload or cloud end resource idling, resource allocation of a CPU, a memory and the like is optimized, resource waste is reduced, and the system collaboration efficiency is integrally improved.

The utility model relates to remote monitoring control technical field discloses a kind of remote monitoring control device for EIGA equipment, including total data processing mechanism, the end of total data processing mechanism is provided with probe mechanism, the probe mechanism includes frame component, the surface of frame component is connected with the end of total data processing mechanism, the inside of frame component is provided with self-cleaning component, the self-cleaning component includes outer extension cylinder, the surface of outer extension cylinder is provided with air hole, the inner wall of air hole is fixedly connected with dust baffle, the outer surface of outer extension cylinder is fixedly connected with helical rib, the inner wall of outer extension cylinder is rotatably connected with baffle. In the utility model, self-cleaning design reduces the interference of dust to monitoring, without disassembly cleaning, the layout of multiple probe multiple type monitoring element realizes multi-region multidimensional synchronous monitoring, hierarchical data processing and transmission mode according to demand networking, reduce data transmission volume and total control operation pressure.