381 results about "Collaborative interaction" patented technology

The invention relates to a cross-modal knowledge reasoning method based on a multi-modal large model. In a cross-modal knowledge reasoning process, an existing model is usually limited by single-modal information extraction and shallow feature fusion, so that deep semantic association among data such as texts, images and videos is difficult to fully capture. In order to solve the problem, the invention provides a model for fusing multi-modal information such as texts, images, videos, documents and the like, and processing of multi-modal data is converted into unified feature extraction, interaction and deep reasoning tasks by fully utilizing a supervision fine tuning strategy, a self-adaptive attention mechanism and a cross-language processing technology. The model adopts a modular design, integrates multi-source data complementary analysis, spatial-temporal feature modeling and emotional semantic analysis, and realizes multi-modal collaborative interaction, dynamic scene understanding, long video key event analysis and man-machine co-emotional response. Through sufficient training, the multi-modal large model shows excellent logical reasoning ability and emotion understanding ability in a complex cognitive task, and a brand new solution is provided for efficient extraction, deep semantic analysis and intelligent response of cross-modal information.

The invention discloses a heat supply intelligent decision-making system based on an artificial intelligence large model, and the system comprises a data layer which is used for storing multi-type data of a heat supply system source network load; the knowledge base establishment and large model training layer is used for establishing a heat supply intelligent decision diversified task knowledge base and establishing each task large model; the man-machine enhancement optimization large model layer is used for providing improvement suggestions for a large model, optimizing generated answers, evaluating the answers generated by the large model and performing large model parameter optimization training; the agent decision-making layer is used for integrating each task large model into each agent to carry out environment perception, collaborative interaction and autonomous adaptive decision-making; the analogue simulation layer is used for providing a simulation operation environment, a user interaction interface and scene dynamic parameter simulation; and the agent evaluation optimization layer is used for constructing performance indexes for evaluating the agents, and evaluating, optimizing and adjusting behaviors and decisions of the agents.

The invention relates to the technical field of information security, in particular to a power distribution Internet of Things cloud side end collaborative interaction security protection system, which comprises a network flow monitoring module, an abnormal flow identification module, a security threat response module, a network attack early warning module, a behavior pattern analysis module and an access authority management module. According to the method, the network flow data is collected and analyzed in real time, the abnormal flow recognition speed and accuracy are enhanced, the security threat response speed and efficiency are improved, measures are taken in time at the early stage of a problem, the risks of data leakage and network attacks are reduced, and the timeliness of defense measures is improved by combining security threat response and network attack early warning; by analyzing the relevance between threat events, the complex multi-stage attack activity is effectively predicted and identified, the access data and the communication mode of the equipment are monitored in real time, and the access authority and the trust level are adjusted, so that the security protection is more targeted and flexible, and the management efficiency of the risk equipment is improved.

The invention discloses a virtual-real fusion exhibition display interaction system and a multi-mode perception method, and belongs to the technical field of exhibition display interaction. The system collects audience eyeball fixation points, gesture actions and ambient light data through AR / VR equipment, analyzes coordinates of a region of interest through an eyeball fixation point attention mechanism, a gesture space-time encoder and a multi-modal fusion unit, triggers holographic projection explanation and virtual exhibition stand light and shadow dynamic adjustment (including illumination intensity, color, Gaussian blur and the like) based on a threshold value, and performs real-time display on the virtual exhibition stand. And multi-user collaborative interaction is realized through federal learning. According to the method, reinforcement learning is adopted to optimize an event-driven threshold value, and virtual and real visual splitting is eliminated in combination with ambient light adaptive mapping. The problems of low participation degree, insufficient single-mode interaction information and multi-user cooperation of traditional exhibition are solved, interest analysis accuracy is improved through multi-mode fusion, personalized experience is enhanced through dynamic interaction, the method is suitable for multiple scenes such as museums and science and technology museums, and exhibition intellectualization, immersion and group interaction efficiency are effectively improved.

The invention discloses a laboratory automatic process management and multi-source data fusion system based on the Internet of Things, and belongs to the technical field of laboratory management. The system comprises a sensing layer, an analysis layer, an intelligent management layer and an application layer. The sensing layer carries out global data acquisition and real-time analysis; the analysis layer integrates data, mines an association relationship and optimizes task matching; the intelligent management layer performs full-process automatic management and control on a laboratory, and comprises an equipment cooperation module, a dynamic detection module, a dynamic configuration module, a real-time simulation module, a preset trigger module and an intelligent auditing module; and the application layer performs multi-terminal collaborative interaction and intelligent assistant assistance processing. According to the system, intelligent collaboration of laboratory equipment, automatic detection of samples, dynamic optimization of equipment parameters and automatic early warning and processing of abnormal conditions are realized through technical means such as knowledge graph construction, a digital twinborn technology and multi-mode biological recognition, and the laboratory management efficiency and the data processing accuracy are effectively improved.

The invention belongs to the technical field of smart city construction and intelligent construction management, and particularly relates to an intelligent scheduling and cooperation system and method for the whole life cycle of city reconstruction. The system comprises an edge sensing layer, a digital twinning network module, a space-time brain module, a block chain collaborative trust layer and an XR collaborative interaction layer. The system collects multi-source data of a construction site in real time through a 5G edge device, realizes fusion modeling of BIM, GIS and TIN models by using a graph convolutional neural network, and performs multi-target scheduling optimization in combination with meta reinforcement learning and a dynamic graph neural network; and meanwhile, construction task verification and fund payment linkage is realized through a block chain smart contract, and immersive cooperation and visual acceptance are provided in cooperation with an AR / VR platform. According to the method, the problems of model splitting, scheduling response lagging, low data collaboration efficiency, insufficient credibility of the performance process and the like in the urban reconstruction project are solved, and the intelligence, transparency and automation level of the construction process is remarkably improved.

The invention relates to the technical field of man-machine collaborative interaction, and discloses a resource allocation method and system in a man-machine collaborative decision-making scene, and the method comprises the steps: generating corresponding task features based on the three dimension indexes of task complexity, knowledge density and intelligent adaptation degree of a to-be-processed task; initializing initial weight coefficients of the three-dimensional indexes, and dynamically optimizing the weight coefficients corresponding to the three-dimensional indexes by using a preset strategy network according to the task characteristics and the real-time system resource state; performing weighted normalization on the three-dimensional indexes according to the weight coefficient to generate a task comprehensive score; task priorities are divided according to the task comprehensive scores, and the tasks are dynamically allocated to manual and / or intelligent systems to execute the tasks according to the priorities, so that the flexibility of artificial experience and the high efficiency of the intelligent systems can be brought into full play, man-machine labor division is flexibly adjusted according to task characteristics, and the universality of cross-task scenes is improved. And the dynamic adaptability, decision reliability and task execution efficiency of the man-machine cooperation system are improved.

The invention provides a middle and primary school multi-person interactive teaching method and system based on a VR technology, and relates to the technical field of virtual reality, and the method comprises the steps: generating a model through deep learning based on pre-obtained teaching aid model data, determining subcomponents, combining a teaching aid generation engine, and constructing a virtual teaching aid; a color image and a depth image are obtained through a structured light depth camera, two-dimensional pixel coordinates are obtained, depth information is combined, a three-dimensional skeleton curve of limb movement of a student is generated, an optical motion capture result is obtained, an inertial motion capture result is obtained through inertial drift calibration based on the three-dimensional skeleton curve, and a limb movement three-dimensional track of the student is reconstructed; generating a force feedback signal by solving a kinetic equation through a collision detection algorithm based on the three-dimensional trajectory of the limb movement of the trainee; and rendering the virtualization model into a virtual teaching scene, synchronizing the limb movement three-dimensional track and the force feedback signal in real time, and generating a multi-person collaborative interaction process of the virtual teaching aid.

The invention provides a multifunctional inspection device detection system based on a distribution network mobile operation terminal, and relates to the technical field of electric power detection, and the multifunctional inspection device detection system comprises a portable main terminal of a dynamic collaborative architecture, a wearable terminal for augmented reality interaction and a distributed heterogeneous sensing cluster, which form a closed-loop data chain through an electric power dedicated low-delay wireless communication network; the portable main terminal is integrated with a heterogeneous computing unit with adaptive computing power distribution, can perform real-time fusion analysis on multi-dimensional sensing data, and outputs a visual result containing fault location and confidence; the wearable terminal superposes fault information to a real scene in a three-dimensional marking form through a virtual-real fusion positioning technology, and supports eye movement and voice collaborative interaction; multi-module collaborative acquisition of the distributed heterogeneous sensing cluster is combined with a nanosecond timestamp synchronization mechanism, so that the limitation of traditional single parameter detection is broken through, rich and synchronous basic data is provided for subsequent analysis, and the comprehensiveness of routing inspection is greatly improved.

The invention relates to the technical field of informatization management systems, and particularly discloses an AI-aid decision-making product full-life-cycle informatization management system which comprises a full-link data sensing module, a digital main line construction module, an AI decision-making center module, a service execution interface module and a man-machine collaborative interaction module. The method comprises the following steps: collecting multi-source heterogeneous data of each stage of a full life cycle of a product through a full-link data sensing module to form a full-amount data sequence with a space-time stamp; and in combination with a data fusion engine, an association graph construction unit and a twinborn model driving unit of the digital main line construction module, data cleaning, alignment, semantic fusion and cross-stage association are realized, a dynamically updated product digital twinborn model is constructed, real-time mapping of a physical entity and a virtual model is achieved, and the real-time mapping of the physical entity and the virtual model is realized. Unified and complete data support is provided for full-link decision making, and the problems of data fragmentation and prominent collaborative barriers of a traditional system are thoroughly solved.

The invention discloses a distribution network source-load collaborative micro-grid autonomous system and method, relates to the technical field of micro-grids, and realizes interconnection and intercommunication between an intelligent fusion terminal and equipment such as a charging pile, a photovoltaic device, an energy storage device, a low-voltage intelligent switch and the like by utilizing wireless communication technologies such as HPLC (High Performance Liquid Chromatography), 5G (5th Generation) and the like compared with the previous micro-grid autonomous system. By applying intelligent algorithms such as linear regression and machine learning, the platform automatically generates various optimization adjustment strategies, and after the strategies are audited by management personnel, a control command is issued to the terminal equipment through the intelligent fusion terminal; and remote intelligent operations such as energy storage charging and discharging mode adjustment, charging pile output power limit, photovoltaic output flexible regulation and control and automatic switching on and switching off of a low-voltage intelligent switch are realized. And performing whole-process monitoring on strategy execution, determining whether the strategy execution reaches a preset target, outputting a result analysis report, continuously optimizing an intelligent algorithm in combination with field equipment operation parameters, and continuously improving a source-network-load-storage collaborative interaction level.

The invention is suitable for the field of environment monitoring, and provides a sampling information management system for intelligent environment monitoring, which comprises a user authority management and control module for realizing multi-level authority management based on an RBAC (Role Based Access Control) model; the equipment full life cycle management module monitors the equipment state in real time through the Internet of Things and carries out early warning calibration; the standard dynamic adaptation module intelligently associates a standard with a sampling scene, and synchronously authorizes updating; the sampling closed-loop management module supports double-end cooperation, offline operation and block chain evidence storage; the data interaction and analysis module integrates the data and intelligently predicts the data; the auditing and tracing module records whole-process operation and gives an early warning for abnormity; and the multi-terminal collaborative interaction module is adapted to multiple systems. The monitoring efficiency and the data quality are improved, and support is provided for environmental protection decision making.

The invention belongs to the technical field of image processing, and discloses a remote digital image analysis cooperation system. The virtual diagnosis module is used for collecting a continuous pathological section sequence and carrying out space registration to obtain a registration section; the model building module is used for performing three-dimensional voxel reconstruction on the registration slices to obtain a three-dimensional voxel reconstruction model, and performing semantic enhancement to obtain a three-dimensional pathological voxel model; the collaborative interaction module is used for generating virtual avatars of G experts based on the VR technology, labeling the three-dimensional pathological voxel model and obtaining space anchor point labeling data of the experts; the graph driving module is used for constructing a structured semantic tree according to the space anchor point annotation data, detecting annotation conflicts and obtaining an annotation conflict detection result; the conflict resolution module is used for performing conflict resolution on the marking conflict detection result to obtain a consensus suggestion; the collaborative efficiency and conclusion reliability of remote diagnosis are improved, and a systematic solution is provided for precise diagnosis of complex pathological cases.

The invention discloses a digital large-screen interaction method and device based on multi-agent cooperation and a medium, and relates to the technical field of digital large-screen interaction.The method comprises the steps that postures, expressions and voice data of a user are collected in real time, the attention weight is calculated in combination with spatial position information, the emotional state change rate is monitored, and the user experience is improved in combination with personal historical browsing preferences; acquiring a main interaction user, an emotional state feature and an emotional change trend; according to the main interaction user, the emotional state features and the emotional change trend, obtaining an initial confidence coefficient of the suspected interested field through a semantic understanding model; and based on the candidate guide images, identifying a user selection intention through a multi-modal fusion processing mechanism, calculating a selection probability, triggering content activation of the main interaction area and content dynamic generation of the auxiliary information area, synchronizing state information, and starting an immersive collaborative interaction process. Through three-level collaborative service configuration, the beneficial effects of improving large screen content organization efficiency and enhancing immersive interaction experience are achieved.

The invention discloses a multi-modal recommendation method and system for enhancing user representation through a graph convolutional neural network, and the method comprises the steps: extracting project embedding, original user embedding and original ID embedding from an input data set; features are extracted from neighbors of users, aggregation operation is carried out to enhance user representation so as to generate user embedding after aggregation of other user information, and then the user embedding and project embedding are spliced into a user-project collaborative interaction matrix; extracting features of each mode for an input data set, and constructing a user-item diagram of each mode in combination with the user-item collaborative interaction matrix; and obtaining recommendation items of the user through multi-modal information representation, multi-modal feature fusion and recommendation results. According to the method, the recommendation accuracy is improved by introducing the multi-modal information, meanwhile, a user feature enhancement technology is introduced, user features and features of similar users are subjected to aggregation operation to obtain personalized embedding of the users, and finally the recommendation accuracy of the multi-modal recommendation system is improved.

The invention provides a smart space multi-screen collaborative interaction method based on micro-service architecture and edge computing, and relates to the technical field of smart screens, comprising: determining a master-slave terminal relationship based on a terminal type and a resource state by receiving a screen interaction request of a smart space terminal; a data distribution center is constructed by adopting a distributed message queue, and directional pushing based on a message theme is realized; and deploying a lightweight task execution container at the slave terminal to finish screen content rendering, and dynamically updating the terminal mapping relationship. According to the method, real-time collaborative interaction among multiple terminals can be realized, the screen content rendering efficiency is improved, the fluency of interaction experience is ensured, dynamic joining and quitting of the terminals are supported, and the expansibility is relatively high.

The invention discloses an intelligent fusion analysis and decision support system and method for multi-source heterogeneous data of a spacecraft. The intelligent fusion analysis and decision support system for the multi-source heterogeneous data of the spacecraft and the intelligent fusion analysis and decision support method for the multi-source heterogeneous data of the spacecraft are included. The system comprises a dynamic adaptation access layer, a unified semantic modeling layer, a space-time semantic fusion engine, a digital twin collaborative decision-making center, a knowledge enhancement decision-making auxiliary subsystem, a cross-department collaborative interaction platform and a side cloud collaborative intelligent processing framework. The method comprises the steps of multi-source heterogeneous information dynamic access and semantic modeling, space-time and semantic deep fusion, digital twin driven decision deduction, knowledge enhanced decision assistance, cross-department collaborative decision and interaction, edge cloud collaborative intelligent processing and the like. According to the method, the safety, reliability and decision-making efficiency of spacecraft tasks can be remarkably improved, and the method is suitable for development, testing and on-orbit task stages of various spacecrafts.

The invention relates to the technical field of ship unloader linkage, in particular to a port ship unloader full-automatic multi-machine linkage system and a method thereof.The port ship unloader full-automatic multi-machine linkage system comprises a distributed intelligent scheduling module, the distributed intelligent scheduling module is in coupling connection with a full-link data middle station, and the full-link data middle station is in coupling connection with a self-adaptive edge computer unit; the self-adaptive edge computer unit is in coupling connection with a three-dimensional perception safety monitoring network, the three-dimensional perception safety monitoring network is in coupling connection with a man-machine collaborative interaction platform, and the man-machine collaborative interaction platform is in coupling connection with a production management module. The port ship unloader full-automatic multi-machine linkage system and the method thereof solve the problems that in the prior art, a ship unloader full-automatic multi-machine linkage system is mostly controlled in a centralized mode in the actual using process, depends on a fixed algorithm and is difficult to dynamically deal with complex operation scenes (such as ship position deviation and uneven cargo distribution), and the working efficiency is high. And equipment conflict or idle waiting is caused.

The invention discloses a balance control scheduling method and system based on distributed new energy, and the method comprises the steps: obtaining power grid parameters, and constructing a time-space characteristic model of multi-type adjustable resources and a distributed scheduling frame based on the obtained parameters; based on the space-time characteristic model and the distributed scheduling framework, establishing a distributed new energy participation power grid adjustable and controllable resource group internal cooperation strategy; establishing a distributed new energy participation power grid dispatching collaborative interaction and balance optimization control strategy according to the collaborative strategy; and realizing active / reactive coupling balance collaborative optimization of the high-permeability distributed new energy access power grid based on a collaborative strategy and an optimization control strategy. According to the invention, the utilization rate of new energy can be improved, cooperative work of multiple types of adjustable and controllable resources is realized, the flexibility and stability of a power grid are improved, dynamic adjustment of a power system is realized, and optimal matching of power supply and demand at different time and space scales is ensured.

The invention discloses a video question answering method for specific domain fine-grained heuristic prompt. The method comprises the following steps: 1, designing a prompt template of a specific domain through data engineering; performing space-time cutting processing on the original video data; the space-time cutting treatment is carried out; 2, taking the prompt template and the clipped video data as input of an entity prompter and an action prompter to obtain a heuristic label; and 3, through a heuristic enhanced answer reasoning scheme, collaborative interaction between the visual language basic model and the entity prompter and between the visual language basic model and the action prompter is enhanced, that is, a label output by the visual language basic model is compared with a heuristic label, and the ability of the visual language basic model to accurately deduce answers is improved. According to the method, a large-scale model is converted into a dynamic knowledge engine, complex content can be efficiently and accurately analyzed, and attention to basic cross-modal elements is enhanced by integrating a fine-grained inspiration method in a specific field into design of a prompt template.

The invention discloses an atmosphere lamp control method, electronic equipment and a program product. The method comprises the following steps: acquiring PCM data of an audio signal in real time in the music playing process of a vehicle; performing frequency domain analysis on the PCM data corresponding to each audio frame, and extracting frequency information and loudness information; the method comprises the following steps: calculating frequency information and loudness information of a preset number of continuous audio frames, and respectively calculating a frequency change rate and a loudness change rate within a preset time; respectively comparing the frequency change rate and the loudness change rate with corresponding change rate thresholds; and if at least one of the frequency change rate and the loudness change rate exceeds the corresponding change rate threshold value, a corresponding light updating instruction is sent to the atmosphere lamp control module. The music rhythm function of the automotive interior atmosphere lamp can be enhanced, and the cooperative interaction ability of music and the atmosphere lamp is improved.

The present application relates to a microgrid energy management optimization method and system in a micro-grid and distribution network collaborative interaction scenario, and relates to the technical field of power grid regulation and distribution. It includes: establishing a power consumption data acquisition base to monitor the power consumption data of the main power grid and the microgrid, and analyzing the power consumption merchant information of conventional power consumption loads and new power consumption loads; analyzing based on the power consumption merchant information to determine the power consumption order and power consumption load priority in the power consumption merchant information; sending an automatic allocation instruction to a preset distribution collaboration system according to the power consumption load priority and power consumption order, and calculating a power energy allocation balance coefficient; performing power energy allocation based on the automatic allocation instruction, and when the power energy allocation balance coefficient is less than a preset good balance allocation coefficient, sending a power energy interaction management instruction. The present application has the advantages of improving the interaction and collaboration ability between the microgrid and different distribution network ends and improving the power energy allocation balance effect.

The invention discloses an on-chain and off-chain collaborative interaction system based on a block chain, and the system comprises a data structure module which is used for designing a composite data structure containing metadata, data content, a hash value and a timestamp, and employs a Merkle tree to manage data; the distributed storage and transmission module is used for storing data under the chain by adopting a distributed file system, storing key data on the chain by using a block chain, and designing a secure transmission protocol; by means of the Merkle tree and Hash verification, data integrity can be quickly and accurately verified, tampering can be perceived, a distributed storage and transmission technology and a two-way synchronization strategy can be designed, on-chain and off-chain efficient collaboration is achieved, data processing efficiency and reliability are improved, data security privacy is guaranteed by means of block chain characteristics and encryption, digital signature and other technologies, and the method is suitable for large-scale popularization and application. Distributed storage and a P2P network facilitate node and capability expansion to adapt to data growth, an intelligent contract is introduced, online and offline data collaborative automatic management is achieved, risks are reduced, and efficiency is improved.

The invention discloses an automatic control system and method for a four-way shuttle vehicle, relates to the field of intelligent control, and adopts a data analysis and coding technology based on deep learning to perform embedded coding on the current electric quantity, the driving distance of the shuttle vehicle to a target point and the reversing node number of the shuttle vehicle. Meanwhile, semantic embedding is carried out on the natural language description of the current demand; a current electric quantity weight ratio, a driving distance weight ratio and a reversing node weight ratio are intelligently generated according to external dynamic collaborative interaction representation among a current electric quantity low-dimensional embedded coding feature, a driving distance low-dimensional embedded coding feature, a reversing node number embedded coding feature and a current demand semantic embedded coding feature; and obtaining a score value. Through the mode, dependence on artificial experience is reduced, and the problem that resources in other aspects are wasted due to the fact that some factors are paid attention excessively is avoided.

The invention discloses a collaborative interaction intelligent regulation and control method for source network load storage resources, and relates to the technical field of resource regulation and control, and the method comprises the following steps: Sa1, obtaining the real-time fluctuation of a power grid load and the power grid flow distribution in a power grid system, and carrying out the prediction of the power flow distribution based on the real-time fluctuation of the power grid load and new energy power generation power prediction data; generating a supply-demand imbalance characteristic quantity of the power supply and the load; sa2, according to the supply and demand imbalance characteristic quantity, constructing a multi-objective optimization model containing participation of an energy storage system and an adjustable load; sa3, outputting a regulation and control instruction set by solving the multi-objective optimization model; and Sa4, carrying out coordination control on the source network load storage resources according to the regulation and control instruction set so as to realize dynamic balance. The method can solve the problem of how to regulate and control the new energy generation power according to the real-time fluctuation of the power grid load so as to solve the problem of mismatching between the power supply output and the load demand, thereby ensuring the stable power supply.

The invention relates to the technical field of intelligent terminals, in particular to an intelligent screen multi-terminal collaborative interaction system and method based on edge computing. The intelligent screen multi-terminal collaborative interaction system based on edge calculation comprises a terminal display unit, an edge calculation unit and an intelligent screen display unit, according to the method, feature information is extracted by integrating multiple factors, terminal display requirements and importance are accurately reflected, important information is judged according to priority permission levels, judgment is performed according to the feature information when the levels are the same or no level exists, the result is more reasonable, random or average distribution display is avoided, meanwhile, the memory occupancy rate of the smart screen is monitored in real time, and the user experience is improved. In addition, the historical information features are continuously updated, and the intelligence and adaptability of the whole system are improved.

The invention discloses a distributed power supply-containing power distribution network coordinated scheduling method, which relates to the field of power distribution network coordination, and comprises the steps of S1, multi-flexibility resource refined modeling and interaction characteristic analysis, S2, power distribution network linear load flow calculation and sensitivity analysis, and after the power distribution network linear load flow calculation and sensitivity analysis in S2 are completed, carrying out power distribution network coordinated scheduling. And S3, generating an uncertainty scene based on the generative adversarial network. According to the coordinated dispatching method for the power distribution network containing the distributed power supply, differences of various resources in control modes, response speeds and adjusting capabilities are analyzed through refined modeling, complementary characteristics of the resources are fully utilized by a collaborative optimization model, an overall optimization effect is achieved, a single type of resources are not optimized in an isolated mode, and the method is suitable for large-scale popularization and application. All adjustable resources such as a distributed power supply, an energy storage system, a reactive power compensation device, a flexible load and an intelligent soft switch are incorporated into a unified modeling and optimizing framework, and deep fusion and collaborative interaction of flexible resources can be realized.

The invention relates to the field of digital data processing, and discloses a virtual display interaction system and method based on meta universe, and the method comprises the steps: capturing a weak interaction leading signal of a user in real time, converting the weak interaction leading signal into an interaction intention primitive carrying main body, target, action and intensity information through a lightweight rule, and broadcasting the interaction intention primitive; and each client integrates the elements to construct a dynamic interaction intention flow field, so that relevant data are preloaded prospectively, and fine auxiliary regulation and control are carried out on high-intention collaborative interaction. According to the method, the interaction intention flow field is used for estimating the group trend, intelligent preposition of resources and precise assistance of cooperation are achieved, virtual feedback time delay is remarkably shortened, and the success rate and naturalness of a complex cooperation task are improved.

The invention discloses an intelligent blasting platform which comprises a physical layer, a data layer, a business logic layer, a function module layer and a user interaction layer. The physical layer is provided with an unmanned aerial vehicle, a GNSS receiver, a blasting recorder and Internet of Things sensing equipment, and blasting engineering three-dimensional geographic space information and a BIM model are generated through three-dimensional live-action modeling and BIM forward modeling; the data layer integrates GIS data, BIM data, monitoring data and engineering data, and constructs a data resource center comprising a time sequence database and a knowledge graph database; the business logic layer comprises a GIS + BIM + IoT information sensing module, a multi-source data fusion module, a blasting design module, an intelligent optimization module, a monitoring identification module and a blasting effect evaluation module; the functional module layer develops a 3D visual query module, a dynamic monitoring module, a blasting design module, an intelligent optimization module, a statistical analysis module, a forecasting and early warning module and a system management module through a front-end and rear-end separation architecture; and the user interaction layer realizes multi-terminal cooperative interaction based on WebGL, Vue3 and a mobile terminal technology.

The invention relates to the technical field of enterprise ESG digital management, in particular to a sustainable management ESG platform. The platform comprises a data access layer, a twin modeling layer, an intelligent analysis layer, a report generation layer and a collaborative interaction layer. The data access layer is used for standardized acquisition, cleaning and block chain evidence storage of multi-source ESG data; the twinborn modeling layer constructs enterprise ESG digital twinborn bodies through index mapping and scene simulation; the intelligent analysis layer realizes index dynamic monitoring, abnormity early warning and risk quantitative evaluation based on time sequence prediction and causal reasoning; the report generation layer outputs a compliance report through a multi-template automatic adaptation and natural language generation technology; and the collaborative interaction layer realizes multi-role data sharing, task tracking and strategy optimization. According to the method, multi-modal data fusion and an intelligent algorithm are fused, the efficiency of ESG data integration, risk response, report generation and collaborative management is comprehensively improved, and the problems of data isolation, response lag and manual dependence in a traditional mode are effectively solved.