235 results about "Data collaboration" patented technology

The invention relates to the technical field of remote sensing data processing and water environment monitoring, and discloses a black and odorous water body intelligent identification method based on a multi-source remote sensing image, and the method comprises the steps: firstly obtaining a first high-resolution remote sensing image, and extracting a global water body mask through a TransUNet model; secondly, removing non-target plaques based on geometric features and a basic spectrum rule; then, calculating a black and odorous water body index by using the second multispectral remote sensing image, and screening suspected black and odorous water bodies by combining adaptive threshold segmentation; further, performing fine classification confirmation on the suspected target by using a third high-frequency remote sensing image and an Officient Net model; and finally performing fusion output on the identification result. Through multi-source data collaboration and a coarse screening-fine classification multi-stage strategy, the limitation of insufficient spatial-temporal resolution of a single data source is overcome, and the positioning precision and the anti-interference capability of urban black and odorous water body recognition are improved.

The invention discloses a private data security sharing method based on federal learning, particularly relates to the field of private data security protection and sharing, and is used for solving the problems of insufficient model credibility and lack of precision control of data exchange in the existing cross-mechanism data collaboration process. According to the method, homomorphic encryption processing is carried out on local data of all participants, a ciphertext verifiable calculation task is constructed in combination with federated learning, forward propagation and back propagation calculation of a ciphertext are carried out by outsourcing calculation nodes, credible verification is carried out on a calculation process by utilizing zero-knowledge proof, and gradient aggregation and model updating are completed in a ciphertext domain; after model training is completed, based on federal learning model output, intelligent judgment is conducted on the sharing value of local data samples, ciphertext re-encryption and data exchange control are driven, multi-party safe and controllable data circulation is achieved, and therefore on the premise that privacy safety and compliance requirements are guaranteed, cross-mechanism data collaboration efficiency and decision-making precision are improved.

The invention discloses a chromatographic data optimization processing method for a liquid chromatograph, and relates to the technical field, and the method comprises the following steps: collecting an original signal flow, carrying out preliminary peak detection, and generating an original peak list; extracting modal exclusive characteristics of each chromatographic peak; converting the modal exclusive features into a unified multi-dimensional semantic feature vector; calculating a time interval weight, and calculating a semantic relevancy weight based on the multi-dimensional semantic feature vector; correcting the time interval weight, generating a network edge weight, and constructing a peak correlation topology network by taking the multi-dimensional semantic feature vector as a node; identifying node clusters connected with high edge weights, and aggregating the node clusters into candidate compound entities; tracking a node signal intensity change track, and adding a conflict mark; conflict resolution arbitration is carried out on the candidate compound entities with the added conflict marks, dominant detector evidence is output, and an analysis report is generated. According to the method, the problems of poor data collaboration of multiple detectors, inaccurate peak identification and association and isolated data processing flow are effectively solved.

The invention discloses a building industry multi-subject collaborative full life cycle carbon emission management system and method, and relates to the technical field of building industry carbon emission management. The system comprises a carbon perception and data collaboration module, a carbon simulation and deduction module, a carbon optimization and collaborative regulation and control module, a carbon accounting and auditing traceability module and a carbon decision and knowledge generation module. Multi-source heterogeneous data is converted into a carbon flow unit with time, space and responsibility subject attributes, data checking, locking and compliance sharing are achieved by means of a multi-subject data collaboration pool, carbon data barriers among all responsibility subjects are broken through, the problems of fragmentization of carbon data collection and lack of collaboration are solved, and the data collection efficiency is improved. And meanwhile, the carbon accounting and audit traceability module completes multi-dimensional accounting based on the carbon flow unit, and establishes a digital carbon chain pointing to an original data source and a responsibility subject, so that full-link traceability of carbon emission data is realized.

The invention discloses a dynamic adaptive operation, maintenance and metering optimization method for an electric energy metering box, and the method comprises the steps: collecting electrical parameters, environmental parameters and box body state parameters in real time, constructing a three-dimensional data set through preprocessing, and carrying out the local storage and preliminary analysis through edge calculation; the condensation occurrence probability is calculated based on the environmental parameters, and self-adaptive regulation and control are triggered and a ventilation structure is linked; abnormal features are extracted, abnormity is recognized in a rule judgment and trend analysis double-engine mode, and graded early warning is carried out; performing comprehensive state scoring in combination with the three-dimensional data set, and matching a differentiated inspection mechanism; presetting a metering error reference value of a temperature and humidity interval, calculating a compensation value in real time and remotely correcting parameters of the electric energy meter; and establishing a shared data platform of the power supply and the power consumption, and realizing full-process data tracing and automatic report generation. According to the method, the condensation prevention and control accuracy is improved, the abnormal false alarm rate is reduced, the operation and maintenance resource allocation is optimized, the metering accuracy is improved, and the data collaboration and tracing capability is enhanced.

The invention belongs to the technical field of energy retail, and particularly relates to an energy retail intelligent interaction system and implementation method based on RAG and Text2SQL, and the implementation method comprises the following steps: initiating a natural language query through an intelligent session agent; completing pre-processing and dynamic classification of the problem, and splitting the problem into a data type sub-task and a non-data type sub-task; if the sub-task is a data type sub-task, analyzing a data type demand, generating an SQL query adaptive to the energy retail database Schema, executing the SQL query, and returning to a structured structure; and if the subtask is a non-data type subtask, retrieving an unstructured knowledge base by utilizing a large language model, and generating a text answer with source reference. Through an energy retail intelligent interaction system which is driven by RAG and Text2SQL and is based on an intelligent session agent, natural language processing and multi-source heterogeneous data cooperation capability are deeply fused, user intentions can be efficiently analyzed and dynamically disassembled into data class tasks and non-data class tasks, SQL instructions are automatically generated through Schema links according to structured query requirements, and the method has the advantages of being high in efficiency and high in efficiency. And second-level data response is realized.

The invention relates to the technical field of low-altitude prevention and control, in particular to a low-altitude target detection identification and countering prevention and control system which comprises an operation and maintenance management platform, a multi-source data fusion unit, an intelligent noise reduction preprocessing unit, a general command platform, a dynamic threat evaluation unit and a cross-domain collaborative interface module. The detection and recognition precision and efficiency are improved through intelligent noise reduction and multi-source data fusion, intelligent collaborative countering is achieved through an intelligent decision center and a full-link countering unit, global situation awareness is enhanced through cross-domain data collaboration, operation and maintenance management and system stability are optimized by means of a prediction maintenance module and a modular architecture, and the detection and recognition efficiency is improved. The system can make up for the shortages of domestic existing systems, guarantees the airspace safety of key scenes, and reduces the long-term operation cost.

The invention discloses a cross-platform teaching tool data collaboration and personalized resource recommendation system based on an MCP protocol, and belongs to the technical field of education. According to the system, a multi-platform teaching tool is in unified butt joint through the MCP protocol adaptation layer, and the problem of data splitting is solved; the data co-processing layer cleans and fuses multi-tool data, generates a teacher / student / parent data view and stores an evidence through a block chain; the personalized recommendation engine generates role-based resource recommendation based on a teaching knowledge graph and multi-dimensional behavior analysis; the user interaction layer supports multi-terminal access, and the data security module guarantees compliance. According to the system, the cross-platform data collaboration efficiency is improved by 70% or above, the resource recommendation matching degree reaches 92%, the system is suitable for K12 education, higher education and vocational education scenes, teaching tool data barriers are effectively broken through, and the teaching data utilization rate and the resource recommendation accuracy are improved.

The invention relates to the technical field of alimentary canal diagnosis and treatment, in particular to an alimentary canal detection drug delivery system which comprises an alimentary canal sensing unit for collecting an image, a pH value, a temperature and pathological tissue pathological characteristic data in an alimentary canal cavity; the lesion positioning analysis unit identifies a lesion area through an image segmentation algorithm, constructs a lesion three-dimensional coordinate model according to physiological parameters, prejudges a lesion displacement trend in combination with an alimentary canal peristalsis rule, analyzes a lesion state in stages, and outputs lesion severity; the response type drug delivery module controls the micro drug delivery device to perform targeted release and adjust the drug release rate based on the lesion coordinates and the intracavity environment parameters; the data collaboration platform shares a detection result and a drug administration record through a real-time interaction interface; the curative effect feedback unit is used for collecting physiological index change and patient symptom improvement data after drug administration, judging the drug onset period and possible adverse reactions, and optimizing drug administration parameters and detection frequency. Therefore, the problems of low targeting precision, poor diagnosis and treatment efficiency and the like in the prior art are solved.

The invention provides a dual-CAN channel fusion J1939 protocol stack of a vehicle-mounted terminal and a parallel communication diagnosis method, and aims to solve the problems that an existing dual-CAN channel terminal lacks a protocol layer parallel processing mechanism and an intelligent routing strategy, communication and diagnosis conflicts still exist, and a J1939 protocol is insufficient in adaptation and poor in baud rate adaptation flexibility. The method comprises the following steps: S1, constructing a dual-CAN FD channel and dynamic baud rate adaptive detection mechanism, and providing a link basis for service isolation; s2, integrating J1939 and UDSonCAN dual protocol stacks based on dual CAN FD channels, and establishing data mapping to realize data collaboration between protocols; s3, designing an intelligent message routing and channel flow monitoring mechanism, and ensuring conflict-free parallel transmission of communication and diagnosis services; and S4, newly adding J1939 network management, configuration parameter persistence and firmware online upgrading functions, and improving the maintainability of the terminal. According to the invention, the advantages of dual-CAN channel hardware are fully exerted, efficient cooperation of communication and diagnosis and protocol deep compatibility are realized, and the compatibility, flexibility and stability of the terminal are greatly improved.

The invention discloses a data management method and system based on electric power data intermediate station services, and relates to the technical field of electric power data intermediate stations. The method comprises the following steps: constructing a dynamic semantic modeling mechanism, and forming an evolvable semantic ontology library based on a domain knowledge system; constructing a data behavior graph evolution mechanism, and carrying out semantic monitoring on the whole data governance process; constructing a business semantic consistency verification mechanism, and establishing a multi-layer verification system covering grammar compliance, logic rationality and business integrating degree; a credible data collaboration mechanism is constructed, credible identification is generated for high-quality data, and hierarchical data service is provided. The method solves the problems that in the prior art, a semantic model is static, data behavior tracing is difficult, the quality evaluation dimension is single and credible collaboration is insufficient, and whole-process management of electric power data from semantic unification, behavior tracing, quality guarantee to service collaboration is achieved. And the data service capability and the business support level of the power data medium station are obviously improved.

The invention discloses a high-density electrical method infiltration surface three-dimensional inversion method based on multi-source data collaboration, and the method comprises the steps: constructing a multi-source heterogeneous data collection network, synchronously obtaining four types of data of a dam body monitoring region, and achieving the unification of coordinates and time scales of the four types of data through a space-time registration algorithm; establishing a multi-scale coupling model; on this basis, a deep learning inversion framework fused with physical constraints is developed; an inversion result is optimized through a self-adaptive dynamic correction module; and outputting the corrected three-dimensional distribution model of the infiltration surface. According to the method, a resistivity-moisture content-pore structure-fluid pressure quaternary coupling equation is macroscopically established through a multi-scale coupling model, pressure data are obtained in real time in combination with optical fiber sensing, pressure and pore deformation are correlated through a mesomechanical equation, a physical mechanism is fully fused, resistivity deviation caused by pressure is eliminated, and the resistivity is measured. The three-dimensional form of the infiltration surface is more suitable for the real situation, and an accurate position basis is provided for dam body permeability stability evaluation.

The invention relates to the technical field of electric power system digital twinning, and discloses an electricity metering digital twinning high-fidelity modeling method, system, equipment and medium based on mechanism and multi-source data collaboration, which organically combines the interpretability of physical mechanism modeling and the dynamic correction capability of data driving. Through standardization and fusion of multi-source heterogeneous data, the comprehensiveness and real-time performance of the model are remarkably improved; and meanwhile, a dynamic correction and consistency constraint mechanism is introduced to ensure that the digital twin model keeps high-precision synchronization with a physical entity in the whole operation process, so that high-fidelity mapping and prediction of the operation state of the electricity metering device are realized. The key technical breakthroughs effectively solve the problems of insufficient model precision, poor adaptability and desynchrony of virtuality and reality in a traditional method, and a core method with high reliability and popularization value is provided for the field of power marketing measurement.

The invention relates to the technical field of data collaborative analysis, in particular to a printing order commission distribution and resource allocation linkage method based on multi-channel data collaboration, and the method comprises the steps: integrating various key information of an order through constructing an order-resource map, and reflecting the correlation between the order and resources; an order-resource map is input into a map neural network model to extract a map embedding vector and construct a sub-map, so that a complex relationship between orders and resources can be mined, and accurate initialization of commission distribution and resource nodes is realized; local sub-graphs are shared through distributed communication, and a global commission distribution resource map is generated, so that centralized overall planning of all channels and all resources is realized, and commission distribution and resource allocation decisions are ensured to be based on an overall optimal principle; linkage operation is executed according to the global map to generate a matrix, and an instruction is issued, so that each channel order is ensured to obtain corresponding resources and commission according to a fair and reasonable principle; and the execution node is combined with a state execution algorithm and uploads data, so that a resource allocation path can be dynamically optimized in real time.

The invention relates to the technical field of plastic film production data management, and discloses a plastic film production process and BOM integrated maintenance and sharing method. According to the method, BOM (Bill of Material) and process route maintenance are integrated through a tree structure, and batch data generation with multiple selected materials and multiple production purposes is supported; a cross-material and cross-customer BOM and process route sharing mechanism is constructed, personalized configuration of process parameters such as the screw rotating speed and the temperature partition is associated, and the method adapts to a film production multi-process scene. The technical problems that traditional BOM and process routes are dispersedly maintained, reusability is poor, and parameter configuration is disjointed are solved, efficient management and reusability of production data are achieved, and the process adaptability and data collaboration efficiency of thin film production are improved.

This invention discloses a collaborative management method and system for the entire warehousing and logistics process, belonging to the field of warehousing and logistics information technology. Addressing the technical shortcomings of existing warehousing and logistics management, such as low inventory accuracy, poor scheduling efficiency, lagging information collaboration, and insufficient cost control, this invention integrates the entire process of inbound, storage, picking, outbound, transportation, and traceability, constructing a closed-loop management system of "data perception - algorithm decision-making - process collaboration - dynamic optimization." Through multi-dimensional data collection, optimized algorithm scheduling, cross-system data collaboration, and full-process traceability technology, this invention achieves precise inventory control, optimized logistics route planning, and efficient resource allocation, significantly improving warehousing and logistics operational efficiency, reducing overall costs, and enhancing management transparency. It is applicable to the digital management needs of warehousing and logistics in various industries, including manufacturing, retail, and e-commerce.

The invention provides a cross-device data collaborative question-answering method and device, equipment and a storage medium, which are used for obtaining a retrieval result in a cross-device manner in combination with a question-answering request of a user in a question-answering scene so as to generate a question-answering result according to the retrieval result. The problem that in an existing question and answer scene, a question and answer result can only be generated depending on a local retrieval result, and a data island is formed is solved, and the technical scheme of cross-device data search and intelligent fusion is achieved so as to support highly-personalized question and answer services. The method can comprise the steps that in response to a question and answer request, target equipment related to the question and answer request is determined; under the condition that the target device comprises at least one second device, a retrieval instruction is sent to the at least one second device, and the retrieval instruction is generated according to the question and answer request; receiving at least one retrieval result sent by at least one second device according to the retrieval instruction; and generating a question-answer result according to the at least one retrieval result.

The invention discloses an intelligent scheduling method and system for a wind-light-hydrogen storage integrated logistics park, and relates to the technical field of computers, a data collaboration system is constructed, multi-dimensional data alignment is executed, and a hydrogen production prediction function is calculated by using an inference model; calculating a dynamic hydrogenation admission threshold based on the pressure feedback and the logistics demand change; according to the predicted hydrogen production trend of the prediction function, predicting whether the generated power of the power system is in a crest period or a trough period, limiting hydrogenation in the trough period in combination with a threshold value, and guiding the vehicle to supplement energy in the crest period, so as to cope with hydrogen production demand mismatch caused by fluctuation of wind and light resources, and change post-management into prospective regulation and control to reduce potential safety hazards. Energy supply is guaranteed, and an energy storage strategy is optimized.

The invention discloses a hospital performance evaluation system based on multi-source scientific research data collaboration, and the system comprises a multi-source data collection module which is used for collecting scientific research performance original data from an internal information system of a hospital and an external scientific research database; the data collaborative processing module is connected to the multi-source data acquisition module and is used for cleaning, integrating and standardizing the scientific research performance original data to generate high-quality collaborative data; the performance indicator modeling module is connected to the data collaborative processing module and is used for calculating the high-quality collaborative data based on a data envelope analysis model and a radial basis function neural network to generate a performance evaluation result; and the performance management platform is connected to the performance indicator modeling module and is used for displaying the performance evaluation result. According to the invention, automatic acquisition, cooperative processing, intelligent modeling and visual management of scientific research data can be realized, and accurate, efficient and dynamic evaluation can be carried out on scientific research performance of hospitals, departments and individuals.

The invention discloses a lightweight master data management method, which relates to the technical field of digital office, and realizes flexible iteration and cross-system data collaboration of a master data specification by creating a master data source system, issuing a dynamic adaptation system and standard and utilizing a master data classification dynamic mapping mechanism to clarify a master data unique source system; the method comprises the following steps: establishing an intelligent workflow, establishing a main data application function and approval permission intelligent adaptation engine in an office OA, and automatically generating a main data distribution interface with permission binding after obtaining approval, thereby improving the approval efficiency and the main data use security; an adaptive API interface is created, an interface dynamic adaptation and load balancing mechanism is constructed in a main data source system, and efficient and direct distribution of main data is achieved; through main data distribution quality closed-loop monitoring, log analysis and dynamic optimization engine linkage are utilized, and the main data distribution quality is guaranteed.

The invention discloses a digital environment infrastructure system and method, and relates to the technical field of the Internet, and the system comprises a demand management module which is connected with a target user terminal, and is used for generating a demand list; the supply management module is used for collecting supply information of suppliers in real time and determining the supply state of each supplier; the supply and demand decision module is used for generating and executing an optimal solution based on the demand list and the supply information of the target supplier; the data management module is used for cleaning data and converting the cleaned data into data assets by using a block chain technology, wherein the data is data acquired and generated by each module; and the digital environment intelligent support management module is used for managing the operation state of each module in the implementation process. The invention aims to solve the problems that data splitting and data collaboration are difficult and cross-platform data element circulation and capitalization are difficult to realize due to the fact that an existing digital scheme mostly focuses on a single link or a specific scene.

The invention discloses a supply chain privacy data collaboration method based on a block chain channel, and belongs to the technical field of block chain privacy protection. The system comprises a channel management module, a data classification module, an authority management module and a data verification module. The method comprises the following steps: establishing an independent private data channel for a core enterprise and each supplier in an alliance chain network; dividing the supply chain data into global shared data and channel private data according to the data sensitivity; dynamic authority control based on roles and business scenes is realized through an intelligent contract; and data credibility verification under privacy protection is realized by adopting a zero-knowledge proof technology. According to the method, through a channel isolation mechanism, on the premise of ensuring that a core enterprise is globally visible to a supply chain, commercial confidentials such as production cost and process parameters of suppliers are effectively protected, the contradiction between privacy protection and data transparency in supply chain collaboration is solved, and the security and credibility of multi-level supply chain collaboration are remarkably improved.

This invention relates to the field of data processing, and more specifically, to a method and system for constructing high-speed engineering BIM models based on data analysis. The method includes: collecting data including point clouds of a BIM design model, point clouds of the construction site, and GIS geographic information of the project area; calculating the dynamic weight of each point cloud at the construction site; constructing a weighted ICP objective function using the dynamic weights of all point clouds at the construction site, and then performing precise registration between the point clouds of the BIM design model and the point clouds of the construction site to obtain a precisely registered BIM design model; and fusing the precisely registered BIM design model with the GIS geographic information to achieve multi-source data collaboration and optimization of the model. The dynamic weighting mechanism constructed in this invention can more accurately measure the importance of each point cloud in the registration process, effectively distinguishing between BIM design entities representing permanent structures and a large number of temporary objects without corresponding BIM semantics.

This invention discloses a multi-source data intelligent connection management method, belonging to the field of data processing and information fusion technology. The method includes: deploying an intelligent agent program to listen to window message streams and reconstruct operation paths; synchronously capturing and parsing network requests to obtain structured business data; establishing a mapping relationship between operations and data through multimodal fusion parsing; filtering target data based on a no-code rule base; standardizing formats using a conversion engine; generating RPA instructions with the assistance of a large model; embedding a digital credential mechanism throughout the entire chain to ensure data integrity; and dynamically enhancing business logic through extension point injection. This invention aims to solve the problems of difficult data collaboration, high adaptation costs, and insufficient security caused by the lack of standard interfaces in heterogeneous business systems. It achieves high-precision, low-latency, and auditable automatic data collection, conversion, and entry across closed systems, significantly shortening the supplier access cycle and improving the efficiency of supply chain four-flow collaboration and system scalability.

The invention relates to a demand entry control method and system. The method comprises the following steps: step S1, demand compilation and structured export; s2, platform entry control is carried out; and S3, performing DOORS entry editing permission control. Through entry-level authority control and a precise change operation mechanism, the problem of data islands is effectively solved, fine processing of a single demand entry is supported, the method has the advantages of improving the fine level of demand management, enhancing the data collaboration capability, optimizing the change control process and the like, the limitation that DOORS data can only be stored in a local server is broken, and the demand management efficiency is improved. An interconnection mechanism between the DOORS client and the product data management platform is established, so that fine control and rapid iterative updating of the demand items are realized, operations such as tree-shaped display, batch signing and auditing, version raising and release freezing of the demand items are supported, and the automation degree and the control efficiency of demand change processing are greatly improved.

The invention discloses an optical transmission equipment hardware fault linkage method and equipment for communication operation and maintenance fault simulation, and belongs to the technical field of power system communication. The method comprises the five steps of fault feature standardized modeling, difficulty level intelligent division, training mode linkage configuration, linkage rule dynamic generation and multi-module data collaborative updating. According to the method, data normalization is realized by constructing a standardized fault feature library, fault difficulty grading is realized by a dynamic weight algorithm, stepped training is realized by training mode linkage configuration, adaptive rule generation is realized by a linkage rule engine, scene consistency is realized by multi-module data collaboration, and finally, the fault handling capability of operation and maintenance personnel is improved.

The invention discloses a multi-source heterogeneous data pollution traceability and management system based on end-edge-cloud collaboration. The system comprises a multi-source heterogeneous data acquisition module, a cloud-edge collaboration data management and control module, an environment traceability graph embedded sensing module, an interpretable traceability analysis module, a closed-loop regulation and control decision module and a pollution abatement feedback module. A sensing end multi-dimensional sensor collects various types of data, edge end preprocessing and cloud deep analysis cooperation are carried out, an abnormal sensing algorithm is embedded based on an environment traceability graph, a dynamic pollution source identification mechanism is constructed by an interpretable environment pollution traceability analysis model, and a strategy is adjusted in combination with a data pollution closed-loop regulation and control decision model. And the links of early warning, patrol, traceability, disposal and feedback are covered. According to the system, the robustness and maintainability of a multi-source data system are improved, rapid response, accurate traceability and intelligent closed-loop management of pollution events are realized, the problems of insufficient monitoring data collaboration and poor traceability treatment closed-loop performance are effectively solved, and the fine management requirement of environment monitoring is met.

This invention relates to the field of privacy computing and discloses a collaborative analysis method for potential financial risks based on fuzzy privacy set intersection. The method first protects the privacy of deposit and loan data from various financial institutions through Paillier homomorphic encryption. Then, it utilizes a fuzzy privacy set intersection algorithm based on Unintentional Key-Value Storage (OKVS) and the discrete logarithm problem to achieve fuzzy matching of user identities across multiple institutions. While ensuring the privacy of user feature data, it identifies records of the same user that meet a predetermined distance threshold. Finally, it aggregates the encrypted deposit and loan data of the matched records and compares them with the threshold. A trusted third party decrypts the data and completes the judgment of potential financial risks, thus realizing financial privacy and security risk analysis under cross-institutional data collaboration.

The invention belongs to the technical field of medical apparatus and instrument control, particularly relates to an atomization control system for respiratory nursing, and aims to solve the problems of low medicine deposition efficiency, serious waste and incapability of precise medicine administration caused by the lack of the capability of sensing and responding to the real-time respiratory state of a patient in a traditional atomization device. The system comprises a breathing state real-time monitoring module, an aerosol generation and regulation module, an intelligent control center, a man-machine interaction interface and a cloud data collaboration platform. Breathing parameters are collected through a high-sensitivity sensor, the particle size and the output opportunity of fog drops are dynamically adjusted in combination with a dual-mode ultrasonic atomization technology, and accurate inspiration phase dosing is achieved; a self-adaptive learning engine is arranged in the intelligent control center, the breathing cycle can be predicted, atomization can be started in advance, and the response speed is increased; local closed-loop control and remote personalized management are supported, and the medicine utilization rate and treatment compliance are remarkably improved.

The present application relates to the technical field of data processing and analysis, in particular to a cross-system data collaborative intelligent analysis method based on business logic. The method first deploys edge computing nodes at key traffic locations for data collection and preprocessing, then networks and communicates between nodes, then each node extracts data features and performs local analysis, starts and assigns collaborative analysis tasks according to predefined trigger conditions including quantitative and qualitative conditions, nodes share and fuse data according to tasks, use traffic flow and machine learning models to collaboratively analyze and generate decision suggestions based on the fused data set, and feed back to the traffic management system, and finally optimize and adjust according to the feedback information. The corresponding system includes multiple edge computing nodes with corresponding function modules working collaboratively. The present application effectively overcomes the problems of insufficient collaboration and incomplete analysis in existing traffic data processing, can quickly respond to traffic condition changes, improve traffic data analysis quality and the scientific nature of management decisions, and ensure efficient operation of the traffic system.