703 results about "Cloud storage" patented technology

The invention relates to the technical field of land parcel management, in particular to a land parcel full life cycle compliance management and operation monitoring system, which comprises a multi-source data acquisition module for acquiring multi-dimensional land parcel data such as spatial geographic ownership planning and approval from a plurality of heterogeneous data sources in real time; the data fusion and storage module performs data cleaning and standardized fusion, adopts a distributed cloud storage architecture and introduces data version management to support historical tracing; the intelligent compliance judgment engine generates a compliance state judgment result and a compliance risk report based on the dynamic compliance rule base and machine learning; the interactive visual monitoring module is used for dynamically displaying the compliance state of the land parcel space information life cycle stage and the key index trend; and the automatic early warning and intervention module is used for performing graded early warning and triggering a rectification or emergency intervention process. According to the invention, the problems of difficulty in compliance judgment, low efficiency, non-visual monitoring and slow risk response of existing land parcel management data integration are solved, and intelligent compliance management and operation monitoring are realized.

The invention relates to the technical field of cloud storage, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a load and message queue regulation-based migration method, device, equipment and medium. Monitoring message backlog amount and consumption rate to generate message queue state information, generating migration regulation and control parameters based on the two types of state information, determining concurrency level and issuing rhythm by combining object size classification information, reducing issuing frequency and preferentially scheduling small objects when the message backlog amount is increased and oversize objects exist, and distributing the tasks to the working nodes according to the concurrency level and the issuing rhythm to execute migration, and adjusting migration regulation and control parameters based on execution state updating information. According to the method, concurrency and rhythm are regulated and controlled in real time, object size classification is combined, the problems that traffic is uncontrollable and throughput is affected by large files are solved, and efficient and stable data migration is achieved.

The invention belongs to the technical field of cloud storage, is suitable for the financial field and the medical field, and discloses a data table migration method, device, equipment and medium, and the method comprises the following steps: obtaining the name of an original database, a connection character string and a configuration file of a to-be-migrated data table, and analyzing the configuration file of the to-be-migrated data table to obtain a data table to be migrated; obtaining a table name and a table owner of the to-be-migrated data table; connecting the original database according to the connection character string of the original database, generating a table existence verification statement through the table name and the table owner of the to-be-migrated data table, and verifying the validity of the to-be-migrated data table according to the generated table existence verification statement; renaming the to-be-migrated data table in the target database according to a preset naming rule and performing compatibility processing; the migration instruction of the data table is generated in the target database, and the compatible data table to be migrated is migrated into the target database according to the generated migration instruction, so that the migration efficiency of the data table is effectively improved.

The invention provides a cloud storage method and system for Internet of Things equipment data, and relates to the technical field of Internet of Things data storage and processing, and the method comprises the steps: collecting metadata of a plurality of Internet of Things equipment in an Internet of Things environment; performing tagging processing on the metadata to form a standardized data packet; performing hierarchical compression processing on the standardized data packet, and extracting multi-dimensional features from the data packet after the hierarchical compression processing; inputting the multi-dimensional features into a multi-modal neural network model based on deep learning, analyzing the multi-dimensional features through the multi-modal neural network model, generating a target storage priority index, and determining a corresponding security level according to the target storage priority index; and based on the security level, performing differential encryption processing on the data packet after hierarchical compression processing by using a lightweight encryption algorithm, and transmitting the encrypted data packet to a storage area corresponding to the cloud. According to the invention, the efficiency and security of Internet of Things data storage are improved.

The invention relates to the technical field of cloud storage, can be applied to business system platforms of financial science and technology, medical treatment and health and the like, and discloses a hierarchical storage method, device and equipment for data files and a medium, and the method comprises the following steps: acquiring the data files in a storage unit, and extracting data characteristic parameters in the data files; performing multi-dimensional quantitative analysis on the data feature parameters to obtain a dimensional feature analysis value; identifying a dynamic weight of the data feature parameter, and performing weighted calculation on the data feature parameter according to the dimension feature analysis value and the dynamic weight to obtain a dynamic storage analysis value; identifying a data storage type label according to the dynamic storage analysis value; matching the data storage type label with strategies in a storage strategy library to obtain a target storage strategy; determining a storage hierarchy according to the target storage strategy; a storage address of the data file in the storage hierarchy is identified and the data file is stored in the storage address. The accuracy of hierarchical storage of the data files can be improved.

The invention discloses an intelligent fire-fighting inspection system and method for a main transformer of a transformer substation, and the method comprises the steps: collecting fire-fighting inspection related data of an automatic fire extinguishing system, and uploading the data to a cloud for storage; classifying the collected fire-fighting inspection related data of the automatic fire extinguishing system according to different time sequence change types; establishing a corresponding neural network prediction model according to fire-fighting inspection related data of the automatic fire extinguishing system and different classification results of time sequence change types; inputting the classified fire-fighting inspection related data of the automatic fire extinguishing system into a corresponding neural network prediction model, and calculating to obtain a fire-fighting inspection prediction result of the automatic fire extinguishing system; and comparing the fire-fighting inspection prediction result of the automatic fire extinguishing system with a preset fire-fighting inspection data threshold value, and judging whether the fire-fighting inspection prediction result of the automatic fire extinguishing system has a fault risk or not. The working state of the fire extinguishing system is intelligently predicted, and the automatic fire extinguishing system of the transformer substation main transformer is intelligently inspected.

The invention relates to the technical field of log detection, in particular to a real-time anomaly detection and tracing method and system for a cloud storage log, and the method comprises the following steps: calculating an authentication failure proportion based on a user identifier and an internet protocol address, constructing a proportion change sequence, comparing an abrupt change threshold, screening candidate sections, fitting a slope, and aggregating anomaly records; calculating a fluctuation difference sequence, extracting a causal fracture node, recombining a subsequence graph, extracting a cross-node record and correcting a timestamp, connecting a transmission edge based on the timestamp, and accounting time consumption to construct a traceability path. According to the method, the serious defect that a fixed threshold value cannot sense system load fluctuation is overcome by constructing a dynamic proportion change slope, a causal fracture node is established to drive log atlas recombination so as to break an information barrier of a cross-node distributed environment, and a median function is used for correcting time migration to eliminate disorder interference caused by clock asynchronization; and the accurate risk tracing is realized by connecting the correction timestamp with the access transmission edge.

The invention discloses an image secret type cloud storage method and device based on feature block encryption, and the method comprises the steps: a cloud server receives and stores an encrypted image, an encrypted image feature set and a feature inner product, and forms an image database; the cloud server receives a feature ciphertext query feature uploaded by the authorized user when the authorized user needs to query the image; the cloud server performs retrieval according to the received ciphertext query features, separately calculates the similarity between color and texture sub-features in the ciphertext query features and features in each encrypted image feature set in the image database by using a hierarchical earth moving distance algorithm, and calculates the comprehensive similarity corresponding to each encrypted image; and screening out a plurality of encrypted images according to the comprehensive similarity and returning the encrypted images to the authorized user. According to the method, safe and efficient search of the image can be realized, and the image retrieval performance is improved.

Embodiments of the present disclosure relate to migrating data from the cloud to on-premises storage. More specifically, a processing device obtains an indication of a plurality of cloud storage resources associated with a plurality of cloud storage providers and a plurality of geographic regions. The processing device generates an on-premises file structure based on the indication of the plurality of cloud storage resources and the plurality of geographic regions. The processing device migrates the plurality of cloud storage resources to on-premises storage based on the on-premises file structure.

The invention discloses a regional grid safety evaluation method and device based on smart gas and a medium, belongs to the technical field of gas safety supervision, and aims to solve the technical problem of how to overcome the defects of insufficient matching between grid division and gas facility characteristics and lagging leakage risk prediction in the prior art. In order to realize full-process intelligence from risk identification to closed-loop management and improve supervision efficiency and early warning precision, the technical scheme adopted by the invention is as follows: dividing a pressure sensitive grid: performing optimization division on a regional grid based on a gas pipeline pressure grade and facility distribution characteristics, and realizing accurate division of the regional grid where a pipe network is located by combining a GIS and an improved DBSCAN algorithm; acquiring three-level Internet of Things data: integrating sensor data of an unmanned aerial vehicle, a pipe network pressure device and a leakage monitoring device, and covering a full-link data system of a terminal sensing layer, an edge computing layer and a cloud storage layer; constructing a double-engine evaluation model; carrying out digital twinborn visualization; and scheduling the capability matrix.

The invention provides an SM9-based identity-based searchable public key encryption method and an SM9-based identity-based searchable public key encryption system. The system comprises a key generation center, a cloud storage server and a file sending and receiving party. A secret key generation center generates system public and private keys by using an SM9 algorithm, and generates a private key for a user in combination with identity information of the user. The file sender uses the user identity of the receiver and the file keyword to generate a keyword index and uploads the keyword index to the cloud server; when a receiver retrieves the file, the auxiliary parameters in the index are firstly obtained from the cloud server, then a keyword trap door is generated through a private key of the receiver, and the keyword trap door is uploaded to the cloud server; and the server compares the index with the trap door through a matching algorithm, and returns a corresponding ciphertext file to a receiver for decryption if matching succeeds. The secret key generation method is consistent with an SM9 algorithm, the application field of SM9 is expanded, and the safe and efficient searchable public key encryption method which does not need certificate management and can effectively resist internal keyword guessing attacks is achieved.

The present disclosure provides a system and a method for performing real-time cloud-native fingerprinting and managing sensitive content within a cloud storage platform to prevent data leakage. The system comprises a cloud storage platform comprising a data leakage prevention (DLP) server. The DLP server configured for receiving and storing a sensitive document, receiving a sensitivity level of the sensitive document, fingerprinting the sensitive document based on the sensitivity level, indexing and storing the fingerprint, sharing the fingerprint to an endpoint security agent, receiving leak indication, performing leak analysis and notifying the leak to a document owner. The system and method further perform monitoring of the sensitive data that has been fingerprinted and stored under a security folder, for a predefined time and automatically moving the sensitive data from the security folder after the predefined time.

The invention relates to the technical field of security engineering, and discloses a panoramic monitoring video cloud storage processing method and system, and the method comprises the steps: constructing a grading processing strategy set corresponding to multi-source panoramic video data, and a streaming processing rule engine and a value density scoring matrix of the grading processing strategy set; carrying out pre-transmission information reinforcement processing on a high-value event in the multi-source panoramic video data to generate an encrypted data stream of the multi-source panoramic video data; combining the space-time-behavior feature vector of the encrypted data stream with the global information atlas of the global monitoring front-end equipment, and setting a differential storage mode of the encrypted data stream; and finally, according to the hierarchical processing strategy set, the encrypted data stream and the differentiated storage mode, generating a cloud storage optimization scheme of the multi-source panoramic video data. According to the invention, the resource utilization efficiency of the panoramic monitoring video storage system can be improved.

The invention relates to the technical field of containers and micro-service architecture, and discloses a K8s-based Juser Notebook container arrangement method, which comprises the following steps of: S1, packaging Notebook into a Docker mirror image file; s2, mounting a Notebook configuration file on the K8s cluster through a ConfigMap (Configuration Map); s3, deploying and defining the number of copies of the Notebook application through Deployment; S4, configuring a service network and an ingress network; S3, deploying and defining the number of copies of the Notebook application through Deployment; s5, a cloud storage mode is adopted, and calculation and storage are separated; and S6, K8s API automatic management is carried out. The deployment process is simplified, the maintenance and management difficulty is reduced, and the resource utilization rate is improved; a cloud storage mode is adopted, separation of calculation and storage is achieved, and environment configuration is simplified; the Ingress provides network functions such as flow management and reverse proxy, so that the Notebook service is easier to access and integrate; the K8s cluster can ensure the high availability of the Notebook service; and when a fault occurs, quick recovery is realized, service interruption time is reduced, monitoring and management are easy, and management and operation and maintenance efficiency is improved.

The invention discloses a UTM cloud-based multi-source unmanned aerial vehicle flight record analysis method and system, and the method comprises the steps: building data connection with at least two unmanned aerial vehicle flight control systems of different manufacturers through a multi-source flight control connection module, and analyzing and collecting flight record data; uploading the flight record data to a cloud storage module in real time for centralized storage; performing multi-dimensional analysis on the flight record data through an intelligent analysis module, wherein the multi-dimensional analysis comprises the following steps: monitoring a flight state in real time to identify an abnormal flight event; when abnormality is detected, historical and real-time flight record data are called, and whether the cause is manual operation error or not is judged through data correlation analysis; wherein in the recognition process, external environment parameters are introduced to serve as correction factors to carry out normalization processing on basic indexes and composite indexes, and an anomaly judgment threshold value is dynamically adjusted through a Bayesian optimization algorithm; in the judgment process, an operation error probability score is output based on a three-dimensional operation baseline model and an operation error recognition model trained by a random forest classifier.

The invention discloses an SCR adaptive thermal management control method and system based on big data, and the method comprises the steps: collecting vehicle operation parameters through a vehicle-mounted terminal, forming an original data set, and uploading the original data set to a cloud for storage. And scene recognition is carried out according to the original data set, and the driving scene category is determined. And a corresponding control strategy is matched through the driving scene category, and a control instruction set is generated. And adjusting the engine operation mode according to the control instruction set, obtaining the adjusted operation state data, and uploading the adjusted operation state data to the cloud. And processing the operation state data through a cloud analysis module, updating a scene feature library and a control strategy library, and dynamically adapting to the vehicle operation condition. Therefore, according to the SCR self-adaptive heat management control method based on the big data, the dynamic response capability is improved, and the balance between emission control and fuel economy is optimized.

The invention discloses a material database system with enhanced artificial intelligence. The material database system comprises an interactive user interface module, a data management and service module, a visual processing module and an AI analysis and intelligent dialogue module. Structured and unstructured material data are managed in a centralized manner through a unified database and cloud storage, and a standardized data center is constructed; by integrating a chemical structure rendering library and a 3D graphic engine, real-time rendering from a CIF file to an interactive 3D model is realized, and a dynamically generated XRD spectrogram is displayed through an interactive chart library, so that the interpretability of data is greatly improved; by introducing an AI application development framework and an LLM, the system is endowed with intelligent analysis ability exceeding simple data retrieval, and professional material interpretation can be provided; by integrating the RAG system, a traditional search mode is upgraded into an intelligent dialogue mode, so that a user can explore material data like a dialogue with an expert.

Adaptive provisioning of cloud storage volumes includes building a vector database having properties of storage devices of a cloud environment, associating storage devices with storage classes based on the properties of the storage devices, each storage device of the storage devices being associated with a storage class of the storage classes, receiving a request for provisioning a storage volume to support a workload, where the request indicates application requirements associated with servicing the workload, performing a semantic search on the vector database and determining, based on the semantic search, a storage class for the requested storage volume, and provisioning the storage volume on a storage device, of the storage devices, associated with the determined storage class.

The invention provides an improved public key searchable encryption method, system and device, and belongs to the technical field of information security and cryptography, the method comprises the following steps: firstly generating a public and private key pair, encrypting a keyword by using a public key to generate a searchable ciphertext, and associating a storage document; receiving a search request and a trap door derived by a private key, and returning an index after matching; the client downloads the ciphertext and decrypts the ciphertext through a private key; an anti-guess attack mechanism is integrated, and user interests are prevented from being speculated through access mode hiding; a dynamic index structure is constructed, and rapid addition, deletion and modification of documents, Boolean query and multi-user permission control are supported. According to the invention, the encryption security is guaranteed through the public and private key separation and trap door mechanism; the dynamic index supports efficient data operation; user privacy protection is enhanced through anti-guess attack and access mode hiding; and the method is compatible with multi-query and authority control, and is suitable for various scenes with dual requirements on privacy protection and data availability, such as cloud storage, e-mail systems, medical health data management and the like.

A method and system are provided at a local network level and a remote cloud level. The local network level includes compressors and a controller configured to create a short-term schedule having a short-term switching sequence for operation of the compressors, perform a validation assessment on the short-term schedule, and send the short-term schedule to a platform embedded with the main controller of the system. A prediction model, a long-term scheduling approach, and cloud storage that stores measurements from the compressors and executable instructions are provided at the remote cloud level. The long-term schedule is transferred to a safety check module at the local network level. Following validation, the embedded platform refines the long-term switching sequence and the safety check module allows the system to implement the long-term schedule, having the short-term schedule as a backup option.

The invention relates to the technical field of medical image processing, in particular to a pulmonary nodule follow-up visit intelligent management system which comprises a pulmonary nodule intelligent matching and change analysis engine, a pulmonary nodule intelligent follow-up visit scheme generation engine, a cloud storage and collaborative service module, an early warning module and a user management and operation module. The surface of the pulmonary nodule is modeled into a differential manifold, accurate matching of the pulmonary nodule and quantitative analysis of small changes are achieved through a multi-scale differential invariant feature extraction framework and a geodesic distance-based change analysis technology, the system generates a personalized follow-up visit scheme based on a risk assessment model, and through a multi-stage early warning mechanism and multi-channel notification distribution, the risk assessment accuracy of the pulmonary nodule is improved. The system also adopts a GPU acceleration computing architecture, so that the processing efficiency is remarkably improved, multi-terminal cooperative operation is supported, the accuracy, intelligence and individuation of pulmonary nodule follow-up visit management are realized, and the follow-up visit efficiency and the early detection rate of lung cancer are improved.

Techniques are provided for a data format for efficient management of checkpoint support. The data format corresponds to a base metafile and a set of instance metafiles used to track storage operations such as a directory restore operation. The base metafile and the set of instance metafiles can be used to resume the storage operation from where the storage operation left off in the event of a failure. The base metafile and the set of instance metafiles can be used to track progress of the storage operation processing objects stored within an object store of a cloud storage environment.

The invention discloses a cloud storage data synchronization method oriented to multi-terminal collaboration, which comprises the following steps of: deploying a synchronization agent at each terminal, and generating a terminal identifier and a clock calibration result; monitoring a file system event at each terminal to form an operation event record; updating a corresponding version vector of the operation event record, and combining with the operation event record to form a local operation log entry; performing blocking on the target file to obtain changed block information; three-way merging is adopted based on the change block information, and merged block-level operation data is output; carrying out ANS entropy coding on the combined block-level operation data, and constructing an incremental updating packet; submitting the incremental update package to a multi-copy storage cluster by adopting an EPaxos consensus protocol, and outputting a target file version confirmed by a consensus; and generating an updating instruction set oriented to the subscription terminal, and obtaining a final file state consistent with the cloud. According to the invention, the cloud storage data synchronization method is realized.

The invention discloses a dynamic sleep memory intervention method and system based on an ultrathin eyeshade, the system comprises an ultrathin eyeshade body and a cloud platform, and the eyeshade integrates electroencephalogram acquisition, memory content playing, master control and communication modules. The electroencephalogram acquisition module adopts an eight-channel super-soft spandex conductive electrode and a noise reduction unit combining adaptive notch filtering with wavelet threshold filtering; the memory playing module is a hemispherical dome miniature bone conduction loudspeaker, and silent leakage outside 30cm is realized; a dynamic sleep memory dry prediction algorithm is built in the main control module, and playing parameters can be adjusted according to delta wave intensity; the cloud stores personalized memory content and intervention records, and push content can be intelligently updated. The method comprises the steps of equipment starting initialization, electroencephalogram collection and noise reduction, deep sleep recognition, dynamic playing and data encryption synchronous closing, the problems that existing equipment is heavy and intervention is rigid are solved, non-inductive wearing, accurate intervention and privacy protection are achieved, and the method is suitable for sleep memory consolidation.

The invention relates to an equipment black and white list management method and device, a storage medium and electronic equipment. The method comprises the following steps: receiving feedback information input by a user, and identifying a feedback identifier, an equipment problem type and a user appeal in the feedback information; obtaining business data of the target equipment from a business background according to the feedback identifier, and inputting the feedback information and the business data into a target large model, so that the target large model executes semantic understanding and rule reasoning according to the feedback information and the business data in combination with a business knowledge base, and generates a black and white list change suggestion; processing the original blacklist and whitelist of the target device based on the blacklist and whitelist change suggestion, and generating a new blacklist and whitelist meeting user demands; and uploading the new black and white list to a cloud storage platform, and feeding back a processing result of the downloading link containing the new black and white list to the user. The technical problems that equipment capability identification depends on manual editing of black and white lists, the process is tedious and inefficient, and errors are prone to occurring are solved.

The invention relates to the technical field of door lock abnormity warning, and discloses an intelligent door lock abnormity warning method and system based on multi-modal perception, and the method comprises the steps: obtaining a reference coordinate of a door lock handle in an image frame and a centroid coordinate of a human body target, determining an area to which the human body target belongs, and determining target area information; calculating the displacement of the continuous inter-frame centroid coordinates, and when the displacement is smaller than a displacement threshold value, judging that the system is in a static state and starting a staying timer to obtain a staying time length; setting a target stay threshold according to the target area information, and determining a danger level and a corresponding anomaly type; according to the danger level and the abnormity type, voice playing is triggered at the edge end, and an alarm message is sent to the cloud end, a precise monitoring strategy can be implemented according to the space distance between the target and the lock body, the frequent false alarm problem caused by global detection is effectively avoided, the instant response capability of a high-risk scene is guaranteed, and the safety of the high-risk scene is improved. And the cloud storage cost and the network bandwidth occupation are reduced.

The invention provides a special equipment inspection and detection result recording device and method, and the device comprises a data collection assembly which is used for collecting feature equipment inspection and detection data; the data processing component is connected with the data acquisition component and is used for processing the acquired feature equipment inspection and detection data; the central processing unit is connected with the data processing assembly and is used for analyzing and sorting the processed data to obtain a detection result; the cloud memory is connected with the central processing unit and is used for storing the detection result; the mobile terminal is connected with the central processing unit and is used for outputting feature equipment inspection and detection data and checking a detection result after login; according to the special equipment inspection and detection data management system, inspection and detection data of various forms of special equipment can be sorted and analyzed, so that accurate detection results are obtained, recorded and filed, systematic management of the inspection and detection results of the special equipment is realized, and the management efficiency and the management level are improved.

The application discloses an inadvertent random access machine storage system based on a double-buffer data read-write algorithm, which comprises a cloud storage unit and a user end, wherein the cloud storage unit is provided with a full binary tree for storing encrypted data; the user end is provided with a first buffer, a second buffer and a position table located at the user end; a part of the top of the full binary tree is not used for storing data, so that the full binary tree comprises m full binary tree sub-trees.

A system is provided.SOLUTION: A system includes means for collecting data from mail servers, messaging platforms, and cloud storage, means for analyzing text data, image data, and other data in preprocessing and integrating them, means for constructing a multimodal AI model, means for analyzing similarity of data, means for receiving a search query from a user and identifying related data based on the search query, means for searching a past communication log for transmitting related materials, and means for providing a search result to a user terminal.SELECTED DRAWING: Figure 1

A system for radio-frequency identification (“RFID”) label management can include various physical components. An example system includes a reader device having a display, a scanner that detects nearby RFID labs, a memory storage, and processor that executes an RFID label management application. The example system also includes an RFID-enabled printer configured to receive instructions from the reader device and use the instructions to encode a new RFID label by writing data to a memory bank of the new RFID label. The example system further includes a cloud storage that receives information from the reader device and associates the information with a customer associated with the reader device. Other reader devices associated with the same customer can access the information stored in the cloud storage.