275 results about "Data scatter" patented technology

The invention discloses an insurance intelligent decision engine system based on a multi-modal user portrait, and relates to the technical field of insurance industry, the system comprises a semantic representation space construction unit used for performing feature decoupling on collected multi-modal data by using variational modal decomposition, extracting modal features, and constructing a semantic representation space based on each modal feature; a user portrait generation unit; a user classification result acquisition unit; and the insurance decision-making unit is used for analyzing the multi-source health data in the user portrait by using a cross-modal alignment technology, constructing a layered health risk assessment model, and generating an insurance recommendation strategy and a risk avoidance scheme in combination with a user classification result. According to the method, resource waste and efficiency loss caused by scattered storage and repeated development of data are avoided through multi-modal data fusion and construction of a unified semantic representation space; and in combination with a hierarchical label system, the user portrait can be automatically generated, and the intelligent level of insurance business is enhanced.

The invention discloses an intelligent environment monitoring and regulation method for a marine ranch, and belongs to the field of environment monitoring, and the method comprises the steps: collecting water body parameters, employing a data fusion algorithm to generate a comprehensive environment state index, and solving the business problems of data dispersion, response lag and inaccurate adjustment in water body environment monitoring and regulation. A time sequence analysis model and an optimization algorithm are combined, potential anomalies are analyzed, a risk change trend is predicted, environment adjustment requirements are dynamically calculated, a precise regulation and control instruction set is generated and transmitted to equipment to be executed, and meanwhile, through deviation comparison between real-time feedback data and a preset threshold value, comprehensive indexes and regulation and control parameters are iteratively updated, so that environment stability is ensured. Through multi-level data processing and a self-adaptive adjustment mechanism, the timeliness and accuracy of water body environment regulation and control are remarkably improved, closed-loop management from monitoring to optimization is achieved, and efficient support is provided for intelligent decision making in a complex environment.

The invention discloses an intelligent fire-fighting risk prediction and dynamic early warning method and system based on multi-source data fusion, and relates to the technical field of intelligent fire-fighting risk prediction, and the method comprises the steps: collecting multi-source fire-fighting data, and constructing a fire-fighting safety state multi-dimensional data matrix; constructing a risk prediction model based on the fire safety state multi-dimensional data matrix to carry out real-time risk scoring; and executing dynamic early warning through a risk prediction result. According to the method, through the multi-source data acquisition and fusion module, multi-type fire-fighting data are comprehensively acquired and standardized, a structured and multi-dimensional fire-fighting safety state matrix is constructed, and the problems of data dispersion and information splitting are solved. In combination with a risk collaborative prediction and scoring module, the risk level of each region is dynamically output based on multi-factor analysis, and the accuracy and foresight of risk prediction are improved. Through a dynamic early warning generation and linkage module, real-time grading early warning and linkage of a fire fighting system are realized, and rapid response and intelligent prevention and control of a high-risk area are realized.

The invention relates to an intelligent marketing content generation and optimization system, and belongs to the technical field of artificial intelligence and digital marketing. According to the system, through cooperative operation of the data acquisition module, the intelligent text generation module, the multi-modal synthesis module, the risk management and control module and the dynamic optimization module, whole-process closed-loop management of marketing content is realized. The data acquisition module captures unstructured data from a multi-source platform based on a user authorization protocol, semantic cleaning and structured processing are performed through a large model interface, and the problems of data dispersion and fragmentation are solved. The intelligent text generation module receives user parameters through an interactive interface, matches a preset prompt word bank, calls a large model interface to generate multi-version copywriting in batches, and supports concurrent processing of single-choice or multi-choice product lists. The multi-modal synthesis module extracts keywords according to copywriting semantics, matches pre-annotated visual materials and generates multilingual speech paraphrases, so as to ensure the consistency of graphic and text information. The risk management and control module intercepts sensitive content in real time based on an industry rule base, and guarantees output compliance. And the dynamic optimization module integrates the user behavior data to generate a delivery strategy, updates a prompt word bank and a generation model through a closed-loop feedback mechanism, and realizes dynamic adaptation of contents and market demands. Compared with a traditional method, the system has the advantages that the content generation efficiency, the cross-modal matching precision and the compliance control level are remarkably improved, and the system is suitable for the global digital marketing requirements of multiple industry scenes such as e-commerce, industrial equipment and cross-border trade.

The invention discloses an offshore wind power fault monitoring method based on a knowledge graph and digital twinning, and aims to solve the problems that multi-source data acquisition is dispersed, the transmission delay is high, and real-time convergence and integration are difficult to realize in the operation state monitoring of offshore wind power equipment. According to the invention, the following modules are provided: a multi-source data acquisition layer is used for solving the problems of dispersed data acquisition and transmission lag and ensuring the real-time performance; the knowledge graph construction module is used for solving the problems of extraction, fusion and storage of equipment entity relationships; the digital twin modeling module realizes visual presentation and accurate simulation of the state of physical equipment; the fault monitoring reasoning module solves the problems of anomaly detection and root cause positioning; the intelligent early warning decision module determines an early warning level and efficiently matches a solution; the visual interaction module solves the problems of scattered information display and poor linkage, supports third-party docking, realizes accurate early warning and root cause positioning, improves the decision-making efficiency, adapts to severe environments, supports large-scale wind power plant monitoring, and reduces the operation and maintenance cost.

According to the industrial solid waste multi-target collaborative management method and system based on the digital twinborn and hybrid optimization algorithm, industrial solid waste data are collected in real time through an Internet of Things sensor, a dynamic digital twinborn model is constructed to simulate a physical process, and the problems of data dispersion and lag in a traditional method are solved; establishing a multi-objective optimization function by combining three major objectives of economy, environment and society, and generating a Pareto optimal strategy set by adopting an improved NSGA-II and particle swarm optimization (PSO) hybrid algorithm; the method combines historical and real-time data through a twin model, employs an LSTM algorithm to synchronously predict the type and quantity of solid wastes, the equipment operation state and the environment change, achieves the dynamic simulation and prediction of the whole process of solid waste generation, transportation and processing, remarkably improves the data integration efficiency, provides precise real-time support for decision making, and improves the real-time performance of the system. The treatment cost is reduced, the carbon emission is reduced, and the public satisfaction is improved; the strategy response time is shortened through dynamic model correction, an intelligent solution is provided for industrial solid waste management, and the function of multi-dimensional collaborative optimization of industrial solid waste management is achieved.

The invention discloses a law query system based on big data, and relates to the technical field of computer science, and the law query system comprises a multi-source data acquisition module, a data processing module, a knowledge graph construction module, a dynamic semantic retrieval module, an intelligent analysis engine module and a security and combination scale module, the system has the advantages that the problems of dispersity and credibility of legal data are remarkably relieved through the multi-source data collection module and the block chain evidence storage technology, in the claims, the multi-source data collection module is in communication connection with a court public database, a legal library and an academic periodical platform, the legal data are captured through distributed crawlers, and the legal data are stored in the block chain evidence storage technology; by means of the design, the system can widely collect legal information from different channels, a comprehensive and credible data basis is provided for legal practitioners and researchers, the legal practitioners and the researchers do not need to spend a large amount of time to verify the authenticity and accuracy of data when querying and analyzing the legal information, and the legal practitioners and the researchers can check the authenticity and accuracy of the data. And the working efficiency and the research quality are improved.

The invention discloses an AI-based digital project performance evaluation data processing method and system, and relates to the technical field of artificial intelligence and digital project management, and the method comprises a multi-source data collection module which is used for obtaining data; the entity alignment module is used for establishing an association relationship among cross-system data entities; the dynamic index generation module is used for dynamically adjusting the evaluation index weight by utilizing a reinforcement learning framework; the efficiency prediction module is used for modeling a task dependency relationship according to the time sequence diagram convolutional network and outputting a delay risk probability; and the visual interface is used for displaying the data. According to the method, cross-system entity alignment, dynamic index weight adjustment, task delay risk prediction and root cause analysis are realized through AI technologies such as BERT semantic matching and a graph neural network, visual data display and interaction functions are provided by virtue of a visual interface, the problems of data dispersion, index static state, risk lag and the like in traditional project evaluation are solved, and the project evaluation efficiency is improved. And the decision support capability of project management is improved.

The invention provides a method, a device, equipment and a medium for generating an engineering project management digital model, and the method comprises the steps: collecting original data related to engineering project features, carrying out the preprocessing, forming a standardized project data set, constructing a space-time reference frame based on the data set, fusing a multi-dimensional feature tensor of multiple engineering features, and carrying out the construction of a space-time reference frame. The method comprises the steps of generating a project progress node and an integrated feature tensor, fusing the project progress node and the integrated feature tensor to generate a multi-source association graph containing entity relationships and feature semantics, generating a verified engineering project management digital model according to the project progress node, the integrated feature tensor and the association graph, and dynamically updating and optimizing the model in response to change data in project execution. According to the method, the problems of data dispersion, lack of association and static stiffness of the model in a traditional method are solved, automatic construction and dynamic evolution from multi-source heterogeneous data to an intelligent decision-making model are realized, and the accuracy, real-time performance and intelligent level of project management are remarkably improved.

The invention relates to the technical field of communication network operation and maintenance, in particular to a 5GC core network-oriented network health degree assessment method and system, and the method comprises the following steps: multi-source data collection and preprocessing, multi-dimensional health assessment model construction, and dynamic verification and report generation. The method has the beneficial effects that the problems of data dispersion and single evaluation dimension in a traditional method are solved, intelligent and multi-dimensional dynamic evaluation of the network health degree is realized, and the operation and maintenance efficiency and the risk pre-judgment capability of the core network are remarkably improved.

The invention discloses a business log analysis method and device, electronic equipment and a storage medium, and relates to the technical field of log analysis. Generating target log data containing a target field according to related log data of each transfer node in the business creation transfer process, the target field comprises an identification field of the current transfer node, an identification field representing an association relationship between the current transfer node and other transfer nodes in a business creation transfer process, and a target log content field corresponding to the current transfer node; creating an index for the target field in a search engine; and when the query service for the target field content is received, the queried target log content associated with the target field content is aggregated and fed back to the query end, so that the problems that the log data of each node is dispersed, and the related log data cannot be quickly analyzed and then quickly positioned are solved.

The invention relates to the technical field of digital twinborn management, and discloses a full-life-cycle digital twinborn management system and a modeling method. A model driving unit; a decision optimization unit; and a credible evidence storage unit. The modeling method comprises the following steps: S1, analyzing a product design bill of materials; s2, establishing a topological mapping relation between the sensor nodes and the virtual model area; s3, running Monte Carlo simulation to predict the defect probability; and S4, binding and uploading the new virtual model version and the physical product serial number. Aiming at the problem of data dispersion in the prior art, the system automatically converges three types of heterogeneous data of geometric dimension design, working condition manufacturing and maintenance monitoring into a shared cache pool through a main data table of a unified metadata structure, so that cross-stage semantic alignment and time sequence synchronization are realized, data format difference is eliminated, and data consistency is remarkably improved.

The invention discloses an intelligent carbon anode quality detection system, particularly relates to the field of electrolytic aluminum, and comprises a data acquisition module, a data preprocessing module, a data analysis module and a comprehensive judgment module. According to the method, a full-process data acquisition system covering raw materials, forming, roasting and appearance is constructed, accurate acquisition of multi-source data is realized by using equipment such as an X-ray fluorescence spectrometer and a hydraulic sensor, the problem of dispersion of traditional detection data is solved, and the detection accuracy of the multi-source data is improved through multi-stage pretreatment methods such as outlier elimination, sliding window filtering, temperature compensation and wavelet noise reduction. Dimension difference and sensor noise interference are effectively eliminated, and data reliability is improved. A multi-level evaluation model composed of a raw material comprehensive index, forming energy density, roasting maturity and appearance integrity is innovatively established, and intelligent comprehensive evaluation and accurate grading management and control of the carbon anode quality are achieved in combination with a dynamic weighting comprehensive quality index formula and a four-level grading mechanism.

The invention relates to the technical field of chemical production monitoring, and discloses a cloud computing-based chemical production monitoring system, which is characterized in that an on-site data acquisition module is used for acquiring chemical production data in real time and carrying out filtering and denoising processing to obtain preprocessed data; the network transmission module is used for encrypting the transmitted data and reducing the data transmission quantity by adopting a data compression technology; the cloud computing platform module is used for dispersedly storing the data on a plurality of storage nodes by utilizing a distributed storage technology, classifying the data, analyzing the data in real time by adopting a streaming computing technology, detecting the abnormal condition of the data, and immediately triggering an alarm mechanism when the abnormal condition exceeds a preset safety threshold value; the monitoring application module is used for displaying various parameters and equipment operation states, and providing decision suggestions for production optimization in combination with a chemical production process and equipment; the production efficiency can be improved, the production cost can be reduced, the product quality can be improved, and the market competitiveness of enterprises can be enhanced.

The invention relates to the technical field of ground disaster prevention and control report generation, in particular to an intelligent ground disaster prevention and control report generation method and system based on indoor and outdoor work integration. Retrieving geological information of the associated area, and determining the type of a hidden danger point; matching a target template; generating a target template directory structure; calling a workflow agent module according to a directory structure sequence to generate a first draft text; inserting chart data into the first draft text to obtain a complete report; and performing compliance examination and optimization on the complete report, and outputting a final report. The generation system comprises a data acquisition module, an intelligent retrieval engine, a template management unit, a workflow scheduling center and an examination optimization module. The data acquisition module, the intelligent retrieval engine, the template management unit, the workflow scheduling center and the review optimization module are connected in sequence and realize data transmission; synchronous real-time updating of indoor and outdoor data is met, data dispersion and information omission are avoided, and the generation efficiency and accuracy of a ground disaster prevention and control report are improved.

The invention relates to the technical field of power two-ticket management, and discloses a two-ticket full life cycle optimization and management method and system based on workflow, and the method comprises the steps: obtaining the basic data of personnel qualification, equipment state and flow rule, and constructing a typical work ticket library and a typical operation ticket library; calling a work ticket template or an operation ticket template to perform information supplement, performing double verification, and then completing graded auditing and electronic signature according to preset nodes to generate an effective work ticket and an executable operation ticket; and monitoring the execution process of the effective work ticket and the executable operation ticket, and archiving execution data to a historical database to realize multi-dimensional two-ticket full-process data query, generation of an analysis report, update of basic data, a work ticket typical ticket library and an operation ticket typical ticket library. The standardized typical ticket library is constructed by integrating basic data, monitoring and archiving traceability of two tickets are achieved, standardized intelligent management of the two tickets is achieved, and the problems that existing data are scattered, compliance is poor, traceability is difficult, and no improved closed loop exists are solved.

The invention relates to the technical field of VR, AI and psychological therapy crossing, and discloses a psychological universe intelligent psychological tutoring integrated platform which comprises a holographic sensing module used for acquiring multi-modal data of a user in real time; the intelligent psychological engine module is used for receiving and analyzing the multi-modal data and generating a multi-dimensional psychological state vector; and the dynamic meta universe scene and personalized intervention module is used for adjusting virtual scene parameters and behaviors of the intelligent non-player character in real time according to the multi-dimensional psychological state vector. According to the method, multi-modal data such as behaviors, eye movement and physiology are acquired and deployed at edge computing nodes, and attention weight calculation is adopted to carry out weighted fusion and comprehensive analysis on the multi-modal data, so that a unified multi-dimensional psychological state vector is generated; therefore, the technical defects that in the prior art, data are dispersed, and effective integrated analysis cannot be carried out are overcome, and objective, quantitative and comprehensive evaluation on the psychological state of the user is achieved.

The invention provides an agricultural material data collaborative recommendation method, which comprises the steps of establishing a data standardization model based on a data dispersion problem in a multi-subject system, and unifying formats and structures of data of different sources; mapping the agricultural material related data of the multiple subjects into a unified data framework; obtaining an agricultural material demand input by a farmer through a collaborative query algorithm, and generating an initial scheme of an agricultural material combination in combination with multi-dimensional agricultural knowledge; analyzing the historical data by adopting a machine learning algorithm to generate an agricultural material recommendation model; and generating an agricultural material combination scheme according to the agricultural material recommendation model and presenting the agricultural material combination scheme in a visual mode.

The invention discloses a human and house data comprehensive treatment method, system and equipment based on a multi-level address model, and a medium, belongs to the technical field of data treatment, and aims to solve the technical problem of how to effectively integrate human and house data sources of multiple parties and improve the accuracy, consistency and availability of human and house data. The defects that in the prior art, people and house data are scattered, address description is not standard, the incidence relation is inaccurate, data quality is uneven and a unified identification system is lacked are overcome. According to the technical scheme, the method comprises the steps that a five-level core data table comprising a community table, a building table, a house table, a people and house relation table and a personnel information table is constructed; the method comprises the following steps: accessing original human and house data from a plurality of data sources, performing intelligent analysis and standardization processing on address information, and obtaining data after standardization processing; establishing a house unique identification system and a human-house multi-dimensional relation model based on the standardized data; evaluating and repairing the data quality; and standardized human and house data service is provided for the outside through the data service interface.

The invention discloses an optical fiber network intelligent regular checking and fault closed-loop processing system, method and device, and belongs to the technical field of optical fiber communication network intelligent operation and maintenance. The method comprises the following steps: collecting and fusing multi-source heterogeneous data such as resource management, fault network management, distributed sensing and geographic information; a multi-modal model based on a convolutional neural network and a graph neural network is utilized to analyze fusion data, meter-scale accurate positioning of faults is achieved, and a regular inspection plan is dynamically optimized by adopting a long and short-term memory network model; and based on an analysis decision result, a fault list, a mode list and a maintenance list are automatically created, circulated and associated, and a whole-process closed loop from diagnosis list sending to repair verification is realized. According to the scheme, the problems of data dispersion, single analysis dimension and lack of closed loop in the process in the prior art are solved, and the accuracy, efficiency and automation level of optical fiber network operation and maintenance are remarkably improved.

The invention discloses a power generation equipment intelligent diagnosis method and system fused with a knowledge graph, and relates to the technical field of equipment diagnosis. The method comprises the following steps: collecting multi-source operation data and historical fault records of power generation equipment, and constructing a power generation equipment fault knowledge graph; real-time operation data of the power generation equipment are monitored in real time, feature extraction and semantic association are carried out on the real-time operation data of the power generation equipment based on the power generation equipment fault knowledge graph, and a power generation equipment operation state vector is generated; reasoning and analyzing the operation state vector of the power generation equipment, and mining a potential fault mode and an equipment fault causal chain of the equipment; and performing fault positioning diagnosis based on the equipment potential fault mode and the equipment fault causal chain, and determining a power generation equipment diagnosis result. The technical problem that in the prior art, operation data of power generation equipment are scattered, and fault mechanisms are difficult to express explicitly, so that the diagnosis accuracy is low is solved, and the technical effect that potential fault modes are intelligently mined through the graph neural network, so that the fault diagnosis accuracy is improved is achieved.

The invention discloses an industrial and commercial electric charge optimized charging method based on big data analysis, and the method comprises the following steps: S1, multi-source data collection and preprocessing: collecting power utilization data of industrial and commercial users, user equipment operation logs and block chain node transaction data, and constructing a multi-dimensional data set; s2, feature extraction and completion; s3, dynamic prediction and optimization; s4, generating a personalized strategy; s5, performing feedback driving iterative optimization; the invention belongs to the technical field of power system optimization, and aims to solve the problem that power grid load data, user equipment operation logs and block chain transaction data are dispersed and independent and lack of effective integration in the prior art. The method has the technical effects that through a complete chain of data integration, feature fusion, dynamic optimization, credible execution and closed-loop iteration, full-period intelligent optimization of industrial and commercial electricity charges is realized, and the method has economical efficiency, stability and user friendliness.

The invention relates to the technical field of data measurement and calculation, in particular to an ecological system carbon source sink rapid calculation method for a mining area scale. The method comprises the following steps: acquiring mining area remote sensing image data, ground actual measurement data and mining area mining activity records, and constructing a multi-source mining area basic data set; performing spatial registration and time alignment on the multi-source mining area basic data set to obtain an aligned multi-source fusion data set; based on the aligned multi-source fusion data set, mine occupied map spots are identified, land utilization type information of the map spots is extracted, a land utilization type data set is formed, and a carbon library classification data set is generated in combination with mining area carbon library type definition; therefore, by integrating multi-source data, optimizing space and time alignment and refining the carbon reserve calculation process, the problems of data dispersion, inaccurate calculation and the like in a traditional method are solved, and the scientificity and reliability of carbon source sink measurement and calculation of the mining area ecosystem are improved.

The invention relates to the technical field of radio frequency chip performance testing, and particularly provides a real-time visualization method and visualization system for radio frequency chip performance testing, traditional single-thread sequence control is replaced by a multi-thread asynchronous acquisition architecture, and the testing efficiency is remarkably improved; through adding a timestamp label mechanism to each piece of test data, the cross-device data synchronization precision reaches a microsecond level, and the problem of asynchronous triggering of a radio frequency signal and direct current bias is solved. The radio frequency index data table constructed by automatic association realizes intelligent aggregation analysis of multiple parameters under multiple combinations, and avoids manual matching errors caused by data dispersed storage in a traditional scheme. Based on an automatic threshold setting and real-time judgment function of a test protocol, intelligent switching of judgment standards under a multi-protocol standard is supported, errors caused by manual configuration are reduced, and modification during protocol updating is avoided. And real-time visual rendering enables a user to dynamically observe a multi-parameter association change trend, so that the problem positioning efficiency is improved.

The invention provides an aviation maintenance data management method and management system, and belongs to the field of data management.The method comprises the steps that fields of multi-source aviation maintenance data are unified, an aviation maintenance data set is generated, and the incidence relation between aviation maintenance services and preset aviation maintenance standards is built; according to the incidence relation, a business object relation method BOR is adopted to conduct logic modeling on the aviation maintenance data set, business objects of the aviation maintenance data set and the dependency relation of the business objects are defined through a modeling language, and a multi-dimensional aviation maintenance data model is generated; and storing the multi-dimensional aviation maintenance data model and the association relationship in an aviation maintenance standard library, and realizing dynamic updating and verification of the aviation maintenance data based on the multi-dimensional aviation maintenance data model and the association relationship. The series of measures fundamentally solve the problems of data dispersion and standard chaos, so that the maintenance data has a unified storage specification.

The invention discloses a new media operation optimization method and system based on a data closed loop. The system comprises a data acquisition module, a three-dimensional label system module, an intelligent analysis module and a closed loop optimization module. The data acquisition module synchronizes core operation data through an API, and captures unstructured comment data through an RPA; the three-dimensional tag system module is used for carrying out tagging processing on platform characteristics, content forms and user behaviors on the data; the intelligent analysis module generates and outputs optimization suggestions through content diagnosis, flow prediction and strategy; and the closed-loop optimization module feeds back an analysis result to an external content generation system, and new content data is transmitted back to form a closed loop. According to the system, the problems of operation data dispersion, insufficient analysis and optimization lag are solved, automatic data acquisition, structured analysis and dynamic optimization are realized, and the operation efficiency and the traffic conversion effect are improved.

The invention belongs to the technical field of traditional Chinese medicine information processing, and provides a traditional Chinese medicine disease medical case database construction and management system, which comprises a data acquisition module for acquiring original traditional Chinese medicine medical case data from a plurality of heterogeneous data sources; the data processing module is used for sequentially carrying out preprocessing, standardization and deep structured processing on the original data; the knowledge graph engine module is responsible for constructing, storing and managing a traditional Chinese medicine case knowledge graph; the database storage module adopts a distributed storage architecture to store standardized medical case data and a knowledge graph; and the intelligent query and analysis module receives a request input by a user in a natural language or a structured query condition, executes multi-hop association retrieval and bidirectional path reasoning based on the traditional Chinese medicine medical case knowledge graph, and outputs medical case data meeting the condition and an association knowledge reasoning result. According to the system and the method, systematized integration and deep mining are performed on traditional Chinese medicine case data, and through cooperative work of multiple modules, the limitations of data dispersion, different formats and low retrieval efficiency in traditional medical case management are broken through.

The invention relates to an aircraft component intelligent assembly data management system based on compliance verification, and belongs to the technical field of aerospace manufacturing. In order to solve the problems of data dispersion, low verification efficiency and difficulty in quality tracing in the aircraft component assembly process, the system comprises a standard process library construction unit used for constructing an aircraft component assembly standard process library which is clear in classification and contains detailed specifications; the assembly information acquisition unit is used for collecting assembly data in multiple channels and processing the assembly data into a structured data set; the data management system unit is used for integrating multi-source data and analyzing historical data and verification results to form a trend table so as to realize overall management; and the qualification checking unit is used for checking real-time data in multiple dimensions, generating a report and performing synchronous early warning. According to the system, intelligent management of the aircraft component assembly process is realized, the data processing efficiency and accuracy are improved, and the assembly quality and the safety and reliability of an aircraft are guaranteed.

The invention relates to the technical field of data storage processing, and discloses an insurance policy system data migration method, device and equipment based on an MQ message queue, and a medium, and the method comprises the steps: carrying out the fragmentation of data according to the data characteristics of a health insurance policy system, the insurance policy type, the time range and the customer region, and carrying out the parallel processing of the fragmented data; performing format conversion on the processed data, and after the data format is determined to be consistent with the format supported by the message queue, packaging the converted data into a message and sending the message to the MQ message queue; parameters of the MQ message queue are configured according to actual requirements, and the MQ message queue is partitioned and copied. The method can be applied to development of business systems such as financial science and technology, medical health, old-age care and the like, massive insurance policy data are stored in a scattered mode through data fragmentation, and the stability and reliability of the system, the data processing efficiency and the throughput capacity are improved through a partitioning and duplicating mechanism of a message queue (MQ).

The invention relates to the technical field of medical health informatization, and discloses a chronic disease tracking management system, which is characterized in that a data acquisition module, a data analysis module, a health monitoring module, a user interaction module, a control module and a tracking management optimization module are established, key factors of physiology, life and environment influencing chronic diseases are comprehensively covered; the data analysis module is used for deeply mining data values based on a scientific calculation formula and accurately identifying potential health risks; the health monitoring module realizes automatic and personalized health early warning and management suggestion pushing according to an analysis result and threshold setting, all the modules cooperate closely, and finally the system has the advantages of data comprehensiveness, risk pre-judgment accuracy, management personalization and service continuity. The problems of data dispersion, risk assessment lagging and single intervention measure in traditional chronic disease management are solved, and a whole-process and intelligent health management service is provided for chronic disease patients.