349 results about "Integrated management system" patented technology

The invention discloses a low-altitude integrated management system based on a grid digital twin model and an intelligent algorithm, and relates to the technical field of low-altitude aircrafts. The method comprises the following steps: multi-source sensing data fusion and grid coding are carried out, and an airspace environment space-time database is constructed; constructing an airspace environment space-time database to carry out three-dimensional subdivision on the airspace; generating a multi-scale grid twinborn body, and associating a corresponding attribute for each level of grid according to a management requirement; generating an airspace risk thermodynamic diagram in the future 5-30 minutes; establishing a grid state change triggering rule; and generating a multi-target optimal path set by taking the grid navigation cost as a weight. According to the invention, by combining the real-time operation data of the low-altitude aircraft, the meteorological environment and other data with the artificial intelligence algorithm and the navigation rule base, the airspace traffic flow is analyzed, the flight plan is optimized, the flight route is intelligently distributed, the automatic route setting of any two points is realized, and the response speed of the low-altitude flight service system and the processing capability of various flight data are improved.

The invention discloses an operation and maintenance management method of an integrated management system, and belongs to the technical field of operation and maintenance of systems. The invention discloses an operation and maintenance management method of an integrated management system, and aims to solve the problems of data islands, slow fault positioning, experience dependence on strategies and the like in traditional operation and maintenance. The method comprises the following nine core processes: dynamically accessing multi-source heterogeneous data and carrying out standardization processing; constructing a hierarchical time series data storage structure; generating a modeling dependency and fault path of the equipment knowledge graph; adopting a three-layer anomaly detection model to identify anomaly; fault root causes are positioned through causal reasoning and a Bayesian network; generating an energy efficiency strategy based on reinforcement learning and multi-objective optimization; triggering the self-healing workflow to execute operation; testing the robustness of the system in a sandbox environment; and iteratively updating the knowledge graph and the AI model to form a closed loop. According to the method, automation and intelligentization of the whole operation and maintenance process are realized, and the system availability and the energy efficiency management level are improved.

The invention relates to the technical field of risk analysis, in particular to a safety engineering comprehensive management system which comprises a geological parameter dynamic monitoring module, a risk threshold early warning module, a stability weight evaluation module and a risk comprehensive management and control module. According to the method, lithology data are extracted through a drilling profile to calculate the layer thickness sudden change rate and the strength attenuation rate, a lithology abnormal area is positioned through a variable coefficient method, lithology sudden change marks are analyzed through spatial clustering, a dynamic trend is captured through sliding window mean value comparison, and gradient amplitude and slope direction dispersion are calculated through a digital elevation model. Fusing the abnormal point density to generate a terrain instability index; establishing a multi-dimensional quantitative evaluation framework; carrying out fuzzy comprehensive evaluation and cross validation on the instability index and an engineering parameter trend; generating a dynamic priority sequence, carrying out stake number interval matching to construct a risk measure table, carrying out analytic hierarchy process dynamic resource allocation support drainage scheme, and carrying out real-time monitoring and prediction closed-loop iteration. And adaptively adjusting the control strategy.

The invention belongs to the technical field of equipment integration, and discloses a multi-modal equipment integrated management system and method based on intelligent AI, and the system comprises an autonomous sensing module which carries out the real-time causal modeling of multi-modal data through embedded causal analysis; in combination with a self-supervision anomaly detection mechanism, outputting a device cause and effect graph and a data stream with a confidence label; the liquid feature factory module is used for extracting time sequence features by utilizing a gating time sequence convolutional network based on an equipment causal graph and a data stream with a confidence label, reconstructing a feature path through a dynamic feature molten pool mechanism, and performing compression selection on high-dimensional features in combination with a sparse regularization method so as to generate a feature tensor; and accurate perception, efficient decision making, accurate execution and intelligent optimization management of the equipment can be realized.

The invention relates to the technical field of business financial management and control, and discloses a business financial integrated management system. A service activity feature extraction module of the system collects a service end operation behavior data stream, extracts service activity time sequence features, calculates a service operation frequency fluctuation range, and generates a service activity feature vector; the service state judgment module is used for matching a preset service activity feature library according to the service activity feature vector, identifying an abnormal service operation node, calculating a service operation deviation degree and generating a service state judgment index; the financial risk conduction analysis module obtains a business state judgment index, analyzes an association path of a business node and a financial event, evaluates a financial risk conduction probability, and generates a risk conduction evaluation result; and the resource collaborative optimization module analyzes a business and financial resource configuration deviation based on a risk conduction evaluation result, calculates a resource collaborative optimization priority and generates a resource collaborative adjustment strategy.

The invention provides an enterprise financial comprehensive management system based on an intelligent technology, and relates to the technical field of financial management. The accounting intelligent subsystem is used for acquiring financial data, performing semantic analysis and conversion on the financial data through a preset rule and a multi-stage data mapping mechanism, generating a standardized accounting service instruction and issuing the standardized accounting service instruction to an automatic process engine, thereby automatically generating a financial document meeting an accounting criterion; the financial management subsystem is used for integrally realizing execution of backlog management, compliance guidance manual query and financial data structured storage according to a preset standardized process; and the business service subsystem is used for providing tax-related business service, asset management service, fund management service and operation management service processing and guidance for enterprises through modular design. The invention aims to improve the operation efficiency, reduce the error rate, break information islands, realize effective integration and utilization of resources, and provide powerful support for decision making of enterprises.

The invention belongs to the technical field of enterprise financial management, and particularly relates to an intellectualization-based financial integrated management system, which constructs a reference budget reasonable interval of each auditing project through reference project comparison and market prediction change of each auditing project so as to evaluate the rationality of a planned budget amount uploaded by each auditing project principal, thereby improving the management efficiency. After it is determined that the planned budget amount of each auditing project is reasonable, according to the priority coefficient and the risk level coefficient of each auditing project, arranging a corresponding budget payment sequence, and on the basis of the financial funds of the target enterprise in the future preset period, making a project budget scheme of the target enterprise in the future preset period. And the budget execution condition of each auditing project at each accounting time point is collected, the regulation and control requirements of the project budget scheme of the target enterprise in the future preset period are judged, and corresponding dynamic regulation and control are performed, so that effective cooperation of enterprise financial budget and accounting is realized, and the financial decision quality and the operation benefit of the enterprise are further guaranteed.

The invention discloses a business and financial integrated management system, which constructs a high-elasticity and easy-to-expand business and financial integrated management system through deep fusion of cloud native and micro-service architecture. The system realizes real-time acquisition and cleaning of business and financial data through a standardized data interface and an ETL technology, and data islands are thoroughly broken; a business process modeling tool cooperates with a workflow engine, financial management and control nodes are embedded into the whole business process, and the real-time performance of budget execution and cost collection is ensured; the intelligent analysis module combines OLAP and machine learning, provides multi-dimensional data insight and risk prediction, and significantly improves decision scientificity. In addition, due to the distributed log and role grading permission design, the safety and auditing performance of the system are enhanced. The system not only reduces the manual operation error rate and IT operation and maintenance cost, but also assists an enterprise in realizing refined operation and agile decision making through an automatic process and an intelligent early warning mechanism.

The invention relates to the technical field of power plant data processing, in particular to a virtual power plant integrated management system, which comprises a data acquisition module for acquiring voltage fluctuation characteristics and power climbing rate parameters of energy equipment in real time; the equipment fingerprint database construction module generates an equipment fingerprint code comprising a dynamic response time-lag coefficient and an adjustment margin quantized value; the dynamic clustering module is used for dividing simulation sub-models of regional topology constraints based on the geographic position of the equipment and a power regulation threshold value; the multi-time scale prediction module is used for generating source load prediction data by fusing meteorological parameters through a space-time diagram convolutional network; the digital twin simulation module outputs an energy storage charging and discharging threshold value and a demand response priority strategy; and the cross-domain collaboration module adopts a double-chain block chain architecture to realize security verification and data integrity binding of federated learning feature parameters. According to the invention, through equipment characteristic digital modeling, regional co-simulation and multi-energy flow coupling regulation and control, the resource aggregation precision and response real-time performance in a new energy strong fluctuation scene are improved.

The invention discloses a cross-platform job resource integrated management system and method based on the Internet, and belongs to the technical field of job resource management. A baseline model is constructed, and whether resource consumption data is abnormal or not is judged; extracting an abnormal resource type, obtaining a corresponding resource demand, identifying tasks having resource competition with the current job, and obtaining an abnormal competition task set; defining job attributes, determining a resource association relationship between tasks, and constructing an abnormal competition task relationship graph; determining the latest execution time of each competition task; analyzing the maximum bearing capacity of the current resource meeting all task execution under the conflict-free condition; calculating the quantity of resources needing to be added; subtracting the actually added resource quantity from the resource quantity needing to be added to obtain a vacant resource quantity; when personnel resources are vacant, the competition tasks are sorted, and the competition tasks are preferentially allocated to high-priority exclusive jobs in combination with the maximum bearing capacity; when the device resources are vacant, idle special devices are preferentially allocated for exclusive jobs.

The invention discloses a solar power generation integrated management system, equipment and method based on AI intelligence, and particularly relates to the technical field of photovoltaic power generation. By analyzing the light-induced attenuation data of the photovoltaic module, judging whether the light-induced attenuation of the photovoltaic module has reversibility or not by using a convolutional neural network; based on the light intensity change data of the cloud layer edge light intensity abrupt change area, the influence degree of the cloud edge nonlinear shielding and reflection gain effect on the photovoltaic array power fluctuation is evaluated; and determining the working state of the photovoltaic module according to the judgment result of whether the light-induced attenuation is reversible and the evaluation result of the nonlinear shielding and reflection gain effect. When the assembly is in an abnormal working state, the non-linear attenuation influence degree of the aerosol retention layer on the light transmittance is evaluated by analyzing the light transmittance change. And whether an operation and maintenance scheme is started or not is judged according to the evaluation result, so that intelligent diagnosis and fine management of the operation state of the photovoltaic module are realized, and the operation efficiency and reliability of solar power generation are improved.

The invention relates to the technical field of enterprise data management, in particular to a lightweight-based enterprise data dynamic integrated management system, which is characterized in that an acquisition module is used for deploying edge computing nodes, receiving multi-source heterogeneous information streams from manufacturing execution systems and equipment logs, dynamically analyzing and standardizing the information streams, and adding metadata tags; uploading is carried out in a batch processing mode; the map construction module is used for constructing a semiconductor blood relationship map by taking the standardized key information as a blood relationship clue; a graph database is used for efficient storage, and a RESTful API interface is configured to support batch import, so that data storage and relevance expression are more flexible and efficient; the prediction module performs reasoning on the atlas by adopting a graph neural network to generate predictive risk distribution, and a correlation analysis set generated by the prediction module is stored back to the atlas in a structured manner; by introducing a multi-thread concurrent write-in and lock mechanism, the atlas supports complex combination query based on a Cypher query language, and supports multi-level and traceability query.

The invention discloses a BIM building intelligent integrated management system based on Internet of Things control, and relates to the technical field of networking technology and building intelligent management, and the system comprises a sensing layer, a transmission layer, a platform layer and an application layer. The sensing layer comprises a multi-source heterogeneous sensor cluster and is divided into an environment monitoring unit, an equipment state acquisition unit, a personnel positioning unit and a structure health monitoring unit, and each unit is provided with a corresponding sensor; the transmission layer adopts a LoRaWAN and 5G fusion architecture and comprises an edge computing gateway, a TSN switch and a data security encryption unit, and the gateway can perform frequency domain analysis and the like; the platform layer is based on micro-service and is provided with a multi-source data fusion engine and a BIM model dynamic updating module; the application layer provides an equipment fault prediction module, an energy optimization module and a safety risk early warning module, and all the modules adopt corresponding algorithms. According to the invention, a hierarchical collaborative architecture is constructed, a multi-source sensor, a heterogeneous network and the like are integrated, deep integration of multi-dimensional management of a building is realized, and the problems of subsystem independence and data obstruction of a traditional system are solved.

The invention is suitable for the technical field of enterprise purchase management, and provides an enterprise purchase service integrated management system and method, and the method comprises the steps: screening out all target purchase tasks which are not approved by a target enterprise auditor after a planned auditing time point of the target enterprise auditor is received, and determining a specific category and an initial priority index of each target purchase task, and extracting a historical purchase log and a historical application log of the target enterprise in a preset time period. According to the technical scheme, the priority index of the purchase task is dynamically optimized by combining the historical trend gradient and the use benefit deviation coefficient, and the actual demand and the potential delay risk of each task can be more accurately evaluated. The historical trend gradient reflects the difference between the time required for task completion and the estimated time, so that the possible delay trend is revealed; and the benefit deviation coefficient is used for comparing the actual application duration with the standard application duration to help judge whether the goods can be put into use in time or not.

The invention relates to the technical field of management systems, in particular to a pig behavior and pigsty environment integrated management system based on digital twinning, which comprises a digital twinning system, and the digital twinning system comprises an Internet of Things module used for data acquisition and transmission between a physical pig farm and a digital twinning model; the environmental parameter acquisition module is used for acquiring environmental data in the pig farm in real time by installing various sensors in the pig farm; the animal behavior data acquisition module is used for monitoring and identifying pig behaviors, including motion behaviors, feeding behaviors, land laying behaviors and climbing attack behaviors. In the invention, aiming at the problem of weak capabilities of capturing, analyzing and predicting pig behaviors in the prior art, the animal behavior data acquisition module is used for comprehensively monitoring the behaviors such as movement, feeding, land laying, climbing attack and the like of the pigs, so that the dynamic change and interaction relationship between the environment and the behaviors can be effectively captured, and the accuracy of a prediction result is improved.

The invention discloses a comprehensive management system for intelligent power distribution, and the system comprises a sensing layer which is provided with a plurality of sensors, the sensors are disposed on power distribution equipment, and are used for collecting the operation data of a power distribution system in real time, and the operation data comprise a current I, a voltage U, a power P, an equipment temperature T, a power factor cos phi, and an insulation resistance R; the transmission layer is used for transmitting the operation data to a data layer; the data layer is used for preprocessing the operation data to generate standardized data, and preprocessing comprises data cleaning and normalization conversion; and the application layer comprises a fault early warning module, a predictive maintenance module, an energy consumption analysis module and a remote control module, and the application layer realizes collaborative management by calling the standardized data. Multi-dimensional data fusion, a dynamic intelligent algorithm and a module interaction mechanism are introduced, and full-process intelligence of power distribution management is achieved.

The present application relates to the technical field of project management, and discloses an integrated management system and method for a large-scale project. The system comprises: a budget subsystem, used for obtaining target project information, and carrying out multi-level classification processing and coding processing on the target project information to obtain budget codes; a contract management subsystem, used for decomposing the target project information, generating a plurality of project contracts and associating the plurality of project contracts with the budget codes; a construction management and control subsystem, used for splitting the project contracts to obtain unit projects, encoding the unit projects to obtain unit codes, and associating quantity data corresponding to the unit projects with a preset construction drawing list; and a joint control subsystem, used for carrying out joint control on the project cost, the project progress and the project quality on the basis of a measurement visa so as to carry out integrated management on a large-scale project. The present application realizes integrated management of large-scale project construction.

The invention discloses a fuel cell heat and humidity integrated management system and an evaporation phase change cooling method thereof, and belongs to the technical field of fuel cell heat management. The system comprises an air cooling and humidifying module, a heat dissipation, evaporation and phase change module and a water recovery and distribution module. The air cooling and humidifying module distributes compressed air to an ultrasonic atomizing nozzle to be mixed with atomized water, and cooling and humidifying of main path air are achieved. The heat dissipation evaporation phase change module sprays atomized water to the surfaces of ATS radiator fins, and heat dissipation is enhanced through evaporation phase change. And the water recovery and distribution module recovers moisture in wet air at an electric pile outlet through condensation and intelligently distributes the moisture to the two atomization systems. A traditional intercooler and a traditional membrane humidifier are omitted, the air flow resistance is reduced by 15-20%, the heat dissipation efficiency is improved by 10% or above, the weight of the system is reduced by 8%, closed-loop utilization of reaction water is achieved, and the system is particularly suitable for fuel cell systems of mobile carriers such as vehicles and unmanned aerial vehicles.

The invention discloses an integrated management system for safety responsibility insurance information, and particularly relates to the field of risk prevention and control, which comprises a multi-source data acquisition layer, a composite index calculation engine, a progressive analysis model library, an intelligent decision center and a management cockpit. According to the method, insurance services, enterprise production and geographic risk data are integrated through a multi-source heterogeneous data fusion architecture, information islands are eliminated by adopting a streaming cleaning verification mechanism, a panoramic dynamic risk feature library is constructed, the integrity and timeliness of assessment elements are improved, a composite index calculation engine innovatively fuses a Shannon entropy theory and a nonlinear coupling algorithm, and the risk assessment efficiency is improved. Risk density adaptive measurement and calculation are realized through dynamic industry coefficients and seasonal factors, a risk evolution law and compensation association relationship are accurately described, prediction perspectiveness and strategy scientificity are enhanced, and an intelligent decision center is linked with a block chain evidence storage system based on a progressive analysis model, automatically generates an underwriting strategy optimization instruction and issues the instruction in real time.

The invention discloses a GIS-based pipe network geographic information integrated management system, and relates to the technical field of geographic information, a pipe network information acquisition module can accurately extract detailed attribute information of graphic elements in each layer from a GIS management system, and generates feature vectors through preprocessing to build a data basis for subsequent analysis. The layer display module can determine the overlapping rate of graphic elements between layers through a rigorous calculation process, analyzes the overall overlapping distribution condition, and then judges whether a visual conflict hot spot area exists or not. On the basis, the interlayer interference analysis module quantitatively calculates a visual conflict measurement coefficient and a logic correlation coefficient from the perspective of representation and internal correlation and deeply analyzes the multi-dimensional relation between layers, and the comprehensive analysis module utilizes deep learning to construct a model, integrates the coefficients and outputs a comprehensive conflict measurement index. And overall coordination performance among the layers is comprehensively evaluated.

The invention discloses an integrated management system based on an artificial intelligence computing platform, and relates to the technical field of integrated management, and the system comprises the following steps: monitoring and obtaining resources, and obtaining heterogeneous computing resource state information; performing resource health assessment according to the heterogeneous computing resource state information to obtain a resource availability index; performing task resource matching according to the resource availability index to obtain a resource allocation scheme; performing calculation task scheduling according to the resource allocation scheme to obtain a task execution sequence; performing task execution monitoring according to the task execution sequence to obtain a task real-time execution state; and performing resource adjustment according to the task real-time execution state to obtain a resource allocation adjustment result. According to the method, the matching accuracy and the resource utilization rate are improved, resource waste caused by single resource bottleneck is avoided, and the load balance and the overall operation stability of each node are improved.

The invention discloses a safety production standardized comprehensive management system and method, and relates to the technical field of safety production management, the system comprises the following components: a data acquisition module, a data preprocessing module, a model construction and training module, a prediction analysis module and a maintenance management module; according to the method, the time sequence data in the full life cycle of the equipment are continuously collected, the time sequence data comprise key parameters such as operation duration, start-stop times and maintenance records, the improved LSTM neural network is utilized to construct the equipment safety life prediction model, and the model can not only predict the overall life of the equipment, but also can predict the service life of the equipment. The method can accurately predict the residual safe use cycle of the easily-worn part, the accurate prediction capability enables an enterprise to plan a maintenance plan in advance, production interruption and safety accidents caused by sudden equipment faults are avoided, and the accuracy and foresight of equipment safety management are remarkably improved.

The invention relates to the technical field of the Internet of Things, in particular to an integrated parking space management system and method based on the Internet of Things. The system comprises an electronic parking space lock which is used for identifying vehicle license plate information of a vehicle owner and unlocking and locking the parking space lock after comparison according to input information; the parking space management all-in-one machine is used for storing vehicle information of a vehicle owner and controlling opening and closing of the electronic parking space lock; and the client is used for inputting the vehicle information of the vehicle owner into the parking space management all-in-one machine and remotely controlling the electronic parking space lock to be opened and closed. According to the technical scheme, in the equipment installation process, operation is easy and convenient, intelligent management can be effectively carried out on parking spaces, one-to-one independent equipment control and independent installation can be achieved, use is convenient, the trouble of getting on and off of an automobile owner is reduced, and a remote control key does not need to be kept all the time.

The invention discloses a one-stop photovoltaic, energy storage and charging integrated management system, which relates to the field of optical storage and charging intelligent system management and comprises a data acquisition module, a distribution module, a module for further optimizing power distribution and analysis among charging piles based on an energy distribution scheme, a data storage and charging management module, a data storage and charging management module and a power management module, wherein the data acquisition module is used for acquiring operation data of an optical storage and charging intelligent system through various sensors and communication modules; an optimization module which is used for inputting optimized parameters of the optical storage and charging intelligent system and calibrated equipment information into the optical storage and charging intelligent system, analyzing the performance of the optical storage and charging intelligent system, improving an algorithm and a strategy, continuously optimizing the optical storage and charging intelligent system and generating a performance analysis report; by introducing an adaptive energy distribution algorithm and an intelligent data analysis module, power distribution among the charging piles can be dynamically optimized, and system parameters can be automatically adjusted based on a performance analysis report, so that the operation efficiency of the system and the user experience are remarkably improved.

The invention relates to the technical field of education management, in particular to a smart campus integrated management system and method, and the system comprises a course arrangement module, a teacher matching module, a resource scheduling module, a behavior monitoring module and an interaction guiding module. Through intelligent processing, course arrangement and teacher matching optimization, the teaching resource utilization efficiency is improved, errors and deviations in manual processing are avoided, the matching degree of courses and students is improved by means of intelligent screening and conflict elimination, course conflicts are reduced, matching is carried out according to the qualification and preference of teachers, teacher resource configuration is optimized, and the teaching efficiency is improved. The accurate scheduling of classroom and equipment resources avoids resource waste and insufficiency, the smooth campus management is ensured, the behavior monitoring technology and the safety perception means track the behaviors in the teaching process in real time, the interactive guidance provides immediate feedback and guidance in the case of abnormality, the potential safety hazard is reduced, and the teaching efficiency is improved. And the intelligent safety guarantee level of the campus is improved.

The invention relates to the field of aircraft simulation management, and discloses an aircraft full-process multi-field simulation and real-time comprehensive management system, which is used for solving the problem that normal aircraft change is misjudged as a program fault when an aircraft simulation task is carried out, and comprises the following steps: carrying out unified configuration of a simulation scene, generating a standardized configuration file, and storing the standardized configuration file into a database; the method comprises the following steps: completing three-dimensional scene construction and target dynamic modeling, obtaining an image frame, carrying out image frame preliminary anomaly judgment according to the image frame, if the image frame is judged to be abnormal, carrying out image frame actual anomaly judgment according to aircraft data, and if the image frame is judged to be abnormal, carrying out image frame marking and sending out an early warning. The aircraft operation state is dynamically adjusted according to the simulation control instruction, the aircraft operation state is transmitted to the visual display module, an image output and aircraft operation state graphical display interface is provided, the probability of false touch early warning, simulation process interruption and invalid sample output is effectively reduced, and the credibility and stability of a simulation result are improved.

The invention discloses a multi-mode electronic commerce data integrated management system, and relates to the technical field of electronic commerce data management. The multi-modal electronic commerce data integrated management system comprises a data acquisition module used for acquiring the current sales volume and commodity sales data of each commodity after the current period is ended, a data analysis module used for analyzing the customer flow index and the customer emotion fluctuation index of each commodity based on the commodity sales data, and a data storage module used for storing the customer flow index and the customer emotion fluctuation index of each commodity. The prediction analysis module is used for predicting the sales prediction quantity of each commodity in the next period based on the customer flow index and the customer emotion fluctuation index of each commodity, and the inventory calling module is used for carrying out scheduling supplementary processing on each commodity based on the sales prediction quantity of the next period. According to the method, the customer flow index and the customer emotion fluctuation index are integrated, the purchase intention and market demand change of the customer can be reflected more comprehensively, and the sales volume of each commodity can be accurately predicted through the multi-dimensional data fusion mode.

The invention discloses an enterprise and government-oriented brain service integrated management system and method, and relates to the field of intelligent management, and the method comprises the steps: obtaining an industrial index abnormal event containing a multi-dimensional feature in real time, positioning a focus assembly in a service topology and upstream and downstream associated nodes thereof, and combining data blood relationship information to extract a key context; performing semantic embedding coding on an original log, and converting an unstructured log text into computable vector space representation; and finally, through a feature manifold search engine driven by a large model, cross-modal association matching is performed on the structured abnormal event features and the log semantic vectors, and an intelligent report is automatically generated. The system effectively solves the problems that in a traditional scheme, service link fault analysis and heterogeneous data association are difficult, and the dependence degree of artificial experience is too high, and the handling efficiency and decision-making reliability of abnormal events of a complex system are greatly improved.

The invention relates to the technical field of battery car charging management, in particular to a battery car charging integrated management system based on edge calculation, which acquires battery parameters of a battery car and state parameters of a charging pile in real time through a battery car end acquisition module and a charging pile end acquisition module, and performs local processing through an edge calculation unit. The real-time performance of data processing is improved, and abnormal conditions can be quickly responded. Charging behaviors are analyzed through deep learning, abnormal conditions are judged, and data are distributed to a load balancing unit or a risk assessment unit. The load balancing unit utilizes a reinforcement learning model to optimize charging load distribution according to the power grid load, the battery car demand and the charging pile state so as to avoid power grid overload. The risk assessment unit establishes a model through historical data, monitors the risk in real time and gives an alarm, and meanwhile, through edge calculation and local deployment of a classification model, the dependence on the cloud is reduced, and the calculation efficiency and the management efficiency are improved.

The invention relates to an ESG carbon accounting comprehensive management system for an enterprise and a use method of the ESG carbon accounting comprehensive management system in the field of ESG management, a multi-stage jump processing layer is added on a carbon emission data acquisition and accounting module on an original system, and the multi-stage jump processing layer comprises a standard process line and a non-standard process line; the multi-stage jump processing layer further comprises a user-defined module jump node, the user-defined module jump node is in node connection with all the modules, the data management and analysis module comprises an independent database in data connection with the multi-stage jump processing layer, and the independent database comprises an intelligent data simulation module. And the intelligent data simulation module is in data interleaving connection with the standard process line and the non-standard process line so as to deal with ESG carbon accounting comprehensive management of complex multi-product research and development.