5497 results about "Data administration" patented technology

The invention discloses an interactive question intelligent agent system based on a large language model, and relates to the technical field of dialogue interaction systems. Aiming at the technical defects of the traditional BI tool, the technical scheme is as follows: a heterogeneous data management engine realizes unified access and secure access of cross-source data; the NLP semantic recognition engine converts a natural language into structured semantics through multiple steps, drives the hybrid SQL generation engine and provides visual parameters; the generation engine realizes precise generation from semantics to SQL through a two-stage architecture based on metadata and authority rules; and the visual management console is combined with multi-party configuration and parameters to visually build a number-asking agent. The method is used for realizing intelligent conversion from a natural language to a structured query language (SQL) and a data service interface, and automatically generating an interactive data visualization result.

Systems and methods for decentralized data management across interoperable distributed platforms are disclosed. A computing system receives input data associated with a unique decentralized identifier (DID) representing an entity or event. The computing system segments the input data into encrypted data segments, each cryptographically linked to the DID, and distributes these encrypted segments across decentralized storage nodes according to a redundancy scheme. A cryptographic lineage record, including segment identifiers, timestamps, and hashes linked to the DID, is stored in a decentralized ledger. In response to authenticated access requests, the computing system reconstructs the input data by retrieving, decrypting, and cryptographically verifying the distributed data segments against the lineage record. Authorized entities access the reconstructed data through interfaces enforcing cryptographically secured access permissions defined within the decentralized ledger, providing enhanced security, provenance verification, and data resilience.

The invention discloses an intelligent monitoring management method and system based on archive digitization, and relates to the technical field of data management, and the method comprises the steps: collecting and preprocessing multi-source archive data, employing a multi-mode BERT model to carry out the feature fusion of different data sources, and generating a unified semantic representation; semantic labeling is performed on archive data through a multi-label classification model, a semantic graph of archive content is constructed by using a graph database, an association relationship between archives is represented, a semantic index tree is constructed based on the semantic graph, and rapid positioning and calling of the archive content are optimized; and recording the change of each file version, positioning the change position based on a semantic index tree, identifying the semantic change of the file through a semantic difference comparison algorithm, recording hash, carrying out granularity division on the file content through the semantic boundary of each level of node in the index tree, and generating a user access strategy. According to the invention, dynamic perception and risk early warning of user behaviors are realized, and the intellectualization and safety of the archive management system are effectively improved.

The invention discloses a distributed storage method and system for data security, and belongs to the technical field of data storage security, the method comprises the following steps: firstly, fragmenting original data, and generating a unique identifier for each data fragment; for each fragment, an encryption algorithm and key credentials are adaptively selected, and the key credentials are stored in a key management system. By performing homomorphic encryption on the key voucher, an encryption handle is generated, and efficient positioning and retrieval of the key are realized. According to the method, a differentiated encryption strategy is adopted, a most suitable encryption scheme is selected according to fragment characteristics, and encrypted data fragments are dispersed and stored in a plurality of distributed storage nodes. A global mapping index is constructed in a metadata management server, and a corresponding relation between an original data global identifier and metadata of each data fragment is recorded, including information such as identifiers before and after encryption, a storage position, an encryption algorithm, a key handle and the like. According to the method, the data leakage risk is effectively reduced, and the safety and reliability of the storage system are improved.

The invention discloses an intelligent management method and system for port and navigation Internet of Things data, and the method comprises the steps: generating a standardized data flow through a multi-modal data fusion model according to the heterogeneous features of ship navigation data, port equipment operation data and cargo information; generating an anti-interference transmission channel based on the standardized data stream; according to the real-time data received by the anti-interference transmission channel, dynamically generating a tamper-proof storage index through a trusted execution environment; extracting multi-source data based on the storage index, and generating a ship arrival time prediction model and a port resource scheduling strategy; and according to the port resource scheduling strategy, constructing a cross-department data sharing network through a federated learning framework and a zero-knowledge proof protocol, and generating a verifiable shared data set. According to the embodiment of the invention, port and navigation Internet of Things data management with reliable transmission, safe storage and collaborative intelligence can be realized, and the data management efficiency is improved.

The invention relates to the technical field of management and control systems, in particular to a digital intelligence system applied to collaborative management and control of water-power engineering construction participating units, which comprises a project data management module covering water-power engineering construction full life cycle management, extracting multi-source information data from various subsystems, and constructing a project view and a project management information base; the project risk analysis module is used for constructing an intelligent risk analysis model for risk analysis and generating a dynamic evaluation result, a graded early warning notification and an auxiliary decision scheme; the project collaborative management module is used for processing graded early warning notification and auxiliary decision-making schemes by using a multi-layer perceptron model, and generating finalizing service achievements and management process records; and the project document management module is used for performing compliance automatic checking and processing on the electronic documents needing to be archived, and dynamically updating and optimizing the project management information base. Through the closed-loop management and control system, the cooperative management and control efficiency of water-power engineering construction participation units is improved.

The invention discloses a block chain-based medical data management method, system and device, and a medium, and relates to the field of information management. The method comprises the following steps: acquiring medical data, analyzing content attributes and context information of the medical data through a first smart contract on a block chain, and generating a first sensitivity level identifier; based on the first sensitivity level identifier, performing differential encryption on the medical data through a second smart contract on the block chain, and generating verification information; partitioning the differentially encrypted medical data, constructing a data structure together with the verification information, and storing the data structure into a block chain; in response to the received access request, verifying an authority certificate in the access request and the type of the access request through a third smart contract on the block chain, and generating an access authorization certificate; and outputting target medical data corresponding to the access request based on the access authorization certificate. By implementing the technical scheme provided by the invention, the full-life-cycle safety management and control of the medical data from collection, storage to sharing is realized.

The invention discloses a cross-system heterogeneous metadata intelligent acquisition method and system based on LLM, and the method comprises the following steps: S1, collecting and preprocessing heterogeneous system data, and constructing a heterogeneous graph; s2, analyzing nodes by the large language model, and splicing structural features to form initial representation of the nodes; s3, constructing a heterogeneous graph Transform, executing multi-layer propagation and low-rank decomposition, and outputting final node representation; s4, generating a field alignment path, an interface mapping path and a dependency path, and planning an acquisition path and an acquisition sequence; and S5, executing an acquisition task, converting a structured format, writing into a metadata center, and performing closed-loop optimization. According to the method, intelligent acquisition, semantic analysis and automatic integration of cross-system heterogeneous metadata are realized, and the efficiency and intelligent level of metadata management in a multi-source data environment are greatly improved.

The invention discloses a dynamic authority management system and method based on multi-source salary data integration, and relates to the technical field of salary data management, and the method comprises the following steps: collecting role names, authority boundaries and operation granularity information from a plurality of business systems, and generating structured role semantic ontology entries based on a field-level semantic annotation mode; and disassembling the to-be-mapped role according to the authority dimension, calculating a semantic similarity index between the to-be-mapped role and the standard role based on the role semantic ontology library, and outputting a role consistency scoring matrix. According to the method, the authority difference is identified through the role semantic ontology and the similarity score, the minimum authorization judgment is realized in combination with the rule engine and reinforcement learning, the audit traceability and anomaly detection are guaranteed by using the block chain and the dynamic graph, and finally a strategy self-evolution closed loop is constructed. And the problems of permission mismatching and data leakage caused by role semantic inconsistency are effectively solved.

The invention relates to a medical information processing and intelligent data management technology, and discloses a hospital multi-source heterogeneous data integration management system and method based on an EMPI, and the system carries out the real-time subscription and batch extraction of the data of an HIS, an EMR, an LIS, a PACS, a DRG and a pre-hospital first-aid system through an interface adapter, and generates a unified main index identifier through the matching of the EMPI, and carries out the real-time subscription and batch extraction of the data of the HIS, the EMR, the LIS, the PACS, the DRG and the pre-hospital first-aid system. Field-level cleaning, standardization and semantic mapping are carried out on the free text and the structured data, an intermediate standardized record set is formed, an event graph is constructed, event cluster recognition is carried out in combination with time, clinical entities, doctor seeing scenes and department similarity, consistency judgment and EM iterative fusion are carried out on the basis of data source reliability, and event cluster recognition is carried out. And outputting a unified patient file set and a downstream service interface. According to the invention, high-precision integration, standardized management and traceable application of multi-source data are realized, and a reliable data basis is provided for clinical decision support, medical insurance management and scientific research.

The invention belongs to the technical field of data storage, and discloses a multi-source marine environment data storage method and system based on HDF5. According to the method, a hierarchical storage framework is constructed, a domain-type-source three-level directory architecture is constructed, a space-time dimension dynamic extension mechanism is executed, and space-time composite coding is performed; designing an HDF5 nested packet storage architecture, wherein grid topological structure definition, dynamic resolution self-adaptive storage, multi-source data processing and metadata management are carried out; constructing distributed data association and indexes, including data standardization preprocessing and cross-source data association; the storage performance is optimized and expanded, wherein density sensitive blocking and layered compression are carried out. According to the method, redundant storage of a high-latitude region is greatly reduced, and dynamic adaptation of a local encryption grid is supported. According to the invention, open circulation and collaborative utilization of interdisciplinary data resources are facilitated.

The invention discloses a data management system and method based on distributed cloud storage, and relates to the technical field of distributed cloud storage, and the system comprises an access log collection module, a node state monitoring module, a data thermal evaluation module, a redundancy strategy decision module and a storage execution scheduling module. A fragmentation access behavior is recorded through an access log acquisition module, a node state monitoring module acquires a node resource state in real time, and a data thermal evaluation module constructs a three-dimensional thermal model based on an access frequency, a network hop count and a storage cost to calculate a thermal value and supports dynamic weight adjustment; the redundancy strategy decision module divides the fragments into high frequency, medium frequency and low frequency according to the thermodynamic value, and single copy + local cache, erasure code storage and dynamic adjustment strategies are adopted respectively; the storage execution scheduling module executes fragmentation operation and optimizes reading node selection, and data access efficiency is improved through load awareness and a bandwidth-delay joint model; according to the invention, dynamic balance between data access efficiency and storage cost is realized.

The invention discloses an electric power marketing management information platform daily electric power fitting method and related equipment, and relates to the technical field of electric power data management, and the method comprises the steps: obtaining historical load data, external environment data and equipment operation state data of a target region; constructing an initial load fitting model based on the historical load data; extracting a date characteristic factor according to a preset time classification rule, and dynamically correcting the initial load fitting model based on the date characteristic factor to generate a corrected load model; generating a multi-source fusion feature based on the external environment data and the equipment operation state data; and inputting the multi-source fusion features into the corrected load model, and outputting a target load prediction result.

The invention relates to the technical field of data management, in particular to a low-altitude economic flight data management method and system based on edge computing, and the system comprises edge computing nodes deployed on an aircraft and a ground base station, a sensor for collecting multi-source data, a module for preprocessing the data, and an annular data queue caching mechanism. The system comprises a composite biological feature code generation module, a distributed storage edge node, an abnormal fluctuation feature extraction module, an equipment health state and trend analysis and calculation module, a virtual power supply manager, a main power supply, a standby power supply, an abnormal behavior monitoring module and a defense strategy library. After preprocessing and caching, feature codes are generated and encrypted distributed storage is carried out, dynamic resource adjustment is realized through state evaluation and a digital twinning and optimization algorithm, a neural network is utilized to manage a power supply, data security is guaranteed in combination with abnormal monitoring, and a whole-process management system is formed.

A management server system may obtain data associated with a vehicle. The management server system may obtain the data from a plurality of data sources associated with the vehicle. The data may include a plurality of subsets of data that each correspond to correspond to a particular driver assignment category. Each subset of data may identify a particular persona as a driver of a vehicle. The management server system may determine a driver of the vehicle based on each subset of data and a hierarchical plurality of driver assignment categories. Based on the determination of the driver of the vehicle, the management server system can dynamically map the driver to a particular event. The management server system may generate a user interface identifying the driver and the event.

Methods and systems for managing operations of a data processing system are disclosed. To manage operations of the data processing system, a management controller of the data processing system may obtain validated location data for the data processing system via an out-of-band communication channel. The management controller may identify applicable policies based on the validated location data. If the management controller identifies a policy applicable to a geographical location of the data processing system, then the management controller may perform an action set to manage operation of the data processing system based on instructions associated with the applicable policy. The updated operation of the data processing system may increase the security of sensitive data managed by the data processing system.

The invention discloses a supply and demand data management system based on human resources, and relates to the technical field of human resource management, and the system comprises a human resource management center which is in communication connection with a data collection module, a knowledge graph construction module, a post supply and demand matching module, a dynamic adjustment optimization module and a user interaction module. Wherein the modules are connected through electric signals, and the data collection module is used for collecting and preprocessing human resource supply and demand data from different channels. By constructing the knowledge graph based on recruitment data and employee information, the matching relationship between post demands and job seeker skills can be accurately identified, the efficiency of human resource allocation is remarkably improved, and compared with a traditional manual matching mode, the system can quickly analyze a large amount of data, automatically generate post matching coefficients, and improve the efficiency of human resource allocation. And the matching degree is quantitatively evaluated, so that the key post is ensured to obtain the most appropriate talent configuration, and the recruitment cycle is shortened.

The invention discloses an adaptive protocol stack reconstruction and transaction-level data control method for 5G communication, and aims to solve the technical problems of fixed protocol stack structure, coarse transmission control granularity and the like of an existing communication module. The method comprises the following steps: firstly, analyzing an application layer communication session initialization instruction, generating a communication task label, acquiring 5G network environment state data in real time, and constructing a network state feature vector; then, the communication task label and the network state feature vector are input into a protocol mapping decision map, a protocol reconstruction instruction is generated, loading and unloading of a protocol module in a protocol stack resource pool are controlled, a dynamically-adaptive protocol path is constructed, and a transaction identifier is allocated to the protocol path; and establishing a transaction-level data buffer area based on the transaction identifier, performing priority marking on the data packet, and executing differentiated dynamic flow control operation according to the network state feature vector and the priority label, thereby realizing high-reliability and low-delay 5G communication data management.

The invention relates to the technical field of RFID smart tags, and discloses an RFID smart tag positioning and tracking printing method and system, and the method comprises the steps: inputting an RFID tag radio frequency signal into a conditional variation automatic encoder for convolution processing and attention weighting, and obtaining an RFID tag global feature vector; establishing a layered sensor node network to perform multi-dimensional acquisition on environmental parameters to obtain an environmental spatio-temporal data set; inputting the global feature vector of the RFID tag and the environment spatio-temporal data set into a deep fusion network for feature fusion to obtain a multi-modal fusion feature; performing sequence modeling based on the multi-modal fusion features to obtain an article trajectory prediction model; the object track prediction model is applied to a target area grid coordinate system for density distribution calculation, a real-time object positioning heat map and a track database are obtained, an efficient object positioning heat map generation and track data management mechanism is established, and real-time position visualization and historical track query are facilitated for the system.

According to the archive data tracking and multi-party cooperation auditing method based on the block chain smart contract provided by the invention, the authenticity and non-tampering property of archive data are guaranteed through a block chain technology, and an efficient and transparent auditing process is realized in combination with the smart contract. According to the method, a multi-level encryption storage and unique identifier generation mechanism of archive data is designed and is used for accurately tracking an archive circulation process; the access behavior is automatically recorded and verified through the intelligent contract, and the operation compliance is ensured. A distributed consensus algorithm is adopted for multi-party cooperative auditing, multiple auditing parties are allowed to participate together, and meanwhile objectivity and authority of auditing results are ensured. The method improves the safety, transparency and efficiency of archive data management and auditing, and can be widely applied to archive management and auditing scenes in the fields of governments, enterprises, education and the like.

An AI-driven centralized orchestration system (100) with MCP protocol for real-time compliance and risk data management, including: a. a centralized integration and orchestration platform configured to connect heterogeneous enterprise IT systems through standardized API connections and execute automated workflows; b. a variety of domain-specific artificial intelligence (AI) agents that interface with IT service management (ITSM), vulnerability management, and endpoint and asset management platforms for data collection, analysis, and assessment; c. a Multi-Agent Communication Protocol (MCP) layer that enables structured communication, negotiation and coordination between AI agents in real time; d. a data consolidation module configured to aggregate, standardise and align heterogeneous data into a unified repository using machine learning models; e. a compliance reporting module for dynamically generating and distributing audit-ready compliance reports based on AI-analyzed data and triggered workflows; f. an alerting module configured to deliver context-dependent predictive notifications of compliance violations or risk anomalies through various communication channels; g. a predictive dashboard module capable of displaying compliance status, risk metrics, and proactive insights in real time via AI-driven visualization tools; i.e., where the orchestration platform, AI agents, and MCP layer together enable automated, scalable, and proactive compliance and risk actions.

The invention relates to a battery fault diagnosis large language model algorithm based on semantization and a battery interaction management platform. The algorithm comprises the following steps: cleaning and processing real-time data of a new energy automobile battery; carrying out the selection design of related statistical characteristics according to the real-time data of the new energy automobile battery; constructing battery fault diagnosis semantics and a fine tuning data set which are respectively used for instruction input and fine tuning training of the large language model; performing fine tuning on the pre-trained large language model to obtain a fine-tuned battery fault diagnosis large language model; deploying the fine-tuned battery fault diagnosis large language model and performing reasoning diagnosis on real-time data; and establishing a battery knowledge database, a retrieval knowledge base and an intelligent analysis and interaction battery fault diagnosis platform. Under the condition of small samples, by combining the functions of a large model, stronger fault interpretability and intelligent battery data management and maintenance capability are provided, and the method has the advantages of good generalization and accurate fault detection.

The invention belongs to the technical field of financial data management, and particularly discloses a financial multi-source protocol self-adaptive fusion system based on AI semantic understanding and a knowledge graph, which comprises the steps of avoiding fusion errors caused by semantic misunderstanding through deep semantic analysis and a conflict resolution decision based on the knowledge graph; when protocol version updating is detected, incremental learning and model adjustment are carried out based on a newly added sample and historical experience, and a fusion protocol standard is dynamically updated, so that the high adaptive capacity to dynamic change of a financial protocol is realized; an exception monitoring and repairing mechanism is introduced, data missing, format errors and other exceptions are found in time and repaired online based on historical data modes and business logic, and negative influences of abnormal data on downstream risk control, transaction decision making and other key business links are avoided; through deep collaboration and information feedback among the intelligent modules, an intelligent system capable of self-learning and evolution is constructed.

The invention discloses an AI-based medical and health care integrated data management method and system and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the data preprocessing and data standardization of collected multi-source medical and health care data, and obtaining a standardized medical data set; performing classification and semantic annotation on the data of the standardized medical data set by using a preset medical ontology, and constructing a structured medical knowledge graph; performing virtual mapping based on the structured medical knowledge graph by adopting a digital twinborn model to form a virtual medical twinborn body; based on the virtual medical twins, combining real-time monitoring data and historical patient flow data, through multi-dimensional feature extraction and pension mode recognition, dynamically optimizing and presetting a personalized medical scheme and a resource scheduling strategy, and outputting a medical care service optimization scheme; generating a target service list in combination with the analyzed doctor-patient dialogue text, and distributing the target service list to a preset pension service cooperation terminal; the method has the effect of improving the real-time performance and the accuracy of the old people medical care service strategy.

A data management system may include data connectors configured to establish connections with access control systems and receive heterogeneous metadata related to the data access history. The system may include a transformer that stores graph objects in memory. The graph objects may include application account nodes representing application accounts associated with the domain and resource nodes representing data resources associated with the domain. The system may further store event objects. The system may render for display a data access graph that illustrates a data permission traversal path from a source node to a particular data resource. The data permission traversal path may include a graphical representation representing the particular application account having permission to access the particular data resource. At least a portion of the graphical representation may be rendered according to the data access activity level of the particular application account accessing the particular data resource.

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 discloses a block chain-based carbon emission factor data traceability management system, particularly relates to the technical field of cross-supply-chain carbon data management, and is used for solving the problem that cross-enterprise / cross-industry effective association of carbon emission data under an existing single-chain architecture cannot be realized. The problems that the whole life cycle carbon emission data of the same product is repeatedly calculated and accounting boundaries are overlapped are solved; the method comprises the following steps: acquiring a carbon emission factor data packet of each participant through a data acquisition module; the block evidence storage module writes the data packet into a block chain to generate a non-tampering block; the cross-chain identification module creates a cross-chain traceability identifier containing a product batch number and an arrangement stage mark for the block; the coherence detection module analyzes data coherence during cross-chain request, and if the data coherence is lower than a threshold value, cross-chain verification based on matching of the mark and the batch number is triggered; the batch verification module executes repeatability verification on data in different stages of the same batch after verification is passed; and the traceability integration module integrates the verification data to generate a global carbon footprint traceability record and stores the global carbon footprint traceability record to a cross-chain shared account book.

Provided in the present invention is a ship hatch data management method based on point cloud technology. The method is implemented by means of a constructed ship hatch data management system, and the system comprises a ship scanning module, an automatic hatch identification and calculation module, a ship attitude data compensation module, and a hatch data calibration and accumulation module. In the present invention, by means of processing data of a scanner and analyzing point cloud data, a point cloud model of a ship to be subjected to operation is generated in combination with mechanism parameters of a ship loader, the position of a ship hatch is automatically identified, the spatial coordinates of the ship hatch in a rectangular coordinate system of wharf space are automatically calculated, hatch identification data for current berthing is calibrated on the basis of historical hatch data records from the same hull number after berthing in a database, and the ship loader is guided to realize unmanned and automated operation modes by means of the calculated hatch position, thereby enhancing the level of port automation.

The invention relates to a multi-agent medical diagnosis and treatment system which comprises a plurality of agents. The plurality of agents comprise: a task planning agent analyzes input content and generates a corresponding task process, and the task planning agent sequentially issues task instructions to a data management agent, a tool use agent and a medical decision agent according to the task process; the task instructions comprise a data task instruction, a tool task instruction and a decision task instruction; the data management agent extracts patient data from the database and sends the patient data to the task planning agent according to a data task instruction issued by the task planning agent; the tool using agent performs feature extraction processing on the patient data according to the patient data and the tool task instruction issued by the task planning agent so as to obtain key features and send the key features to the task planning agent; and the medical decision-making agent carries out diagnosis and treatment reasoning according to the key features and the decision-making task instruction issued by the task planning agent, and a diagnosis report is obtained and displayed.

Systems and methods are disclosed for preserving patient privacy while allowing health data to be analyzed, managed, and stored in different geographical areas. One method for managing cross-border health data while preserving patient privacy includes: receiving a DICOM object from a hospital computing device for analysis; generating a unique case identifier for the DICOM object; validating the received DICOM object; if, based on the validation, the received DICOM object is valid, anonymizing the received DICOM object; updating the anonymous DICOM object to include the unique case identifier; compressing the updated DICOM object; and sending the compressed DICOM object to at least one data analysis web service(s).