290results about How to "Understand intuitive" patented technology

The invention relates to the technical field of disease follow-up visit, in particular to a health state assessment system applied to disease follow-up visit, which comprises a data acquisition module, a data preprocessing module, a health state assessment module, a personalized health management suggestion module, a dynamic health risk prediction module and a visualization module, the data acquisition module acquires multi-dimensional data of a patient and performs data fusion and integration, the health state evaluation module evaluates the health state of the patient based on multi-level feature extraction and a deep learning model, and the personalized health management suggestion module combines a health state evaluation result and historical data to obtain a personalized health management suggestion result. Customized health management suggestions are generated through a rule engine, and the dynamic health risk prediction module predicts future health risks of patients and provides real-time early warning by using a time sequence analysis model. The visualization module displays health assessment and management suggestion results through a chart and an interactive interface, and the accuracy and individuation degree of health management are improved.

The embodiment of the invention discloses a bridge bolt monitoring image recognition method and system based on deep learning, and belongs to the technical field of bridge image processing. The method comprises the following steps: acquiring a multi-angle monitoring image set of a bridge bolt part through an image acquisition device, and preprocessing the monitoring image set to generate a standardized target image sequence; positioning a bolt monitoring area for each image frame in the target image sequence based on a pre-trained positioning model, and generating an area coordinate set containing bolt position information; inputting the region coordinate set into a state recognition model, extracting structural state features of each bolt monitoring region, and generating a looseness degree prediction result of the bolt part according to the structural state features; according to a matching result of the looseness degree prediction result and a preset safety threshold range, a bolt state abnormity alarm signal is output; and associating the bolt state abnormity alarm signal to the corresponding monitoring image frame, and generating a monitoring report containing a visual mark.

The invention belongs to the technical field of artificial intelligence and big data analysis, and particularly relates to a scenic spot passenger flow trend prediction analysis method based on an AI big language model. According to the method, big data and artificial intelligence technologies are utilized, LBS data, scenic spot data, holiday and festival information, third-party maps, weather data and other multi-source data are comprehensively applied, a comprehensive multi-dimensional knowledge base is constructed, and meanwhile, the knowledge search and generation capability is improved by utilizing an RAG technology; through model pre-training and fine tuning, the universal model capability is developed, and a multi-agent system is further constructed; based on the natural language processing capability of the AI large language model, the LLM can intelligently analyze the text input of the scenic region administrator, drive the cooperative work among multiple agents, and achieve the intelligent prediction and analysis of the scenic region passenger flow trend. The method can more accurately predict the passenger flow trend of the scenic area.

The invention relates to the field of construction planning visualization, in particular to a construction planning visualization method and system for a refuse transfer station. The method comprises the following steps: acquiring a satellite positioning map and a refuse transfer station design drawing of a to-be-developed area; image detail reconstruction is carried out on the satellite positioning map, road space distribution fitting is carried out, and a regional road distribution network is constructed; performing surrounding building positioning calculation on the detail optimization reconstruction satellite image based on a regional road distribution network, performing an optimal site selection decision, and extracting an optimal address region image; carrying out transfer station key feature point identification on the refuse transfer station design drawing, then carrying out three-dimensional point cloud modeling, and constructing a transfer station three-dimensional structure model; and according to the optimal address area image, carrying out corresponding foundation accurate matching on the transfer station three-dimensional structure model, carrying out spatial positioning mapping, and constructing a transfer station address twinborn model. According to the method, the operation efficiency of the transfer station is improved, and the rationality of building planning is enhanced.

The invention relates to the technical field of surface defect detection, in particular to a photovoltaic aluminum frame surface defect detection system which comprises a surface defect detection platform, a surface information unit, an image processing unit, a progressive division unit, a defect positioning unit, a defect classification unit and a management display unit. According to the method, the appearance feature image of the photovoltaic aluminum frame to be detected is preliminarily analyzed, so that whether the surface of the photovoltaic aluminum frame to be detected has defect risks or not is known from the perspective of image difference, light source detection defect positioning analysis is carried out in a progressive mode, meanwhile, detection is carried out in a light source detection mode, and the detection accuracy is improved. According to the method, the defect position can be further determined, defect multi-level verification analysis is carried out in an information feedback mode so as to improve the accuracy and effectiveness of the detection result, and the to-be-detected photovoltaic aluminum frame with the defect is divided and managed in the information feedback mode so as to improve the defect processing effect of the subsequent to-be-detected photovoltaic aluminum frame.

The invention discloses an automatic auditing and analyzing method for cultivated land soil data. The method comprises the following steps: S1, acquiring original soil data through multi-spectral imaging of an Internet of Things sensor and an unmanned aerial vehicle to form a data set; s2, using an extended Kalman filter to reduce noise and remove abnormal values, and using time sequence interpolation to complement missing data; s3, analyzing and auditing the preprocessed data based on the time sequence, and identifying an abnormal mode; s4, analyzing and fusing auditing data by using a causal reasoning graph neural network; s5, performing multi-dimensional analysis and prediction on the fused data by applying a big data analysis technology; s6, realizing real-time data visualization and interactive display through a visualization method driven by quantum computing; s7, using a natural language generation technology to generate a report for the soil data set and the analysis result; and S8, implementing encryption and access control in the data processing and transmission process. The invention provides a comprehensive soil data processing solution, and the data auditing efficiency, accuracy and safety are effectively improved.

The invention relates to the field of power supply equipment monitoring, in particular to a distributed power supply state monitoring method and system based on optical fiber communication sensing. The method comprises the following steps: acquiring a power supply equipment distribution diagram; performing spatial layout distribution analysis on the power supply equipment distribution diagram to obtain power supply node layout distribution data; performing distributed topology reconstruction based on the power supply node layout distribution data to construct a power supply node topology network; acquiring real-time monitoring data of the power supply equipment based on the optical fiber communication sensing node; performing time window fine-grained division on the real-time monitoring data of the power supply equipment to obtain a plurality of time windows; performing multi-layer time-frequency local decomposition on the real-time monitoring data of the power supply equipment based on a plurality of time windows, and constructing a multi-period spectrum feature map; and extracting a power supply equipment time sequence voltage sequence based on the power supply equipment real-time monitoring data. According to the invention, efficient and accurate power supply equipment state monitoring is realized.

The invention relates to the technical field of medical diagnosis systems, in particular to an early gonitis diagnosis system and method based on multi-modal deep learning, a data collection module is used for collecting and preprocessing multi-modal data including knee joint X-ray image data, MRI (Magnetic Resonance Imaging) image data and clinical evaluation data; the model construction module constructs a deep learning model by combining a convolutional neural network and a Transform architecture, realizes mapping from multi-modal data to a clinical assessment phenotype label by adopting a feature automatic learning module and a potential relationship mining module, and integrates a Grad-CAM interpretability method for understanding a model prediction basis; diagnostic data are continuously collected to be fed back to the data collection module for model optimization, the convolutional network is good at capturing local image features, the Transform architecture is good at modeling a long-range dependency relationship, and the feature extraction and relationship modeling capabilities of the model are greatly improved through combination of the convolutional network and the Transform architecture.

The invention relates to the technical field of environment monitoring, in particular to a natural reserve ecological monitoring result display system based on geographic information data, which comprises a data acquisition module, a data fusion module, a dynamic GIS module, an intelligent analysis module, a multi-dimensional display module, an interactive report generation module and a user interaction module. Wherein the data acquisition module is used for acquiring ecological monitoring data; the data fusion module is used for carrying out fusion processing on the multi-source ecological monitoring data; the dynamic GIS module is used for mapping the fused ecological monitoring data into a geographic space in real time; the intelligent analysis module is used for intelligently analyzing the geographic space data; and the multi-dimensional display module is used for displaying the ecological monitoring result. According to the system and the method, the ecological data processing capability is improved through an efficient data fusion technology and an advanced intelligent analysis module, and meanwhile, the user experience is greatly enhanced through an interactive report generation and multi-dimensional display module.

The invention belongs to the field of network attack detection, and particularly relates to an APT attack detection method based on traceability graph behavior information. The method comprises the following four steps: step 1, data preprocessing; step 2, generating a sub-graph; step 3, behavior feature extraction; performing feature extraction on each sub-graph, wherein the feature extraction comprises node feature extraction and edge feature extraction; 4, designing and training a classification model, and performing anomaly detection; and training and testing the classification model, sequentially classifying the type of each edge by using the trained model, and when a certain edge cannot be correctly classified by any existing sub-model, judging that the edge is abnormal, and outputting a behavior structure diagram of the edge. According to the method, behavior attributes and structural information thereof are introduced into the modeling of the traceability graph, and the category of traditionally paying attention to entity interaction relationships is exceeded; by introducing a pooling method and graph representation learning, the expression ability of the model is improved, important information in a behavior structure is more effectively captured, and continuous optimization is performed on the basis of initial structure information.

The invention provides a digital person business card interaction method, electronic equipment and a storage medium, and belongs to the technical field of data processing, and the method comprises the steps: responding to a business card viewing instruction, and outputting a target digital person business card associated with the business card viewing instruction; receiving an inquiry instruction based on the target digital person business card, and judging whether the inquiry instruction has a corresponding standard problem or not; if yes, inputting an information set associated with the standard question and the target digital person business card into a pre-trained information desensitization large model; if not, calling a preset search engine to search the inquiry instruction, determining a search data set based on a search result, and inputting the inquiry instruction, the target digital person business card and the search data set into a pre-trained information desensitization large model; and obtaining a desensitization answer output by the information desensitization large model, and outputting the desensitization answer. According to the method, the interaction efficiency of the recruitment process can be remarkably improved, the hysteresis of information transmission is reduced, and the personal information security is protected.

The invention discloses a transcutaneous electrical stimulation device based on a large language model, and relates to the technical field of wearable devices. The transcutaneous electrical stimulation equipment based on the large language model comprises a data acquisition and preprocessing module, a feature extraction and fusion module, a model training and prediction module and a real-time information processing and response module, real-time data processing and intervention capabilities are integrated, human body data can be analyzed in real time, electrical stimulation parameters can be automatically adjusted, an instant treatment or adjustment scheme is provided for the problems of arrhythmia, chronic pain and the like, and the timeliness and effectiveness of treatment are greatly improved. And secondly, by fusing the physiological signal features and the symptom text features, the equipment can more comprehensively understand the health condition of the user, so that a more accurate treatment scheme is provided. Besides, the equipment also has the functions of anomaly detection and trend analysis, can predict potential health risks, and triggers an alarm in time when a serious anomaly is detected, thereby effectively guaranteeing the life safety of the user.

The invention discloses an existing building outer wall internal and external heat insulation energy consumption optimization method based on a building model, and belongs to the technical field of building design. In order to solve the problems of insufficient data comprehensiveness and incomplete thermal insulation scheme evaluation, the thermal insulation performance of a building can be evaluated more accurately by checking an outer wall structure on site, recording material types, damage degrees and the current situation of a thermal insulation layer and combining scientific methods such as thermal resistance testing and heat transfer coefficient measurement; digitization and visualization of building information are achieved through the BIM technology, historical energy consumption data are collected from multiple data sources and systematic arrangement and classification are carried out, the readability of the data is improved, rapid import and analysis can be conveniently carried out in energy consumption simulation software, and therefore the energy consumption condition of a building is reflected more accurately; according to the method, comprehensive coverage of multiple possibilities is achieved, the influence of different heat preservation schemes on energy consumption can be evaluated more comprehensively, differentiated design is conducted on the thickness of the heat preservation layer based on the energy consumption simulation result, and the heat preservation performance of a building is effectively improved.

The invention belongs to the field of network security, and discloses a network space vulnerability clustering method based on feature value similarity calculation. The method comprises the following steps: (10) vulnerability data acquisition and standardized storage; (20) designing a tagged vulnerability description method; (30) specific network space vulnerability calculation; (40) network security vulnerability data classification, tagging and feature extraction; (50) clustering network security vulnerabilities based on features and a clustering algorithm; and (60) carrying out visual display on the clustered network space vulnerability categories. The method has the beneficial effects that compared with a traditional method, the method provided by the invention does not need to construct a complex network security knowledge graph for huge vulnerability data, and potential association and common points among vulnerabilities can be revealed by systematically analyzing and understanding characteristics and influences of various vulnerabilities aiming at standardized and tagged vulnerability data. By means of the vulnerability clustering method, analysis can be more rapidly and accurately carried out on categories from a large amount of vulnerability data, and therefore the security risk faced by the system is evaluated.

The invention relates to an agricultural data interaction method and platform based on multi-source information, and belongs to the technical field of agricultural data processing. Comprising the following steps: processing collected data through a corresponding edge calculation module to generate a dynamic label; analyzing and processing the agricultural information data to obtain a supervision label and corresponding supervision data; all the tags and the corresponding data are imported into a geographic information system, matching is carried out according to the corresponding areas and the respective tags, and meanwhile, the monitoring tags are recognized and updated through a cloud platform computing center. The real-time data is fused and sent to the cloud computing platform through the edge computing module, the interaction prompt is generated through association with the supervision data, so that the real-time performance and the high efficiency of data processing are improved, meanwhile, the monitoring data and the supervision data are associated through the interaction prompt, and the interactivity of visual display is improved.

The invention discloses a CLCC converter multi-source information carrier construction method and system based on a knowledge graph, and the method comprises the steps: obtaining related data of a CLCC converter, and constructing and storing triple information in an entity-attribute-attribute value manner based on the data; constructing a knowledge hierarchical structure of the converter based on the converter equipment entity; constructing a knowledge graph of the converter multi-source information based on knowledge fusion, and establishing knowledge relationship connection and knowledge fusion; dynamic circulation of CLCC transverter transparent information is realized based on a knowledge hierarchical structure of CLCC transverter multi-source information; and carrying out network topology modeling on the knowledge graph of the CLCC converter by using the graph database, and constructing a transparent information carrier of the CLCC converter. According to the method, the problems that the CLCC multi-source operation and maintenance information processing efficiency is low, the fragmentation problem is serious, the data structure, the technical architecture, the construction standard and the construction content are not uniform, and an effective data organization framework is difficult to form are solved.

The invention relates to a wall-climbing robot positioning system and method based on a space structure circular descriptor. A depth image sensor (RGB-D) camera outputs a depth image; collecting three-dimensional point cloud data of three-dimensional space wall surface points; and conformally mapping the contour of the wall-climbing robot to a minimum bounding ball (MBS). A space structure circular descriptor (SSCD) algorithm module maps the three-dimensional point cloud data to a two-dimensional positioning navigation plane, and an SSCD image is formed on the two-dimensional positioning navigation plane; and point cloud features of the SSCD images from the k-1 moment to the k moment are matched, and positioning of the wall-climbing robot on the three-dimensional space wall surface at the current moment is completed. An airborne inertial measurement unit (IMU) measurement module acquires the angular velocity and acceleration of the wall-climbing robot; the attitude information of the wall-climbing robot at the current moment is obtained by carrying out pre-integration on the collected angular velocity and acceleration. Therefore, three-dimensional data are mapped to a two-dimensional plane through a space structure circular descriptor (SSCD) algorithm, and the wall-climbing robot is accurately positioned and navigated.

The invention discloses a file previewing system and method for realizing real-time online previewing of multi-format files, belongs to the technical field of file processing, and aims to solve the technical problem of how to realize online previewing of files on the basis of ensuring file security and user experience. Comprising an application system interface used for receiving a file preview request and forwarding the file preview request to a file stream processor; the file stream processor is used for reading a file stream of a specified file from the server based on the file preview request and sending the file stream to the format identification module; the format identification module is used for carrying out format identification on the file stream read from the server and sending the file stream and the file stream format to the conversion module; the conversion module is used for calling the corresponding parser and renderer to convert the file stream into a file stream in a renderable format based on the file stream format; and the rendering engine is used for rendering the file stream in the renderable format in real time and returning the file preview content to the service system.

The invention discloses a garden landscape simulation method based on a virtual reality technology and three-dimensional visualization, and the method comprises the steps: obtaining the three-dimensional point cloud data of a garden terrain, and generating a three-dimensional grid model; calculating a gradient value of each block grid of the three-dimensional grid model, generating a gradient matrix of the three-dimensional grid model, and clustering the block grids belonging to the same gradient value interval into similar sub-blocks; sorting from small to large based on the terrain slope intervals corresponding to the subblocks of the same type, selecting adaptive plant species according to the illumination conditions of the sorted terrains, and predicting the photosynthetic rate values of the plant species based on a photosynthetic rate prediction model; calculating the number of plants planted in the terrain according to the area of the terrain corresponding to each sub-block and the photosynthetic rate value of the plants in the terrain; and carrying out simulation planting on the three-dimensional grid model, and carrying out garden landscape virtual reality display on the three-dimensional grid model based on a virtual reality technology. According to the method, targeted design can be carried out on different slope areas of the garden landscape.

The invention provides a three-dimensional visual electric power inspection method, and relates to the technical field of electric power equipment inspection, and the method comprises the steps: collecting real-time operation data and historical operation data, building an inspection model, and training the inspection model through the historical operation data, and inputting the real-time operation data into the trained inspection model, and outputting a first inspection result. According to the invention, the inspection model is established by using the deep learning algorithm, and the historical operation data is deeply analyzed and processed through the inspection model, so that the capability of judging the real-time operation data is obtained, and the real-time monitoring and accurate detection of the inspection target are realized.

The invention discloses a drought and flood saline-alkali soil ecological comprehensive improvement method based on an Internet of Things dynamic monitoring technology, which is used in the field of vegetation comprehensive improvement and comprises the following steps: dividing a preset ecological environment area; acquiring soil environment parameters in each area in the ecological environment by using detection equipment, and uploading the encrypted soil environment parameters to a cloud server of a cloud platform; the encrypted soil environment parameters are decrypted and analyzed; deploying an unmanned aerial vehicle for regional patrol; and according to a soil environment parameter evaluation result, an environment change rule and optimization information of equipment layout, combining real-time data of unmanned aerial vehicle patrol, comprehensively analyzing a change trend of a soil environment, and generating a comprehensive improvement plan. According to the method, the soil environment parameter evaluation result, the environment change rule and the equipment layout optimization information are combined, the change trend of the soil environment is obtained, and the soil improvement plan with high pertinence and predictable implementation effect is formulated.

A reservoir bank dangerous rock mass dynamic monitoring and surge prediction method mainly comprises a three-dimensional river scene module, a dangerous rock mass three-dimensional geologic body model module, a dangerous rock mass geological data monitoring module, a dangerous rock mass video dynamic monitoring module, a dangerous rock mass digital twinborn simulation calculation module and a dangerous rock mass collapse early warning module. Wherein the three-dimensional river scene module is used for establishing a digital river scene model by fusing engineering geological information, including river water level change data, flow data, distribution data of residential areas along a river and river sailing ship information, of bank slopes along the river on the basis of three-dimensional topographic data along the bank of the river; the dangerous rock body three-dimensional geologic body model module is used for fusing dangerous rock body engineering geological information into a three-dimensional river scene model to establish a dangerous rock body three-dimensional geologic body model; and the dangerous rock mass video dynamic monitoring module. The method is used for solving the difficult problems that current reservoir bank dangerous rock mass monitoring data is single, and the application effect is insufficient.

The invention discloses an automatic construction system for financial data management, and relates to the related technical field of financial data management, and the system comprises a user interface module which is used for providing an intuitive graphical interface, and enabling a user to construct an application process in a mode of dragging a component; the business logic module is used for calculating the production cost of the product and automatically generating an asset balance sheet, a profit sheet and a cash flow sheet; and the financial trend prediction module needs historical financial data as input, the user inputs financial data and related characteristics, and the model outputs a prediction result. An automatic data processing and report generating system can be rapidly constructed through an automatic tool, the labor burden is relieved, a low-code platform system allows a user to customize and adjust the financial process in a visual mode, the individual requirement can be met without compiling a large number of codes, and the user experience is improved. The LLM technology can provide natural language understanding and intelligent analysis ability, and assists non-professionals in deep financial insight and strategic decision making.

The invention discloses a construction site rescue path planning method and device, electronic equipment and a storage medium, and relates to the technical field of software algorithms. According to the construction site rescue path planning method, construction site information is collected; according to the environment information, the road information and a plurality of preset path algorithms, calculating and obtaining a plurality of alternative rescue paths; determining a target rescue path according to the feature information of each alternative rescue path; and generating a visual model of the target rescue path by adopting a digital twinning technology. According to the method, multiple alternative rescue paths are calculated and obtained through the collected construction site information and multiple preset path algorithms, manual experience judgment is replaced with algorithm calculation when the target rescue path is determined, the visual model of the target rescue path is generated, related personnel are helped to know the scheme content more visually and rapidly, and the rescue efficiency is improved. Therefore, the scientificity, accuracy and efficiency of rescue path planning on the construction site are improved.

The invention provides a reasoning result generation method and device, a computer storage medium and electronic equipment, and relates to the technical field of artificial intelligence. Comprising the steps of obtaining a to-be-reasoned problem, generating a reasoning example set composed of a target number of reasoning examples corresponding to the to-be-reasoned problem, inputting the to-be-reasoned problem and the reasoning example set into a preset large language model, and enabling the large language model to perform reasoning answering on the to-be-reasoned problem based on each reasoning example in the reasoning example set, obtaining a first reasoning result corresponding to the to-be-reasoned problem; based on a large language model, determining a target reasoning problem matched with the first reasoning result; and searching the target reasoning problem through a search engine, and correcting the first reasoning result according to a search result to obtain a corrected second reasoning result. The generation of inaccurate reasoning results of the model can be reduced, and the fact correctness is improved, so that the model performance is improved, the credibility and effectiveness of the application are improved, and the credibility of the user is improved.

An information processing method acquires input data including a current location of an electric moving body, a background map indicating an area around the current location, a location list in which names of a plurality of locations are registered, and possibilities of arrival from the current location to each location included in the location list; changing the display mode of characters representing the name of each place according to the arrival possibility; and outputting, on the basis of the display mode, a superimposed map obtained by superimposing characters indicating the name of each location on the background map.

The invention relates to the technical field of medical information, in particular to a postoperative prediction system for liver transplantation. The system comprises a serum creatinine level monitoring module, a liver protein evaluation module, a liver tumor detection module and a postoperative rehabilitation prediction module, and original health data of a patient after liver transplantation can be obtained through a blood oxygen sensor; preprocessing the original health data of the patient after the liver transplantation to obtain health data of the patient after the liver transplantation; the serum creatinine determination kit is used for performing serum creatinine level extraction on health data after liver transplantation of a patient to obtain serum creatinine level data. According to the method, through a data processing technology, a mode recognition technology and a machine learning technology, comprehensive analysis of rehabilitation indexes after liver transplantation is carried out according to serum creatinine level change trend information, liver protein evaluation data and liver tumor growth information; and comprehensive postoperative index evaluation and analysis are carried out on the patient, so that the accuracy of liver transplantation postoperative rehabilitation prediction is improved.

The invention provides a visual data early warning method and system. The method comprises the steps of S1, data source configuration and access, S2, data preprocessing and cleaning, S3, real-time monitoring and acquisition, S4, early warning rule setting, S5, data analysis and prediction, S6, early warning triggering and notification and S7, visual display and interaction. According to the invention, through the functions of real-time monitoring, prediction analysis, multi-dimensional display, rapid response, decision support and the like, accurate early warning of various risk indexes of an enterprise is realized; the method comprises the steps of determining a corresponding service rule code set by acquiring service data of an application end in real time, calling a corresponding early warning rule operation model according to a set early warning trigger mode, calculating an early warning value according to an early warning rule, and sending the early warning value to a receiving end in a graphical display form when the early warning value meets an early warning trigger condition. And efficient service data early warning trigger analysis and message early warning can be realized.

The invention provides a coal mine disaster fusion monitoring and intelligent decision-making system and method. The system comprises an index obtaining assembly, a reasoning, studying and judging assembly and a man-machine interaction assembly. The method comprises the following steps: carrying out real-time data acquisition on disaster indexes of an internal environment of a coal mine through monitoring equipment, and carrying out data integration on the acquired disaster index data to obtain integrated disaster index data; on the basis of the integrated disaster index data, information reasoning and intelligent study and judgment are applied to speculate the possibility and severity of coal mine disasters, and possible disaster risks are predicted; according to the prediction result, emergency decision making is carried out, and corresponding measures are taken for disaster prevention and control; through a man-machine interaction interface and a visualization technology, monitoring data, a prediction result and a decision scheme are displayed in a graphical mode, so that a decision maker knows a disaster state, the monitoring data and the prediction result and makes an interactive decision. According to the invention, the efficiency and accuracy of coal mine disaster prevention and control are improved.

The invention discloses an in-building emergency rescue system and method based on digital twinning modularization and multi-scale simulation, and the system comprises a parameterization equipment model construction module, a parameterization floor environment simulation module, a data real-time collection and monitoring module, a fault monitoring and fault analysis module, and an emergency rescue path intelligent generation module. And a user interaction interface module. The system adopts a modular design, can be independently deployed and can also be flexibly combined so as to meet the requirements of different building structures, floor environments and elevator brands. Meanwhile, by means of the multi-scale simulation technology of a Unity 3D platform, high-precision simulation and visualization of the operation state of the equipment are achieved, operation and maintenance personnel and rescue personnel can visually and accurately know the operation state of the equipment and the floor environment, a precise and visual virtual environment is provided for emergency rescue, and the safety of emergency rescue is improved. And powerful technical support is provided for development and application of a simulation equipment emergency rescue system.