829 results about "Cloud storage" patented technology

The invention discloses a cloud edge collaborative multi-source data fusion safety management and control system for intelligent power distribution equipment, relates to the technical field of intelligent power grids and power distribution automation, and is used for managing and controlling 10-35 kV power distribution equipment. The system comprises an edge data acquisition module, a preprocessing module, a cloud storage management module, a cloud edge collaborative scheduling module, a multi-source data fusion module, an intelligent risk assessment module, a safety control execution module, a safety protection module and a man-machine interaction module. The modules are interacted through a 5G / industrial Ethernet; the acquisition module obtains multiple parameters, the preprocessing module cleans standardized data, the cloud side performs hierarchical storage, the scheduling module allocates tasks, the fusion module integrates data, the evaluation module performs grading risk, the protection module guarantees safety, and the interaction module performs visual alarm. The method improves the power distribution data quality and risk assessment precision, optimizes the cloud edge cooperation efficiency, enhances the safety protection capability, achieves the preventive operation and maintenance of equipment, reduces the fault and power failure time, reduces the operation and maintenance cost, and provides support for the safe and efficient operation of a power distribution network.

The invention discloses a human resource archive filing management system, and relates to the technical field of data management, the system comprises an acquisition module, a processing module and a management module, the acquisition module acquires original archive data of employees, transmits the data to the processing module, classifies the original archive data according to a preset first rule, and stores the classified data to the management module; the first archive data is obtained, controlled and managed, a calling permission and a distribution strategy are generated, the first archive data is recognized through a preset second rule, second archive data is generated, corresponding processing is conducted according to the processing priority, a processing log is reserved, third archive data are obtained and transmitted to the management module, and the management module is used for managing the first archive data. A distributed cloud storage cluster and a local storage node are constructed, an overall storage architecture and a retrieval path of third archive data are optimized, archive management is refined through three-dimensional classification, data integrity is guaranteed through field-level verification and automatic completion, scene-based dynamic authority control safety is achieved, compliance risks are intelligently cleared and avoided, and efficiency is improved through mixed storage. And active management of archive management is promoted.

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 agricultural environment monitoring, and discloses a cultivated land quality monitoring method. The method comprises the following steps: acquiring soil multi-parameter data, and carrying out sensor network deployment and anti-interference processing; performing exception filtering, standardization and missing value interpolation on the data; cloud storage data are generated through sliding window segmentation and encryption compression; generating a monitoring report based on the multi-dimensional analysis and the dynamic chart; adopting a plurality of intelligent algorithms to identify abnormal modes and constructing an early warning strategy library; and finally, real-time monitoring and early warning grade division are realized. According to the invention, full-process automatic monitoring and intelligent early warning of the cultivated land quality are realized, and the monitoring precision and the decision-making efficiency are obviously improved.

The invention relates to the technical field of government affair information management, in particular to a cloud-based government affair information management method, which comprises the following steps of: S1, adding a sensitivity label for each piece of government affair data in a cloud storage layer; s2, extracting data from the government affair database and generating a dynamic data view with an authority mark; s3, establishing a mapping relation table between routing keys and data source addresses; s4, acquiring a requester department function code, a business scene code and a target data identifier; s5, matching a target data source, and based on the authority mark in the dynamic data view, executing a desensitization operation on the sensitive field; and S6, if the genetic marker bit of the original data is true, superposing the data security classification in the original tag and the current security classification to form a new tag. According to the method, by constructing the sensitivity label and the dynamic authority control mechanism, safe inheritance and accurate access of government affair data in cross-department circulation are achieved, and the safety and compliance of data management are remarkably improved.

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 discloses a PDF (Portable Document Format) document structured extraction system based on a multi-modal language model, belongs to the technical field of document processing and optical character recognition, and aims at solving the technical problem of how to improve the existing OCR (Optical Character Recognition) technology to improve the analysis capability of a complex document structure and improve the recognition precision of handwritten forms and other non-standard fonts. According to the technical scheme, the system adopts a layered decoupling architecture and comprises an input layer, a preprocessing layer, a reasoning layer, an output layer and a monitoring and fault-tolerant module; wherein the output layer is used for multi-source data access and path management to realize a local file system or S3 cloud storage; the preprocessing layer is used for invalid document filtering and visual feature extraction; the reasoning layer is used for multi-modal model interaction and content processing; the output layer is used for outputting a content aggregation result; and the monitoring and fault-tolerant module is used for realizing real-time state monitoring, resource consumption analysis and exception handling.

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 relates to a medical data screening system and method based on AI auxiliary interrogation, the screening system at least comprises a client APP, an AI client and a cloud which are mutually connected, compared with the prior art, the system fully combines the advantages of AI, cloud storage, a user intelligent terminal and an offline diagnosis and treatment end, and realizes data acquisition, classification, fusion and interaction; the upstream of the AI client side can allow a patient to input basic data and image data, the downstream of the AI client side can call a cloud database, pathological data can be accurately screened through feature comparison, and pathological similarity suggestions are provided; in the high-incidence period of infectious diseases, the screening system or the screening method can be used for shunting hospitals, limited medical resources are fully allocated, and cross infection is avoided; by means of big data screening and online and offline diagnosis and treatment combination, the pathology screening accuracy is improved, accurate diagnosis and treatment suggestions can be given, and the medical diagnosis service experience is improved.

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.

Systems and methods for securely transferring Data Loss Prevention (DLP) incident data from a cloud-based DLP system to a tenant's cloud storage account in a multi-tenant environment include detecting a DLP incident by identifying a policy violation and generating an incident event and an associated request containing metadata and contextual information for the incident; processing the request, the processing comprising validating the tenant's configuration settings for storage access permissions and target storage details and determining routing information for the tenant's cloud storage account; and writing DLP incident data associated with the DLP incident into the tenant's public cloud storage account.

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 discloses a pressure monitoring method and system based on a power transmission cable axis sensor, and belongs to the technical field of data transmission, and the method comprises the steps: S1, a sensor module collects cable traction data and self position data at a measurement time point, and transmits the data to a monitoring module through a relay module; the monitoring module generates adjustment data based on the traction force data, wherein the adjustment data comprises an adjustment numerical value and an adjustment time point; s2, the cloud storage module obtains the data sequence and verifies the data sequence, and if verification is passed, the step S3 is executed; s3, analyzing the adjustment data, if an analysis result does not meet a preset rule, extracting an adjustment time point, and defining the adjustment time point as an abnormal time point; and S4, a marking module obtains a measurement time point which is located after the abnormal time point and is closest to the abnormal time point, obtains corresponding position data based on the measurement time point, and marks an indication label. According to the invention, a manager can remotely supervise the cable laying process.

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.

A system and method for monitoring a patient are disclosed. The method includes receiving and pre-processing image data captured by a set of cameras positioned to acquire images of either medical instrument or a patient within a clinical environment. The method further includes extracting an instrument identification code from a tamper-proof marking in the image data and validating the code against a pre-registered instrument ID. The method also extracts instrument display data using OCR or a trained machine learning model to identify medical parameters displayed on the instrument. The extracted data is transmitted to a time series database on a room integrator computer or cloud storage for storage and further use. Additionally, the method analyzes facial images of the patient to derive medically relevant data, including facial expressions, skin colour corrected for illumination variations, and facial surface or volume changes based on 3-D depth image data. The time series database stores the analyzed medically relevant data and the instrument display data. A visualization and analysis interface is utilized to assist in clinical decision-making based on the stored data.

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 discloses a computer multi-cloud data security backup method and system based on scene security, and the method comprises the steps: carrying out the risk assessment based on scene parameters, and formulating a security backup strategy; the method comprises the following steps: processing cloud data through adaptive fragmentation encryption, and dividing the cloud data into core data and non-core data; based on the relevance between the fragmented data, adding an identifier; performing evaluation based on the security index data of the multiple cloud storage nodes of each cloud storage platform to obtain the cloud storage platform meeting the storage requirement; through intelligent routing distribution, the encrypted data fragments are distributed and stored in the heterogeneous cloud storage platform, and it is ensured that the fragments stored in any single cloud platform are insufficient to reconstruct complete data; and constructing a multi-factor data recovery mechanism based on a data exception condition, and implementing dynamic migration on the fragments of the high-risk region. The method has the advantages that the flexibility and recovery capability of data backup are effectively improved through adaptive fragmentation encryption and intelligent routing distribution, and potential security threats are avoided.

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.

The invention provides a cloud instance login method and device, electronic equipment and a storage medium, and relates to the technical field of cloud computing. The cloud instance login method comprises the steps that an access credential is generated according to a login request, and the access credential comprises the access authority of a cloud storage server; acquiring historical user data from the cloud storage server according to the access credential; and loading the cloud instance in the corresponding state according to the historical user data. According to the method, the cloud instance does not need to be completely restarted or initialized after the user logs in, the operation environment can be directly recovered based on historical user data, the cold start waiting time is shortened, seamless recovery of personalized configuration, application state and operation progress is supported, the user is located at the last leaving position every time the user logs in, and the natural fluency of continuous use is improved.