An emergency command method and system based on AR visualization fusion communication

Abstract

The application relates to the technical field of data visualization, and provides an emergency command method and system based on AR visualization fusion communication. The method comprises the following steps: acquiring basic information of a station, wherein the basic information of the station comprises station facility layout information and station traffic layout information; acquiring facility function information and facility coordinate information according to the station facility layout information; performing sensitive environment assessment according to the facility function information, acquiring sensitive environment state information and sensitive transaction types; performing early warning identification on the facility coordinate information; when the early warning identification result is a trigger state, acquiring a sensitive environment state deviation degree; performing emergency scheduling optimization according to the sensitive environment state deviation degree and the sensitive transaction types, acquiring an emergency scheduling scheme; and performing emergency command. The method can solve the problem that the emergency command efficiency is relatively low due to the complex on-site environment in the station emergency command process, and the efficiency of the emergency command can be improved by combining the visual technology to perform the emergency scheduling optimization.

Description

An emergency command method and system based on AR visualization and fusion communication Technical Field

[0001] This application relates to the field of data visualization technology, specifically to an emergency command method and system based on AR visualization fusion communication. Background Technology

[0002] Data visualization is a technology that transmits data information by encoding data into visual objects such as points, lines, colors, positional relationships, and dynamic effects, and then assembling these objects into graphics. By combining data visualization with technologies such as the Internet of Things (IoT) and 5G, core capabilities for monitoring, command, scheduling, operation, and management can be better leveraged.

[0003] Power plant emergency command refers to the emergency response to major events such as major power grid accidents, natural disasters, and major equipment failures that occur during the operation of power plants. Currently, due to the large number of dangerous facilities and complex situations at power plant emergency command sites, the efficiency of rescue operations, such as dangerous rescue and personnel evacuation, is often low.

[0004] In summary, existing technologies suffer from low emergency command efficiency due to the complex on-site environment during the emergency command process at the site. Summary of the Invention

[0005] Therefore, it is necessary to provide an emergency command method and system based on AR visualization and fusion communication to address the aforementioned technical problems.

[0006] An emergency command method based on AR visualization and fusion communication includes: acquiring basic station information based on an AR digital twin model of a station, wherein the basic station information includes station facility layout information and station traffic layout information; acquiring facility function information and facility coordinate information based on the station facility layout information; conducting a sensitive environment assessment based on the facility function information to acquire sensitive environment status information and sensitive event types; marking the facility coordinate information in the station AR digital twin model with early warning based on the sensitive environment status information and the sensitive event types, and acquiring early warning marking results; acquiring a sensitive environment status deviation when the early warning marking result of the facility coordinate information in the station AR digital twin model is in a triggered state; optimizing emergency dispatch based on the station traffic layout information based on the sensitive environment status deviation and the sensitive event types to acquire an emergency dispatch plan; and conducting emergency command based on the emergency dispatch plan.

[0007] In one embodiment, the method further includes: matching sensitive event record data according to the facility function information and the station facility layout information; performing cluster analysis on the sensitive event record data to obtain sensitive event clustering results, wherein the sensitive event clustering results have a one-to-one correspondence with the sensitive transaction type; storing environmental status record data of the sensitive transaction type in the sensitive event clustering results where the number of sensitive event records is greater than or equal to a number threshold; setting environmental status baseline data according to the facility function information and the station facility layout information; traversing the environmental status record data and performing deviation analysis on the environmental status baseline data to obtain deviation analysis results; classifying the environmental status record data into sensitivity levels according to the deviation analysis results to obtain level classification results; and storing the level classification results and the environmental status record data as the sensitive environmental status information.

[0008] In one embodiment, the method further includes: extracting the level classification result from the sensitive environmental state information, and combining it with the sensitive transaction type to define a pre-set warning level, wherein the pre-set warning level has a one-to-one corresponding warning identifier color and / or warning identifier sound; dividing the warning identifier area in the station AR digital twin model according to the facility coordinate information; and identifying the warning identifier area in the station AR digital twin model according to the warning identifier color and / or the warning identifier sound, and to obtain the warning identifier result.

[0009] In one embodiment, the method further includes: optimizing the evacuation plan based on the warning sign area and the station traffic layout information, and obtaining the evacuation plan optimization result; optimizing the rescue plan based on the warning sign area and the station traffic layout information, and obtaining the rescue plan optimization result; and adding the evacuation plan optimization result and the rescue plan optimization result into the emergency dispatch plan.

[0010] In one embodiment, the method further includes: obtaining evacuation route layout information based on the station traffic layout information, wherein the evacuation route layout information includes evacuation route entrance coordinate information and route evacuation coefficient; inputting the route evacuation coefficient into an evacuation flow assessment model and outputting an evacuation flow assessment result; extracting the number of people to be evacuated based on the station AR digital twin model according to the warning sign area; sorting the evacuation route entrance coordinate information from near to far according to the warning sign area and obtaining an evacuation route entrance sorting result; allocating evacuation scheduling tasks according to the evacuation flow assessment result and the number of people to be evacuated, based on the evacuation route entrance sorting result, and obtaining the evacuation plan optimization result.

[0011] In one embodiment, the method further includes: acquiring communication feedback information, wherein the communication feedback information includes coordinate information of dispatchable rescue stations, information on dispatchable supplies, and information on dispatchable personnel; sorting the coordinate information of dispatchable rescue stations from near to far according to the warning identification area, and acquiring a sorting result for dispatchable rescue stations; matching preset rescue supply information and preset personnel information according to the sensitive transaction type and the deviation degree of the sensitive environmental state; and allocating rescue tasks by traversing the dispatchable supply information and the preset personnel information in the sorting result of dispatchable rescue stations, and acquiring the optimization result of the rescue plan.

[0012] In one embodiment, the method further includes: recording emergency dispatch status information when emergency dispatch is carried out according to the emergency dispatch plan; performing an emergency command quality score on the emergency dispatch status information to obtain a command quality score result; and storing the emergency dispatch plan and the early warning identification result together when the command quality score result is greater than or equal to the quality score threshold.

[0013] An emergency command system based on AR visualization and fusion communication includes:

[0014] The station basic information acquisition module is used to acquire station basic information based on the station AR digital twin model, wherein the station basic information includes station facility layout information and station traffic layout information.

[0015] A facility information acquisition module is used to acquire facility function information and facility coordinate information based on the site facility layout information;

[0016] A sensitive environment assessment module is used to conduct a sensitive environment assessment based on the facility function information, and to obtain sensitive environment status information and sensitive transaction types.

[0017] The early warning identification module is used to identify the facility coordinate information in the AR digital twin model of the site according to the sensitive environmental status information and the sensitive transaction type, and obtain the early warning identification result;

[0018] A sensitive environment state deviation acquisition module is used to acquire the sensitive environment state deviation when the early warning identification result of the facility coordinate information of the AR digital twin model of the site is in a triggered state.

[0019] An emergency dispatch optimization module is used to optimize emergency dispatch based on the station traffic layout information according to the deviation of the sensitive environment state and the type of sensitive transaction, and to obtain an emergency dispatch plan.

[0020] An emergency command module is used to conduct emergency command according to the emergency dispatch plan.

[0021] The aforementioned emergency command method and system based on AR visualization and fusion communication can solve the problem of low emergency command efficiency caused by complex on-site environments during emergency command at stations. First, based on the station's AR digital twin model, basic station information is acquired, including station facility layout information and station traffic layout information. Then, facility function information and facility coordinate information are acquired. Sensitive environment assessment is performed based on the facility function information to obtain sensitive environment status information and sensitive event types. This sensitive environment assessment provides support for the next step of early warning identification. Then, based on the sensitive environment status information and the sensitive event types, early warning identification is performed on the facility coordinate information in the station's AR digital twin model, and early warning identification results are obtained. When the early warning identification result of the facility coordinate information in the station's AR digital twin model is in a triggered state, the sensitive environment status deviation is obtained. Based on the sensitive environment status deviation and the sensitive event types, emergency dispatch optimization is performed based on the station traffic layout information to obtain an emergency dispatch plan. Finally, emergency command is performed based on the emergency dispatch plan, which can improve the efficiency of emergency command.

[0022] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0023] Figure 1 is a flowchart illustrating an emergency command method based on AR visualization and fusion communication provided in this application;

[0024] Figure 2 is a flowchart illustrating the process of sensitive environment assessment in an emergency command method based on AR visualization and fused communication provided in this application;

[0025] Figure 3 is a flowchart illustrating the process of obtaining early warning identifier results in an emergency command method based on AR visualization fusion communication provided in this application;

[0026] Figure 4 is a schematic diagram of the structure of an emergency command system based on AR visualization and fusion communication provided in this application.

[0027] Explanation of reference numerals in the attached diagrams: Module 1: Basic Information Acquisition for the Site; Module 2: Facility Information Acquisition; Module 3: Sensitive Environment Assessment; Module 4: Early Warning Identification; Module 5: Sensitive Environment Status Deviation Acquisition; Module 6: Emergency Dispatch Optimization; Module 7: Emergency Command. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0029] As shown in Figure 1, this application provides an emergency command method based on AR visualization and fusion communication, including:

[0030] Step S100: Obtain basic information about the station based on the station's AR digital twin model, wherein the basic information about the station includes station facility layout information and station traffic layout information;

[0031] Step S200: Based on the site facility layout information, obtain facility function information and facility coordinate information;

[0032] Specifically, an AR digital twin model of the power plant is constructed. The power plant refers to various types of power plants, such as thermal power, gas turbine, wind power, and photovoltaic power. This AR digital twin model is based on computer graphics and artificial intelligence, using a digital twin system to dynamically simulate and recreate the power plant information, achieving a three-dimensional visual representation of the scene. Basic information about the power plant is acquired, including facility layout information and traffic layout information. The facility layout information includes facility type, function, location coordinates, and operating parameters. The traffic layout information includes safety passage information, vehicle route information, and fire lane information.

[0033] Data extraction was performed on the layout information of the site facilities to obtain facility function information and facility coordinate information. The facility function information includes facility type and function, such as gas turbine, boiler body, thermal system, and auxiliary equipment. The facility coordinate information refers to the specific location coordinates of the facilities within the site. Obtaining the facility function information and facility coordinate information provides data support for the next step of sensitive environment analysis.

[0034] Step S300: Conduct a sensitive environment assessment based on the facility function information to obtain sensitive environment status information and sensitive transaction types;

[0035] As shown in Figure 2, in one embodiment, step S300 of this application further includes:

[0036] Step S310: Match sensitive event record data based on the facility function information and the station facility layout information;

[0037] Step S320: Perform cluster analysis on the sensitive event record data to obtain sensitive event clustering results, wherein the sensitive event clustering results have a one-to-one correspondence with the sensitive transaction type;

[0038] Step S330: Store the environmental status record data of the sensitive transaction type in the sensitive event clustering results where the number of sensitive event records is greater than or equal to the number threshold;

[0039] Step S340: Based on the facility function information and the station facility layout information, set the environmental status baseline data;

[0040] Step S350: Traverse the environmental state record data and the environmental state baseline data to perform deviation analysis and obtain the deviation analysis results;

[0041] Step S360: Based on the deviation analysis results, classify the environmental state record data into sensitivity levels and obtain the level classification results;

[0042] Step S370: Store the level classification results and the environmental status record data as the sensitive environmental status information.

[0043] Specifically, based on the facility function information and the site facility layout information, sensitive event record data is obtained. These sensitive events include major hazardous accidents such as fires, extreme weather, natural disasters, major hazardous operations, and major equipment failures. Cluster analysis is performed on the sensitive event record data. This cluster analysis refers to classifying and dividing the sensitive event record data according to the type of sensitive event, obtaining sensitive event clustering results. These results include sensitive event type, sensitive event cause, number of sensitive events, and losses caused by the sensitive events. A one-to-one correspondence exists between the sensitive event clustering results and the sensitive event type.

[0044] The number of sensitive event records in the clustering results of the sensitive events is extracted, and a threshold for the number of sensitive events is preset. This threshold can be customized by those skilled in the art based on actual conditions. When the number of sensitive event records is greater than or equal to the threshold, environmental status record data for the sensitive event type is stored. The environmental status includes information such as temperature, humidity, and equipment operating parameters. Based on the facility function information and the site facility layout information, environmental status baseline data is set. This baseline data refers to the environmental status that ensures the safe operation of the facility and the area where the facility is located. The environmental status record data and the environmental status baseline data are traversed and compared, and deviation analysis is performed to obtain the deviation analysis result. This result refers to the deviation between the environmental status record data and the environmental status baseline data.

[0045] A preset sensitivity level classification rule is established, which can be customized by those skilled in the art according to actual conditions. For example, if the deviation analysis result is less than or equal to 10%, the sensitivity level is Level 1; if the deviation analysis result is greater than 10% but less than or equal to 20%, the sensitivity level is Level 2. The environmental status record data is classified into sensitivity levels based on the deviation analysis result to obtain the level classification result. The level classification result and the environmental status record data are stored as sensitive environmental status information. Obtaining this sensitive environmental status information provides support for the next step of issuing early warning labels for facilities within the site.

[0046] Step S400: Based on the sensitive environmental status information and the sensitive transaction type, mark the facility coordinate information in the AR digital twin model of the site with an early warning, and obtain the early warning mark result;

[0047] As shown in Figure 3, in one embodiment, step S400 of this application further includes:

[0048] Step S410: Extract the level classification result from the sensitive environment status information, and in combination with the sensitive transaction type, mark the warning preset level, wherein the warning preset level has a one-to-one corresponding warning indicator color and / or warning indicator sound;

[0049] Step S420: Based on the facility coordinate information, divide the early warning identification area in the AR digital twin model of the site;

[0050] Step S430: Based on the warning sign color and / or the warning sign sound, and the warning sign area, mark the warning sign in the station AR digital twin model to obtain the warning sign result.

[0051] Specifically, a pre-set warning level is determined based on the classification results and the sensitive event type. The pre-set warning level and the warning indicator color or sound have a one-to-one correspondence. The warning indicator color or sound can be customized by those skilled in the art. For example, when the sensitive event type is a fire, the warning indicator color can be set to red, with light red for level one fires, red for level two, and dark red for level three, etc. The facility coordinate information is input into the station's AR digital twin model, and warning indicator areas are divided based on the facility coordinate information. Finally, the warning indicator color and / or the warning indicator sound are input into the station's AR digital twin model to identify the warning indicator areas, obtaining the warning indicator results. By obtaining the warning indicator results, the sensitive event type and corresponding warning level can be displayed intuitively, improving the efficiency and accuracy of sensitive event identification.

[0052] Step S500: When the early warning identification result of the facility coordinate information of the AR digital twin model of the site is in the triggered state, obtain the sensitive environment state deviation degree;

[0053] Specifically, based on the AR digital twin model of the site, when the warning sign result in the facility coordinate information is in a triggered state, the deviation degree of the sensitive environment state is obtained according to the color or sound of the warning sign. By obtaining the deviation degree of the sensitive environment state, the severity of the sensitive event can be intuitively understood.

[0054] Step S600: Based on the deviation of the sensitive environment state and the type of sensitive transaction, optimize emergency dispatch according to the station traffic layout information to obtain an emergency dispatch plan;

[0055] In one embodiment, step S600 of this application further includes:

[0056] Step S610: Optimize the evacuation plan based on the warning sign area and the station traffic layout information, and obtain the evacuation plan optimization results;

[0057] In one embodiment, step S610 of this application further includes:

[0058] Step S611: Based on the station traffic layout information, obtain evacuation route layout information, wherein the evacuation route layout information includes evacuation route entrance coordinate information and route evacuation coefficient;

[0059] Step S612: Input the channel evacuation coefficient into the evacuation flow assessment model and output the evacuation flow assessment result;

[0060] Step S613: Based on the warning sign area and the station AR digital twin model, extract the number of people to be evacuated;

[0061] Step S614: Sort the coordinate information of the evacuation route entrances from near to far according to the warning sign area, and obtain the evacuation route entrance sorting result;

[0062] Step S615: Based on the evacuation flow assessment results and the information on the number of people to be evacuated, allocate evacuation scheduling tasks according to the evacuation channel entrance sorting results, and obtain the evacuation plan optimization results.

[0063] Specifically, evacuation route layout information is obtained based on the station traffic layout information. This evacuation route layout information includes the coordinates of the evacuation route entrances and an evacuation coefficient. The evacuation coefficient represents the capacity of the evacuation route to evacuate people and is determined by the width and height of the evacuation route; the greater the width and height of the evacuation route, the greater the evacuation coefficient. By setting the evacuation coefficient, the evacuation capacity of the evacuation route can be intuitively represented.

[0064] Historical pedestrian flow data and corresponding evacuation route coefficients are obtained for multiple evacuation routes. A sample dataset is constructed based on these data. An evacuation flow assessment model is built using a backpropagation (BP) neural network. This model is a machine learning-based neural network model capable of iterative optimization. It is obtained through supervised training using a training dataset. The sample dataset is divided according to a preset data partitioning rule to obtain a training set and a validation set. Data from the sample dataset is input into the evacuation flow assessment model for supervised training. When the model output converges, data from the validation set is input into the model for validation. A preset accuracy index is used, which can be customized based on actual conditions, for example, 95%. When the model output accuracy is greater than or equal to the preset accuracy index, the evacuation flow assessment model is obtained. By constructing this evacuation flow assessment model, the accuracy and efficiency of evacuation flow data acquisition can be improved.

[0065] The evacuation coefficient of the passage is input into the evacuation flow assessment model to obtain the evacuation flow assessment result. Based on the station's AR digital twin model, the information on the number of people to be evacuated in the warning sign area is extracted to obtain evacuation personnel information. The coordinates of the evacuation passage entrances are sorted from nearest to farthest according to the location coordinates of the warning sign area to obtain the evacuation passage entrance sorting result. The evacuation flow is determined based on the number of people to be evacuated, and the evacuation passages corresponding to the evacuation flow assessment result are filtered according to the evacuation flow to obtain multiple evacuation passages that meet the evacuation flow requirements. Finally, the evacuation passage closest to the warning sign area is selected first among the multiple evacuation passages to evacuate the crowd, which is the optimized evacuation plan result. By obtaining the optimized evacuation plan result, the efficiency of personnel evacuation can be improved.

[0066] Step S620: Optimize the rescue plan based on the warning sign area and the station traffic layout information, and obtain the rescue plan optimization result;

[0067] In one embodiment, step S620 of this application further includes:

[0068] Step S621: Obtain communication feedback information, wherein the communication feedback information includes coordinate information of dispatchable rescue stations, information of dispatchable materials, and information of dispatchable personnel;

[0069] Step S622: Sort the coordinate information of the dispatchable rescue stations from near to far according to the warning identification area, and obtain the sorting result of the dispatchable rescue stations;

[0070] Step S623: Match the pre-set rescue material information and pre-set personnel information according to the sensitive transaction type and the deviation degree of the sensitive environment state;

[0071] Step S624: Based on the pre-set rescue material information and the pre-set personnel information, traverse the dispatchable material information and dispatchable personnel information in the sorting results of the dispatch rescue stations to allocate rescue tasks and obtain the optimization results of the rescue plan.

[0072] Step S630: Add the optimization results of the evacuation plan and the optimization results of the rescue plan into the emergency dispatch plan.

[0073] Specifically, communication feedback information is obtained, including coordinates of dispatchable rescue stations, dispatchable supplies, and dispatchable personnel. The coordinates of the dispatchable rescue stations are sorted from nearest to farthest based on the location coordinates of the warning area, resulting in a sorting result. A rescue expert system is constructed, which is an emergency rescue expert database combining artificial intelligence and a database. This database stores a large number of sensitive transaction types and corresponding emergency rescue plans, and can be continuously updated through learning. The deviation of sensitive transaction types and sensitive environmental states is input into the rescue expert system for supply matching, including pre-set rescue supply information and pre-set personnel information. The sorting result of the dispatchable rescue stations is filtered based on the pre-set rescue supply information and pre-set personnel information to obtain the nearest dispatchable rescue station that meets the pre-set rescue supply information and pre-set personnel information. This dispatchable rescue station is then added to the rescue plan optimization results. Finally, the evacuation plan optimization results and the rescue plan optimization results are added to the emergency dispatch plan. Obtaining this emergency dispatch plan provides support for the next step of emergency command.

[0074] Step S700: Conduct emergency command according to the emergency dispatch plan.

[0075] In one embodiment, step S700 of this application further includes:

[0076] Step S710: When emergency dispatch is carried out according to the emergency dispatch plan, record the emergency dispatch status information;

[0077] Step S720: Perform an emergency command quality score on the emergency dispatch status information and obtain the command quality score result;

[0078] Step S730: When the command quality score result is greater than or equal to the quality score threshold, the emergency dispatch plan and the early warning identification result are associated and stored.

[0079] Specifically, when a sensitive event occurs, emergency command is conducted according to the aforementioned emergency dispatch plan, and emergency dispatch status information is recorded. This emergency dispatch status information includes personnel safety information, personnel evacuation information, equipment damage information, and actual handling time. The emergency command process is divided according to the emergency dispatch plan; for example, personnel safety information and personnel evacuation information can be grouped into personnel information. The emergency dispatch status information is then scored according to the emergency command process, resulting in multiple quality scores. Preset weight ratios for each emergency stage are used, which can be customized based on actual conditions. The command quality score is obtained by multiplying the multiple quality scores by their corresponding weight ratios and summing the results. A preset quality score threshold is also used, which can be customized by those skilled in the art based on actual conditions. When the command quality score is greater than or equal to the quality score threshold, the emergency dispatch plan and the early warning indicator result are stored together. By storing the emergency dispatch plan and the early warning indicator result together, the emergency dispatch plan can be directly invoked when a similar sensitive event occurs again, further improving the efficiency of emergency command. The above methods address the problem of low emergency command efficiency caused by complex on-site environments during the emergency command process at the station. By combining visualization technology for emergency dispatch optimization, the efficiency of emergency command can be improved.

[0080] In one embodiment, as shown in Figure 4, an emergency command system based on AR visualization and fusion communication is provided, including: a basic information acquisition module 1 for the site, a facility information acquisition module 2, a sensitive environment assessment module 3, an early warning sign module 4, a sensitive environment status deviation acquisition module 5, an emergency dispatch optimization module 6, and an emergency command module 7, wherein:

[0081] Terminal Basic Information Acquisition Module 1 is used to acquire terminal basic information based on the terminal AR digital twin model, wherein the terminal basic information includes terminal facility layout information and terminal traffic layout information;

[0082] Facility information acquisition module 2, which is used to acquire facility function information and facility coordinate information based on the site facility layout information;

[0083] Sensitive environment assessment module 3 is used to conduct sensitive environment assessment based on the facility function information, and to obtain sensitive environment status information and sensitive transaction types.

[0084] Early warning identification module 4 is used to identify the facility coordinate information in the AR digital twin model of the site according to the sensitive environmental status information and the sensitive transaction type, and obtain the early warning identification result;

[0085] Sensitive environment state deviation acquisition module 5, the sensitive environment state deviation acquisition module 5 is used to acquire the sensitive environment state deviation when the early warning identification result of the facility coordinate information of the AR digital twin model of the site is in the triggered state;

[0086] Emergency dispatch optimization module 6 is used to optimize emergency dispatch based on the station traffic layout information according to the deviation of the sensitive environment state and the type of sensitive transaction, and to obtain an emergency dispatch plan.

[0087] Emergency command module 7 is used to conduct emergency command according to the emergency dispatch plan.

[0088] In one embodiment, the system further includes:

[0089] A sensitive event record data matching module is used to match sensitive event record data based on the facility function information and the site facility layout information;

[0090] A clustering analysis module is used to perform clustering analysis on the sensitive event record data to obtain sensitive event clustering results, wherein the sensitive event clustering results have a one-to-one correspondence with the sensitive transaction type;

[0091] An environmental status record data storage module is used to store environmental status record data of the sensitive transaction type in the sensitive event clustering results where the number of sensitive event records is greater than or equal to a number threshold.

[0092] An environmental status baseline data setting module is used to set environmental status baseline data based on the facility function information and the site facility layout information.

[0093] A deviation analysis module is used to traverse the environmental state record data and the environmental state baseline data to perform deviation analysis and obtain the deviation analysis results.

[0094] A sensitivity level classification module is used to classify the environmental state record data into sensitivity levels based on the deviation analysis results, and obtain the classification results.

[0095] A sensitive environment state information acquisition module is used to store the level classification result and the environmental state record data as the sensitive environment state information.

[0096] In one embodiment, the system further includes:

[0097] A pre-set warning level calibration module is used to extract the level division result from the sensitive environment state information, and calibrate the pre-set warning level in combination with the sensitive transaction type. The pre-set warning level has a one-to-one corresponding warning indicator color and / or warning indicator sound.

[0098] A warning sign area division module is used to divide the warning sign area in the AR digital twin model of the station according to the facility coordinate information.

[0099] The warning sign result acquisition module is used to identify the warning sign result in the AR digital twin model of the station based on the warning sign color and / or the warning sign sound and the warning sign area.

[0100] In one embodiment, the system further includes:

[0101] The evacuation plan optimization result acquisition module is used to optimize the evacuation plan based on the warning sign area and the station traffic layout information, and obtain the evacuation plan optimization result.

[0102] The rescue plan optimization result acquisition module is used to optimize the rescue plan based on the warning sign area and the station traffic layout information, and to acquire the rescue plan optimization result.

[0103] An optimization result addition module is used to add the optimization results of the evacuation plan and the optimization results of the rescue plan into the emergency dispatch plan.

[0104] In one embodiment, the system further includes:

[0105] An evacuation route layout information acquisition module is used to acquire evacuation route layout information based on the station traffic layout information, wherein the evacuation route layout information includes evacuation route entrance coordinate information and route evacuation coefficient.

[0106] An evacuation flow assessment result output module is used to input the channel evacuation coefficient into the evacuation flow assessment model and output the evacuation flow assessment result.

[0107] The module for extracting information on the number of people to be evacuated is used to extract information on the number of people to be evacuated based on the warning sign area and the AR digital twin model of the station.

[0108] The evacuation route entrance sorting result acquisition module is used to sort the coordinate information of the evacuation route entrances from near to far according to the warning sign area, and acquire the evacuation route entrance sorting result.

[0109] The evacuation plan optimization result acquisition module is used to allocate evacuation scheduling tasks according to the evacuation flow assessment result and the number of people to be evacuated, and to acquire the evacuation plan optimization result.

[0110] In one embodiment, the system further includes:

[0111] A communication feedback information acquisition module is used to acquire communication feedback information, wherein the communication feedback information includes coordinate information of dispatchable rescue stations, information of dispatchable materials, and information of dispatchable personnel;

[0112] The dispatch and rescue station sorting result acquisition module is used to sort the coordinate information of the dispatchable rescue stations from near to far according to the warning sign area, and acquire the dispatch and rescue station sorting result.

[0113] A pre-set information matching module is used to match pre-set rescue material information and pre-set personnel information based on the sensitive transaction type and the deviation degree of the sensitive environmental state.

[0114] The rescue plan optimization result acquisition module is used to allocate rescue tasks by traversing the dispatchable material information and dispatchable personnel information in the sorting result of the dispatch rescue station based on the preset rescue material information and the preset personnel information, and to obtain the rescue plan optimization result.

[0115] In one embodiment, the system further includes:

[0116] An emergency dispatch status information recording module is used to record emergency dispatch status information when emergency dispatch is carried out according to the emergency dispatch plan.

[0117] The command quality scoring result acquisition module is used to score the emergency command quality of the emergency dispatch status information and acquire the command quality scoring result.

[0118] An associated storage module is used to associate and store the emergency dispatch plan and the early warning indicator result when the command quality score result is greater than or equal to the quality score threshold.

[0119] In summary, this application provides an emergency command method and system based on AR visualization and fusion communication, which has the following technical effects:

[0120] 1. This addresses the problem of low emergency command efficiency caused by complex on-site environments during emergency command at the site. By combining visualization technology with emergency dispatch optimization, the efficiency of emergency command can be improved.

[0121] 2. By obtaining the early warning identification results, the sensitive transaction type and corresponding early warning level can be displayed intuitively, which can improve the efficiency and accuracy of sensitive event identification.

[0122] 3. By linking and storing emergency dispatch plans and early warning results, the emergency dispatch plans can be directly invoked when similar sensitive events occur again, which can further improve the efficiency of emergency command.

[0123] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0124] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. An emergency command method based on AR visualization and fusion communication, characterized in that, include: Based on the AR digital twin model of the station, basic station information is obtained, including station facility layout information and station traffic layout information. Based on the station facility layout information, facility function information and facility coordinate information are obtained. Based on the facility function information, a sensitive environment assessment is performed to obtain sensitive environment status information and sensitive event types. Based on the sensitive environment status information and the sensitive event types, early warning labels are applied to the facility coordinate information in the station's AR digital twin model, and early warning label results are obtained. When the early warning label result of the facility coordinate information in the station's AR digital twin model is triggered, the sensitive environment status deviation is obtained. Based on the sensitive environment status deviation and the sensitive event types, emergency dispatch optimization is performed based on the station traffic layout information to obtain an emergency dispatch plan. Emergency command is performed based on the emergency dispatch plan. The step of optimizing emergency dispatch based on the sensitive environment status deviation and the sensitive event types, and obtaining the emergency dispatch plan, includes: based on the early warning label area and the station... The process involves optimizing evacuation plans based on traffic layout information to obtain optimization results; optimizing rescue plans based on the warning sign area and the station traffic layout information to obtain optimization results; adding the optimization results of the evacuation plans and the optimization results of the rescue plans to the emergency dispatch plan; the optimization of evacuation plans based on the warning sign area and the station traffic layout information to obtain optimization results includes: obtaining evacuation channel layout information based on the station traffic layout information, wherein the evacuation channel layout information includes evacuation channel entrance coordinate information and channel evacuation coefficient; inputting the channel evacuation coefficient into the evacuation flow assessment model and outputting the evacuation flow assessment result; extracting the number of people to be evacuated based on the warning sign area and the station AR digital twin model; sorting the evacuation channel entrance coordinate information from near to far based on the warning sign area to obtain the evacuation channel entrance sorting result; and allocating evacuation dispatch tasks according to the evacuation flow assessment result and the number of people to be evacuated based on the evacuation channel entrance sorting result to obtain the evacuation plan optimization result.

2. The method as described in claim 1, characterized in that, The process of conducting a sensitive environment assessment based on the facility function information to obtain sensitive environment status information and sensitive event types includes: matching sensitive event record data with the facility function information and the site facility layout information; performing cluster analysis on the sensitive event record data to obtain sensitive event clustering results, wherein the sensitive event clustering results have a one-to-one correspondence with the sensitive event types; storing environmental status record data of the sensitive event types in the sensitive event clustering results where the number of sensitive event records is greater than or equal to a certain threshold; setting environmental status baseline data based on the facility function information and the site facility layout information; performing deviation analysis on the environmental status record data and the environmental status baseline data to obtain deviation analysis results; classifying the environmental status record data into sensitivity levels based on the deviation analysis results to obtain level classification results; and storing the level classification results and the environmental status record data as the sensitive environment status information.

3. The method as described in claim 2, characterized in that, The step of marking the facility coordinate information with a warning label in the AR digital twin model of the station based on the sensitive environmental status information and the sensitive transaction type, and obtaining the warning label result, includes: extracting the level division result from the sensitive environmental status information, and, in combination with the sensitive transaction type, marking a preset warning level, wherein the preset warning level has a one-to-one corresponding warning label color and / or warning label sound; dividing the warning label area in the AR digital twin model of the station based on the facility coordinate information; and marking the warning label area in the AR digital twin model of the station based on the warning label color and / or the warning label sound, and obtaining the warning label result.

4. The method as described in claim 1, characterized in that, The step of optimizing the rescue plan based on the warning sign area and the station traffic layout information, and obtaining the rescue plan optimization result, includes: obtaining communication feedback information, wherein the communication feedback information includes coordinate information of dispatchable rescue stations, dispatchable material information, and dispatchable personnel information; sorting the coordinate information of dispatchable rescue stations from near to far according to the warning sign area, and obtaining the dispatchable rescue station sorting result; matching pre-set rescue material information and pre-set personnel information according to the sensitive transaction type and the sensitive environmental state deviation; and allocating rescue tasks by traversing the dispatchable material information and dispatchable personnel information of the dispatchable rescue station sorting result according to the pre-set rescue material information and pre-set personnel information, and obtaining the rescue plan optimization result.

5. The method as described in claim 1, characterized in that, include: When emergency dispatch is carried out according to the emergency dispatch plan, the emergency dispatch status information is recorded; the emergency dispatch status information is scored for emergency command quality, and the command quality score result is obtained; when the command quality score result is greater than or equal to the quality score threshold, the emergency dispatch plan and the early warning indicator result are associated and stored.

6. An emergency command system based on AR visualization and fusion communication, characterized in that, include: The system includes: a station basic information acquisition module, used to acquire basic station information based on the station's AR digital twin model, including station facility layout information and station traffic layout information; a facility information acquisition module, used to acquire facility function information and facility coordinate information based on the station facility layout information; a sensitive environment assessment module, used to conduct a sensitive environment assessment based on the facility function information, acquiring sensitive environment status information and sensitive event types; and a warning identification module, used to identify sensitive environment status information and sensitive event types based on the sensitive event type in the station's AR digital twin model. The twin model assigns early warning labels to the facility coordinate information and obtains the early warning label results; a sensitive environment state deviation acquisition module is used to acquire the sensitive environment state deviation when the early warning label result of the facility coordinate information in the AR digital twin model of the station is in a triggered state; an emergency dispatch optimization module is used to optimize emergency dispatch based on the sensitive environment state deviation and the sensitive transaction type, based on the station traffic layout information, and obtain an emergency dispatch plan; an emergency command module is used to conduct emergency command according to the emergency dispatch plan; and an evacuation plan optimization result acquisition module... The evacuation plan optimization result acquisition module is used to optimize the evacuation plan based on the warning sign area and the station traffic layout information, and obtain the evacuation plan optimization result; the rescue plan optimization result acquisition module is used to optimize the rescue plan based on the warning sign area and the station traffic layout information, and obtain the rescue plan optimization result; the optimization result adding module is used to add the evacuation plan optimization result and the rescue plan optimization result into the emergency dispatch plan; the evacuation route layout information acquisition module is used to obtain evacuation route layout information based on the station traffic layout information. The evacuation route layout information includes evacuation route entrance coordinate information and route evacuation coefficient; an evacuation flow assessment result output module, which inputs the route evacuation coefficient into the evacuation flow assessment model and outputs the evacuation flow assessment result; a person to be evacuated information extraction module, which extracts the person to be evacuated information based on the warning sign area and the station AR digital twin model; and an evacuation route entrance sorting result acquisition module, which sorts the evacuation route entrance coordinate information from near to far based on the warning sign area and obtains the evacuation route entrance sorting result.The evacuation plan optimization result acquisition module is used to allocate evacuation scheduling tasks according to the evacuation flow assessment result and the number of people to be evacuated, based on the evacuation channel entrance sorting result, and to acquire the evacuation plan optimization result.

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