3639 results about "Informatization" patented technology

The invention discloses an informatization project management system based on big data analysis, which belongs to the field of big data and comprises a data acquisition module, a time sequence modeling module, a task coupling analysis module, a risk clustering identification module, a resource allocation prediction module and the like. The data acquisition module asynchronously and parallelly acquires structured and unstructured data and uniformly encodes the structured and unstructured data; the time sequence modeling module constructs a multi-dimensional time sequence based on an autoregressive residual network; the task coupling analysis module fuses the task trajectory and the dependency relationship to generate a task influence directed graph; the risk clustering identification module identifies risks through variational graph auto-encoder mapping; the resource allocation prediction module constructs a dynamic resource priority based on a graph attention mechanism; a progress deviation traceability module identifies a deviation causal chain; the knowledge graph decision-making module corrects resource priorities and path strategies in a cross-graph manner; and the project global control module dynamically adjusts key paths and resource configuration and performs closed-loop self-correction. The beneficial effect is that the intelligent level and the risk response capability of project management are improved.

The invention belongs to the technical field of knowledge maps and artificial intelligence, and discloses a building safety risk identification method of a big language model assisted knowledge map. According to the technical scheme, the overall process comprises the steps of data collection and preprocessing, construction of urban building structured table data, construction of an urban building safety knowledge graph, integration of the structured table data and knowledge graph data, model fine adjustment, model training, model performance evaluation and model recognition effect verification. According to the technical scheme, the large language model with the high semantic modeling capacity and the knowledge graph with the high graph structure expression capacity are integrated, the related knowledge of urban building safety is automatically extracted, constructed and integrated, high-risk events such as fire disasters and structural hidden dangers are recognized, and the informatization level and the intelligent level of urban building safety management are improved.

The invention discloses a transformer substation engineering construction drawing intelligent analysis and evaluation system based on image recognition, and relates to the technical field of transformer substation engineering construction informatization. The data processing center is in communication connection with a data acquisition layer, an image preprocessing layer, a feature extraction layer, an intelligent analysis layer, an evaluation decision-making layer and an application display layer, and all layers of architectures are in electric signal connection. According to the method, the improved convolutional neural network model is adopted, and an image preprocessing algorithm specially aiming at engineering drawing feature optimization is combined, so that the drawing recognition accuracy is remarkably improved compared with a traditional OCR technology, the manual proofreading workload is greatly reduced, a drawing element correlation analysis system based on a knowledge graph is constructed, and the engineering drawing recognition accuracy is improved. Key information such as equipment arrangement, line connection and size marking in the drawing can be automatically extracted and associated, and structural storage and intelligent retrieval of drawing content are achieved.

The present invention discloses a safety risk analysis system and method based on multimodal data processing; it relates to the field of industrial automation and information technology; the purpose of the present invention is to specifically target high-risk scenarios of hazardous chemical enterprises, and provide a safety risk analysis system and method based on multimodal data processing, which is based on deep learning technology, comprehensively considers the changes in spatiotemporal characteristics, can monitor and evaluate the safety risks of hazardous chemical enterprises in real time, and automatically integrates multimodal data such as monitored videos, sensor data, and operation logs. The spatial features are extracted through convolutional neural networks, and the time series data is processed using recurrent neural networks and long short-term memory networks, and further feature extraction and fusion are performed. The key risk factors are also identified through the attention mechanism, thereby achieving a comprehensive and accurate safety risk assessment, thereby providing real-time warnings for safety managers to ensure that potential safety hazards are discovered in a timely manner.

The invention discloses a BIM-based building electromechanical full life cycle management platform and an optimization strategy thereof, relates to the technical field of building informatization management, and solves the defects of the existing BIM technology in the aspects of processing efficiency, model precision, data synchronization and change management. According to the invention, a data layer is used for data cleaning and standardization through a machine learning model, and distributed storage is realized through a cloud management system; the model layer constructs and updates a high-precision BIM model; the synchronization collaboration layer ensures the consistency and traceability of data by using a real-time synchronization mechanism and a block chain technology; the decision analysis layer performs data analysis and prediction through a deep learning algorithm; the full life cycle management layer integrates historical data and current data and automatically triggers a management process; according to the method, the data processing efficiency and the model precision are greatly improved, and the seamless sharing capability of information and the transparency of data synchronization and change management are remarkably improved, so that the overall collaborative efficiency and the management level of a project are enhanced.

The invention relates to the technical field of highway engineering informatization, in particular to a geometric registration method and system based on a BIM model and an AR real scene. The method comprises the following steps: obtaining multi-source data of a construction site, and generating an AR real scene of the construction site according to the multi-source data; fusing multi-source data to obtain accurate parameters of the construction equipment; calculating a spatial transformation matrix of a construction site through accurate parameters of construction equipment, and obtaining an initial registration result of the BIM model and the AR real scene by combining engineering characteristics and the spatial transformation matrix; a dynamic error compensation mechanism is introduced, the initial registration result is corrected through the dynamic error compensation mechanism, and a local registration result is obtained; and constructing a global and local coordinate system mapping optimization model, and mapping the local registration result to a global coordinate system by using the global and local coordinate system mapping optimization model to obtain a global registration result. According to the method, a reliable spatial data basis is provided for highway engineering quality inspection, construction guidance and defect identification.

A BIM-based engineering information management system of the present invention relates to the field of constructional engineering informatization management, and comprises a data processing module, a model construction module, a block chain evidence storage module, a verification module, a data fusion module and an authority management module. The data processing module receives original engineering data and generates a structured data signal. And the model construction module generates a BIM model according to the structured data signal. And the block chain evidence storage module encrypts and stores the metadata signal, generates an evidence storage completion signal and feeds back the evidence storage completion signal to the model construction module. And the verification module analyzes the dynamic operation log signal, and generates a risk early warning signal and a repair suggestion signal when abnormality is detected. And the data fusion module generates a fusion data signal, transmits the fusion data signal to the model construction module and triggers BIM model updating. And the authority management module adjusts the user authority according to the risk early warning signal. According to the invention, the problems of data islands, safety risks, low cooperation efficiency and insufficient intelligence in engineering information management can be solved.

The invention discloses a building structure monitoring and management method, system and equipment and a storage medium, and relates to the field of civil engineering. The method comprises the following steps: acquiring three-dimensional data of a building structure, and constructing a digital twinborn model of the building structure according to the three-dimensional data; acquiring real-time state data of the building structure from a preset sensor network, and comparing the real-time state data with reference state data in the digital twin model; and when the difference between the real-time state data and the reference state data in the digital twin model is smaller than a first threshold value, performing performance prediction and life evaluation on the building structure according to the real-time state data in combination with influence factors. By implementing the technical scheme provided by the invention, informatization and intelligent management of the whole life cycle of the project is realized.

The invention discloses a highway informatization intelligent management and control system, and relates to the technical field of intelligent construction, and the system comprises the steps: collecting multi-source data in real time, uploading the multi-source data to an edge calculation node for timestamp alignment and format standardization, and inputting the multi-source data to a space-time Transform fusion model, extracting spatial-temporal features of sensor data and semantic features of video pictures through a multi-head attention mechanism, and generating a dynamic risk score; and updating a virtual construction progress model of the digital twin, superposing the adjusted construction standard to a real scene through an AR terminal, guiding a worker to carry out deviation correction, and encrypting and storing a closed-loop processing record to a block chain. According to the method, a pulse code driven distributed learning framework is adopted to greatly improve the anomaly detection efficiency, and quick response and global optimization of equipment cluster behaviors are realized through event triggered feature compression and an adaptive weight updating mechanism.

The invention relates to the technical field of civil engineering informatization and automation design, in particular to a parameterized construction drawing generation method based on a constraint solution algorithm, and the method comprises the steps: defining a construction drawing foundation structure and variable parameters through an engineering design model embedded with a parameterized template; a parameter constraint relation set is generated in combination with geometric constraints, size constraints and logic constraints input by a user, constraint rules are converted into intermediate expressions through a formula analyzer, a syntax tree is constructed, and an executable parameter association rule set is generated through semantic verification. The auditing module verifies the drawing compliance based on the engineering specification database and generates a correction suggestion; and realizing cross-system data linkage between the multi-terminal collaborative interface and external BIM model parameter mapping. According to the method, the problems of detail loss and specification deviation in three-dimensional model projection are effectively avoided, and the drawing generation efficiency and the multi-specialty collaborative robustness are improved.

The invention discloses an intelligent multimedia interactive teaching and examination system and method, and relates to the technical field of education informationization, and the method comprises the steps: obtaining user information and a learning state, and generating a learning portrait; based on the learning portrait, utilizing the generative AI to dynamically generate personalized teaching content, and marking the abnormal state of the user in real time; storing an abnormal state marking result of the user to a dynamic feature field of the learning portrait, and dynamically optimizing a learning path; based on the optimized learning path, a personalized assessment task is dynamically generated, and answer data and learning behavior data of the user are recorded; and performing multi-dimensional evaluation on the performance of the user through a semantic analysis method by utilizing the answer data and the learning behavior data. According to the method, through the comprehensive analysis model and the multi-modal feature vector, multi-dimensional evaluation of the performance of the learner is realized, multiple aspects of knowledge mastery, behavior performance, emotional state and the like are covered, and detailed feedback and improvement suggestions are provided for the learner.

The invention relates to the technical field of accounting informatization, and discloses an accounting document cross-platform synchronization system based on a block chain and a conflict processing method, and the system automatically judges a multi-mechanism concurrent operation conflict based on a preset medical authority level and a millisecond timestamp. And when a plurality of branch hospitals modify the same patient voucher at the same time, preferentially adopting a high-authority mechanism to operate, if the authority is at the same level, selecting the operation with the latest timestamp, and if logic conflicts exist, pushing to a general hospital for manual auditing. And an operation log is recorded in real time by adopting Apache Kafka, and a non-tampering historical version is generated through a block chain technology. All modification records are stored in a Merkle tree structure, a complete operation track at any time point can be inquired through a patient ID, the complete operation track comprises modification content, operator identity and block chain transaction hash, a national medical insurance platform is connected in real time, and cost compliance is automatically verified; the system can solve the problems of data conflicts, version chaos and auditing tracing among heterogeneous ERP (Enterprise Resource Planning) systems.

The invention relates to the technical field of energy scheduling, and discloses an intelligent optimization scheduling method of an informatization energy management system, which comprises the following steps of: data acquisition and fusion: acquiring real-time data of each node in an energy system through distributed Internet of Things equipment and a multi-mode sensor network, and fusing and processing the acquired data to obtain a data fusion result; a high-quality data set in a unified format is generated; and prediction modeling and demand response: based on user behavior analysis and a machine learning algorithm, establishing a demand response model, and constructing a multi-stage energy demand and supply prediction model including short-term, medium-term and long-term time dimensions. Through combination of a collaborative optimization algorithm and a distributed decision-making mechanism, a global optimal energy scheduling scheme is realized on the basis of local optimization of each distributed energy unit, high collaboration and optimal resource allocation among the energy units in a complex energy network are ensured, and the energy scheduling efficiency is improved. Therefore, the energy utilization efficiency and the operation stability of the whole system are improved.

The invention provides a building construction scheme intelligent auditing system based on a large model, and belongs to the field of building construction. According to the technical scheme, the method comprises the steps that a construction scheme template library and a building construction standard specification library are constructed, a building specification knowledge graph is constructed, a to-be-audited construction scheme document is received and subjected to structural division and preprocessing, semantic vector data are obtained, matching operation is conducted on the semantic vector data and graph nodes in the building specification knowledge graph, and the graph nodes in the building specification knowledge graph are obtained; and outputting audit target data, analyzing and generating an analysis result data structure based on the audit target data, generating an audit report according to an analysis result, and completing recording and tracking of an audit process. The method has the beneficial effects that automatic auditing and whole-process tracking of the construction scheme are realized by constructing the structured template and the standard specification knowledge graph in combination with semantic vector matching and rule work efficiency comparison, the accuracy, consistency and efficiency of auditing are effectively improved, and the informatization and intelligence level of building construction management is remarkably enhanced.

The invention discloses a food safety sampling inspection data verification method and system and a computer storage medium thereof, particularly relates to the technical field of food safety supervision informatization, and is used for solving the problem of false consistency caused by silent failure when an external data source fails in an existing verification system. Field-level binding is realized by establishing a dependency mapping table of a sampling inspection system and an external data source; constructing a service response causal graph model, and dynamically marking a failure data source based on the deviation between the anti-fact response and the actual response; analyzing the verification field set and positioning a key verification field; degrading the weight of the key field to be below a threshold value and activating a manual auditing flag bit; scanning a preset coupling relationship between fields, freezing associated fields which do not trigger rules, verifying and constructing a conflict topology; when the check engine is executed, dynamically skipping the weight reduction field, suspending the freezing field, and generating a to-be-rechecked report in combination with the artificial flag bit and the topological graph; error data transmission is blocked from the source, and the food safety risk missed judgment rate is remarkably reduced.

The present application relates to the field of warehouse management technology, and provides an information management method, device, electronic device and storage medium for intelligent warehousing. By preprocessing the target data set to realize a standardized spatiotemporal fusion data stream, a virtual space is dynamically mapped based on the standardized data stream to generate a virtual-real synchronized digital twin warehouse model, and multi-target scheduling is performed according to the real-time status data in the digital twin warehouse model to generate an AGV path matrix, and the AGV path matrix is ​​dynamically replanned according to the real-time status data to generate anti-disturbance scheduling instructions. At the same time, root cause analysis of the product data set is performed to obtain predicted improvement data, and finally, material allocation analysis is performed on the anti-disturbance scheduling instructions and predicted improvement data according to the preset optimization method to obtain warehousing and logistics decisions. This application realizes flexible scheduling of warehousing and logistics based on the current status of warehousing and combined with the predictive analysis of the product cycle, which can accurately respond to actual needs and adjust the operation strategy in time.

The invention discloses a law shield AI intelligent case handling all-in-one machine system based on a large language model, and relates to the technical field of law artificial intelligence and judicial informatization, the system comprises an integrated terminal device, a case semantic modeling module, a class case knowledge engine, a risk prediction module, a large language model service interface and an intelligent document generation module; the system constructs a case semantic graph through multi-modal information fusion and a graph neural network, performs legal rule path matching and similarity reasoning based on a class case database, outputs structured legal suggestions and standard legal instruments in combination with user context recognition and large language model multi-round generation capability, and realizes dynamic updating of the semantic graph. The method improves the automation, structuring and interpretability of case processing, and is suitable for intelligent case handling scenes such as legal assistance, litigation assistance and judicial mediation.

The invention discloses a medical and educational informatization comprehensive supervision and diagnosis platform system based on multi-modal data fusion. A data acquisition module acquires multi-modal data from a medical and educational information system and preprocesses the multi-modal data; the data storage module constructs a hybrid architecture to classify and store data and establishes an index. The multi-modal data fusion module deeply fuses medical records, images and physiological monitoring data of medical treatment and teaching resources, learning behaviors and teaching evaluation data features of education by means of a feature extraction technology and a fusion algorithm. The supervision and diagnosis module constructs models of medical service quality evaluation, disease diagnosis assistance, teaching quality monitoring and the like based on fusion features to realize accurate analysis. The user interaction module provides interaction interfaces for different roles and supports operations such as data query and uploading. The platform system breaks the data barrier, fully mines the data value, provides powerful support for informatization management, decision making and service optimization in the medical and education fields, and promotes the innovative development of the two fields.

The invention relates to the technical field of consumable traceability, and discloses an SPD medical consumable intelligent monitoring and traceability management system, which comprises a consumable warehousing module for inputting information through a UDI code and updating the inventory; the receiving plan generation module is used for calculating the demand quantity of each department for different types of consumables according to the demands of clinical departments, and generating a receiving plan according to the demand quantity; according to the distribution and use module, the SPD system distributes the consumables according to the receiving plan and selects the earliest batch for distribution according to the FIFO principle or the FEFO principle; and the refund processing module is used for re-evaluating the remaining period of validity when the unused consumables are refund. According to the method, UDI coding runs through the whole consumable management process, a complete closed-loop management process of intelligently analyzing and predicting future demands, dynamically optimizing inventory, recording consumable circulation information in the whole process, generating and finally purchasing execution is introduced, an informatization means and a management optimization strategy are combined, and the SPD medical consumable management level can be effectively improved.

The invention provides a classroom behavior analysis method and system, electronic equipment and a storage medium, and relates to the technical field of educational informationization, and the method comprises the steps: collecting videos and audios, carrying out image enhancement, noise filtering and frame segmentation on the videos, carrying out noise reduction, sound source positioning and voice segmentation on the audios, and generating standardized images and voice sequences; an improved MTCNN cascade network is combined with a posture estimation technology, facial key points of students are extracted from videos, class arrival states, head postures and facial micro-expressions are recognized, audios are analyzed through a bidirectional LSTM network, and speaking duration and frequency are obtained; constructing individual behavior indexes according to attendance, head actions and expressions of the students; constructing an interaction index according to the teacher and student speaking data; the individual and interaction indexes are summarized to generate the multi-dimensional classroom behavior portrait, and the relation between the portrait and the teaching effect is analyzed, so that the classroom behavior analysis precision can be improved, the data processing capability can be enhanced, and the multi-dimensional classroom behavior comprehensive evaluation can be realized.

The invention discloses an intelligent enterprise financial data analysis system and method based on artificial intelligence, and belongs to the technical field of enterprise informatization management and intelligent finance. The objective of the invention is to solve the technical problems of low processing efficiency, insufficient data insight, lagging risk identification, weak intelligent decision-making assistance capability and the like in the existing enterprise financial data analysis process. The system generally integrates a data automatic acquisition and integration module, a financial data deep analysis and modeling engine based on artificial intelligence, a key financial index and operation performance intelligent calculation module, a multi-dimensional financial risk intelligent identification and dynamic early warning module and an interactive visual analysis report and decision support module. The core of the method is that internal and external multi-source heterogeneous financial and operation data of an enterprise are automatically collected and fused, deep processing and intelligent analysis are performed on the data by applying artificial intelligence technologies such as machine learning and natural language processing, and accurate portrait of the financial condition of the enterprise, dynamic evaluation of operation performance and real-time monitoring and prediction of financial risks are realized. And analysis reports and optimization suggestions with insight are generated, so that enterprise managers can make efficient and scientific operation decisions. According to the method, the automation and intelligence level of enterprise financial data analysis can be remarkably improved, the financial information quality and decision support efficiency are improved, the risk prevention capability of enterprises is enhanced, and the enterprises are assisted to realize refined operation and value creation.

The invention discloses a field monitoring method based on engineering informatization, and the method comprises the steps: collecting the tightness data of a rope in real time through a tension sensor integrated on a protection rope, and transmitting the data to a field monitoring system; the method comprises the following steps: acquiring a worker operation picture shot by video monitoring equipment deployed in a construction site, and extracting posture features such as a body inclination angle and arm extension length of a worker in the picture; determining a real-time position coordinate of the worker according to the information of the positioning tag worn by the worker, and judging whether the coordinate is in a preset dangerous area electronic fence or not; according to the distance relation between the connection points of the worker and the protection rope, the swing track of the protection rope and the movement track calculated by the position coordinate change of the worker are analyzed, and whether the worker breaks away from the protection rope illegally or not is judged; if it is judged that the worker is separated from the protection rope, the position of a connection point of the protection rope suspected to fall off is marked in the monitoring picture according to the material characteristic and the color characteristic of the protection rope.

Provided is a concrete full lifecycle green quality control method based on Internet of Things and big data, comprising the following steps: step 1, on the basis of an information platform, selecting raw materials required by concrete, so as to achieve the control of the selection of the raw materials of concrete; step 2, on the basis of the information platform, performing engineering concrete mix ratio intelligent design, and obtaining the mix ratio of the raw materials required by concrete corresponding to a project under construction; step 3, on the basis of the information platform, taking into account the obtained concrete mix ratio to mix and prepare concrete by means of an intelligent concrete factory, and automatically testing and controlling the quality of the prepared concrete at the same time; and step 4, on the basis of the information platform, using the mixed and prepared concrete to perform intelligent construction. Automatic, intelligent and green control of concrete throughout the full lifecycle from raw materials, mix ratio design, production, and construction to the service life of the structure are achieved by controlling each stage of the full lifecycle of the concrete.

The invention discloses a text knowledge automatic extraction and mapping method based on deep learning, which optimizes a semantic understanding algorithm by combining a deep learning model, enhances the perception ability of the model for the internal structure and external relationship of a text, realizes comprehensive extraction and detailed relationship analysis of equipment fault knowledge, and utilizes a knowledge mapping technology to realize automatic extraction and mapping of equipment fault knowledge. According to the method, an automatic graph construction process is implemented to improve the query efficiency and analysis capability of the graph, and the method comprises the following steps: S1, performing structured processing on an original document, segmenting the original document into independent case units, and extracting key information related to an equipment fault; s2, key entities in the document and mutual relations of the key entities are recognized and marked; and S3, based on the extracted entities and relationships, constructing and updating a knowledge graph of the fault case. The system has high automation, intellectualization, expandability and modular design, can be easily integrated into an existing industrial informatization system, and assists an enterprise in realizing intellectualized transformation and upgrading.

The invention discloses a power grid equipment state sensing driving dynamic response method based on the Internet of Things technology, and relates to the technical field of power system automation and informatization, and the method comprises the following steps: S001, collecting original multi-dimensional state signals of a plurality of sensors deployed in a power grid equipment state sensing channel, constructing an electromagnetic disturbance recognition model, and carrying out the recognition of the original multi-dimensional state signals; frequency domain and time domain feature extraction is carried out on the signals, and a feature comparison parameter set used for distinguishing electromagnetic interference and real faults is generated. Frequency domain and time domain features are extracted through an electromagnetic disturbance recognition model, dynamic threshold judgment and response strategy adjustment are achieved in combination with multi-source sensing data, interference and faults can be accurately distinguished, early warning and protection logic can be corrected in real time, protection actions can be accurately triggered, closed-loop control is achieved, the delayed fault tolerance and multi-source verification capacity is achieved, and the method is suitable for large-scale popularization and application. The false operation rate and the false stop risk are effectively reduced, and the intelligence, the safety and the stability of power grid operation are improved.

The invention discloses a BIM model-based water conservancy project cost accurate calculation method and system, and relates to the technical field of water conservancy project informatization management, and the method comprises the steps: obtaining BIM model component data, construction scheduling data, construction path data and construction cost data, constructing a scheduling component diagram for conflict recognition, calculating the load value of a path segment, and calculating the load value of the path segment; a construction progress deviation value is determined by combining sensing data of the internet of things, and finally a comprehensive cost estimation value is calculated; the method has the beneficial effects that BIM model component data, construction scheduling data, path data and cost data can be integrated, a three-dimensional scheduling component diagram is constructed for conflict detection, a progress deviation value is dynamically calculated in combination with sensing data of the Internet of Things, quantitative association of construction cost and progress deviation is realized, and the construction efficiency is improved. The method has the advantages of improving the construction cost calculation accuracy, enhancing the dynamic response capability of the construction process and realizing the real-time linkage of the cost and the progress.

The invention discloses a power enterprise intelligent collaborative office method and system based on artificial intelligence, and relates to the technical field of power informatization. According to the intelligent collaborative office method and system for the power enterprise based on artificial intelligence, request data is received from a user terminal through a deep learning model, a service demand type, an emergency degree and task complexity are identified, a service priority index is generated, classification and priority distribution are carried out, and based on the service priority, the user terminal is subjected to intelligent collaborative office. The method comprises the following steps of: matching associated tasks and resource requirements through a model, retrieving related historical data to optimize a resource configuration path, dynamically tracking task progress, execution state and resource consumption, identifying a bottleneck in an execution process and generating an optimization instruction, and finally, dynamically adjusting model parameters and resource configuration rules through an adaptive learning algorithm. And a closed-loop feedback mechanism is formed. Information flow and resource configuration are effectively integrated, the flexibility and response speed of collaborative office are improved, and the development requirements of smart grids and smart cities are met.

The invention relates to a prefabricated building quality defect tracing system and method applied to the field of building informatization, and the system comprises a user interaction layer, a data processing and storage layer, a data collection layer and a function layer, and the data collection layer is used for collecting key quality data of prefabricated building components in different links; the user interaction layers interact with each other through a network and the function module layer; the data processing and storage layer performs encryption, hash operation, scattered storage and index verification on the quality data transmitted by the data acquisition layer by using an intelligent contract, an IPFS network and a block chain; the function module layer provides support for each unit of the user interaction layer to trace quality defects, judge responsibility and take prevention measures, and the system can collect the quality data of the whole process of the prefabricated building, comprehensively manage the quality tracing process, strengthen multi-party collaboration and sharing, and improve the quality of the prefabricated building. And it is ensured that tracing of the quality defects of the fabricated building has comprehensiveness, transparency and non-tampering performance.

The invention relates to the technical field of informatization war, and particularly provides a big data analysis-based combat decision auxiliary system and method, and the system comprises a data collection module, a data preprocessing module, a multi-source intelligence fusion module, a situation prediction depth mining and analysis module, a military strength deployment module, and an auxiliary optimization module. The method comprises the following steps: S101, data acquisition, connection and preprocessing; s102, fusing multi-source intelligence to judge a target; s103, accurately analyzing and predicting the attempt of the enemy; s104, carrying out multi-dimensional association recommendation on the available strength; s105, assisting in optimizing a combat scheme; according to the scheme, how to apply a big data analysis technology is introduced in detail, a set of efficient and intelligent combat scheme generation system is constructed, and scientific and accurate tactical and strategic guidance is provided for military decision makers. According to the system, key technical links such as data acquisition, fusion, analysis, modeling and visualization are integrated so as to cope with a complex and dynamic battlefield environment, and maximization of combat effectiveness is achieved.

The invention relates to the technical field of geological informatization, in particular to a time-space sequence prediction and risk assessment model for geological disaster monitoring data, which comprises a data acquisition module, an edge processing module, a cloud analysis module, a mobile terminal module and a data processing module, the server is connected with the cloud analysis module through a WebSocket protocol, and is used for receiving the prediction result and the visual data; and displaying the three-dimensional illness state evolution graph on augmented reality (AR) equipment. Through the innovative technical scheme, comprehensive breakthrough is achieved in the aspects of multi-modal data fusion, dynamic feature extraction, accurate prediction, robustness design, visual display and the like. The innovation points cooperate with one another and promote one another, and an efficient, reliable and intelligent MS remote monitoring and prognosis prediction system is jointly constructed.