57 results about "Cloud data management" patented technology

The invention discloses an artificial intelligence self-adaptive education system based on big data, and relates to the field of intelligent education, the artificial intelligence self-adaptive education system comprises an education resource management module, a student data management module, a self-adaptive learning recommendation module, an auxiliary teaching decision module and a security reinforcement module, and a cloud data management library is used for classifying and integrating education resources. The method comprises the steps of establishing a knowledge graph, performing knowledge point classification on resources by constructing the knowledge graph, performing accurate matching on personal portraits of students and the knowledge graph through an incremental self-adaptive matching model, dynamically adjusting recommended learning resources in real time, analyzing collective learning problems through a big data intelligent analysis model, and generating collective teaching suggestions. A three-layer security firewall is adopted to ensure the security of the system; the problem that an existing self-adaptive education system neglects the learning progress and weak links of classes or groups is solved, and intelligent management, personalized learning recommendation and collective problem analysis of education resources can be achieved.

The invention relates to shipbuilding flatness inspection equipment and a use method thereof, and belongs to the technical field of shipbuilding flatness inspection. The shipbuilding flatness inspection equipment comprises a magnetic adsorption type mobile robot platform, a high-precision vision module, an edge computing unit and a cloud data management platform; the magnetic adsorption type mobile robot platform is provided with a crawler-type walking mechanism and a self-adaptive vacuum adsorption unit. According to the invention, efficient and high-precision whole ship flatness intelligent detection can be realized through multi-sensor fusion and a self-adaptive robot platform, the system is suitable for real-time quality monitoring in ship body section construction, deck assembly and fitting-out stages, local fine scanning can be executed along a welding seam area in a ship body section detection scene, and the detection accuracy is improved. A welding deformation out-of-tolerance area is synchronously marked, a non-key plane area can be switched to a global rapid scanning mode, and in the deck assembly stage, a cloud platform can integrate data in real time and assist in carrying out an assembly dislocation correction scheme.

The invention discloses a road guardrail real-time monitoring device and system based on wireless networking, and relates to the technical field of road facility monitoring, the road guardrail real-time monitoring device comprises a cloud data management platform, the cloud data management platform is in communication connection with a guardrail monitoring node module, an edge computing gateway module, an abnormal state alarm module and an operation and maintenance management module, the modules are in electric signal connection; the guardrail monitoring node module is used for planning monitoring nodes in an area to be monitored and deploying guardrail monitors at the monitoring nodes so as to acquire guardrail state data of the monitoring nodes in real time. Through the wireless networking technology, the road guardrail state is monitored in real time, and tiny deformation, abnormal vibration and inclination angle change of the guardrail can be captured in time, so that the real-time performance and accuracy of traffic safety monitoring are improved, and compared with traditional passive inspection, the active sensing mode has the advantages that the traffic safety is improved, and the traffic safety is improved. The labor cost and the leak detection risk are greatly reduced, and a powerful guarantee is provided for road traffic safety.

The invention discloses a new energy automobile charging detection system, and relates to the field of new energy automobiles, and the system comprises a battery state monitoring module which is used for collecting and analyzing the health condition, residual capacity and chargeable quantity parameters of a battery in real time. The system has the beneficial effects that the charging strategy is modulated in real time through the battery state monitoring module and the intelligent charging control module, the charging efficiency is high, and the damage to the service life of the battery is reduced; a safety protection module is arranged, the states of the battery pack and the charging system are monitored in real time, response to abnormal conditions such as short circuit, over-temperature and over-current is fast, and potential safety hazards are reduced; the user interaction module is arranged, the user interactivity is high, and a user can know the charging state and the battery health condition in real time and flexibly adjust charging setting according to requirements; and a cloud data management module is arranged to deeply analyze the charging data, so that decision support is provided, and remote data access and sharing are realized.

The invention discloses a hotel intelligent registration system, which comprises a user mobile terminal, a self-service terminal, a cloud data management system, a data analysis module and an intelligent customer service robot, the application of the self-service terminal and the mobile terminal reduces manual operation links, and improves the handling speed of registration, check-out and other procedures; a CRM module is integrated, customer information and interaction history are managed, personalized customer care and promotion activities can be provided, and customer loyalty and satisfaction are increased; the descriptive analysis provides basic operation data statistics, the diagnostic analysis identifies potential problems, the predictive analysis predicts market trends and the like, managers are helped to comprehensively understand hotel operation conditions, the intelligent customer service robot can solve common problems, the common problems are automatically processed in peak periods, the manual customer service pressure is relieved, and the customer service efficiency is improved. Complex problems are intelligently routed to manual customer service, and customer satisfaction is guaranteed; the international customer service experience is improved through multi-language support; customer consultation and feedback are received, and continuous service improvement is facilitated.

The present invention provides a photovoltaic power generation data acquisition system and method; the data acquisition system includes a photovoltaic power generation unit, a photovoltaic power generation data acquisition unit, a central data processing terminal, a cloud change operation unit, a malicious tampering identification unit, a cloud data storage repository, a power generation power prediction unit, a power quantity centralized scheduling unit, a scheduling task adjustment unit, and a power generation anomaly monitoring unit; by adding the cloud change operation unit, the present invention realizes cloud data management and processing of the power generation data stored in the photovoltaic power generation, and improves the management security and efficiency through identity verification processing before management. By adding the scheduling task adjustment unit, the present invention realizes the distribution processing of the power quantity of the photovoltaic power generation to substations at various locations, and adaptively changes the power distribution values of each substation.

A method for data management is described. The method may include generating a first snapshot of a first state of a data object, generating, using metadata associated with the first snapshot of the first state, a first hash value, and storing the first hash value to a blockchain. If the data object or device or system supporting the data object fails, then a failover procedure may be used to recover the data object. The method may include receiving an instruction to recover the first state of the data object using the first snapshot, retrieving the first hash value from the blockchain, comparing the first hash value retrieved from the blockchain to a second hash value of the metadata associated with the first snapshot, and determining, based at least in part on a result of the comparing, whether the first snapshot stored in the data management system is unmodified.

The present invention belongs to the field of cloud-edge-end Internet of Things application technology, and in particular, relates to a cloud-edge-end collaborative Internet of Things management and scheduling system and a data interaction method. It includes a cloud service layer and an edge information layer; the cloud service layer is composed of a cloud tag service component, a cloud data management component, and a cloud resource scheduling component; the edge information layer includes multiple edge service terminals, and the edge service terminals are composed of an edge resource service component, an edge tag service component, a data sharing component, and an edge data management component; based on the current cloud-edge-end Internet of Things structure, this application provides a method for reducing the pressure of cloud data storage and transmission, optimizing data transmission delay, and through data distributed storage and management and data cache sharing mechanisms, to minimize the data interaction operation content required in the process of providing services to users, reduce the amount of data transmission across terminals and regions, thereby improving the response speed of the system and terminals, and enhancing the real-time performance of services.

The invention belongs to the technical field of small animal mental disease diagnosis, and provides a neuroimaging-based small animal mental disease diagnosis system, which comprises an image data acquisition and preprocessing module for performing multi-modal imaging on a small animal by using high-precision neuroimaging equipment, acquiring neuroimaging data, preprocessing the acquired image data, and acquiring neuroimaging data; comprising the steps of denoising, registration, segmentation and the like so as to improve data quality; a feature extraction and analysis module; according to the invention, the resolution and the signal-to-noise ratio of the image data are improved through the multi-modal neural imaging technology, and a reliable data basis is provided for accurate diagnosis; image features are automatically extracted and analyzed through a deep learning algorithm, human intervention is reduced, and the accuracy and efficiency of diagnosis are improved; a personalized diagnosis model is constructed, individual differences of small animals are considered, and more accurate diagnosis is realized; through introduction of the cloud data management platform, centralized storage, sharing and cooperative analysis of data are realized.

The invention relates to the field of cloud data management, in particular to a cloud game data management system. The system comprises a plurality of cloud game devices which are deployed in a plurality of edge cloud nodes, comprise at least one first cloud game device and are used for updating a first game in a readable and writable first cloud disk, and the first cloud disk is only used for storing data information of the first game; the distributed block storage module comprises a plurality of block storage units, the block storage units are respectively deployed in a plurality of edge cloud nodes, the first block storage unit is used for generating a second cloud disk under the condition that the updating of the first cloud disk is finished, and synchronizing the second cloud disk to the second edge cloud node; enabling a second block storage unit in the second edge cloud node to generate a third cloud disk which is the same as the second cloud disk and is used for running the first game; the first block storage unit is a unit of a first edge cloud node, the first edge cloud node is a node where the first cloud game device is located, and the second cloud disk stores snapshot data of the first cloud disk.

The invention discloses a cloud data management and control method and system based on multi-level protection, and aims to determine a protection path of cloud data according to an important coefficient of the cloud data, a protection mechanism of a working space and a data system corresponding to the cloud data, ensure the accuracy of the protection path and realize multi-level protection of the cloud data. Further, in the multilevel protection of the cloud data, the attack position of the cloud data is determined based on the protection state of each protection node in the protection path, the reading frequency of the cloud data and the data system corresponding to the cloud data, and a plurality of attack factors are determined according to the attack position of the cloud data and the protection mechanism of the working space; according to the method, the auxiliary protection system is constructed according to the attack factors, the cloud data interaction path and the working space, and the multi-level management and control system of the cloud data is determined based on the auxiliary protection system, the multi-level protection of the cloud data and the load of the cloud data, so that the accuracy of the multi-level management and control system of the cloud data is ensured, and multi-level management and control of the cloud data are realized.

Methods, systems, devices, and computer-readable media used by a cloud data management system for collecting data from accounts hosted by a cloud-based data storage system on different cloud platforms or in different cloud regions of a cloud platform. Collection of data in the multi-cloud platform and / or multi-cloud region environments may be facilitated by the on-demand creation of one or more data collection accounts. Based on the collected data, one or more recommendations, notifications, or alerts associated with usage of the data storage system may be generated.

The application discloses a kind of light security communication method and system for agricultural perception node.The method includes that 256-bit static master key is preset in the bottom layer security storage area of perception node and heterogeneous convergence gateway, and the unique hardware serial number is read as node identification;Synchronous acquisition environmental data and visual feature data, splice into long payload plaintext;Derive dynamic session key, use dynamic session key to drive stream cipher to encrypt long payload plaintext, static master key drives block cipher to encrypt short header, and encapsulates into data frame;Data frame is sent through wireless channel, and heterogeneous convergence gateway receives and reversely decrypts short header to extract dynamic anti-fake factor, and replay attack verification is carried out;After verification, dynamic session key is reconstructed to restore data and uploaded to cloud data management server.The application also discloses a system using the above light security communication method for agricultural perception node, realizes the high security node legitimacy authentication and anti-replay attack under limited hardware computing power.

The invention discloses a ship-shore cloud intelligent platform, a ship intelligent management method and a storage medium. The ship-shore cloud intelligent platform comprises a ship end edge processing module, a cloud intelligent analysis module, a cloud data management module and a dynamic transmission control module. The ship end edge processing module is used for collecting data of a ship sensor, carrying out edge side preprocessing on the data and then sending the data; the cloud intelligent analysis module is used for receiving the preprocessed data, establishing a domain model based on multi-dimensional relevance of the data, and calculating and generating a state result of each functional module; the cloud data management module is used for carrying out relevance storage and management on the data based on the domain model; and the dynamic transmission control module is used for dynamically adjusting the data sampling strategy of the ship end edge processing module according to the real-time data flow. According to the invention, the problems of function abnormity and insufficient function real-time performance caused by satellite signal interruption and high propagation time delay in the existing ship intelligent platform are solved.

The invention discloses a pet personalized meal whole-process service system and method, and relates to the technical field of intelligent pet services, and the system comprises a cloud data and service module and an intelligent cooking execution module. The cloud data and service module is used for establishing and managing pet structured archives, generating quantitative recipes through a catering algorithm based on archive data, associating an e-commerce system to carry out clean vegetable commodity matching and order process management, and storing full-process data, and the full-process data comprises archive updating, cooking feedback and order recording. According to the pet personalized meal whole-process service system and method provided by the invention, through integration of intelligent hardware, cloud data management and e-commerce service, comprehensive personalization and scientization of pet feeding are realized, the problem of unbalanced nutrition in traditional pet feeding is effectively solved, and the pet can be fed according to the specific health condition and nutritional requirements of the pet. A nutrition formula is dynamically generated and adjusted, and pet health is promoted.

The invention relates to the technical field of civil engineering detection equipment, in particular to a wireless crack width measurement method and system based on image recognition, and the system is composed of a detection end, a handheld terminal and a cloud server. The detection end can collect a crack image and transmit position information; the handheld terminal realizes image preprocessing, crack identification and width calculation through an AI processor; the cloud server constructs a distributed storage system and is internally provided with a crack prediction model; according to measurement, crack data are collected through a detection end, an AI processor of a handheld terminal executes Gaussian filtering, CNN recognition and Canny edge detection to calculate the width, and a cloud server predicts the crack trend through an LSTM + SVR model. Through multi-module integration, a depth AI algorithm and cloud data management, the problems of low measurement precision, insufficient intelligence, difficulty in data management and the like are solved, high-precision and intelligent crack detection and prediction are realized, and the data management efficiency and safety are improved.

The invention belongs to the technical field of high-voltage cable monitoring, and relates to a high-voltage cable metal sheath grounding state diagnosis method and system fusing multiple parameters. And a complete'digital twinning 'closed loop fed back comprises physical world perception, network transmission, cloud data management, multi-parameter fusion, intelligent diagnosis decision, visual presentation, artificial feedback and model self-optimization. A data island is broken through multi-parameter fusion, a leap from'static threshold alarm 'to'dynamic intelligent prediction' is realized through adaptive learning, and finally a predictive maintenance system capable of continuously accumulating knowledge and improving accuracy is formed.

The invention specifically relates to the technical field of aircraft control and navigation, and discloses an intelligent unmanned aircraft trajectory control and navigation system based on multi-source data fusion, which comprises an airborne data acquisition module, a ground cloud data management module, a flight action recognition module, an energy consumption decomposition calculation module, a trajectory calculation calibration module and a trajectory correction control module, flight associated data, flight meteorological data and flight plan data are fused through an airborne data acquisition module and a ground cloud data management module, a flight associated data set is constructed, the trajectory length is calculated in a backstepping manner in an environment without GNSS signals, a high-precision trajectory measurement result of a region without GNSS signals is continuously output, an associated energy consumption coefficient is corrected, and a high-precision trajectory measurement result of a region without GNSS signals is obtained. It is ensured that the mapping relation between the level flight equivalent energy consumption and the flight distance is accurate and reliable, real-time feedback is provided for autonomous navigation and path control of the unmanned aerial vehicle, and the adaptability of the system in a complex environment is remarkably improved.

The invention relates to the technical field of cloud data management, in particular to an emergency data sharing method based on a cloud platform, which comprises the following steps: acquiring cloud emergency data distribution characteristics, access authority and transmission path state, associating three types of data to evaluate overall state identification node connection, analyzing transmission load and bandwidth to evaluate reliability, and sharing the data. And comparing the instruction with the node state, adjusting transmission correction feedback, monitoring a transmission track and load change analysis stability, and outputting a shared path maintenance state label. According to the invention, association verification is carried out by acquiring cloud emergency treatment data distribution characteristics and access levels, so that cross-node data state perception and complete mapping are realized, the transmission direction and rate are automatically adjusted according to load change and network stability, and balanced transmission and reliable output under multi-node cooperation are ensured; and the transmission track change is continuously monitored to keep the sharing period stable, so that the data flow is kept continuous, safe and efficient in a complex cloud environment, and the emergency data sharing real-time performance and consistency are improved.

Methods, systems, devices, and computer-readable media used by a cloud data management system for collecting data from accounts hosted by a cloud-based data warehousing system on different cloud platforms or in different cloud regions of a cloud platform. Collection of data in the multi-cloud platform and / or multi-cloud region environments may be facilitated by the on-demand creation of one or more data collection accounts. Based on the collected data, one or more data warehouse resources not managed by the cloud data management system may be discovered, configured, and onboarded to the cloud data management system.

The invention provides a point cloud data management and Web rapid identification visualization method, and relates to the technical field of point cloud data processing. After point cloud similar clustering is carried out on the point cloud database, adaptive denoising processing is carried out through a similar clustering result, and a denoised point cloud set is established; establishing a scale space pyramid, performing calling matching on the scale space pyramid by using a similar clustering result, and reconstructing a position multi-scale model according to a calling matching result; performing feature extraction of the de-noising point cloud set through a position multi-scale model, and establishing a tunnel structure feature set; and performing tunnel visual fitting by using the tunnel structure feature set, and creating a Web visual model. The technical problem that in the prior art, due to the fact that the tunnel point cloud data size is large and noise and redundant information exist, the Web visualization quality is not high is solved, and the processing efficiency and the rendering performance precision of the tunnel point cloud data at the Web end are remarkably improved.

The present application relates to a kind of ship construction flatness inspection equipment and its use method, belong to ship flatness inspection technical field, including magnetic adsorption type mobile robot platform, magnetic adsorption type mobile robot platform, high-precision vision module, edge computing unit, cloud data management platform, magnetic adsorption type mobile robot platform is provided with track type walking mechanism and adaptive vacuum adsorption unit.In the present application, efficient, high-precision full-ship flatness intelligent detection can be realized by multi-sensor fusion and adaptive robot platform, suitable for real-time quality monitoring of hull block construction, deck assembly and outfitting stage, can perform local fine scanning along the weld area in the hull block detection scene, simultaneously mark the welding deformation out-of-tolerance area, can be switched to global fast scanning mode for non-key plane area, in deck assembly stage, cloud platform can integrate data in real time, assist in carrying out assembly misalignment correction scheme.

This application provides a method for point cloud data management and rapid Web identification and visualization, relating to the field of point cloud data processing technology. The method involves establishing a point cloud database; performing point cloud similarity clustering on the point cloud database, and then performing adaptive denoising processing based on the similarity clustering results to establish a denoised point cloud set; establishing a scale-space pyramid, using the similarity clustering results to call and match the scale-space pyramid, and reconstructing a position multi-scale model based on the call matching results; performing feature extraction on the denoised point cloud set using the position multi-scale model to establish a tunnel structure feature set; and using the tunnel structure feature set to perform tunnel visualization fitting and create a Web visualization model. This application solves the technical problem in the prior art of low Web visualization quality due to the large amount of tunnel point cloud data and the presence of noise and redundant information, significantly improving the processing efficiency and rendering performance accuracy of tunnel point cloud data on the Web.

The invention relates to the technical field of cloud data management, and particularly discloses a resource scheduling management system and method based on a cloud platform, and the method comprises the steps: obtaining heterogeneous resources from cloud platform resources, carrying out the information collection of the heterogeneous resources through a heterogeneous data interface, carrying out the same-type division of the heterogeneous resources, and obtaining heterogeneous resource nodes, the method comprises the steps of obtaining historical resource scheduling data of equipment, performing resource scheduling feature extraction and time sequence analysis, constructing a resource scheduling feature vector, performing similarity matching, determining equipment scheduling heterogeneous resource nodes, establishing a dynamic load prediction algorithm, performing fitting analysis on a load trend in combination with a sliding window, predicting load change and generating a scheduling early warning signal. And in combination with a resource priority strategy, a resource allocation scheme is obtained, task migration is performed on high-load heterogeneous resource nodes, and the migration tasks are allocated to the same type of heterogeneous resource nodes with low loads, so that optimization of resource allocation is facilitated, and the resource utilization rate of the cloud platform is improved.

The present invention discloses a method for managing point cloud data of highlighted buildings based on multispectral images, which relates to the technical field of building point cloud data management. The method for managing point cloud data of highlighted buildings based on multispectral images includes the following steps: collecting predefined spectral images of highlighted buildings by using an unmanned aerial vehicle; performing a first comparative analysis on the multispectral point cloud segmentation data of highlighted buildings; performing a first evaluation analysis on the multispectral point cloud segmentation data of highlighted buildings; performing a second evaluation analysis on the multispectral point cloud segmentation data of highlighted buildings; and performing a third point cloud data management process according to the results of the third comparative analysis. Through the regulation of the first and second evaluation analyses and hierarchical comparative analyses, the present invention achieves the effect of improving the accuracy of collecting point cloud data of highlighted buildings in multispectral images at night, and solves the problem of low accuracy of collecting point cloud data of highlighted buildings in multispectral images at night in the prior art.

The application discloses a kind of ship-shore cloud intelligent platform, ship intelligent management method and storage medium, ship-shore cloud intelligent platform includes ship end edge processing module, cloud intelligent analysis module, cloud data management module, dynamic transmission control module;Ship end edge processing module is used to collect the data of ship sensor, and the data is sent after edge side pretreatment;Cloud intelligent analysis module is used to receive the data after pretreatment, and the field model is established based on the multidimensional correlation of data, and the state result of each functional module is calculated and generated;Cloud data management module is used to store and manage the correlation of data based on the field model;Dynamic transmission control module is used to dynamically adjust the data sampling strategy of the ship end edge processing module according to real-time data flow.The application solves the problem of abnormal function, insufficient real-time function caused by high satellite signal interruption and propagation delay in the existing ship intelligent platform.

The invention relates to an intelligent garbage treatment system and a treatment method thereof.The treatment system comprises a garbage can body and intelligent garbage management equipment communicating with the garbage can body; the processing method comprises the following steps: step 1, establishing a cloud data management platform for unified management of kitchen garbage; 2, the collected kitchen garbage is sorted, and the separated kitchen garbage is screened into organic garbage and inorganic impurities; and step 3, putting the collected kitchen garbage to be treated into a storage pool, and carrying out water cleaning, retting and dehydration. The method has the superior technical effects that a large amount of organic garbage in the sorted organic kitchen garbage is subjected to biological hydrolysis, so that slurry formed by biological hydrolysis can be used as a recyclable biomass carbon source, and the resource recycling rate is increased. The intelligent garbage treatment system is provided with the garbage recognition module, the type of garbage can be accurately recognized, and the garbage sorting efficiency is effectively improved.

The invention discloses an elevator Internet of Things abnormity diagnosis data management method and system. The method comprises the following steps: collecting heterogeneous time sequence data of an elevator and carrying out time alignment; performing real-time anomaly detection, data cleaning and adaptive compression on the edge computing node; uploading the processed data to a cloud, extracting and intelligently fusing multi-source features, and forming a unified feature vector; outputting an anomaly type, a severity level and a fault root cause chain by using the dynamic anomaly diagnosis model; and based on historical data and feature vectors, predicting the remaining service life of the key component through a fusion model, and generating a maintenance strategy by using a reinforcement learning optimization engine. The system comprises a physical sensing layer, a data acquisition and edge processing layer, a cloud data management and intelligent analysis layer and an application service layer. According to the elevator abnormal diagnosis system and method, full-process intelligent management from real-time monitoring and accurate diagnosis to predictive maintenance is achieved, and the accuracy, timeliness and operation and maintenance efficiency of elevator abnormal diagnosis are remarkably improved.

The embodiment of the invention provides a data processing method and device, electronic equipment and a storage medium, and relates to the technical field of Internet. The data processing method comprises the steps of obtaining a resource processing application sent by a data demand terminal; updating a first use record of target resource data in the cloud data platform based on the resource processing operation; if an update completion message for the first use record of the target resource data sent by the cloud data platform is received, sending an update notification to a private cloud data management platform, so that the private cloud data management platform updates a second use record of the target resource data in the private cloud data platform; if the preset verification condition is met, reading a first use record of each piece of resource data in the cloud data platform, and reading a second use record of resource data in the private cloud data platform; and matching the first use record and the second use record of the same resource data to obtain a data verification result. The accuracy of resource data use can be ensured, and resource abuse is prevented.

The embodiment of the invention belongs to the technical field of cloud computing, and particularly relates to a data server distribution method, a cloud data management platform and a computing device cluster, and the method comprises the steps that a management server receives an IP query request and obtains data transmission time delay corresponding to each data server, the data transmission time delay is used for indicating the time delay when the data server sends data to the terminal. And the management server determines a first data server corresponding to the data transmission time delay in the plurality of data servers, and sends a first IP address corresponding to the first data server to the domain name server so as to instruct the domain name server to transfer the first IP address to the terminal, and the terminal requests data from the first data server according to the first IP address. By adopting the application, the operation cost of the management server can be reduced, and the efficiency of transmitting data from the data server to the terminal can be improved.