A 5G-based immersive emergency training and drill method and system

Abstract

The present invention provides a 5G-based immersive emergency training and drill method and system, belonging to the technical field of emergency management, specifically including: using a 5G-based monitoring device to obtain a real-world scene matching different simulation training scenarios of an emergency training system, and using the real-world scene matching different simulation training scenarios to build different simulation training scenarios, constructing an interactive video of different simulation training scenarios through the emergency training subjects and training purposes of different simulation training scenarios, determining the comprehensive scene change amount based on the scene change amount of the real-world scene matching different simulation training scenarios and the authenticity requirements of different simulation training scenarios, and using the comprehensive scene change amount to determine the simulation training scenarios that need to be updated, thereby further ensuring the reliability of the training.

Description

Technical Field

[0001] The present invention belongs to the technical field of emergency management, and in particular relates to a 5G-based immersive emergency training and simulation method and system. Background Art

[0002] Traditional actual combat emergency simulation drills have defects such as long preparation time, high consumption of manpower, material resources and financial resources, and single set scenarios and processes, and are not suitable for frequent implementation. Therefore, how to use computer virtual reality technology to build an emergency rescue virtual simulation system is of great significance.

[0003] To solve the above technical problems, in the existing technical solutions, virtual simulation systems of various forms are built to meet the simulation needs of users. Specifically, similar virtual reality-based emergency training systems are given in the invention patents CN202211566410.3 "A Method and System for Interactive Training of Power Failure Emergency Augmented Reality Intelligent Devices" and CN202310127652.0 "A Virtual Reality-based Emergency State Simulation Training System". However, through analysis, it is not difficult to find that the following technical problems exist in the existing technical solutions:

[0004] Existing emergency training scenarios are often built based on fixed scenarios and are not updated once built. However, the real scenarios corresponding to the emergency training scenarios are not static. Therefore, if the emergency training scenarios cannot be dynamically updated according to the real scenarios, the reliability of the emergency training results cannot be guaranteed.

[0005] In view of the above technical problems, the present invention provides a 5G-based immersive emergency training and simulation method and system. Summary of the Invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, a 5G-based immersive emergency training and simulation method is provided.

[0008] A 5G-based immersive emergency training and simulation method, characterized in that it specifically includes:

[0009] S1 Use a 5G-based monitoring device to obtain the real scenarios matching different simulation training scenarios of the emergency training system, and use the real scenarios matching different simulation training scenarios to build different simulation training scenarios, and construct interactive videos of different simulation training scenarios through the emergency training subjects and training purposes of different simulation training scenarios;

[0010] S2 Obtain the usage data of the training personnel in different simulation training scenarios, and determine the authenticity requirements of different simulation training scenarios and the analysis period of the monitoring device in combination with the emergency training subjects and training purposes of different simulation training scenarios;

[0011] S3 Obtain the monitoring images of the monitoring devices that match the real scenarios of different simulation training scenarios through the analysis period, use the analysis results of the monitoring images to determine the scene change amount and the violently changing scenarios of the different simulation training scenarios that match the real scenarios, and when there are violently changing scenarios, proceed to the next step;

[0012] S4 Determine the comprehensive scene change amount based on the scene change amount of the different simulation training scenarios that match the real scenarios and the authenticity requirements of different simulation training scenarios, and use the comprehensive scene change amount to determine the simulation training scenarios that need to be updated.

[0013] The beneficial effects achieved by the present invention are as follows:

[0014] 1. By determining the authenticity requirements of different simulation training scenarios and the analysis period of the monitoring device, the screening of simulation training scenarios with high authenticity requirements from the perspective of the usage of different simulation training scenarios and emergency training subjects is realized. Furthermore, the determination of different analysis periods for different simulation training scenarios is realized, which ensures the reliability of the update processing of simulation training scenarios while guaranteeing the analysis and processing efficiency.

[0015] 2. Use the analysis results of the monitoring images to determine the scene change amount and the violently changing scenarios of the different simulation training scenarios that match the real scenarios, thereby realizing the evaluation of the scene change situation of the different simulation training scenarios that match the real scenarios from the analysis results of the monitoring images, and laying a foundation for the screening of simulation training scenarios for differential update processing.

[0016] 3. Use the comprehensive scene change amount to determine the simulation training scenarios that need to be updated, thereby realizing the determination of the differential comprehensive scene change amount based on the scene change situation and authenticity requirements of different simulation training scenarios, and realizing the screening of simulation training scenarios with large change amounts, which not only ensures the efficiency of the scene update processing, but also guarantees the accuracy and reliability of the training results.

[0017] A further technical solution is that the matching of the simulation training scenario to the real scenario is determined according to the corresponding relationship between different simulation training scenarios and different real scenarios.

[0018] A further technical solution is to use the matching of different simulation training scenarios to the real scenario to build different simulation training scenarios, specifically including:

[0019] Based on the matching of the simulated training scenario to the real scenario, the corresponding models of different objects in the real scenario are determined, and the construction result of the simulated training scenario is obtained through rendering using the corresponding models of different objects.

[0020] A further technical solution lies in that the method for determining the interactive video of the simulated training scenario is as follows:

[0021] Design the interactive plot of the simulated training scenario according to the emergency training subjects and training purposes of the simulated training scenario, and determine the interactive video of the simulated training scenario according to the interactive plot.

[0022] A further technical solution lies in that the usage data of the training personnel includes the number of training personnel, the usage times of different training personnel, and the usage duration.

[0023] A further technical solution lies in that the authenticity requirement of the simulated training scenario is determined according to the usage frequency and the weighted sum of the basic analysis period.

[0024] A further technical solution lies in that the number of monitoring devices is determined according to the area of the real scenario that the simulated training scenario matches.

[0025] A further technical solution lies in using the comprehensive scene change amount to determine the simulated training scenarios that need to be updated, specifically including:

[0026] When the comprehensive scene change amount is greater than the preset change amount threshold, it is determined that all simulated training scenarios need to be updated;

[0027] When the comprehensive scene change amount is not greater than the preset change amount threshold, the severely changed scenarios are used as the simulated training scenarios that need to be updated.

[0028] On the other hand, the present invention provides a computer system, including: a memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes the above-mentioned 5G-based immersive emergency training and drill method.

[0029] Other features and advantages will be described in the subsequent specification, and, in part, will become apparent from the specification or will be understood by implementing the present invention. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification and the drawings.

[0030] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following specific preferred embodiments are given, and in conjunction with the accompanying drawings, the detailed description is as follows. Description of the Drawings

[0031] The above and other features and advantages of the present invention will become more apparent by describing its exemplary embodiments in detail with reference to the accompanying drawings.

[0032] Figure 1 is a flowchart of a 5G-based immersive emergency training and drill method;

[0033] Figure 2 is a flowchart of a method for determining the analysis period of a monitoring device;

[0034] Figure 3 is a flowchart of a method for determining the comprehensive change amount of a scene. Detailed Embodiments

[0035] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be implemented in various forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. Like reference numerals in the figures denote the same or similar structures, and thus their detailed description will be omitted.

[0036] The terms "a", "an", "the", and "said" are used to denote the presence of one or more elements / components / etc.; the terms "comprising" and "having" are used to mean an open inclusion and mean that there may be additional elements / components / etc. in addition to the listed elements / components / etc.

[0037] Example 1

[0038] To solve the above problems, according to one aspect of the present invention, as Figure 1 shown, according to one aspect of the present invention, there is provided a 5G-based immersive emergency training and drill method, characterized in that it specifically includes:

[0039] S1 Use a 5G-based monitoring device to obtain a real-scene matching for different simulation training scenarios of an emergency training system, and use the real-scene matching of different simulation training scenarios to build different simulation training scenarios, and construct an interactive video for different simulation training scenarios through the emergency training subjects and training purposes of different simulation training scenarios;

[0040] Further, the real-scene matching of the simulation training scenario is determined according to the corresponding relationship between different simulation training scenarios and different real scenes.

[0041] Specifically, different simulation training scenarios are built by matching realistic scenarios of different simulation training scenarios, specifically including:

[0042] Based on the matching of the simulation training scenario with the realistic scenario, the corresponding models of different objects in the matching realistic scenario are determined, and the construction result of the simulation training scenario is obtained by rendering through the corresponding models of different objects.

[0043] It should be noted that the method for determining the interactive video of the simulation training scenario is:

[0044] Design the interactive plot of the simulation training scenario according to the emergency training subjects and training purposes of the simulation training scenario, and determine the interactive video of the simulation training scenario according to the interactive plot.

[0045] Furthermore, the usage data of the training personnel includes the number of training personnel, the usage times of different training personnel, and the usage duration.

[0046] S2 Obtain the usage data of the training personnel for different simulation training scenarios, and determine the authenticity requirements of different simulation training scenarios and the analysis period of the monitoring device in combination with the emergency training subjects and training purposes of different simulation training scenarios;

[0047] Specifically, for example, as Figure 2 shown, the method for determining the analysis period of the monitoring device is:

[0048] Determine the basic analysis period of the simulation training scenario by using the number of emergency training subjects of the simulation training scenario and the training purposes of different emergency training subjects;

[0049] Determine the usage times and usage duration of the training personnel of the simulation training scenario through the usage data of the training personnel of the simulation training scenario, and determine the usage frequency of the simulation training scenario in combination with the number of training personnel of the simulation training scenario;

[0050] Determine the analysis period of the monitoring device corresponding to the simulation training scenario based on the usage frequency and the basic analysis period.

[0051] Furthermore, the usage data of the training personnel is determined according to the background reading result of the training personnel of the simulation training scenario.

[0052] In another possible embodiment, the method for determining the analysis period of the monitoring device is:

[0053] Determine the basic analysis period of different simulation training scenarios based on the number of emergency training subjects in the simulation training scenario and the training purposes of different emergency training subjects, and determine whether the basic analysis period of the simulation training scenario is less than the preset analysis period. If so, use the basic analysis period as the analysis period of the monitoring device. If not, proceed to the next step;

[0054] Determine whether the number of users of the training personnel in the simulation training scenario is less than the preset number of users. If so, use the basic analysis period as the analysis period of the monitoring device. If not, proceed to the next step;

[0055] Determine the number of uses and the usage duration of the training personnel in the simulation training scenario through the usage data of the training personnel in the simulation training scenario, and determine the personnel usage busy degree of different training personnel based on the number of uses and the usage duration of different training personnel. Determine whether the number of users of the training personnel whose personnel usage busy degree meets the requirements is less than the preset number of users. If so, use the basic analysis period as the analysis period of the monitoring device. If not, proceed to the next step;

[0056] Determine the usage frequency of the simulation training scenario through the personnel usage busy degree of different training personnel, the number of users of the training personnel whose personnel usage busy degree meets the requirements, and the number of users of the training personnel in the simulation training scenario. Determine whether the usage frequency of the simulation training scenario is greater than the preset busy degree. If so, determine the analysis period of the monitoring device corresponding to the simulation training scenario through the preset analysis period. If not, proceed to the next step;

[0057] Determine the analysis period of the monitoring device corresponding to the simulation training scenario based on the usage frequency and the basic analysis period.

[0058] In another possible embodiment, the method for determining the analysis period of the monitoring device is as follows:

[0059] Determine whether the number of users of the training personnel in the simulation training scenario is greater than the preset number threshold. If so, use the preset analysis period as the analysis period of the monitoring device. If not, proceed to the next step;

[0060] Determine the number of uses and the usage duration of the training personnel in the simulation training scenario through the usage data of the training personnel in the simulation training scenario, and determine the personnel usage busy degree of different training personnel based on the number of uses and the usage duration of different training personnel. Determine whether the number of users of the training personnel whose personnel usage busy degree meets the requirements is greater than the second preset number threshold. If so, use the preset analysis period as the analysis period of the monitoring device. If not, proceed to the next step;

[0061] Determine the usage frequency of the simulation training scenario by using the personnel usage busy degree of different trainers, the number of trainers whose personnel usage busy degree meets the requirements, and the number of trainers in the simulation training scenario, and judge whether the usage frequency of the simulation training scenario is greater than the preset busy degree. If so, determine the analysis period of the monitoring device corresponding to the simulation training scenario through the preset analysis period. If not, proceed to the next step;

[0062] Determine the basic analysis period of different simulation training scenarios by using the number of emergency training subjects in the simulation training scenario and the training purposes of different emergency training subjects, and determine the analysis period of the monitoring device corresponding to the simulation training scenario based on the usage frequency and the basic analysis period.

[0063] Furthermore, the authenticity requirement of the simulation training scenario is determined according to the weight sum of the usage frequency and the basic analysis period.

[0064] S3 Obtain the monitoring images of the monitoring devices that match the real scenarios of different simulation training scenarios through the analysis period, use the analysis results of the monitoring images to determine the scene change amount and the drastic change scene of the simulation training scenarios that match the real scenarios, and when there is a drastic change scene, proceed to the next step;

[0065] Furthermore, the number of the monitoring devices is determined according to the area of the simulation training scenario that matches the real scenario.

[0066] It should be noted that the method for determining the scene change amount of the simulation training scenario that matches the real scenario is as follows:

[0067] Obtain the number of the monitoring devices that match the on-site scenario and the original images of different monitoring devices, and determine the image change amount of different monitoring devices according to the monitoring images of different monitoring devices;

[0068] Determine the scene change amount of the simulation training scenario that matches the real scenario through the image change amounts of different monitoring devices.

[0069] It should be noted that when there is no drastic change scene, there is no need to update the scene of the simulation training scenario.

[0070] S4 Determine the comprehensive scene change amount based on the scene change amounts of the simulation training scenarios that match the real scenarios of different simulation training scenarios and the authenticity requirements of different simulation training scenarios, and use the comprehensive scene change amount to determine the simulation training scenarios that need to be updated.

[0071] Specific examples are as follows: Figure 3 As shown in and

[0072] , the method for determining the comprehensive scene change amount is as follows:

[0072] Divide the simulation training scenarios into drastic change scenarios and other change scenarios according to the scene change amounts of different simulation training scenarios matching the real scene;

[0073] Determine the comprehensive scene change amount of the drastic change scenarios according to the scene change amounts of the drastic change scenarios and the authenticity requirements of different drastic change scenarios, and determine the comprehensive scene change amount of the other change scenarios according to the scene change amounts of the other change scenarios and the authenticity requirements of different other change scenarios;

[0074] Determine the weight values of the comprehensive scene change amount of the drastic change scenarios and the weight values of the comprehensive scene change amount of the other change scenarios respectively according to the means of the scene change amounts of different drastic change scenarios and the means of the scene change amounts of the other change scenarios, and determine the comprehensive scene change amount by combining the comprehensive scene change amount of the drastic change scenarios and the comprehensive scene change amount of the other change scenarios.

[0075] In another possible embodiment, the method for determining the comprehensive scene change amount is as follows:

[0076] Divide the simulation training scenarios into drastic change scenarios and other change scenarios according to the scene change amounts of different simulation training scenarios matching the real scene. When the number of drastic change scenarios is greater than the preset number of scenarios, it is determined that all simulation training scenarios need to be updated;

[0077] When the number of drastic change scenarios is not greater than the preset number of scenarios, determine the comprehensive scene change amount of the drastic change scenarios according to the scene change amounts of the drastic change scenarios and the authenticity requirements of different drastic change scenarios. When the comprehensive scene change amount of the drastic change scenarios does not meet the requirements, it is determined that all simulation training scenarios need to be updated;

[0078] When the comprehensive scene change amount of the drastic change scenarios meets the requirements, determine the comprehensive scene change amount of the other change scenarios according to the scene change amounts of the other change scenarios and the authenticity requirements of different other change scenarios;

[0079] Determine the weight values of the comprehensive scene change amount of the drastic change scenarios and the weight values of the comprehensive scene change amount of the other change scenarios respectively according to the means of the scene change amounts of different drastic change scenarios and the means of the scene change amounts of the other change scenarios, and determine the comprehensive scene change amount by combining the comprehensive scene change amount of the drastic change scenarios and the comprehensive scene change amount of the other change scenarios.

[0080] In another possible embodiment, the method for determining the comprehensive scene change amount is as follows:

[0081] S41 Determine the number of changes in the simulation training scenarios by the scene change amounts of different simulation training scenarios matching the real scene, and judge whether the number of changes in the simulation training scenarios is less than the scene number threshold. If so, proceed to the next step; if not, proceed to step S43;

[0082] S42 Divide the simulation training scenarios into severely changing scenarios and other changing scenarios based on the scene change amounts, and judge whether the number of severely changing scenarios meets the requirements. If so, use the severely changing scenarios as the simulation training scenarios that need to be updated; if not, proceed to the next step;

[0083] S43 Determine the comprehensive scene change amount of the severely changing scenarios according to the scene change amounts of the severely changing scenarios and the authenticity requirements of different severely changing scenarios, and judge whether the comprehensive scene change amount of the severely changing scenarios meets the requirements. If so, proceed to the next step; if not, determine that all simulation training scenarios need to be updated;

[0084] S44 Determine the comprehensive scene change amount of the other changing scenarios according to the scene change amounts of the other changing scenarios and the authenticity requirements of different other changing scenarios, determine the weight values of the comprehensive scene change amount of the severely changing scenarios and the weight values of the comprehensive scene change amount of the other changing scenarios respectively according to the mean values of the scene change amounts of different severely changing scenarios and the mean values of the scene change amounts of the other changing scenarios, and determine the comprehensive scene change amount in combination with the comprehensive scene change amount of the severely changing scenarios and the comprehensive scene change amount of the other changing scenarios.

[0085] Specifically, using the comprehensive scene change amount to determine the simulation training scenarios that need to be updated specifically includes:

[0086] When the comprehensive scene change amount is greater than the preset change amount threshold, determine that all simulation training scenarios need to be updated;

[0087] When the comprehensive scene change amount is not greater than the preset change amount threshold, use the severely changing scenarios as the simulation training scenarios that need to be updated.

[0088] Embodiment 2

[0089] On the other hand, the present invention provides a computer system, comprising: a memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes the above-mentioned 5G-based immersive emergency training and drill method.

[0090] Through the above embodiments, the present application achieves the following technical effects:

[0091] 1. By determining the authenticity requirements of different simulated training scenarios and the analysis period of the monitoring device, the screening of simulated training scenarios with higher authenticity requirements from the usage of different simulated training scenarios and the perspective of emergency training subjects is realized. Furthermore, the determination of different analysis periods for different simulated training scenarios is achieved, ensuring the reliability of the update processing of simulated training scenarios while guaranteeing the analysis and processing efficiency.

[0092] 2. Using the analysis results of the monitoring images to determine the scene change amount of different simulated training scenarios matching the real scene and the violently changing scenarios, thereby realizing the evaluation of the scene change situation of the real scene matched from the analysis results of the monitoring images, and laying a foundation for the screening of simulated training scenarios with differential update processing.

[0093] 3. Using the comprehensive scene change amount to determine the simulated training scenarios that need to be updated, thereby realizing the determination of different comprehensive scene change amounts for different simulated training scenarios according to the scene change situation and authenticity requirements, and realizing the screening of simulated training scenarios with larger change amounts, which not only ensures the efficiency of scene update processing, but also ensures the accuracy and reliability of the training results.

[0094] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, equipment, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0095] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be executed in a different order than in the embodiments and still achieve the desired results. Additionally, the processes depicted in the figures do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0096] The above description is only for one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, various changes and modifications can be made to one or more embodiments of this specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. An immersive emergency training and drill method based on 5G, characterized in that, Specifically, it includes: Using a 5G-based monitoring device to obtain the matching real scenarios of different simulation training scenarios of the emergency training system, and using the matching real scenarios of different simulation training scenarios to build different simulation training scenarios. Construct the interactive videos of different simulation training scenarios through the emergency training subjects and training purposes of different simulation training scenarios; Obtain the usage data of the training personnel in different simulation training scenarios, and determine the authenticity requirements of different simulation training scenarios and the analysis period of the monitoring device in combination with the emergency training subjects and training purposes of different simulation training scenarios; Obtain the monitoring images of the monitoring device for the matching real scenarios of different simulation training scenarios through the analysis period, use the analysis results of the monitoring images to determine the scene change amount and the severely changed scenarios of the matching real scenarios of different simulation training scenarios, and when there are severely changed scenarios, enter the following steps; Divide the simulation training scenarios into severely changed scenarios and other changed scenarios according to the scene change amount of the matching real scenarios of different simulation training scenarios. When the number of severely changed scenarios is greater than the preset number of scenarios, it is determined that all simulation training scenarios need to be updated; When the number of severely changed scenarios is not greater than the preset number of scenarios, determine the comprehensive scene change amount of the severely changed scenarios according to the scene change amount of the severely changed scenarios and the authenticity requirements of different severely changed scenarios. When the comprehensive scene change amount of the severely changed scenarios does not meet the requirements, it is determined that all simulation training scenarios need to be updated; When the comprehensive scene change amount of the severely changed scenarios meets the requirements, determine the comprehensive scene change amount of the other changed scenarios according to the scene change amount of the other changed scenarios and the authenticity requirements of different other changed scenarios; Determine the weight value of the comprehensive scene change amount of the severely changed scenarios and the weight value of the comprehensive scene change amount of the other changed scenarios respectively according to the mean value of the scene change amount of different severely changed scenarios and the mean value of the scene change amount of other changed scenarios, and combine the comprehensive scene change amount of the severely changed scenarios and the comprehensive scene change amount of the other changed scenarios to determine the comprehensive scene change amount.

2. The immersive emergency training and drill method based on 5G according to claim 1, characterized in that The matching real scenarios of the simulation training scenarios are determined according to the corresponding relationships between different simulation training scenarios and different real scenarios.

3. The immersive emergency training and drill method based on 5G according to claim 1, characterized in that, Using the matching real scenarios of different simulation training scenarios to build different simulation training scenarios, specifically including: Determine the corresponding models of different objects in the matching real scenarios based on the matching real scenarios of the simulation training scenarios, and render through the corresponding models of different objects to obtain the construction results of the simulation training scenarios.

4. The immersive emergency training and drill method based on 5G according to claim 1, wherein, The method for determining the interactive video of the simulation training scenario is: Design the interactive plot of the simulation training scenario according to the emergency training subject and training purpose of the simulation training scenario, and determine the interactive video of the simulation training scenario according to the interactive plot.

5. The immersive emergency training and drill method based on 5G according to claim 1, wherein The training personnel usage data includes the number of training personnel using the training personnel, the number of times different training personnel use the training personnel, and the duration of use.

6. The immersive emergency training and drill method based on 5G according to claim 1, wherein The method for determining the analysis period of the monitoring device is: Determining a basic analysis period of the simulated training scenario by utilizing the number of emergency training subjects in the simulated training scenario and the training objectives of different emergency training subjects; Determining the number of times and duration of use of the simulated training scenario by the trainees based on the usage data of the simulated training scenario, and determining the frequency of use of the simulated training scenario based on the number of users of the simulated training scenario by the trainees; The analysis period of the monitoring device corresponding to the simulated training scenario is determined based on the usage frequency and the basic analysis period.

7. The immersive emergency training and drill method based on 5G according to claim 1, wherein The method for determining the scene change amount of the simulated training scene to match the real scene is: Obtaining the number of monitoring devices matching the real scene and original images of different monitoring devices, and determining image change amounts of different monitoring devices based on the monitoring images of different monitoring devices; The scene variation amount of the simulated training scene matching the real scene is determined by the image variation amount of different monitoring devices.

8. The immersive emergency training and drill method based on 5G according to claim 1, characterized in that, The simulation training scenario that needs to be updated is determined by using the comprehensive change amount of the scenario, specifically including: When the comprehensive change amount of the scenario is greater than the preset change amount threshold, it is determined that all simulation training scenarios need to be updated; When the comprehensive change amount of the scene is not greater than the preset change amount threshold, the drastic change scene is regarded as a simulation training scene that needs to be updated.

9. A computer system, comprising: A memory and a processor in communication connection, and a computer program stored in the memory and capable of running on the processor, characterized in that when the processor runs the computer program, it executes a 5G-based immersive emergency training and drill method as described in any one of claims 1-8.

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