442 results about "Cloud storage" patented technology

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 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 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 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 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.

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.

The invention discloses a multi-cloud data possession proving method, and relates to the field of cloud computing and data security. The method aims at solving the problems that in the multi-cloud storage environment, the data integrity verification efficiency is low, abnormity positioning is difficult, and damaged data is difficult to automatically repair. According to the method, a plurality of storage positions are intelligently distributed for data blocks through a dynamic weight model, and data fingerprints associated with multiple clouds are constructed; during verification, data block risk scores and random selection are fused to generate a challenge set, and each cloud service party calculates local response based on stored data blocks and fingerprints; the verifier aggregates all the responses, compares the responses with an expected value through a consistency verification function, and outputs a comprehensive verification result; if it is judged that the data are not completely held, an exception positioning and repairing mechanism is triggered. According to the method, efficient verification, accurate positioning and autonomous recovery of the integrity of the multi-cloud data are realized, and the reliability and security of cross-cloud storage of the data are remarkably improved.

The present disclosure provides a digital conference interaction method, device, system and related device, comprising: accessing a conference system through a webpage end by a user terminal, and sending user data to an edge node; analyzing user semantics and intention based on the user data by the edge node, and requesting a rendering flow of public semantics from a cloud server; requesting three-dimensional model data corresponding to the user from a cloud storage based on information saved by a public semantic library of the cloud server, constructing a public semantic scene and cloud rendering by the cloud server; returning the cloud rendering flow to the edge node; constructing a private semantic library based on the user data by the edge node, requesting data from the cloud storage, constructing a private semantic scene and edge rendering; rendering and synthesizing the cloud rendering flow and the edge rendering flow; and returning the synthesized flow to the user terminal, so that the user terminal receives a conference scene and a picture of a user digital person in real time on the webpage end, the picture including real-time expressions, actions, position states of the digital person.

This invention discloses a fully decentralized multi-committee attribute-based encryption method, belonging to the field of information security. It modifies the attribute organization into a committee composed of multiple nodes and designs the committee initialization, attribute key issuance and verification, and encryption and decryption algorithms. The committee uses the DKG protocol to generate public and private keys between nodes, while ensuring that the committee can tolerate 1 / 2 Byzantine nodes. An attribute key verification algorithm is designed to allow users to filter out invalid keys issued by Byzantine nodes. This invention applies X-ABE to implement the Decentralized Access Control Protocol (DACCS) in cloud storage scenarios, applying X-ABE to the stages of issuing user attribute keys and encrypting session keys to achieve encrypted data transmission. Combined with a sharded blockchain architecture, intra-shard consensus is used to ensure consistency among committee nodes during key issuance. User attribute information, ciphertext hash values, and other information are recorded on the blockchain.

The invention relates to the technical field of cloud storage, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a migration method, device and equipment of a storage placement group and a medium, and the migration method comprises the following steps: obtaining a distributed storage cluster, and collecting multi-dimensional load data of object storage equipment nodes in the distributed storage cluster; calculating a load score of the object storage device node according to the multi-dimensional load data, and constructing a device capability matrix of the object storage device node by using the load score; identifying a storage cluster mapping graph in the distributed storage cluster, and mapping the equipment capability matrix into a soft weight of the storage cluster mapping graph; soft weight parameter configuration operation is carried out on the storage cluster mapping graph by using the soft weight, and a storage placement group of the distributed storage cluster is constructed according to the configured storage cluster mapping graph; and generating a batch migration scheme of the storage placement group, and executing migration operation on the storage placement group according to the batch migration scheme. The accuracy of migration of the storage placement group can be improved.

The invention belongs to the technical field of information security, relates to zero-knowledge proof and block chain technologies, and particularly provides a public verifiable data service method for an instrument control system, so as to solve the technical problem of huge calculation overhead caused by the fact that commitment consistency check of large-scale data needs to be executed in a circuit in an existing zk-SNARK-based scheme. According to the invention, a hybrid proving system based on a cryptographic protocol Plonk and Groth16 is designed, the promise adaptive to the system is designed, and the consistency check of the promise of the database is transferred from the inside of an arithmetic circuit to the outside of the circuit, so that the huge calculation overhead introduced into a zk-SNARK circuit by the promise consistency check of a large-scale database is avoided; and finally, the verifiable execution of safe calling and operation on the data subset from the third-party cloud storage is realized, the accuracy and integrity of industrial data are ensured, and the problem of trust missing in a cross-domain scene is solved.

This invention discloses a lightweight traceability method for constructing a data chain across the entire lifecycle of prefabricated components, relating to the field of data processing technology. The specific steps of this method are: encoding association, chain construction, cloud storage, request triggering, and hierarchical retrieval. This invention generates a unique digital identity code for each prefabricated component that spans its entire lifecycle, and associates this digital identity code with BIM model elements to generate associated data. Based on this associated data, a data chain is constructed according to the lifecycle time sequence and event nodes of the prefabricated component. Heterogeneous data from each event node are systematically linked to their corresponding event nodes, and the correlation degree between adjacent nodes is calculated to form a complete data chain. This allows the lifecycle data of prefabricated components to form an orderly and continuous association system around a unified code, achieving integrated data integration and node-based management at each stage, enabling full-process traceability of component data throughout its lifecycle.

The invention relates to the technical field of data processing, and discloses a data processing method and device, equipment and a medium, and the method comprises the steps: obtaining the optimal configuration information of a target data table in a data lake cabin, and constructing strategy coordination information based on the optimal configuration information; collecting real-time feature data of the writing end and the query end by a feature collector based on the strategy coordination information to obtain a combined feature data set; constructing an input vector based on the joint feature data set, and analyzing the input vector through a large model to obtain a compression strategy decision result; and converting the compression strategy decision result into an atomic compression instruction which can be identified by the target data table, and triggering a compression task based on the atomic compression instruction to compress the target data table. The method can be applied to financial science and technology or medical care service program systems, and can dynamically generate the adaptive compression strategy, so that the write-in performance, query efficiency and cloud storage cost of the data lake bin are optimized at the same time.

A system is provided.SOLUTION: A system comprising: means for collecting past data of a user from a cloud storage; means for analyzing the collected data; and means for providing a service in a plurality of modes according to a selection of the user.SELECTED DRAWING: Figure 1

The invention discloses a distributed cloud storage optimization method oriented to large-scale data, which relates to the technical field of distributed cloud storage and comprises the following steps of: 1, generating a distribution decision, label mapping and time alignment number at an entrance according to a small object threshold and a late access score, and filing the distribution decision, the label mapping and the time alignment number; 2, storing a source object in a storage bucket, synthesizing a composite container according to the identifier, outputting a list file, an index segment and a pre-write log, and setting a source object retention window; 3, during reading, a cloud side firstly copies a source object to a heat collection barrel return link by a server side, and an object side performs container segmentation reading and triggers hot fragment extraction; 4, collecting a standard layer returning proportion or a hot layer returning proportion, delay and cost, performing closed-loop updating on parameters, and rewriting and recycling according to a combined triggering amount; according to the method, cross-cloud read-write collaboration, caliber consistency and traceability are realized, long-term cost is reduced, tail time delay is stabilized, and maintainability and expansibility are enhanced.

The invention provides a field geological data acquisition method and device based on artificial intelligence, and the method comprises the steps: connecting an intelligent acquisition terminal and an RTK positioning terminal, loading a working area map, planning an optimal hole-placing route, broadcasting a task list, reading the current hole position coordinate through the RTK positioning terminal after a hole position measuring point is reached, storing the current hole position coordinate in an acquisition form, and completing the hole position measurement. Corresponding hole position numbers and positioning time are generated; geological data of the current hole site are collected, a corresponding template or voice is selected to record stratum lithology description, the stratum lithology description is converted into structured data, and the structured data are stored in a collection form to which the current hole site belongs; a rock stratum picture of the current hole position is obtained and recognized, a rock stratum recognition result is obtained, and comparison verification is conducted on the rock stratum recognition result and the corresponding rock stratum picture in the database; and if the rock stratum photos are matched, the verification is passed, and the acquisition form is synchronized to the cloud platform in real time. The geological data acquisition efficiency and accuracy can be improved, and fusion, cloud storage and intelligent analysis of multi-source data are realized.

The invention provides an information sharing method and device, electronic equipment and a storage medium, relates to the field of cloud storage, and can be applied to a cloud platform. The method comprises the steps of displaying sharing prompt information on a sharing panel in response to an identified information sharing request for to-be-shared information; displaying a sharable group on a prompt panel based on an operation for sharing the prompt information, the prompt panel being a sub-panel of a sharing panel; determining a target sharing group from the sharable groups based on the operation for the sharable groups; and storing the to-be-shared information in the sharing space of the target sharing group. The information sharing efficiency is improved, and the group value is also improved through the function of sharing the information by the group.

The application provides a cloud storage method and system for Internet of Things device data, and relates to the technical field of Internet of Things data storage and processing, wherein the method comprises the following steps: collecting metadata of a plurality of Internet of Things devices in an Internet of Things environment; performing labelization processing on the metadata to form standardized data packets; performing hierarchical compression processing on the standardized data packets, and extracting multi-dimensional features from the data packets 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; based on the security level, performing differential encryption processing on the data packets after the hierarchical compression processing by using a lightweight encryption algorithm, and transmitting the data packets after the encryption processing to a corresponding storage area in the cloud. The application improves the efficiency and security of Internet of Things data storage.

A newly created or modified object is sent to a networked local or remote server for analysis. While the object is being analyzed for vulnerabilities, the object is locked and made inaccessible to users, devices, and networks. If the object is identified as malicious, it may be marked for review, deleted, placed in quarantine, or have its permissions changed so that it cannot cause harm by propagating through the environment. Conversely, if the object is identified as safe, the risk of ransomware attacks may also be mitigated by replicating the object across multiple cloud storage platforms.

The invention relates to the technical field of pet medical information, and discloses a pet cloud medical record management method and system, and the method comprises the steps: collecting pet health data through a user terminal, and the pet health data comprises video and text description; uploading the video to a video processing module, automatically editing the video through the video processing module, and extracting key segments; the text description and the key segments are integrated, and a structured pet electronic medical record is generated through a medical record generation module; storing the pet electronic medical record to a cloud storage server, and storing the hash value of the pet electronic medical record to a block chain network; and according to a user instruction, safe sharing and multi-terminal synchronization of the pet electronic medical record are realized through the safety control module. According to the method, the problem that the pet cannot know the pain point of the illness state by himself / herself is solved, the behavior performance of the pet can be effectively recorded and traced, the burden of a pet owner for sorting data is relieved, and meanwhile, a more intuitive and complete diagnosis and treatment basis is provided for veterinarians.

A system includes an image forming device, a first information processing device, and a second information processing device. The first information processing device, the second information processing device, and the image forming device is connected to the Internet. The image forming device is configured to execute an image upload process of uploading, to the cloud storage, first image data indicating a first remote operation screen. The first information processing device is configured to execute a screen display process of downloading the first image data from the cloud storage to cause the user interface of the first information processing device to display the first remote operation screen indicated in the first image data.