1862 results about "Digitality" patented technology

The invention relates to the technical field of digital factory production management, and discloses a digital factory-oriented multi-target production plan optimization method and system, and the method comprises the steps: decomposing an enterprise order into a plurality of subtasks through a production task decomposition module, and extracting related information; the resource dynamic evaluation module collects data in real time to generate a resource state matrix; the multi-objective optimization algorithm module constructs a model and adopts an improved non-dominated sorting genetic algorithm to solve; the dynamic priority distribution module adjusts the priorities of the sub-tasks according to the real-time data; and the conflict resolution unit is used for solving resource allocation conflicts. The method can accurately decompose tasks, evaluate resources in real time, collaboratively optimize multiple targets, flexibly deal with abnormities, efficiently resolve conflicts, comprehensively improve the production efficiency and benefits of the digital factory, and effectively solve the complex problems in the production plan making and optimizing process of the digital factory.

The invention relates to the technical field of power distribution, in particular to a construction method and system for a digital twinborn model of a power distribution network. Establishing a digital element of the multi-physical field coupling characteristic of the power distribution network equipment based on quantum state space mapping, and simulating a collaborative degradation process of insulation aging and electromagnetic interference of the equipment; constructing a dynamic energy flow entanglement relationship among the nodes of the power distribution network according to the equipment degradation characteristic tensor; based on the quantum entanglement relationship between the device degradation feature tensor and the topology connection hypergraph, establishing a time-space coupling eigenmode of the device multi-physical field state and network energy flow distribution, and generating a quantum topology covariant tensor of a twin model; and carrying out dynamic fusion on real-time characteristic data and the quantum topology covariant tensor to form the digital twin model of the power distribution network. According to the method, the digital twin model capable of accurately reflecting the power distribution network equipment aging and energy transmission spatio-temporal evolution law is constructed, and a high-fidelity simulation platform is provided for power distribution network state evaluation, fault early warning and optimization regulation and control.

The invention discloses an industrial MBSE model generation and evaluation method based on a large language model, and the method comprises the steps: collecting and sorting an aerodynamic model, assembly design rules and related basic design parameters, and carrying out the formatted expression of the rules applied in MBSE, so as to form a special enhanced knowledge base in the industrial field; the method comprises the following steps: converting a demand described by a natural language of a user into a standard MBSE model code based on a large language model through a cue word engineering technology, selecting an optimization algorithm and a simulation algorithm through a function call technology, performing real-time optimization on the model according to a design target, and applying the generated MBSE model to propulsion device design and verification test. And determining availability and model consistency. Reconstruction and acceleration of digital design are realized through automatic configuration based on requirements and components. The method has remarkable advantages in the aspects of reliability, effectiveness and adaptability.

The invention relates to a digital finance and taxation auditing method based on artificial intelligence, and the method comprises the following steps: S1, obtaining electric finance and taxation multi-source data, and carrying out the preprocessing of the data, and obtaining the preprocessed electric finance and taxation multi-source data; s2, constructing a finance and taxation knowledge graph according to the preprocessed power finance and taxation multi-source data; s3, constructing a multi-modal risk detection model, and obtaining a risk event list and a whole-course data traceability path according to the finance and taxation knowledge graph and the real-time electric finance and taxation multi-source data; s4, according to the risk event and traceability, based on a rule model, generating a structured decision instruction set including all key information and traceability links; and S5, converting the structured decision instruction set and the finance and tax knowledge graph into a standard relation graph for input, and dynamically displaying fund flow, risk events, abnormal aggregation and traceability paths among enterprises through D3. Js rendering. According to the invention, the efficiency and reliability of electric power digital finance and taxation auditing are significantly improved.

A system and method for providing a digital financial advisor using fine-tuned large language models is disclosed. The system includes a data advisor application, data fusion suite advisor engine, human advising engine, a knowledge base and large language model (LLM) fine-tuning engine to create specialized language models (SLMs) that mimic specific human financial advisors. Multiple digital avatars embodying the appearance and communication style of human advisors are generated. The system processes user and client profile data, along with advisor-specific information, to provide personalized financial advice. It handles client queries, escalating complex issues to human advisors when necessary. The digital advisor system communicates with profile datastores, user devices, and external data sources for comprehensive financial analysis. Continuous learning capabilities allow the system to improve its performance based on interactions and feedback, combining AI efficiency with personalized human-like advisory.

The invention relates to the technical field of digital factories, in particular to a full-process collaboration method and system for a digital factory. The method comprises the following steps: obtaining production decision data, and carrying out process parameter analysis according to the production decision data to obtain process parameter data; according to the process parameter data, building a factory resource agent through a preset digital factory model to obtain factory resource agent data; performing multi-agent negotiation according to the factory resource agent data to obtain digital workshop task allocation data; and carrying out industrial Internet of Things monitoring according to the digital workshop task allocation data to obtain industrial Internet of Things real-time data so as to carry out digital factory whole-process collaborative auxiliary operation. By constructing a task allocation mechanism based on semantic comprehension and multi-agent cooperation, intelligent matching and flexible scheduling among various resources in a digital factory are realized, and the task execution efficiency and the resource utilization rate of the system are effectively improved.

The invention discloses a digital intelligent management method and system for hydraulic engineering construction, particularly relates to the technical field of hydraulic engineering construction management, and is used for solving the problems of regulation lag and insufficient environmental disturbance adaptability of an existing method under the action of multi-physics field coupling. According to the method, a concrete three-dimensional temperature field model is established, initial regulation and control parameters are generated, and a heat conductivity coefficient under the seepage influence is corrected based on space-time relevance of pore water pressure and temperature data; the constraint boundary is dynamically adjusted in combination with the construction progress and the material strength curve, a cooling water pipe coordinated regulation and control matrix is constructed, and target flow instructions of space differentiation are generated through the included angle between the distance and the water flow direction; setting a lag time threshold and optimizing an execution time sequence according to the thermal inertia parameter, splitting the threshold and allocating a weight coefficient when the environmental wind speed suddenly changes, and finally updating the model parameter and the regulation and control instruction; accurate temperature control response and abnormal heat conduction suppression under multi-field coupling are achieved, and the structural safety and construction efficiency under complex working conditions are improved.

The invention relates to a power grid construction management and control method based on three-dimensional digital twinning, and relates to the technical field of power grid construction management and control, and the construction management and control method comprises the following steps: S1, a three-dimensional digital twinning model construction stage: constructing a power grid project high-precision three-dimensional model based on BIM, and superposing GIS geographic data to generate a construction scene three-dimensional digital twinning model; s2, in a construction process dynamic mapping stage, processing data of the multi-source data acquisition module in real time through an edge computing node; s3, optimizing a construction management and control decision; s4, a dynamic risk management and control stage; and S5, an execution feedback stage: forming a closed loop of three-dimensional digital twinborn model construction-construction rehearsal analysis-decision-execution-model updating. According to the power grid construction management and control method based on the three-dimensional digital twinning, the construction management and control process can be transformed from extensive experience driving to data intelligent driving, and high-reliability and high-adaptability digital infrastructure support is provided for novel power system construction.

The invention discloses a multi-granularity multi-dimensional power transmission and transformation equipment digital twinning mechanism method and system, and relates to the technical field of power transmission and transformation equipment digital modeling, and the method comprises the steps: collecting multi-dimensional physical field data, and carrying out the preprocessing; constructing a layered multi-physics field coupling model; carrying out integration and parameter adjustment on the output of the layered multi-physics field coupling model to form a unified multi-physics field coupling model; and performing simultaneous analysis on multiple physical fields to complete dynamic simulation and fault prediction. By improving the finite element analysis method and the hierarchical multi-physics field modeling technology, the technical problem that the operation state of the power transmission and transformation equipment in a complex multi-physics field coupling environment is difficult to accurately monitor and predict the fault in real time is technically solved, and the effects of improving the monitoring precision and enhancing the fault diagnosis real-time performance and the prediction accuracy are achieved.

The invention relates to the technical field of building design and digitization, and discloses an automatic design method for a special-shaped facing structure based on parametric modeling. The method comprises the following steps: firstly, acquiring a geometrical characteristic parameter set of the special-shaped facing structure, wherein the geometrical characteristic parameter set comprises curved surface curvature distribution, boundary constraint conditions and a material attribute threshold value; thirdly, according to the curved surface curvature distribution, generating an initial geometric topological grid by using a dynamic subdivision algorithm, adjusting node positions according to boundary constraint conditions to obtain an optimized structural framework, and performing layered mapping on material attribute thresholds to generate a material distribution map; then, the input parametric modeling engine generates a three-dimensional parametric model, finally, a self-adaptive adjustment strategy graph is constructed through a multi-objective optimization algorithm, and a final design scheme is output. By means of the method, automation of design of the special-shaped facing structure is achieved, design efficiency and accuracy are improved, material utilization is optimized, scheme adaptability is enhanced, and design process collaboration is improved.

The invention relates to the technical field of digital quality management, in particular to a light-weight glass bottle quality digital traceability method and system. The method comprises the following steps: acquiring glass bottle design data, and constructing a lightweight glass bottle model; detecting the structural strength of the bottle body based on the lightweight glass bottle model; carrying out bottle body surface defect detection based on the bottle body structural strength to generate bottle body surface defect data; performing defect tracing based on the bottle body surface defect data to obtain bottle body production defect process data; carrying out wall thickness non-uniformity anomaly detection based on the structural strength of the bottle body to obtain wall thickness non-uniformity data; the alignment offset of the mold core and the mold cavity is evaluated based on the wall thickness non-uniformity data; and carrying out positioning pin fracture detection according to the alignment offset of the mold core and the mold cavity to obtain positioning pin fracture data. The glass bottle production process is optimized based on the digital quality management technology, and the quality recognition rate, the abnormal response speed and the production process transparency are effectively improved.

The invention relates to the technical field of digital manufacturing, and discloses a digital twin middle station and self-healing decision system for oil and gas equipment management, which comprises a multi-source sensing terminal, a twin optimization module, a fault topology diagnosis module and an early warning execution terminal, a multi-modal synchronous fusion mechanism is constructed, and when the state of oil and gas equipment is monitored, a heterogeneous data alignment standard is formulated, and a dynamic frequency normalization rule is set for different equipment types, so that the definiteness of multi-source sensing data fusion is ensured; meanwhile, vibration, temperature, pressure and sound wave data are synchronously collected in real time, millisecond-level detection can be achieved, the data time difference problem can be eliminated, the accuracy of equipment state feature extraction is guaranteed, and the feature fusion error is further reduced; and generating a self-adaptive correction coefficient in real time by calculating the dynamic deviation of the physical model and the data model.

The invention discloses a high and large formwork engineering supporting system construction method, and belongs to the technical field of building engineering. Comprising the following steps: step 1, arranging intelligent nodes in a high and large template support system to realize information sharing and group cooperative regulation and control among the nodes; step 2, dividing the support system into a plurality of mutually associated load control areas, and setting differentiated load control parameters; step 3, automatically optimizing a pouring path; 4, when the concrete strength reaches a preset threshold value, the supporting rigidity or the reserved deformation amount is automatically adjusted according to a preset program, and the concrete structure bears the dead weight step by step; 5, the temporary load is automatically compensated, when the load exceeds a safety threshold value, a load redistribution mechanism and a reinforcing device are triggered, meanwhile, an alarm is started, and abnormal data are pushed; and step 6, continuously optimizing control parameters, accumulating construction data, constructing a digital construction record and a knowledge base, and realizing intelligent iterative upgrading of the construction method.

The invention relates to the technical field of intelligent education, and discloses an integrated English teaching method and system based on artificial intelligence. The method comprises the following steps: constructing a digital resource library; generating pre-class preview data based on the resource library and the initial cognitive level of the student, analyzing the pre-class preview data and updating the cognitive level; generating classroom courseware based on the resource library and the student updating cognitive level, and analyzing classroom learning data to update the cognitive level again; generating personalized after-class homework based on the resource library and the re-updated cognitive level of the student, and analyzing homework data to finally update the cognitive level; and forming a heavy and difficult comment report based on the resource library and the final cognitive level of the student. Through continuous data collection and analysis, dynamic adjustment of teaching content is realized, pre-class preview, classroom teaching and after-class review are closely combined to form a complete teaching closed loop, teaching pertinence and effectiveness are improved, personalized learning and precise teaching are realized, and the overall effect of English teaching is greatly improved.

The invention discloses a solid waste resource utilization management method based on a digital city, and the method comprises the steps: collecting data through deploying an Internet of Things sensor in a solid waste treatment link, building a data set, and constructing a digital twinborn model in a virtual environment; carrying out capability prediction and risk assessment on processing equipment in the model, and dynamically predicting the solid waste output in combination with historical data; the resource efficiency and the processing cost are taken as optimization objectives, a dual-objective optimization function is constructed, an optimal resource processing strategy is solved and generated through a genetic algorithm, and the digital twinborn model is updated by calculating an output error; according to the method, the solid waste recycling efficiency and the treatment economy are remarkably improved, through combination of the digital twinning algorithm and the genetic algorithm, precise scheduling of the equipment capacity is achieved, the treatment process is optimized, the equipment load fluctuation and the operation cost are reduced, and an intelligent solution is provided for smart city solid waste management.

The invention discloses a digital intelligent service system for enterprise services, which belongs to the field of enterprise digital services and comprises a user demand analysis module, an intelligent data adaptation module, a service resource matching module, a service efficiency evaluation module and a user-friendly interface. The user demand analysis module is used for semantic analysis and classification decision making; the intelligent data adaptation module identifies and analyzes the protocol type, and establishes an intelligent data transmission channel; the service resource matching module carries out resource pre-screening and accurate matching; the service efficiency evaluation module tracks an identifier and captures a four-dimensional index system in real time, and the dynamic evaluation unit realizes service state grading early warning through a sliding window algorithm; according to the invention, accurate demand identification is realized, the response speed and the data transmission efficiency are improved, the user satisfaction is improved, the service matching accuracy is enhanced, the resource utilization efficiency is optimized, the service capability and the customer experience are improved, and maximization of economic benefits and social values is realized.

The invention provides an industrial load portrait and situation prediction system and method based on multi-time scale characteristics, and relates to the technical field of industrial load and situation prediction. According to the method, diversified industrial loads are acquired by acquiring power utilization information and equipment characteristics of users in an industrial park, an industrial load portrait is established accordingly, and the diversified industrial loads are analyzed by fusing multi-time scale sequence characteristics with industrial load portrait characteristics and combining a double-layer multi-head self-attention mechanism. The feature multi-head self-attention layer focuses important features and excavates input feature sequence relevance, and the time sequence multi-head self-attention layer excavates periodic trend features and local fluctuation features of industrial loads by capturing time sequence relevance and strengthening information expression of important feature variables and key time points; the method can achieve the multi-time-scale prediction of the energy consumption situation of the load of the industrial park, remarkably increases the flexible regulation and control space of the industrial park, and improves the digital perception and flexible regulation and control level of a demand side.

The invention discloses a comprehensive management system for an intelligent digital campus, and relates to the technical field of digitization, and the system comprises the steps: collecting the learning behavior data of students in real time, and forming a preliminary data set of the students; the learning behaviors of the students in the preliminary data set are analyzed, and a personalized learning portrait of each student is generated; based on the personalized learning portrait, determining a learning demand and a resource demand feature of the student; pushing a personalized learning path and dynamically adjusting a teaching resource allocation scheme according to the learning demand characteristics and the resource demand characteristics of the students; and collecting energy consumption data of each region, and automatically optimizing an energy consumption use strategy in combination with a resource allocation result and the energy consumption data of each region to obtain an optimized learning environment. According to the resource scheduling strategy based on personalized demands, the learning efficiency of students can be improved, and full utilization of resources can be ensured.

The invention discloses a hydraulic engineering digital design method based on digital twinning, and relates to the technical field of hydraulic engineering design. According to the digital twin-based hydraulic engineering digital design method, design demand information of a to-be-designed diversion tunnel is obtained and input into a pre-trained building recognition model for comprehensive analysis, a spatial layout map of the to-be-designed diversion tunnel is obtained, and a tunnel design digital twin model is constructed; simulation data of the tunnel design digital twinborn model are obtained, simulation analysis is carried out respectively, a tunnel construction risk index and a hydraulic action risk comprehensive index of the tunnel design digital twinborn model are obtained, comprehensive analysis is carried out, and a tunnel feasibility index of the tunnel design digital twinborn model is obtained; according to the method, the tunnel design digital twin model is subjected to design optimization based on the feasibility index, so that a lagging mode of re-evaluation after building is effectively avoided, later frequent reinforcement and reworking are prevented, and the engineering safety coefficient is improved.

The invention provides a dynamic exhibition system for digital museum exhibits, and relates to the technical field of digital exhibition, and the system comprises a database building module which is used for obtaining an exhibit multi-angle image set to generate an exhibit three-dimensional model set, and building a digital database; the dynamic scene construction module is used for setting a display scene and constructing a dynamic scene to obtain a dynamic scene layout library; the exhibition platform building module is used for carrying out association mapping exhibition and virtual interactive visiting on the digital database and the dynamic scene layout library and building a virtual exhibition platform; and the dynamic exhibition module is used for calling the virtual exhibition platform to the target user to carry out exhibition interaction service and scene dynamic adjustment. According to the method and the device, the technical problems of single exhibition form and insufficient immersion and interactivity of the digital museum due to the fact that the exhibition scene is statically set and the exhibit and the exhibition environment are lack of linkage coupling in the prior art are solved, and the technical effects of improving the exhibition flexibility, richness and immersion experience are achieved.

The invention discloses a digital twin architecture for a satellite-ground collaborative edge network, and belongs to the field of network simulation and intelligent management in the satellite internet. According to the digital twin architecture of the satellite-ground collaborative edge network provided by the invention, the operation state, the resource state and the association state of terminal equipment such as an unmanned aerial vehicle and edge equipment such as a satellite are returned through a sliced feeder line, and a digital twin model integrating a data layer, a model layer and a decision layer is established at a gateway station side. Based on the architecture, a satellite-ground collaborative model training task is oriented, and model training and aggregation are realized by utilizing a block chain technology. According to the architecture, full-life-cycle management of the satellite-ground collaborative edge network is realized, through real-time simulation and optimization decision, the digital and intelligent level of the satellite network is improved, the simulation precision, real-time performance and resource utilization efficiency of the network are improved, and efficient and stable operation of the satellite network in a complex dynamic environment is ensured.

The invention relates to the technical field of education informatization, and discloses a digital teaching resource library intelligent management and application method and system. The method comprises the steps of constructing a digital resource library, constructing a resource application big data analysis model to calculate a resource quality index, a popularity index and an update index, performing intelligent resource sorting and elimination based on the indexes, analyzing the correlation between a user retrieval request and resources, and performing intelligent recommendation. According to the method, efficient management and accurate application of teaching resources are realized, the resource utilization rate and the teaching effect are improved, the storage space and the management cost are saved, and data support is provided for education decision making.

The invention discloses an electrical work ticket intelligent generation method and device, a medium and equipment in the technical field of power systems, and aims to solve the problems of serious module decoupling, dependence on manual connection and insufficient intelligent generation capability in the prior art. The method comprises the following steps: generating a required digital knowledge base and an electrical work task description generation work ticket based on a pre-constructed work ticket by utilizing a multi-model collaborative generation architecture; the multi-model collaborative generation architecture comprises a rule driving module used for calling a corresponding template based on task element matching; the task execution unit is used for executing a specific subtask according to a pre-deployed lightweight model or rule engine; and the large language model is used for performing semantic understanding and reasoning according to the electrical work task description, calling the rule driving module and the task execution unit according to a semantic understanding and reasoning result, and generating a work ticket in combination with a digital knowledge base required by work ticket generation. The method has both the accuracy of structured knowledge recognition and the flexibility of natural language generation.

The invention discloses an intelligent logistics digital warehouse management method based on deep learning, and relates to the technical field of warehouse management, and the method comprises the steps: calculating the correlation of SKUs through Graph SAGE, constructing an SKU incidence matrix, optimizing an SKU combination based on an SKU co-occurrence frequency, calculating an SKU storage optimization strategy through Transform, analyzing the storage relation between the SKUs through an attention mechanism, and optimizing a storage layout in combination with GNN. A high-frequency SKU can be located in an optimal storage area, in a sorting task scheduling link, a sorting robot is trained by adopting reinforcement learning, an optimal sorting path is autonomously learned in a warehouse environment, optimal distribution of AGVs and manual tasks is calculated in combination with GNN, collaborative operation of automatic equipment and manual operation is balanced, and path conflicts and invalid movement are effectively reduced; and after the task is executed, recording the sorting time and a path optimization result, and applying feedback data to self-supervised learning to optimize a warehouse management strategy, so that SKU storage, a sorting path and task scheduling can be dynamically adjusted.

The invention discloses a modeling analysis system based on digital energy configuration, and relates to the technical field of energy consumption management analysis, and the system comprises an energy consumption model which is established based on production data of energy consumption feature point grouping, equipment operation data and equipment operation environment data, and reflects the changes of the production data and the equipment operation data through the energy consumption model, the influence of the equipment operation environment on the energy consumption model is determined, the equipment state is predicted by combining the production data and the change of the equipment operation data, and production optimization suggestions are made; the decision-making model is used for carrying out optimization decision-making according to analysis of the energy consumption model on the energy consumption points, determining decision-making cost according to the decision-making and optimizing calculation of flow energy consumption and efficiency; according to the method, the energy consumption of the production line is predicted, the optimization suggestion for the production line can be made according to the energy consumption of the production line, the energy consumption hot spots are determined according to the energy consumption data corresponding to different equipment operation data and production data, and the process steps are optimized according to the energy consumption.

The invention discloses a scheduling optimization method for an aviation composite material manufacturing hot-press forming process, which comprises the following steps of: 1, establishing a hot-press forming production plan scheduling objective function by taking the minimum total delay time of a workpiece as an objective according to an aviation composite material manufacturing hot-press forming production plan; 2, establishing a two-dimensional hot press molding process batch scheduling model considering a workpiece release time window and machine applicability; and step 3, taking the objective function as an optimization objective, taking the two-dimensional hot-press forming process batch scheduling model as an optimization model, and utilizing a genetic algorithm embedded with a self-adaptive domain search strategy to solve and obtain a hot-press forming production plan scheduling scheme. According to the method, the total delay time of workpieces can be remarkably shortened while the machining batch of the workpieces is minimized, the occurrence of prepreg deterioration conditions is reduced, and conditions are created for improving the hot press molding production efficiency and promoting digital and intelligent transformation and upgrading of composite material manufacturing enterprises.

The invention relates to the technical field of construction stage management, in particular to a BIM-based road construction digital management system, which comprises a component parameter acquisition module, a process topology construction module, a state trigger mapping module, a logic conflict judgment module and a scheduling path adjustment module. According to the method, through continuous collection and analysis of the component state, dynamic monitoring of the connection state, geometric intersection and contact time is achieved, the construction change sensing capacity is improved, the dependency relationship is constructed in combination with component space adjacency and time overlapping, the dispatching path and field matching degree is enhanced, and through linkage updating of the component state and model attributes, the construction efficiency is improved. According to the method, the execution state is visual and controllable, scheduling reconstruction is carried out after time dependence conflicts are recognized, synchronous updating of model views is completed, a closed-loop dynamic scheduling mechanism is formed, the task allocation accuracy, the flow connection efficiency and the field scheduling response capability are integrally improved, and the real-time performance and the intelligent level of construction management are enhanced.

The invention relates to a digital life individuation implementation method and device, equipment and a medium. The method comprises the steps of obtaining user interaction information in response to an obtained user input instruction; preprocessing the user interaction information according to a set mode to obtain a user interaction text; inputting the user interaction text into the digital life entity to obtain a personalized reply; the personalized reply comprises a target person and audio data; and generating an interactive video corresponding to the personalized reply based on digital human rendering. By adopting the method, personalized digital cloned construction, cross-space-time emotional interaction and cultural heritage digital inheritance can be realized through emotional analysis, behavior pattern learning and the like, and the method is suitable for scenes of emotional science and technology, digital immortality, family archive management and the like.

The invention discloses a digital intelligent management early warning system based on power grid construction, and relates to the technical field of power grid early warning management. The intelligent management early warning center is in communication connection with a data acquisition module, a fault feature analysis module, a fault monitoring module, a fault evaluation module, an early warning grading module, an early warning generation and release module and an emergency response module. According to the method, the electrical parameters and the environmental parameters in the operation of the power grid are monitored in real time, abnormal conditions in the power grid are rapidly identified, fault features are extracted from a large number of historical fault cases and real-time data, the design parameters and the operation specifications of the power grid are combined, the fault evaluation standard is formulated, the coping capacity for the power grid faults is improved, and the fault diagnosis accuracy is improved. When a fault occurs, a response is quickly made, and through timely issuing of early warning information, it is ensured that related personnel can take actions quickly, so that the power failure time is shortened, and the reliability of a power grid and the satisfaction degree of users are improved.

The invention relates to the technical field of multimedia regulation and control, in particular to a regulation and control system for a digital multimedia exhibition hall, which comprises a multimedia content control module for managing a digital screen, a projector and audio multimedia in the exhibition hall in real time and realizing dynamic switching of display contents and multimedia linkage; the environment regulation and control module is responsible for controlling light, sound, temperature and humidity in the exhibition hall, synchronously adjusting the exhibition hall environment and exhibition content, monitoring environment parameters in real time by using an intelligent sensor, providing an intelligent adjustment scheme, and monitoring behaviors of visitors in real time by using a sensor, a camera and intelligent bracelet equipment. The digital multimedia exhibition hall regulation and control system integrates an intelligent control technology, audience behavior monitoring and data analysis, and has the functions of real-time regulation and control, dynamic interaction, data feedback and optimization and the like. Through the unified central control system, the exhibition hall can intelligently adjust the multimedia content and environment according to the actual exhibition content and the behaviors of visitors, and the efficient and flexible exhibition effect is achieved.