2085 results about "Middleware" patented technology

The invention discloses an unmanned aerial vehicle cluster intelligent cooperative control method, and the method comprises the steps: optimizing a network topology through heterogeneous unmanned aerial vehicle cluster dynamic networking and a dynamic clustering algorithm, and guaranteeing the reliability of a communication link; a layered hybrid decision architecture is designed to improve the task allocation rationality and the dynamic adaptability of the unmanned aerial vehicle cluster; a distributed control strategy network is trained by using a multi-agent near-end strategy optimization MA-PPO algorithm, and unmanned aerial vehicle cluster behavior collaboration is ensured in combination with space-time consistency constraint; an asynchronous incremental consensus protocol AICP is provided, the data transmission amount is reduced, and topology reconstruction is accelerated; real-time three-dimensional environment reconstruction and dynamic threat prediction are realized based on a neural radiation field NeRF technology; a lightweight anti-interference communication middleware is developed, and the instruction transmission stability is enhanced by adopting a space-time coding diversity technology. The method solves the problems of high delay of centralized control of the unmanned aerial vehicle cluster, poor convergence of a distributed algorithm and the like, and is suitable for high-dynamic task scenes such as urban street battle and complex terrain search.

The invention provides a cache information processing method and device of a port platform and a medium, and belongs to the technical field of port distributed information processing. An update request is received, and authentication and flow limiting processing are performed on the request; obtaining a cache key prefix and a data structure type, routing a cache key to a fragment node based on a consumption write-back event, executing a write-in operation in a distributed cache service, and setting survival time and multi-copy synchronization; delivering the message body to the message middleware and obtaining delivery confirmation; the messages are pulled from the queue according to the configured concurrency, deduplication verification is carried out on idempotent identifiers of the messages, and data persistence operation is executed after the verification message version is higher than the current version of the database; index collection points are implanted into all modules of the whole link, and the request delay, the cache hit rate and the message accumulation depth index are visually displayed. The reasonable distribution and optimization of system resources are realized; the consistency and integrity of the data are guaranteed, and the reliability of message transmission is improved at the same time.

The invention discloses an intelligent multi-dimensional automatic inspection operation and maintenance management method, device and equipment, relates to the technical field of network inspection, and aims to solve the problems that the inspection efficiency of network equipment is low and fault early warning is lagged. The method comprises the following steps: scanning equipment in a target machine room to establish an equipment registration file, wherein the registration file comprises an equipment type identifier and an associated inspection strategy template; collecting multi-dimensional data of each registered device according to the inspection strategy template, wherein the multi-dimensional data comprises a hardware operation state, a business middleware state and an environment monitoring parameter; determining abnormal data from the multi-dimensional data according to a preset dynamic threshold value, and generating and issuing graded alarm information according to the influence degree of the abnormal data; and creating a work order according to the abnormal data and automatically distributing the work order so as to process the abnormal data.

The invention discloses a distributed energy collaborative scheduling optimization method based on edge computing. According to the method, a plurality of edge computing nodes are deployed in a distributed energy system, a multi-protocol compatible OPC UA communication channel is constructed through protocol conversion middleware to collect data, and after the edge computing nodes clean and normalize the data, a preliminary scheduling scheme is generated through an improved genetic algorithm; the improved genetic algorithm is optimized through cooperation of a deep reinforcement learning model and an adaptive attenuation mechanism. And uploading the preliminary scheduling scheme to a cloud end, and obtaining a global optimal scheduling strategy through a multi-target particle swarm optimization algorithm. And the cloud carries out credible evidence storage on the global optimal scheduling strategy abstract value through an alliance chain smart contract, and establishes a PoA consensus mechanism. And when the communication is interrupted, the edge computing node starts the local emergency scheduling module, and incremental data synchronization is performed after the communication is recovered. The distributed energy scheduling optimization problem is effectively solved, the energy utilization efficiency is improved, and the system stability and reliability are enhanced.

The invention provides a whole-process engineering consultation management design method, which comprises the following steps of: constructing a unified data exchange standard and protocol, converting heterogeneous data output by design tools of different professions and different units into a standardized data format, realizing seamless joint and real-time sharing of data through data middleware, eliminating data barriers, and improving the data exchange efficiency. The collaborative design efficiency is improved; according to the method, digital technologies such as BIM are adopted, a digital twin model of an engineering project is constructed in a design stage, a design scheme is deepened through virtual construction simulation and optimization, factors such as a construction process, construction procedures and resource allocation are fully considered, and the construction feasibility and economic rationality of design are improved; a collaborative mechanism of a design stage and a construction stage is established, experienced construction managers and technicians are invited to participate in design review, improvement suggestions and suggestions are provided from the construction perspective for a design scheme, a designer is helped to comprehensively understand construction requirements, and the design scheme is optimized.

The invention relates to the related technical field of distributed computing power resources, and discloses a distributed computing power resource dynamic fusion and cooperative computing system which comprises a resource sensing module, a task analysis module, a dynamic scheduling module, a virtualization adaptation layer, a cooperative computing engine, a global controller and a hierarchical communication bus. The resource sensing module collects and quantifies the hardware computing power of the heterogeneous computing nodes in real time. According to the invention, a complete closed-loop control system is formed through a five-layer dynamic fusion architecture (a sensing layer, an analysis layer, a scheduling layer, a virtualization layer and a collaboration layer), so that a distributed computing system can adapt to a scene that edge nodes are dynamically added and pushed out; meanwhile, through the purpose of developing virtualization middleware supporting cross-platform instruction real-time conversion and based on a multi-target dynamic weight adjustment mechanism of online learning, the heterogeneous task scheduling success rate can be greatly improved through the overall structure of the system, and the fault recovery time is shortened.

The invention provides a software ecological migration method and system based on intelligent analysis. Wherein a compatibility evaluation database is deployed in a target architecture, an instruction set mapping rule is preset, and migration risk data is generated through semantic verification; dynamically allocating resources through a heterogeneous virtualization scheduling engine, calling a hardware acceleration unit translation defect instruction, and generating virtualization equipment simulation parameters based on the migration risk data; deploying protocol conversion middleware, dynamically analyzing and reconstructing a network protocol data packet, and combining instruction execution delay data to adjust analysis granularity; in cross-architecture transmission, instruction conversion defects are injected into control logic, timing sequence errors are corrected through clock offset compensation, and corrected data are transmitted back to update instruction mapping rules. According to the technical scheme provided by the invention, the data leakage risk is reduced, and zero shutdown in the migration process is ensured.

The invention relates to the field of low-altitude airspace monitoring, and relates to a low-altitude monitoring system based on multi-source heterogeneous perception fusion and rule engine driving, which comprises a perception access layer used for completing data standardization and protocol adaptation and realizing data stream release through message middleware; the processing calculation layer is used for generating a structured alarm event; the application support layer is used for three-dimensional visual interactive display of target situation data and alarm events, unified access of multiple types of sensors such as radar, photoelectricity, radio frequency, ADS-B and meteorological sensors is realized through a plug-in protocol adapter, and target state estimation and track smoothing are realized by combining space-time registration and extended Kalman filtering. The limitation that an existing system can only process a single data source or simple superposition is overcome, and the target recognition precision and the track continuity are remarkably improved.

The invention discloses an equipment data acquisition and query optimization method based on a large model enabling ERP-MES system, and relates to the technical field of integrated enterprise resource planning and monitoring management systems, and the method comprises the following steps: carrying out the dynamic adaptive data acquisition and preprocessing of equipment: employing an edge node to deploy a lightweight noise detection model, identifying an electromagnetic interference mode in sensor data collected by the equipment in real time, and dynamically compensating and correcting by combining environment temperature and humidity data; according to the method, an edge node lightweight noise detection model is combined with environmental data compensation and correction, and a BERT large model is utilized to analyze a protocol document design middleware, so that accurate acquisition and efficient processing functions of dynamic self-adaptive data of equipment are realized; preprocessed data are mapped and fused through a multi-modal large model to construct a unified data warehouse, and a mapping strategy is optimized through reinforcement learning, so that the equipment data quality is improved, and the data fusion and utilization efficiency is enhanced while heterogeneous data fusion is achieved.

The invention provides a cross-protocol identification data intelligent analysis middleware method and system. The method comprises the following steps: taking multiple industrial communication protocol identifiers in advance to form a metadata set, and constructing a protocol feature element model library containing a non-standard protocol feature template; a programmable logic device is introduced, physical layer signal waveform characteristics are matched, and corresponding communication protocol stacks are dynamically switched at a hardware level according to a matching result; receiving a communication data stream through an electric domain processing unit of the programmable logic device, and generating a protocol analysis logic sequence in combination with a state transition rule of the meta-model library and a mode matching rule of the protocol stack; performing combined operation on the structured feature template and the analysis logic sequence to generate an executable cross-protocol data analysis rule; and when unknown protocol characteristics are detected, triggering dynamic reconstruction of the template, so that the analysis rule is adapted to a newly added protocol. According to the technical scheme provided by the invention, the protocol compatibility development cost in an industrial multi-protocol scene is remarkably reduced.

The invention discloses an intelligent operation and maintenance distributed cloud native application computing method, and relates to the technical field of cloud computing, and the method comprises the steps: collecting heterogeneous data of an application layer, a middleware layer, a container layer and a service governance layer, constructing a dynamic multilayer dependency graph, and explicitly modeling a cross-layer dependency relationship and implicit dependency caused by resource competition; based on the spatio-temporal features of the spatio-temporal diagram neural network learning map, predicting a cascade fault risk and outputting a high-risk sub-graph; candidate operation and maintenance operations are generated through reinforcement learning, indirect negative influences of the operations on non-target components are evaluated in combination with a causal inference model, and risk filtering operations are verified through a multi-dimensional safety threshold value; and after the safety operation is executed, continuously optimizing the model and the atlas through a feedback closed loop. According to the method, deep insight, accurate risk prediction and self-adaptive decision making of side effect minimization can be carried out on a complex dependency relationship, and the system stability and the operation and maintenance efficiency are remarkably improved.

The invention relates to the technical field of industrial internet, and discloses a water affair industry internet data acquisition and instruction control middleware, which comprises a data acquisition module for acquiring water affair data through a multi-source heterogeneous interface and transmitting the water affair data in a classified manner; the data processing module is used for performing protocol normalization processing and standardized data packet generation; the instruction control module is used for receiving and analyzing an instruction and generating an equipment executable instruction set; and the collaborative scheduling engine is used for distributing transmission paths based on priorities and load states and coordinating module interaction. The data processing module comprises a protocol adaptation unit and a topology construction unit, and the collaborative scheduling engine has a load balancing strategy. In addition, each module is further subdivided into units to improve functions, such as an equipment interface unit of the data acquisition module, a protocol analysis unit and the like. According to the invention, the problems of multi-source heterogeneous data acquisition and instruction control in the water affair industry are solved, the data processing efficiency, the instruction control accuracy and the system stability are improved, and intelligent management of a water affair system is realized.

The invention discloses a method for realizing SQL (Structured Query Language) grammar conversion of different databases based on middleware and the middleware, belongs to the technical field of databases, and aims to solve the technical problem of how to realize SQL grammar conversion of different databases through the middleware. The following operations are executed through the middleware to realize the grammar conversion of the SQL between the source database and the target data constructing an abstract syntax tree AST by taking various SQL elements as nodes; operating nodes in the AST on the basis of requirements of a target database; based on the data type in the target database, performing data type mapping by applying a data type conversion rule, and generating an SQL statement adapted to the target database; performing security check on the generated SQL statement; caching the query result and the generated SQL statement based on a caching mechanism; and recording the conversion process and query processing of the SQL statement.

The invention discloses a food production traceability management system based on a block chain, which belongs to the field of food management systems, and is characterized in that a unique identifier ID of an inheritor is generated based on an SHA-256 Hash algorithm, a Merkle tree root Hash value of food production data is dynamically associated, a non-tampering digital identity file is constructed, a data island of traditional decentralized management is broken through, and the traceability of food production is improved. According to the technical scheme, full-chain credible association between the non-abandoned technology and the production process is ensured, validity of an electronic signature is automatically verified by means of an intelligent contract, data tampering or identity failure risks are recognized in real time by comparing a public key decryption result with a signature hash value, JSON format alarms are pushed by means of Apache Kafka message middleware, cross-department collaborative response is achieved, and the security and reliability of the electronic signature are improved. The risk prevention and control efficiency is remarkably improved, encryption signature is performed in combination with an ECDSA key pair of a hardware security module, strong binding of an inheritor identifier, a production batch and equipment is ensured, identity fraudulent use or qualification counterfeiting is prevented, and traceability of the whole life cycle of non-abandoned skill inheritance is achieved.

The invention relates to the technical field of urban intelligent management, and discloses a cloud service-based software-defined urban component internet-of-things control method and system, and the method comprises the steps: constructing an urban component digital twin model, and fusing multi-source data to generate a state feature vector; predicting resource demand distribution by using a graph neural network prediction model in combination with environment and user behavior data; a reinforcement learning algorithm is adopted to optimize a network strategy, and cross-layer protocol adaptation and time delay constraints are considered; deploying an edge cloud cooperative control mechanism to ensure state synchronization; and constructing protocol conversion middleware to realize heterogeneous device protocol adaptation. According to the method, accurate state perception, reasonable resource allocation, efficient network operation, edge cloud collaboration and heterogeneous equipment compatibility of the urban components can be realized, the intelligent management level of the urban components is effectively improved, the urban operation efficiency and the resource utilization rate are improved, and the method has a good application prospect.

The invention provides an intelligent laboratory full-process collaborative management system and method based on multi-dimensional data fusion, and the method comprises the steps: obtaining an original data stream from laboratory instrument equipment, carrying out the format recognition and conversion of heterogeneous instrument data through a standard protocol adapter, and generating a first data set in a unified format; aiming at the first data set, executing automatic analysis by adopting data middleware, and integrating into a structured second data set based on a metadata rule of field mapping and unit conversion; according to the second data set, a multi-source data fusion model is constructed, data are classified according to instrument types through batch processing and aggregated according to timestamps, and a fused third data set is generated; aiming at the initial process configuration, adjusting a node sequence and a parameter threshold value by using a visual design tool, and generating an optimized process configuration adaptive to the diversified scene; according to the optimized process configuration, process scheduling is executed through a dynamic process engine, execution time and resource occupation are monitored in real time, and a process execution log is generated.

The invention relates to the technical field of industrial internet data processing, in particular to a cross-platform multi-source data integration analysis method and system based on the industrial internet, and the system comprises a data collection layer, a data preprocessing layer, a data integration layer, a data storage layer, an intelligent analysis framework, an application layer and a data security layer. Through the data adapter and middleware technology, efficient collection and integration of multi-source heterogeneous data are achieved, multiple data sources and communication protocols are supported, the compatibility and expansibility of the system are improved, and the system can rapidly adapt to different industrial scenes and data source changes; according to the method, advanced big data and artificial intelligence technologies are applied, a specific analysis model for industrial production is combined, deep analysis can be performed on the data, potential values in the data are mined, an accurate analysis result is provided for equipment fault prediction and production process optimization, and the intelligent level of industrial production is improved.

The invention discloses a logistics carbon emission data monitoring system based on a block chain and edge calculation, and relates to the technical field of logistics systems. According to the logistics carbon emission data monitoring system based on the block chain and edge calculation, on the aspect of data integration and estimation, multi-source heterogeneous data is fused to construct a dynamic compensation model, a lag compensation algorithm is developed, emission factors are adjusted, more accurate real-time carbon emission estimation is achieved, and full-chain data standardization and association are achieved through middleware; in the aspect of privacy protection, the blockchain and zero-knowledge proof technology are combined, enterprise data authenticity verification is ensured, original information is not leaked, a carbon emission result is subjected to chaining evidence storage, original data is encrypted and stored, and cross-enterprise federal learning ensures that data cannot be out of a domain; the logistics carbon emission data monitoring accuracy, privacy protection and auditing supervision intelligent level are improved.

The invention discloses a method and tool for manufacturing a cold shield of a nuclear fusion device, and relates to the technical field of metal plate machining. The manufacturing method of the cold shield of the nuclear fusion device comprises the following steps: providing a sub-panel, a flange and a pipe fitting; the multiple sub-panels are welded, and a first middleware is obtained; welding the edge of the first middleware and the turnup to obtain a second middleware; after the pipe fitting is welded to the surface of the second middleware, a third middleware is obtained; and the third middleware is shaped. According to the method, the third middleware is shaped, that is, the third middleware is shaped after all welding procedures are completed, so that the third middleware has relatively small profile tolerance, the profile tolerance of the cold shield meets the design requirement, the assembly difficulty of the cold shield is reduced, and the risk of failure of the cold shield is reduced.

The invention discloses an intelligent fusion and standardization processing system and method for multi-source heterogeneous operation and maintenance data, and belongs to the technical field of operation and maintenance data. The system comprises a data acquisition module, a data preprocessing module, a data fusion module and an information extraction module; the data acquisition module is used for collecting original multi-source heterogeneous operation and maintenance data from different data sources, and the data sources comprise facilities, operating systems, basic components, middleware, databases and / or information systems; the data preprocessing module is used for cleaning, denoising and standardizing the acquired data; the data fusion module is used for selecting a low-level data fusion model, a middle-level data fusion model or a high-level data fusion model according to the fusion scene and fusing the preprocessed data; and the information extraction module is used for carrying out feature extraction on the fused data. According to the method, deep fusion and standardized processing of the multi-source heterogeneous operation and maintenance data are realized, and a unified and high-quality data basis is provided for data analysis and decision making.

The invention provides a universal control system for a body-equipped robot and the body-equipped robot. The system comprises an elastic microkernel, a time-sensitive bus network and hardware components which are deployed in the body-equipped robot, the elastic microkernel is in communication connection with each hardware component through a time-sensitive bus network; the elastic microkernel deploys a basic industrial operating system, virtualizes a plurality of virtual domains in the industrial operating system according to an application scene of the robot with the body, and constructs a real-time communication framework based on deterministic communication middleware in the industrial operating system; the elastic microkernel is further provided with a hardware abstraction layer, a mainstream hardware instruction set is integrated in the hardware abstraction layer, and cross-platform support is provided for functional software in the virtual domain through a standardized interface. According to the method, the problems of scattered computing resources, complex communication and the like in the prior art are solved, and a highly-integrated, flexible, extensible and cross-platform compatible control scheme is provided for the robot with the body.

The invention relates to the technical field of mine production operation management, in particular to a mine production operation intelligent decision-making system based on multi-source heterogeneous data fusion. A data preprocessing module; a data fusion modeling module; an intelligent decision module; and a decision execution feedback module. In the scheme, an edge computing terminal is deployed through a data acquisition unit, a multimode communication technology is integrated, data of an underground sensor, electromechanical equipment and the like are accessed in real time, and the data transmission reliability is ensured through a communication quality evaluation formula; the business system interconnection unit maps heterogeneous fields of systems such as ERP, WMS and the like into global unified business keys by means of semantic middleware, and semantic ambiguity is eliminated. The data preprocessing module integrates the dispersed data into a standardized data set through intelligent cleaning, format conversion and three-dimensional association, and provides data support for decision making.

The invention provides a method for accessing user equipment to a vehicle-mounted system in a cross-system virtual manner and navigating, which comprises the following steps of: in a cross-system virtual access process, converting an operation request and a data transmission instruction of the user equipment into a format which can be identified by the vehicle-mounted system through a virtualization middleware technology, and performing encryption and integrity verification on transmission content; the compatibility and security of communication are ensured; a heartbeat detection mechanism between a vehicle-mounted system and user equipment is established, network connection quality is evaluated in real time by periodically sending probe packets and monitoring response time, and if overtime or too high packet loss rate is found, a standby link is automatically switched to ensure seamless connection and service continuity; historical load data of a vehicle-mounted system are analyzed through a machine learning algorithm, a load prediction model is constructed, and computing resources and network bandwidths are dynamically scheduled and reserved in advance according to spatial and temporal distribution characteristics of navigation requests, so that resource bottlenecks and service congestion are avoided.

The invention relates to the technical field of distributed response, in particular to a distributed message dynamic response method based on websocket. The method comprises the following steps: constructing a distributed message service cluster to configure a websocket communication module, message middleware and a client for each service node, and providing a unified service access point to the outside through an Nginx load balancer, so as to automatically register and subscribe a global control theme to the message middleware and form a hierarchical theme subscription structure; when the client initiates a connection request, the connection is distributed and a secure channel is established; the client sends a service request message, packages the service request message into a standardized message format, and associates session information of the client at the same time; and receiving the session message, performing intelligent filtering, generating a response result, and pushing the response result to the client in real time. According to the invention, efficient processing and real-time response of messages in a distributed environment can be realized.

The invention discloses a multi-role collaborative management architecture based on RBAC + HIS synchronization, and the architecture comprises a role authority management module which builds a static role authority baseline based on an RBAC model, and associates the real-time organization architecture data of an HIS system through a dynamic rule engine, and generates a multi-level role authority tree; the data synchronization middleware adopts an API gateway to realize one-way data push between the HIS system and the psychological assessment platform, comprises a field-level encryption unit and an incremental data verification unit, and supports isolated transmission of patient medical records, medical advices and assessment tasks according to inpatient areas; the multi-terminal cooperation engine realizes authority mapping of the doctor workstation, the mobile nursing terminal and the patient self-service terminal through distributed session management, a conflict detection mechanism is built in, and a secondary authentication process is triggered when cross-inpatient-area operation is detected. According to the invention, dynamic authority management is realized, data secure transmission and multi-terminal cooperation are guaranteed, auditing tracing is enhanced, and business continuity when the system is abnormal is ensured.

The invention provides a training and examination robot system based on a multi-modal large model, equipment and a computer program product, and aims to accelerate training transformation and upgrading and improve coping ability as basic appeals, and based on regular training work of teams, training and examination robot, sensor acquisition equipment and big data platform three-terminal equipment. A multi-modal data acquisition layer for realizing real-time attitude detection and motion capture by using an edge calculation algorithm, a data processing and analysis layer for finishing real-time image processing through localized edge calculation in a network-free or power-free environment, and system control functions for finishing intelligent decision making, evaluation, error correction and the like are provided; an intelligent decision-making and control layer of a training subject rewriting decision-making mechanism is established, cross-modal collaborative learning middleware is utilized to realize modal representation consistency while training subject transposition evaluation is realized, training and assessment operations of the same subject of multiple persons or different subjects of multiple persons are supported, and the training and assessment efficiency is remarkably improved.

The invention provides a data driving and multi-element cloud edge cooperative computing method for intelligent workshop construction, which comprises the functions of multi-protocol heterogeneous equipment sensing, edge node adaptive load balancing, lightweight real-time edge computing processing, cloud centralized management control, industrial intelligent application service deployment scheduling, cloud edge task unloading and the like. The system comprises a data acquisition and transmission middleware, an edge stream processing engine and a cloud service center. The method has the characteristics of real-time performance, low delay, flexibility, expandability, loose coupling, low resource occupancy, high availability and privacy security.

The invention discloses a project progress, quality and safety collaborative management and control system and method based on BIM and Internet of Things, and belongs to the technical field of constructional engineering informatization management. In order to improve engineering management efficiency and reliability, the system comprises a data acquisition layer, a data processing layer, an application layer and a security module. The data acquisition layer is connected with the data processing layer, the data processing layer is connected with the application layer, and the security module is respectively connected with the data acquisition layer, the data processing layer and the application layer; the data acquisition layer comprises IoT equipment, an external data interface, data middleware and a BIM model, the IoT equipment acquires data through the external data interface, the IoT equipment is connected with the BIM model through the data middleware, and the data processing layer comprises a multi-source data fusion engine and an intelligent algorithm module; the application layer comprises a model management module, a model display module, an early warning management module, a data management module, a three-dimensional visual monitoring platform, an intelligent decision center and a mobile terminal module. The project management efficiency is improved.

The invention relates to a railway material purchasing asynchronous task processing method, device and system, and the method comprises the steps: constructing a six-layer message channel architecture of a purchasing business process, and executing an instruction of deploying a message agent node in an active-active mode for each channel based on the core message middleware of a Kafka cluster; the front-end gateway is instructed to package the purchase event into a binary message body with a transaction ID and a timestamp, and the binary message body is written into a persistent queue after priority labeling is carried out according to a task type label; processing the concurrent tasks by adopting a multi-stage feedback queue scheduling algorithm, and dynamically allocating computing resources based on a thread pool; a maximum retry threshold value is set according to an exponential backoff retry strategy, so that the failed task is automatically transferred into a dead message queue; and dynamically calculating an optimal message routing path based on the supplier portrait and the material classification model, and extracting the order to an exclusive processing queue of the optimal supplier according to Topic dynamic switching of the message queue. According to the invention, the coupling degree is reduced, the system performance is improved, and the fault tolerance is enhanced.

The invention provides a data real-time analysis output method and system, and belongs to the technical field of data processing, and the method comprises the steps: scanning a preset directory of a manufacturer server, generating a trigger message used for representing a data file for each detected data file, and writing the trigger message into message middleware; in the stream processing framework, the trigger message is consumed in real time from the message-oriented middleware through the data source component, and a corresponding data file is read according to a file path indicated in the trigger message to form an original data stream; in the stream processing framework, performing real-time conversion processing on the original data stream to generate an index data stream for representing the performance index of the target object; and writing the index data stream into the target storage medium and / or the message middleware. According to the method, the triggering message is generated by monitoring the data file and is read, converted and distributed in the stream processing framework in real time, so that the timeliness and the accuracy of real-time analysis and output of the data are effectively improved.