682 results about "Service layer" patented technology

The invention provides a dynamic routing selection method and system, electronic equipment and a storage medium, and aims to solve the problem that a routing strategy is difficult to adapt to a dynamically changing network, the method comprises the following steps: a terminal layer collects the state of a terminal and network data, and performs lightweight feature extraction; the edge node layer receives the data of the terminal layer, carries out space-time-semantic feature aggregation, and generates a region-level resource scheduling and routing decision strategy based on fragmented reinforcement learning; the central cloud service layer gathers whole network data, generates a global optimization strategy and issues the global optimization strategy; the edge node layer fuses global optimization and a region-level strategy, and executes dynamic routing selection; and security and privacy protection are provided through the trusted chain layer. According to the invention, adaptive path selection can be realized, the network resource utilization rate is improved, and the network stability is improved.

The invention discloses a computer big data information processing system, which comprises a data acquisition layer, a data processing layer and a data processing layer, wherein the data acquisition layer is used for accessing structured, unstructured and streaming data by using a multi-source adapter and Apache NiFi, executing format standardization, and extracting basic metadata and semantic tags through a rule engine and an NLP model; the metadata intelligent management layer integrates four modules, namely a federal learning framework for realizing cross-domain dynamic classification labels, an intelligent contract for real-time uplink storage evidence blood relationship change, a Neo4j combined graph neural network for constructing a knowledge graph for mining implicit association, and a reinforcement learning engine for optimizing a storage strategy based on frequency and risk indexes; the distributed storage calculation layer is used for processing batch and real-time metadata by adopting a Cassander + MinIO mixed framework and Spark / Flink, and dynamic partition balance performance is realized; and the application service layer is used for outputting functions of blood relationship query, classified browsing, compliance report and the like through a Vue.js portal and a Spring Cloud micro-service API (Application Program Interface) to form a full-link closed loop.

The invention discloses a surface mine transportation real-time intelligent scheduling method and system based on multi-objective optimization. The method comprises the steps that S1, an initial data loading module initializes the system; s2, the algorithm module verifies the vehicle state after receiving the scheduling request; s3, executing a path generation strategy according to states, wherein a normal vehicle generates all feasible routes based on the global path network; when a user appoints a starting point and a terminal point, a point-to-point optimal route is intelligently generated; s4, performing dynamic optimization scheduling based on the multi-source data; optimal task allocation is solved through a multi-objective optimization model, and a vehicle and route mapping relation is output; and S5, a scheduling result is issued to the vehicle-mounted terminal through the service layer, and a terminal interface displays a recommended route and operation guidance. According to the invention, a dynamic event-driven mechanism and a multi-source data collaborative optimization intelligent scheduling framework are fused, so that efficient distribution of vehicle tasks, real-time generation of paths and quick response to abnormal conditions are realized.

The invention discloses a unified search and page configuration rendering method and system based on a data model. The method comprises the following steps: S1, data acquisition and model mapping; s2, indexing and synchronizing data; s3, unified search request processing; s4, processing and returning a result set; and S5, dynamically rendering the page. The system comprises a data source layer, a data unification layer, an index layer, an application service layer and a display layer. The invention provides a set of end-to-end integrated solution for solving the problems that multi-source heterogeneous data is difficult to integrate, the cross-system search efficiency is low, page rendering lacks flexibility and the like. According to the scheme, by constructing a standardized data model, a unified search engine index system and a dynamic page rendering mechanism driven by configuration, a complete technical link from data source access to front-end display is achieved, and the efficiency and expansibility of the system in the aspects of data management, information retrieval and page display are remarkably improved.

The invention discloses a real-time state synchronization method and system, electronic equipment and a storage medium, and belongs to the technical field of network communication.The method comprises the steps that in response to a connection request from a client side, persistent connection with the client side is established, and a state subscription relation is recorded; performing semantic analysis on the state change event from the business service layer to determine a push priority; a corresponding target intelligent gateway is found according to the target object identifier of the state change event, a pushing strategy is executed by fusing the client network condition maintained by the target intelligent gateway and the pushing priority, and the state is updated and synchronized to the related client; and monitoring the health state of the persistent connection, and when the connection is abnormal and recovered, performing state synchronization with the client by the intelligent gateway based on the stored incremental state information. According to the invention, the problems of unreliable connection, redundant pushing and poor expansibility of a traditional SSE scheme are solved, and high-reliability, high-efficiency and horizontally-expandable real-time state synchronization is realized.

The invention discloses an intelligent RAG enhanced large model auxiliary writing system, and relates to the technical field of artificial intelligence auxiliary writing. In order to overcome the defects of an existing writing auxiliary tool, the adopted scheme comprises an interface and user layer for receiving a writing demand and redisplaying a generation result; the service layer is used for deploying three types of intelligent agents including writing, interactive writing enhancement and checking; the platform layer is used for carrying out industry adaptation analysis, mixed retrieval and RAG enhancement on writing demands and then sending the writing demands to the large model layer; three intelligent agents of writing, interactive writing enhancement and checking are called in sequence based on the output of the large model layer, and then a text is redisplayed to the interface and user layer after fact accuracy verification is completed through a tense knowledge graph; the data layer is used for providing a multi-type data storage system; the large model layer outputs a paragraph-level text and a reference index based on a writing large model, the paragraph-level text is returned to the platform layer, and reference index information is fed back to the interpretability and security layer for tracing; and the infrastructure layer is used for providing bottom layer resource support for each layer.

The invention discloses a hierarchical priority task orderly scheduling method based on a virtual thread, which comprises the following steps: S10, receiving task parameters transmitted by a business layer, performing task packaging setting, outputting packaged task objects, and transmitting the packaged task objects to a multi-dimensional calibrator; s20, performing task expiration verification, task fusing verification and dependency verification in the multi-dimensional verifier, returning a passing or failing identifier and a failing reason, and if the passing or failing identifier does not pass, triggering a monitoring alarm to record a discard log; s30, the verified tasks enter a two-dimensional queue manager to be subjected to hierarchical enqueue processing and capacity dynamic adjustment, and the capacity dynamic adjustment uses a dynamic resource allocator to achieve elastic allocation of queue capacity and virtual threads based on load awareness; and S40, performing task execution and task retry management on the tasks in the two-dimensional queue.

The invention provides an automatic production station working hour statistical system and method based on near field communication, the system comprises five layers of architectures including an identity recognition layer, a data acquisition layer, an edge computing layer, a cloud service layer and a terminal interaction layer, and the method completes the steps of initialization, NFC interaction triggering, multi-mode mistaken touch prevention verification and the like by means of the system. NFC, a sensor and a face recognition technology are fused, core modules such as task intelligent matching, energy consumption-man-hour linkage accounting and cross-station collaborative man-hour splitting are designed, and the system further has the functions of offline intelligent caching and multi-dimensional man-hour analysis. According to the invention, automation and precision of man-hour statistics are realized, single-station standardization and multi-station collaborative production scenes are adapted, data are ensured to be reliable and free of loss, deep fusion of production data is realized, enterprise hardware and management costs are reduced, and the intelligent manufacturing fine management level is improved.

The invention discloses a material batching and conveying process monitoring system based on digital twinning, and belongs to the technical field of industrial automation and intelligent manufacturing. The system comprises a physical entity layer used for storing, proportioning and conveying materials; the data acquisition and sensing layer is used for acquiring multi-source heterogeneous data of materials and equipment in the physical entity layer in real time; the digital twinborn model layer is used for constructing and operating a digital twinborn model synchronously mapped with the physical entity layer; and the application service layer is internally provided with a multi-modal fusion fault diagnosis module, and the multi-modal fusion fault diagnosis module is used for diagnosing material batching and conveying faults. According to the method, the digital twinborn and multi-modal AI algorithms are deeply fused, the early warning and accurate root cause positioning of equipment faults are realized, the diagnosis confidence is improved through evidence fusion, the process decision is optimized in combination with a simulation sand table, the production continuity and quality stability are improved, the non-planned shutdown and maintenance cost is reduced, and the system is endowed with the continuous self-evolution capability.

The invention relates to the technical field of power system security, and particularly discloses a ground wire management operation system based on ground wire cabinet monitoring, which comprises a physical sensing layer, an edge computing layer, a block chain consensus layer and an application service layer. The physical sensing layer collects the identity, the in-place state and the electrical parameters of the grounding wire; the edge calculation layer carries out local data processing and event judgment; the block chain consensus layer realizes data credible evidence storage and cross-domain sharing through an intelligent contract and a distributed account book; and the application service layer provides asset panoramic display, cooperative verification and risk early warning services. Through the above architecture, unified management and safety collaboration of data of the whole life cycle of the grounding wire are realized, and the safety operation and maintenance level of a power grid is improved.

The invention belongs to the technical field of aviation airborne system design, and provides a helicopter airborne system-oriented novel software architecture and a construction method thereof, and the architecture comprises a hardware abstraction layer, a framework resource layer, an intelligent platform service layer and an application software layer from bottom to top. And the hardware abstraction layer realizes decoupling of hardware and basic software of an operating system. The framework resource layer supports operation of a hybrid key operating system, supports and isolates tasks and application programs with different key levels, software bases and computing power requirements, and provides basic computing communication resources and AI computing power resources. The intelligent platform service layer comprises middleware, a servitization function unit and a servitization management unit, and the servitization function unit comprises atomic services and enhanced services. And the application layer interacts with the intelligent platform service layer and is decoupled from a bottom software and hardware environment. The framework is suitable for unmanned / manned helicopters, and generalization of platform support and maximum reuse of software assets are achieved.

The invention belongs to the technical field of financial science and technology, and discloses a multi-agent collaborative document-driven quantitative research and transaction self-evolution system and method. The system adopts a layered architecture, comprises a data and factor service layer, an execution engine layer, an agent layer, an interface service layer and a front-end control layer, and aims to solve the core problems that research and engineering implementation are separated in quantitative strategy research and development, code generation lacks interface constraints and strategies lack self-evolution ability. According to the system, through cooperative work of a research agent, a factor agent and a coding agent, a strategy idea described by a natural language is automatically converted into a standardized document, configuration and executable code; through a closed loop formed by self-monitoring, self-diagnosis and self-improvement intelligent agents, automatic diagnosis and optimization of problems of strategy overfitting, factor attenuation and the like are realized, continuous self-evolution of the strategy is driven, and full-life-cycle automatic management from strategy conception, factor design, automatic coding and real disk back-testing to feedback autonomous optimization is realized.

The invention relates to a digital twin-driven distributed warehousing system and method, and belongs to the technical field of intelligent logistics. The system comprises a sensing execution layer, a network transmission layer, an edge computing layer, a cloud platform layer and an application service layer. The method comprises the following steps: acquiring storage physical entity data through a perception execution layer; the data is transmitted to the edge computing layer and the cloud platform layer through the network transmission layer; in the cloud platform layer, a high-fidelity virtual warehouse is constructed and synchronized through a digital twin engine; using a multi-agent reinforcement learning algorithm to perform centralized training in a digital twin environment to generate a distributed cooperative scheduling strategy; and issuing the strategy to an edge computing layer and a sensing execution layer, and driving an autonomous mobile robot cluster to execute a cooperative task. According to the invention, step-type improvement of the warehousing system in flexibility, intelligence and cooperative capability is realized, and the problems of rigid bottleneck, non-optimal decision and low cooperative efficiency of a traditional system are solved.

The invention discloses a social group discovery system based on fused semantic information. The system comprises a presentation layer, a presentation layer, a service layer and a data layer. The presentation layer supports checking of a group division result; the display layer displays a user structure network, group dynamic division and group characteristic indexes through a visual tool; the service layer is composed of a semantic tag generation module, a user structure analysis module, a social group division module and a social group analysis module, semantic and structural features are fused through a graph attention network, and accurate group division is realized in combination with an adaptive embedded graph aggregation algorithm; and the data layer stores the original data set of the social platform and the processed data. The system inputs user texts into a large language model to generate semantic tags, node embedding is generated by calculating node association weights, group division is completed by combining an adaptive embedding graph aggregation algorithm, and finally group characteristics are quantitatively analyzed from the aspects of cohesion, conductivity and the like. The system is suitable for scenes such as vertical domain community mining.

The invention relates to an intelligent data asset management system. The system comprises a data access layer, a data processing layer, an intelligent analysis layer and an application service layer, the intelligent analysis layer comprises an intelligent label recommendation unit, an intelligent cataloguing unit, an intelligent management unit and an intelligent housekeeper unit; the data access layer is used for receiving the multi-modal data assets and performing format standardization conversion to obtain standardized multi-modal data assets; the data processing layer is used for preprocessing the standardized multi-modal data assets and extracting modal features of each modal data; the intelligent housekeeper unit is used for inputting a question of a user into the intelligent question-answering big language model, performing intelligent question-answering according to an intelligent directory and a knowledge graph and outputting answer content; and the application service layer is used for calling the output of the intelligent analysis layer and providing a data asset query service, a quality monitoring service and a decision support service for a user. By adopting the method, a professional, accurate and efficient data asset data analysis report can be output.

The invention provides a micro-service unified access control and governance system in a hybrid cloud environment, and the system comprises a unified entrance layer which takes an Istio gateway as a unique access point of external flow, and receives all business requests from the outside; according to the authentication and authorization intermediate layer, the Istio Gateway forwards the service request to the Oathkeeper, and Kratos authentication and SpiceDB authentication are carried out. The rule routing layer is used for performing routing decision on the service request passing the Kratos authentication and the SpiceDB authentication based on a predefined dynamic rule set, and generating a routing instruction; and the heterogeneous service layer comprises a VM environment and a K8S environment, and forwards the request to a corresponding target service instance according to the routing instruction. According to the method, the problems of flow entrance dispersion, authentication splitting and non-uniform routing rules in a mixed cloud environment are solved, and uniform, safe and efficient access control and management of heterogeneous micro-services are realized.

The invention discloses a dynamic adaptive management system for road traffic safety planning driven by artificial intelligence. According to the system, multi-source data are acquired through a data acquisition and preprocessing layer and are cleaned and standardized; the knowledge engineering layer constructs a policy knowledge graph and a rule engine; the large model service layer realizes natural language generation, semantic understanding and multi-modal reasoning; the intelligent generation layer uses a GAN model to generate multi-modal planning content and dynamically adapts the multi-modal planning content; the implementation process management layer monitors planning implementation, middle-stage evaluation and last-stage summarization in real time; and the interaction and output layer provides visual editing and multi-format output. The system integrates the technologies of deep learning, generative adversarial network and the like, realizes intelligent planning generation and dynamic supervision, has the capabilities of multi-modal data processing, dynamic self-adaption and full-process management, can effectively improve the scientificity, high efficiency and adaptability of road traffic safety planning, and provides powerful support for road traffic safety management.

The invention provides a fault detection method and device for an intelligent computing platform, electronic equipment and a medium, and the method comprises the steps: obtaining the heterogeneous data of at least one of an infrastructure layer, a platform service layer and a business system layer in the intelligent computing platform, and carrying out the fusion processing of at least one piece of heterogeneous data, and obtaining a target data flow; decomposing at least one of a fault analysis task, a fault positioning task and a fault recovery task of the intelligent computing platform according to the target data stream to obtain at least one subtask; determining a diagnosis context according to the target data flow, and determining at least one model service through the diagnosis context; and obtaining a fault detection result or a fault recovery result of the intelligent computing platform according to the diagnosis context, the at least one subtask and the at least one model service.

A service layer may be configured to offload requests and responses on behalf of IoT applications in order to reduce congestion and / or overhead on underlying networks, applications and devices. The service layer may be enabled with the capability to script and generate IoT application requests such that the requests can be initiated by the service layer without the IoT application having to re-issue the same request repeatedly (e.g., to periodically retrieve a sensor reading). This scripting may be initiated by request originators. The service layer may support the capability to monitor and detect repetitive request patterns and initiate the scripting itself. This scripting functionality may enable the service layer to perform operations on behalf of IoT applications. As a result, the messaging overhead on IoT applications and devices as well as underlying networks can be minimized.

The invention discloses a data warehouse intelligent construction and management method and system, and belongs to the technical field of data warehouse construction and management, and the data warehouse intelligent construction and management method comprises the steps: obtaining an enterprise data source, and extracting the feature parameters of the data source; constructing a data warehouse logic model; self-adaptive ETL configuration parameters are defined; constructing a three-layer physical architecture comprising a data access layer, a data storage layer and a data service layer; intelligent cache strategy configuration is executed based on a deep learning algorithm, a three-level cache architecture is established, and a pre-cache rule and a failure strategy are defined; and running management optimization is implemented through a multi-objective optimization function. According to the method, the construction automation level is remarkably improved, the cache hit rate is increased, the average query response time is shortened, the data consistency and the system performance are effectively balanced, the elastic adaptive capacity of the system is enhanced, the operation and maintenance complexity and cost are reduced, and meanwhile efficient sharing of cache resources is achieved on the premise that data security isolation is guaranteed.

The invention provides a marine target monitoring system and method based on a micro-front-end architecture, relates to the technical field of marine target monitoring, and solves the problem that an existing system is difficult to develop and maintain. The marine target monitoring system comprises a main application and a plurality of sub-applications with independent technical stacks of a front-end application layer, the corresponding sub-applications are dynamically loaded and rendered, and a data access processing service of the data service layer is configured to access original target data and process and store the original target data in real time; the application service of the data service layer is configured to obtain the processed target data and push the data to the corresponding sub-applications in real time, and the sub-applications are independently deployed and configured to interact with the application service through the unified gateway to receive and display the target data. According to the application, each sub-application can be independently developed and deployed and is easy to develop and maintain, the unnecessary query load of the server is reduced, and the overall resource utilization efficiency of the system is optimized.

According to the encryption communication system based on multi-level key distribution provided by the invention, the environment sensing layer acquires target environment parameters in real time and forms closed-loop feedback with a dynamic security score generated by the strategy control layer, and the key management layer is driven to realize three-stage dynamic switching from an initial key to a session key to a master key; a key fragmentation bidirectional authentication mechanism of a secure transmission layer and a double-key pool non-inductive updating strategy of a password service layer are matched, under the quantum resistance storage guarantee of a hardware isolation layer, an annular defense system with a space-time adaptive characteristic is constructed, and the security and availability are greatly and comprehensively improved.

The invention relates to a water level flow intelligent monitoring system and method based on space-time prediction and a quantum sliding window. The system comprises a sensor layer, a data processing layer, an intelligent algorithm layer and an application service layer. Water level and flow point cloud data are synchronously collected through a 79G millimeter wave radar array, and after preprocessing and feature extraction, a space-time joint prediction model fuses time trend, space consistency, environmental factors and historical modes when data are missing to perform intelligent complementation; then, a quantum heuristic sliding window is used for conducting self-adaptive filtering and exception processing on the data through intelligent conversion of a superposition state, a collapsing state and a tunneling state; the integrated high-precision synchronous monitoring of the water level flow is realized, the problems of discontinuous data, insufficient precision, poor adaptability and high cost in the traditional water level flow monitoring are solved, and the reliability, the self-adaptive capability and the intelligent level of hydrological monitoring are remarkably enhanced.

The embodiment of the invention relates to a multi-protocol self-adaptive BMS upper computer monitoring system and a data interaction method, and the system comprises a device access layer which is used for establishing a communication link between any BMS device and a BMS upper computer, and enabling the original data of the BMS device to be transmitted to the BMS upper computer; the protocol analysis layer is used for receiving the original data transmitted by the BMS upper computer and analyzing the original data according to a specified rule to obtain standard data; the data service layer is used for receiving the standard data, integrating and packaging the standard data and then providing a data interface for calling; the application function layer is used for calling the data interface, so that the system can process data from any BMS equipment with a consistent interface and logic; wherein the protocol analysis layer is designed with a protocol driving library, and the protocol driving library comprises implementation of a driving library interface IMcuDriver and implementation of an abstraction class driver Abstraction McuDriver; according to the invention, plug-and-play and unified management of the heterogeneous BMS equipment can be realized.

The invention belongs to the technical field of production testing in the manufacturing industry, and particularly discloses a production testing system and method based on the manufacturing industry, a terminal and a medium, and the system comprises a back-end service layer which is in communication connection with a front-end service layer for information interaction, dividing the business logic of the production test into a plurality of business modules which can be independently managed through a module registration mechanism; the equipment interaction layer comprises an equipment driving interface, at least one equipment driving plug-in and an equipment communication unit; and the system integration layer is used for carrying out information exchange with a manufacturing execution type service system through a standardized data interaction mode so as to obtain and send the production test data. Test data is aligned with a manufacturing execution type business system through a standardized data interaction mode, connection between a production test link and manufacturing process management is realized, and the overall cooperative capability of a production line is improved.

The invention relates to the technical field of robot interaction, in particular to a guide robot interaction method and system based on a large language model and an intelligent agent architecture, and the interaction method comprises the steps: S1, carrying out the input processing of a user; s2, identifying and classifying user intentions; s3, service intelligent routing is carried out; s4, executing control; and S5, performing interrupt processing. The interaction system comprises a user interaction layer, a core processing layer, a back-end service layer and an execution layer.

The invention relates to an intelligent file management system based on RAG and metadata full-life-cycle management, which is characterized by comprising a front-end application layer, a back-end service layer, an RAG knowledge base analysis layer and a data storage layer, and all the layers work cooperatively through standardized interfaces; the RAG knowledge base analysis layer is constructed by taking a self-built RAG knowledge base as a core, and the back-end service layer encapsulates a metadata management center. According to the method, through a multi-dimensional retrieval mode of'metadata screening + semantic retrieval + knowledge graph association ', the retrieval range is narrowed by metadata, then a knowledge unit is accurately positioned through RAG semantic retrieval, and finally associated document information is supplemented, so that compared with traditional full-text retrieval, the retrieval precision is improved, and the retrieval response time is shortened to millisecond level; automatically mining a document association relationship through a knowledge graph construction module, and supporting a user-defined association rule; and through a document-knowledge integrated view and a scenarized knowledge aggregation function, cross-department and cross-project knowledge rapid circulation is realized, and the knowledge reuse efficiency is improved.

The invention provides a virtual simulation training system and method for a forest fire fighting commander. The virtual simulation training system comprises a physical layer, a service layer, an element simulation layer and an application layer. The physical layer provides a hardware infrastructure; the service layer provides a data processing function; the element simulation layer simulates key elements in the forest fire fighting process and comprises a fire investigation module, a field communication module, an information submission module, a situation research and judgment module, a tactical making module, an instruction issuing module and a tactical execution module. The application layer provides a user interaction interface and comprises a training end situation display function, a training end interaction function and a guiding end function. According to the system, real-time analysis of the fire scene situation is realized by adopting multi-source data fusion and a deep learning technology, and the training effect is improved through dynamic scene injection and an automatic evaluation function. The system can provide a highly vivid training environment for forest fire suppression commanders, effectively improve command decision and coordination ability, reduce training cost, and enhance emergency disposal effect.

The invention relates to the technical field of special equipment, in particular to an intelligent auditing system and method for a special equipment report, and the system comprises an infrastructure layer, a data layer, a service layer and a display layer. A server platform and an operating system are deployed in the infrastructure layer so as to provide hardware resources, the operating system, middleware and a network environment for system operation, the data layer is connected with the infrastructure layer, a relational database is adopted to store service data, and a memory database is utilized to perform data caching; the service data comprises a test report template, a parameter variable and a rule set; the service layer is connected with the data layer and is used for bearing an auditing rule engine and a business processing module; the display layer is connected with the service layer and comprises a management end and a user end, the management end provides rule configuration and system management functions, and the user end is integrated in an existing service system in a browser plug-in mode. Therefore, the detection efficiency and accuracy of the special equipment report are improved.

The invention discloses a multi-modal feedback lower limb rehabilitation robot cooperative control system, which relates to the technical field of rehabilitation robots, and comprises a multi-source heterogeneous sensing layer, an intention and environment fusion understanding layer, a bilateral differentiation cooperative planning layer, a distributed cooperative execution layer, a central safety coordinator and a data management and remote service layer, the multi-source heterogeneous sensing layer collects multi-dimensional signals, the intention and environment fusion understanding layer generates a motion intention vector and a terrain disturbance expectation vector, and the double-side differential collaborative planning layer dynamically synthesizes a personalized gait track and deconstructs the personalized gait track into a double-side differential control target set. The distributed cooperative execution layer drives an actuator to move through a differential control algorithm, the central safety coordinator guarantees training safety, and the data management and remote service layer realizes control strategy iterative optimization. According to the invention, active fusion of intention and environment and dynamic generation of a cooperative motion strategy are realized, and adaptability and naturalness of rehabilitation training are improved.