A data processing method and system for emergency rescue skills simulation

Abstract

This invention provides a data processing method and system for emergency rescue skills simulation, relating to the field of simulation technology. It constructs an emergency rescue scenario information database and retrieves target emergency rescue scenario information, performs 3D scene modeling to construct a virtual emergency rescue scenario, embeds a multi-dimensional emergency rescue training module within the virtual emergency rescue scenario, generates a dynamic simulation space, obtains adaptive emergency rescue plans for simulation training in the dynamic simulation space, acquires real-time simulation information for comprehensive evaluation, and adjusts and controls the emergency rescue simulation based on the evaluation results. This addresses the technical problems of existing technologies where emergency rescue plans are mainly adapted based on the experience of rescuers to suit different rescue scenarios, resulting in subjective factors, inability to complete independently when lacking experience, and too many uncontrollable factors. By conducting rescue simulation training, the plan is simultaneously optimized as the rescue unfolds, improving the scenario fit of the rescue plan and its broad adaptability, effectively ensuring rescue results.

Description

Technical Field

[0001] This invention relates to the field of simulation technology, specifically to a data processing method and system for simulating first aid skills. Background Technology

[0002] In real life, we inevitably encounter various sudden illnesses or accidents. In such cases, comprehensive first aid measures are tantamount to a race against time. At the same time, if there are deviations in the first aid process or the first aid plan is not suitable, it may cause irreversible consequences. First aid plans vary in different scenarios, and the external environment will also have a certain impact on the first aid process. Accurate judgment and operation are the key to the success of first aid. At present, there are corresponding first aid plans for different first aid directions. However, due to the universality of the plans, if the first aid process cannot be adapted to the real-time situation, it will have a certain impact on the subsequent first aid effect.

[0003] In existing technologies, emergency rescue operations mainly rely on the experience of rescuers to adapt rescue plans to different rescue scenarios. This involves a certain degree of subjectivity, and those with insufficient experience cannot complete the operation independently, resulting in too many uncontrollable factors. Summary of the Invention

[0004] This application provides a data processing method and system for simulating first aid skills, which addresses the technical problems in the prior art where first aid operations mainly rely on the experience of rescuers to adapt rescue plans to different rescue scenarios, which involves a certain degree of subjectivity, and the inability to complete the task independently when lacking experience, as well as too many uncontrollable factors.

[0005] In view of the above problems, this application provides a data processing method and system for simulating first aid skills.

[0006] In a first aspect, this application provides a data processing method for simulating first aid skills. The method includes: constructing a first aid scenario information database; retrieving target first aid scenario information based on the database; constructing a virtual first aid scenario by performing three-dimensional scene modeling based on the target first aid scenario information; constructing a multi-dimensional first aid training module; embedding the multi-dimensional first aid training module into the virtual first aid scenario to generate a dynamic simulation space; interacting with a first aid information system to obtain an adaptive first aid plan; performing simulation training in the dynamic simulation space based on the adaptive first aid plan to obtain real-time simulation information; comprehensively evaluating the real-time simulation information; adjusting and controlling the first aid simulation based on the evaluation results; and determining and storing the scenario first aid plan in the system.

[0007] Secondly, this application provides a data processing system for simulating first aid skills. The system includes: a scene information acquisition module for constructing a first aid scene information database and retrieving target first aid scene information based on the database; a simulated scene construction module for constructing a virtual first aid scene based on the target first aid scene information through three-dimensional scene modeling; a training module construction module for constructing a multi-dimensional first aid training module; a simulated space generation module for embedding the multi-dimensional first aid training module into the virtual first aid scene to generate a dynamic simulated space; a solution acquisition module for interacting with a first aid information system to acquire an adaptive first aid solution; an information acquisition module for performing simulated training in the dynamic simulated space based on the adaptive first aid solution to acquire real-time simulation information; and an adjustment control module for comprehensively evaluating the real-time simulation information, adjusting and controlling the first aid simulation based on the evaluation results, and determining the scene first aid solution for system storage.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] This application provides a data processing method for emergency rescue skills simulation. It constructs an emergency rescue scenario information database, retrieves target emergency rescue scenario information from the database, performs 3D scene modeling to construct a virtual emergency rescue scenario, embeds a multi-dimensional emergency rescue training module within the virtual emergency rescue scenario, generates a dynamic simulation space, interacts with an emergency rescue information system to obtain adaptive emergency rescue plans, performs simulation training in the dynamic simulation space, and obtains real-time simulation information. The real-time simulation information is comprehensively evaluated, and adjustments and controls are made to the emergency rescue simulation based on the evaluation results. The scenario-based emergency rescue plan is then stored in the system. This method addresses the technical problems in existing technologies where emergency rescue operations rely primarily on the experience of rescuers to adapt to different rescue scenarios, resulting in subjective factors, inability to complete tasks independently due to insufficient experience, and excessive uncontrollable factors. By conducting rescue simulation training, the method synchronously optimizes the plan as the rescue unfolds, improving the scenario fit of the rescue plan and increasing its adaptability, thus effectively ensuring the rescue outcome. Attached Figure Description

[0010] Figure 1 This application provides a schematic flowchart of a data processing method for simulating first aid skills;

[0011] Figure 2 This application provides a schematic diagram of the target emergency rescue scenario information retrieval process in a data processing method for emergency rescue skills simulation;

[0012] Figure 3 This application provides a schematic diagram of the adaptive first aid scheme acquisition process in a data processing method for first aid skills simulation;

[0013] Figure 4 This application provides a schematic diagram of a data processing system for simulating first aid skills.

[0014] Figure labeling: Scene information acquisition module 11, simulated scene construction module 12, training module construction module 13, simulated space generation module 14, scheme acquisition module 15, information acquisition module 16, adjustment and control module 17. Detailed Implementation

[0015] This application provides a data processing method and system for simulating first aid skills. It constructs a first aid scenario information database and retrieves target first aid scenario information, performs 3D scene modeling to construct a virtual first aid scenario, embeds a multi-dimensional first aid training module within the virtual first aid scenario, generates a dynamic simulation space, obtains adaptive first aid plans for simulation training in the dynamic simulation space, acquires real-time simulation information for comprehensive evaluation, adjusts and controls the first aid simulation based on the evaluation results, and stores the scenario-based first aid plan in the system. This addresses the technical problems in existing technologies where first aid operations rely primarily on the experience of rescuers to adapt rescue plans to different rescue scenarios, resulting in subjective factors, inability to complete tasks independently due to insufficient experience, and excessive uncontrollable factors.

[0016] Example 1

[0017] like Figure 1 As shown, this application provides a data processing method for first aid skills simulation, the method comprising:

[0018] Step S100: Construct an emergency rescue scenario information database, and retrieve target emergency rescue scenario information based on the emergency rescue scenario information database;

[0019] Specifically, to ensure rapid rescue in the face of emergencies, deep learning can be used through rescue simulation training. Simultaneously, current rescue plans can be experimented with and further refined. This application provides a data processing method for emergency rescue skills simulation, which conducts emergency rescue simulation training based on different emergency rescue scenarios. Emergency rescue training is conducted as the simulation unfolds, and emergency rescue plans can be simultaneously verified, adjusted, and corrected to determine the most suitable emergency rescue plan for the current scenario. First, multiple emergency rescue scenario information is acquired, scenario classification standards are determined, and the information is classified into multiple levels. The classification results are then labeled to generate an emergency rescue scenario information database. The characteristics of the scenarios to be simulated are determined, and the database is traversed. Through comparison and analysis, suitable emergency rescue scenario information is identified, retrieved, and used as the target emergency rescue scenario information. The acquisition of the target emergency rescue scenario information provides a foundation for subsequent emergency rescue simulation training.

[0020] Furthermore, such as Figure 2 As shown, the step S100 of this application further includes: constructing an emergency rescue scenario information database and retrieving target emergency rescue scenario information based on the database.

[0021] Step S110: Obtain information on various emergency rescue scenarios based on the big data platform;

[0022] Step S120: Perform multi-level classification of the various emergency rescue scenario information based on information relevance to obtain scenario classification results;

[0023] Step S130: Generate visual tags to identify the scene classification results and obtain the completed emergency rescue scene information database;

[0024] Step S140: Obtain scenario requirement information;

[0025] Step S150: Based on the scenario requirement information, traverse the emergency rescue scenario information database layer by layer to determine the target emergency rescue scenario information.

[0026] Specifically, the rescue plans and simulation methods corresponding to different emergency scenarios are not entirely the same. Conducting emergency simulations based on multiple emergency scenarios can effectively ensure the comprehensiveness of training. Based on a big data platform, various emergency scenario information is determined, mainly including external environmental information. Optionally, images, videos, parameter data, etc., can be used as the display form of scenario information. Further correlation analysis is performed on the various emergency scenario information to determine the correlation between each scenario. Using scenario correlation as the classification standard, the various emergency scenario information is classified. The various emergency scenario information is classified into multiple levels based on geographical features, climate features, human features, etc., generating a scenario classification tree. The scenario classification tree is used as the scenario classification result. Further, the feature information corresponding to each node in the scenario classification tree is determined. Based on this, visual tags are generated to identify the corresponding nodes of the scenario classification tree, generating the emergency scenario information database for subsequent rapid identification of scenario information.

[0027] Furthermore, the scenario type to be constructed and related limiting information are determined as the scenario requirement information. The scenario requirement information is tagged to obtain requirement scenario tags. Then, the emergency scenario information database is traversed layer by layer according to the requirement scenario tags, and the overlap comparison is performed with the node tags. The identified emergency scenario information is used as the target emergency scenario information. Based on the emergency scenario information database, multiple scenario information can be provided and the scenario recognition efficiency can be improved.

[0028] Step S200: Based on the target emergency rescue scene information, construct a virtual emergency rescue scene by performing three-dimensional scene modeling;

[0029] Specifically, the target emergency rescue scenario information is used as the information source, and 3D modeling is performed on the corresponding modeling platform using 3D modeling software. The target emergency rescue scenario information includes various information types such as scene images and videos to ensure the model construction result matches the actual rescue scenario and improve the accuracy of model construction. After the modeling is completed, the virtual emergency rescue scenario is obtained, and the virtual emergency rescue scenario is the main domain for the emergency rescue training to be carried out.

[0030] Furthermore, step S200 of this application also includes:

[0031] Step S210: If it is necessary to switch the virtual emergency rescue scenario, obtain the switching scenario tag;

[0032] Step S220: Generate scene switching instructions;

[0033] Step S230: Based on the scene switching instruction and the scene switching label, traverse the emergency scene information database and retrieve the scene information to be switched;

[0034] Step S240: Based on the scene information to be switched, switch the virtual emergency rescue scene.

[0035] Specifically, by performing 3D modeling on the target emergency rescue scenario information, the virtual emergency rescue scenario is generated. During emergency rescue training, multiple different scenarios need to be performed separately. When a scenario switch is required, the currently constructed virtual emergency rescue scenario is switched synchronously to obtain the switching scenario tag, which is the general feature summary of the scenario to be switched. At the same time, the scenario switching command is generated. As the scenario switching command is received, the emergency rescue scenario information database is traversed based on the switching scenario tag. Through multi-level tag comparison analysis, the scenario information that matches the switching scenario tag is determined as the scenario information to be switched. Further 3D modeling is performed based on the scenario information to be switched, and the modeling result is used as the current virtual emergency rescue scenario. The previous round of virtual emergency rescue scenario is switched. Optionally, the switching method includes, but is not limited to, overwriting, replacement, etc., to ensure the comprehensiveness of emergency rescue training.

[0036] Step S300: Construct a multi-dimensional first aid training module;

[0037] Step S400: Embed the multi-dimensional first aid training module into the virtual first aid scenario to generate a dynamic simulation space;

[0038] Specifically, the constructed virtual emergency rescue scenario is used as the main training domain. Multiple necessary components for emergency rescue simulation training are further identified, such as treatment areas, treatment equipment, patients, and emergency personnel, to demonstrate the necessity of emergency rescue simulation. Based on these multi-dimensional necessary components, corresponding emergency rescue training modules are constructed, such as treatment area simulation modules, treatment equipment simulation modules, patient simulation modules, and emergency personnel simulation modules. These are used as the multi-dimensional emergency rescue training modules, which are dynamic control modules. Furthermore, these multi-dimensional emergency rescue training modules are embedded within the virtual emergency rescue scenario, and the two are linked and combined to jointly construct the dynamic simulation space. This dynamic simulation space serves as the basis for emergency rescue simulation training. Corresponding control parameters are obtained to control the dynamic simulation space to perform dynamic simulation simulation exercises for emergency rescue simulation training. The construction of this dynamic simulation space lays a solid foundation for subsequent emergency rescue training.

[0039] Step S500: Connect with the emergency medical information system to exchange information and obtain an appropriate emergency medical plan;

[0040] Specifically, the system connects to the emergency medical information system, which is a central control and management system for emergency medical information. This system encompasses various types of medical emergency information and can effectively ensure the completeness and authority of medical information. Through information interaction with the emergency medical information system, an emergency plan suitable for the current emergency situation is determined and retrieved as a primary emergency plan. Since the primary emergency plan has strong universality, it may not meet the simulation requirements of the dynamic simulated vacuum. The primary emergency plan is evaluated and analyzed, and the parts of the plan that do not meet the standards are adaptively modified and adjusted to determine the suitable emergency plan. The suitable emergency plan serves as the basic basis for subsequent emergency simulation training.

[0041] Furthermore, such as Figure 3 As shown, the associated emergency medical information system interacts with other systems to obtain an appropriate emergency medical plan. Step S500 of this application further includes:

[0042] Step S510: Retrieve the primary emergency medical plan based on the emergency medical information system;

[0043] Step S520: Perform a correlation analysis between the primary first aid plan and the dynamic simulation space to obtain the plan fit.

[0044] Step S530: Determine whether the fit of the proposed solution meets the preset requirements;

[0045] Step S540: If the conditions are not met, generate a scheme adjustment instruction;

[0046] Step S550: Optimize the plan based on the plan adjustment instructions to obtain the adaptive emergency plan.

[0047] Specifically, the emergency information system is a central control and management system for emergency information, encompassing various types of medical emergency information. By interacting with the emergency information system, an emergency plan adapted to the current emergency content is determined as the primary emergency plan. Further, the primary simulation plan and the dynamic simulation space are correlated and analyzed. For example, multiple correlation levels can be set, and the correlation levels of the two can be evaluated. Based on the obtained correlation levels, the fit of the primary emergency plan with the dynamic simulation space is determined.

[0048] Furthermore, a preset requirement is set, which is a critical value for judging whether the fit of the plan meets the standard. When the fit of the plan meets the preset requirement, the primary first aid plan is used as the adaptive first aid plan. When the fit of the plan does not meet the preset requirement, the plan adjustment instruction is generated. The plan adjustment instruction is the start instruction for plan modification. As the plan adjustment instruction is received, the primary first aid plan is optimized, and the optimized plan is used as the adaptive first aid plan, which can effectively reduce the number of sudden situations in the subsequent first aid simulation training process.

[0049] Furthermore, step S550 of this application also includes:

[0050] Step S551: Perform deviation analysis on the primary emergency rescue plan based on the plan fit to obtain plan deviation information;

[0051] Step S552: Determine the scheme correction parameters based on the scheme deviation information;

[0052] Step S553: ​​Optimize the scheme based on the scheme correction parameters to generate the adaptive emergency rescue scheme.

[0053] Specifically, when the fit of the proposed solution does not meet the preset requirements, it indicates that the retrieved primary emergency medical plan is substandard and requires further adjustment. Based on the fit of the proposed solution, the correlation deviation of the primary emergency medical plan with the dynamic simulation space is determined, and the deviation information of the proposed solution is generated. When adjusting the proposed solution subsequently, the deviation information is used to make a reverse adjustment to determine the direction and scale of the adjustment, which are used as the correction parameters of the proposed solution. The part of the proposed solution corresponding to the correction parameters is then corrected and adjusted, and the adjusted proposed solution is used as the adaptive emergency medical plan. The overall process of the adaptive emergency medical plan is relatively accurate, but there may still be some minor deviations. During subsequent simulation training, these deviations are analyzed and corrected synchronously as the emergency medical plan is implemented.

[0054] Step S600: Based on the adaptive emergency rescue plan, perform simulation training in the dynamic simulation space to obtain real-time simulation information;

[0055] Step S700: The real-time simulation information is comprehensively evaluated, and the emergency simulation is adjusted and controlled based on the evaluation results. The scenario emergency rescue plan is determined and stored in the system.

[0056] Specifically, the adaptive first aid plan is determined by retrieving and correcting the plan. Based on the adaptive first aid plan, the control parameters of the multi-dimensional first aid training module are determined. Based on the control parameters, the state of the multi-dimensional first aid training module in the dynamic simulation space is controlled for simulation training. As the simulation training progresses in real time, the real-time simulation information, i.e., the real-time simulation state effect, is obtained. Further, based on the real-time simulation information, the state of the multi-dimensional first aid training module is analyzed to determine whether there are any anomalies. If no anomalies are found, the current simulation process is considered. If anomalies are found, deviation analysis is performed on the adaptive first aid plan portion corresponding to the real-time simulation information to determine the plan adjustment parameters for correction. Simultaneously, the current first aid simulation process can be paused, and the corrected portion of the plan can be simulated a second time to ensure the accuracy of the first aid state and avoid affecting subsequent simulations. After the simulation is completed, the final determined plan is used as the scenario first aid plan, identified with the corresponding scenario, and stored in the system for easy identification and retrieval later.

[0057] Furthermore, step S600 of this application also includes:

[0058] Step S610: Determine multiple sets of module control parameters based on the adaptive emergency rescue plan, wherein the multiple sets of module control parameters correspond one-to-one with the multidimensional emergency rescue training module;

[0059] Step S620: Identify the multiple sets of module control parameters based on timing to determine the synchronous braking parameters;

[0060] Step S630: Perform braking control of the multi-dimensional emergency training module according to the synchronous braking parameters to realize emergency simulation in the dynamic pseudo-vacuum and obtain the real-time simulation information.

[0061] Specifically, the adaptive emergency care plan is obtained, and the dynamic state of the multi-dimensional emergency care training module during the implementation of the plan is determined. Based on the state characteristics, real-time control parameters are determined. For example, when conducting simulated training for the treatment of fracture patients, the simulation modules for treatment areas, treatment equipment, patients, and emergency personnel need to cooperate with the adaptive emergency care plan to complete dynamic simulation. For instance, in the patient simulation module, the patient's condition, location, and recovery status during the implementation of the emergency care plan all need to be controlled. The control parameters corresponding to each module in the multi-dimensional emergency care training module are determined, and they are integrated to generate the multiple sets of module control parameters, wherein the parameter data is in a dynamic state.

[0062] Furthermore, based on the temporal sequence, the module control parameters corresponding to the same time node in the multiple sets of module control parameters are determined and identified based on the time sequence to generate the synchronous braking parameters, that is, the corresponding parameters for each module to perform state control simultaneously at the same time node. Then, the multi-dimensional emergency training module is braked based on the synchronous braking parameters to perform emergency simulation in the dynamic simulated vacuum. The real-time simulation state effect is used as the real-time simulation information. By performing multi-module linkage control, the parameter data analysis rate can be effectively improved while ensuring the simulation accuracy.

[0063] Furthermore, step S700 of this application also includes:

[0064] Step S710: Construct an emergency medical service efficiency assessment model based on machine learning algorithms, including an information identification layer, an analysis and evaluation layer, and a plan correction layer;

[0065] Step S720: Input the real-time simulation information into the emergency medical efficiency assessment model;

[0066] Step S730: Determine the module to which the information belongs based on the information identification layer, and obtain the identifier deduction information;

[0067] Step S740: Based on the analysis and evaluation layer, perform a deduction step evaluation on the identifier deduction information and obtain the step evaluation result;

[0068] Step S750: When the evaluation result of the above step meets the standard, output the result;

[0069] Step S760: When the evaluation result of the step does not meet the standard, the evaluation result of the step is transmitted to the scheme correction layer to obtain the simulation adjustment parameters.

[0070] Specifically, the acquired real-time simulation information is evaluated and analyzed for further simulation control. A primary emergency medical service efficiency assessment model is constructed based on machine learning algorithms. Historical emergency medical service data is collected as sample data and divided into training and validation sets. The training and validation sets are input into the primary emergency medical service efficiency assessment model. The model is trained and validated to improve the model's analytical accuracy until a predetermined accuracy is reached, at which point model training stops to determine the emergency medical service efficiency assessment model. The emergency medical service efficiency assessment model is a multi-layered network, including the information recognition layer, the analysis and evaluation layer, and the scheme correction layer. At the same time, the emergency medical service efficiency assessment model is associated with the dynamic simulation space, allowing for synchronous analysis of the real-time simulation information acquired from the dynamic simulation space.

[0071] Furthermore, the real-time simulation information is input into the information recognition layer of the emergency medical efficiency assessment model. The real-time simulation information is matched and corresponded with the multi-dimensional emergency medical training module. The matching results are marked for identification and differentiation, generating the marked simulation information. The marked simulation information is input into the analysis and evaluation layer to determine whether there are any abnormalities in the simulation steps corresponding to the marked simulation information. The step evaluation results are obtained. When the step evaluation results meet the standards, no further analysis of the network layer is required, and the results are directly output. When the step evaluation results do not meet the standards, it indicates that there is a deviation in the adaptive emergency medical plan corresponding to the simulation step. The step evaluation results are input into the plan correction layer to identify the deviation in the plan and determine the corresponding adjustment direction and adjustment scale as the simulation adjustment parameters. Then, the plan is corrected based on the simulation adjustment parameters. Preferably, the simulation process in the current dynamic simulation space can be paused, and the plan part corresponding to the simulation adjustment parameters can be re-analyzed. The plan determined after the emergency medical simulation is completed is the optimal emergency medical plan and is stored in the system.

[0072] Example 2

[0073] Based on the same inventive concept as the data processing method for first aid skills simulation in the foregoing embodiments, such as Figure 4 As shown, this application provides a data processing system for simulating first aid skills, the system comprising:

[0074] Scene information acquisition module 11, the scene information acquisition module 11 is used to construct an emergency scene information database and retrieve target emergency scene information based on the emergency scene information database;

[0075] The simulated scene construction module 12 is used to construct a virtual emergency scene based on the target emergency scene information by performing three-dimensional scene modeling.

[0076] Training module construction module 13, which is used to construct a multi-dimensional first aid training module;

[0077] The simulation space generation module 14 is used to embed the multi-dimensional first aid training module into the virtual first aid scene to generate a dynamic simulation space.

[0078] Solution acquisition module 15, which is used to associate with the emergency information system for information interaction and to acquire an appropriate emergency plan;

[0079] Information acquisition module 16, the information acquisition module 16 is used to perform simulation training in the dynamic simulation space according to the adaptive emergency rescue plan, and acquire real-time simulation information;

[0080] The adjustment control module 17 is used to comprehensively evaluate the real-time simulation information, adjust and control the emergency simulation based on the evaluation results, and determine the emergency rescue plan for system storage.

[0081] Furthermore, the system also includes:

[0082] An emergency scene acquisition module, which is used to acquire information on various emergency scenes based on a big data platform;

[0083] A scene classification module is used to perform multi-level classification of the various emergency rescue scene information based on information relevance and obtain scene classification results.

[0084] A scene identification module is used to generate visual tags to identify the scene classification results and obtain the constructed emergency scene information database.

[0085] A requirement information acquisition module, which is used to acquire scenario requirement information;

[0086] The target determination module is used to traverse the emergency rescue scenario information database layer by layer based on the scenario requirement information to determine the target emergency rescue scenario information.

[0087] Furthermore, the system also includes:

[0088] A tag acquisition module is used to acquire a switching scene tag when the virtual emergency rescue scene needs to be switched.

[0089] A switching instruction generation module, which is used to generate scene switching instructions;

[0090] The information retrieval module is used to traverse the emergency scene information database based on the scene switching instruction and the scene switching label, and retrieve the scene information to be switched.

[0091] A scene switching module is used to switch the virtual emergency rescue scene based on the scene information to be switched.

[0092] Furthermore, the system also includes:

[0093] A primary emergency response plan retrieval module is used to retrieve primary emergency response plans based on the emergency information system.

[0094] A correlation analysis module is used to perform correlation analysis between the primary first aid plan and the dynamic simulation space to obtain the plan's fit.

[0095] A solution judgment module is used to determine whether the suitability of the solution meets preset requirements.

[0096] An adjustment instruction generation module is used to generate a scheme adjustment instruction when the conditions are not met.

[0097] The solution optimization module is used to optimize the solution based on the solution adjustment instruction and obtain the adaptive emergency rescue solution.

[0098] Furthermore, the system also includes:

[0099] A deviation analysis module is used to perform deviation analysis on the primary emergency rescue plan based on the plan fit degree, and to obtain plan deviation information.

[0100] A correction parameter determination module is used to determine the scheme correction parameters based on the scheme deviation information.

[0101] The solution correction module is used to optimize the solution based on the solution correction parameters and generate the adaptive emergency rescue solution.

[0102] Furthermore, the system also includes:

[0103] A control parameter determination module is used to determine multiple sets of module control parameters based on the adaptive emergency rescue plan, wherein the multiple sets of module control parameters correspond one-to-one with the multidimensional emergency rescue training module;

[0104] A parameter identification module is used to identify the multiple sets of module control parameters based on timing to determine the synchronous braking parameters.

[0105] The simulation control module is used to control the braking of the multi-dimensional emergency training module according to the synchronous braking parameters, realize the emergency simulation in the dynamic pseudo-vacuum, and obtain the real-time simulation information.

[0106] Furthermore, the system also includes:

[0107] The model building module is used to build an emergency medical efficiency assessment model based on machine learning algorithms, including an information identification layer, an analysis and evaluation layer, and a plan correction layer.

[0108] Information input module, the information input module is used to input the real-time simulation information into the emergency rescue efficiency assessment model;

[0109] The information identification module is used to determine the module to which the information belongs based on the information identification layer and to obtain identification deduction information;

[0110] The information evaluation module is used to evaluate the deduction steps of the identifier deduction information based on the analysis and evaluation layer, and obtain the step evaluation results;

[0111] The result output module is used to output the result when the evaluation result of the step meets the standard;

[0112] The adjustment parameter acquisition module is used to transmit the step evaluation result to the scheme correction layer when the step evaluation result is not up to standard, and to obtain the inference adjustment parameters.

[0113] Through the foregoing detailed description of a data processing method for emergency skills simulation, those skilled in the art can clearly understand the data processing method and system for emergency skills simulation in this embodiment. As for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to the method section description.

[0114] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A data processing method for simulating first aid skills, characterized in that, The method includes: Construct an emergency medical scenario information database, and retrieve target emergency medical scenario information based on the emergency medical scenario information database; Based on the target emergency rescue scenario information, a virtual emergency rescue scenario is constructed by performing 3D scene modeling; Construct a multi-dimensional first aid training module; The multi-dimensional first aid training module is embedded into the virtual first aid scenario to generate a dynamic and realistic space. Interact with emergency medical information systems to obtain appropriate emergency medical plans; Based on the adaptive emergency rescue plan, simulation training is conducted in the dynamic simulation space to obtain real-time simulation information; The real-time simulation information is comprehensively evaluated, and the emergency simulation is adjusted and controlled based on the evaluation results. The scenario emergency rescue plan is determined and stored in the system. Based on the adaptive emergency rescue plan, multiple sets of module control parameters are determined, wherein each set of module control parameters corresponds one-to-one with the multidimensional emergency rescue training module. The multiple sets of module control parameters are identified based on timing to determine the synchronous braking parameters; The braking control of the multi-dimensional emergency training module is performed based on the synchronous braking parameters to realize the emergency simulation in the dynamic pseudo-vacuum and obtain the real-time simulation information.

2. The method as described in claim 1, characterized in that, The construction of the emergency medical scenario information database, and the retrieval of target emergency medical scenario information based on the database, include: Information on various emergency rescue scenarios is obtained based on a big data platform; Based on information relevance, the various emergency rescue scenario information is classified into multiple levels to obtain scenario classification results; Generate visual tags to identify the scene classification results and obtain the completed emergency rescue scene information database; Obtain scenario requirement information; Based on the scenario requirement information, the emergency rescue scenario information database is traversed layer by layer to determine the target emergency rescue scenario information.

3. The method as described in claim 1, characterized in that, include: If it is necessary to switch the virtual emergency rescue scenario, obtain the switching scenario tag; Generate scene switching instructions; Based on the scene switching command and the scene switching label, the emergency scene information database is traversed to retrieve the scene information to be switched; Based on the scene information to be switched, the virtual emergency rescue scene is switched.

4. The method as described in claim 1, characterized in that, The associated emergency medical information system interacts with other systems to obtain appropriate emergency medical plans, including: Retrieve the primary emergency medical plan based on the aforementioned emergency information system; A correlation analysis was performed between the primary first aid plan and the dynamic simulation space to obtain the plan's fit. Determine whether the suitability of the proposed solution meets the preset requirements; If the conditions are not met, a scheme adjustment instruction will be generated; Based on the aforementioned adjustment instructions, the plan is optimized to obtain the adaptive emergency rescue plan.

5. The method as described in claim 4, characterized in that, include: Based on the fit of the proposed solutions, a deviation analysis is performed on the primary emergency medical plan to obtain deviation information. Determine the scheme correction parameters based on the scheme deviation information; Based on the proposed solution, the parameters are modified to optimize the solution and generate the adaptive emergency rescue solution.

6. The method as described in claim 1, characterized in that, include: An emergency medical service efficiency assessment model is constructed based on machine learning algorithms, including an information identification layer, an analysis and evaluation layer, and a plan correction layer. The real-time simulation information is input into the emergency medical efficiency assessment model; Based on the information identification layer, the module to which the information belongs is determined, and the identifier deduction information is obtained; Based on the analysis and evaluation layer, the deduction steps of the identifier deduction information are evaluated, and the step evaluation results are obtained; When the evaluation results of the above steps meet the standards, the results are output. When the evaluation result of the step fails to meet the standard, the evaluation result is transmitted to the scheme correction layer to obtain the simulation adjustment parameters.

7. A data processing system for simulating first aid skills, characterized in that, The system is used to perform the method according to any one of claims 1 to 6, the system comprising: A scene information acquisition module is used to construct an emergency scene information database and retrieve target emergency scene information based on the emergency scene information database. A realistic scene construction module is used to construct a virtual emergency scene based on the target emergency scene information by performing three-dimensional scene modeling. A training module construction module, which is used to construct a multidimensional first aid training module; A simulated space generation module is used to embed the multi-dimensional first aid training module into the virtual first aid scene to generate a dynamic simulated space. The solution acquisition module is used to interact with the emergency medical information system to obtain an appropriate emergency medical solution. An information acquisition module is used to perform simulation training in the dynamic simulation space based on the adaptive emergency rescue plan and acquire real-time simulation information. The adjustment control module is used to comprehensively evaluate the real-time simulation information, adjust and control the emergency simulation based on the evaluation results, and determine the emergency rescue plan for system storage. A control parameter determination module is used to determine multiple sets of module control parameters based on the adaptive emergency rescue plan, wherein the multiple sets of module control parameters correspond one-to-one with the multidimensional emergency rescue training module; A parameter identification module is used to identify the multiple sets of module control parameters based on timing to determine the synchronous braking parameters. The simulation control module is used to control the braking of the multi-dimensional emergency training module according to the synchronous braking parameters, realize the emergency simulation in the dynamic pseudo-vacuum, and obtain the real-time simulation information.

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