Visual virus experiment simulation operation system
By designing a visual virus experimental simulation operating system, the problem of insufficient simulation of laboratory leakage scenarios in the existing technology is solved, and the detailed evaluation of the virus transmission path and consequences is realized, the experimental risk prediction and prevention capabilities are improved, and the system's interactiveness and custom functions are enhanced.
Patent Information
- Application Number
- CN202510235218.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-28
- Publication Date
- 2025-07-08
AI Technical Summary
The existing biosecurity simulation platform lacks the capabilities of laboratory leakage scenario simulation, virus transmission path and consequence assessment, user interaction and customization, making it difficult to effectively predict and prevent leakage risks in high-risk pathogen experiments.
Design a visual virus experiment simulation operating system, including interactive control module, simulation platform module, data generation module, propagation path and epidemiological investigation module, early warning and evaluation module, and data storage module. The laboratory environment and leakage events are simulated through three-dimensional models, combined with infectious disease dynamics and geographical diffusion models, dynamically evaluate the infection probability and propagation path, and generate a multi-dimensional quantitative evaluation report.
It realizes comprehensive simulation and risk assessment of laboratory leakage scenarios, improves the risk prediction capabilities of scientific researchers, provides detailed virus transmission paths and consequence analysis, enhances the system's user interactivity and custom functions, and simplifies the operation process.
Smart Images
Figure CN120277874A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of biological experiment simulation, and particularly to a visual simulation operation system for virus experiments. Background Art
[0002] In the current laboratory environment, when conducting experiments on high-risk pathogens (such as the novel coronavirus), potential leakage risks may lead to extremely serious consequences. However, traditional experimental operation training often relies on the guidance of manuals or training videos, making it difficult to effectively evaluate the actual impact after leakage in different environments and for researchers to comprehensively master the links that may cause leakage during the experimental process. At the same time, the simulation of real leakage accidents is restricted by many factors. It is not only costly but also poses potential biosafety risks. Therefore, virtual simulation technology has gradually become an important means for experimental operation training and risk assessment.
[0003] In the existing technical solutions, although there are some biosafety virtual simulation platforms, the limitations of these platforms are obvious. Specifically, they include:
[0004] (1) Lack of simulation of leakage event scenarios: Most current simulation systems focus on the standardized training of experimental operations, but the simulation of real laboratory leakage scenarios is relatively limited, and it is impossible to fully present the possible risk trigger points in the laboratory;
[0005] (2) Insufficient evaluation of transmission paths and consequences: The existing technology lacks the function of simulating and quantitatively analyzing the virus transmission path, influence range, and consequences after leakage, which makes it difficult for researchers to effectively predict and prevent risks before the experiment;
[0006] (3) Lack of interactivity and customization: Some simulation systems lack sufficient user interaction and the function of customizing scenarios, making it difficult to meet the customization needs of researchers for specific experimental situations or leakage events, and restricting the application scope and learning effect of the simulation system. Summary of the Invention
[0007] Aiming at the problems existing in the prior art, the present invention provides a visual simulation operation system for virus experiments, enabling researchers to simulate and evaluate leakage scenarios in the virtual environment during the experimental operation of high-risk pathogens, providing risk points that may trigger leakage in the real scenario, so as to effectively predict and prevent potential risks before the real experiment.
[0008] The technical solution of the present invention is realized as follows:
[0009] A visual simulation operation system for virus experiments includes an interactive control module, a simulation platform module, a data generation module, a transmission path and epidemiological investigation module, an early warning and evaluation module, and a data storage module;
[0010] The data generation module is used to generate simulation data, including experimental environment parameters, experimental step parameters, and event parameters;
[0011] The experimental environment parameters include several types of objects, including laboratories, experimental equipment, and virtual personnel; the experimental equipment includes experimental instruments and sample containers; the objects have several attributes, including static attributes, dynamic attributes, and interactive attributes; the dynamic attributes include coordinates; static attributes are fixed attributes that do not change, and dynamic attributes are attributes that change dynamically over time, interaction, status, etc.; the dynamic attributes of the virtual personnel include the infection status;
[0012] The experimental step parameters include multiple experimental steps with a sequential relationship, and the duration of each experimental step;
[0013] The event parameters include the types of leakage events, such as improper sample handling, experimental instrument failure, etc., and the event occurrence probability, such as the probability of pathogen leakage when operating improperly; the leakage event is randomly triggered according to the event occurrence probability;
[0014] The simulation platform module models and renders a 3D model according to the experimental environment parameters, and displays the 3D model through the interaction and control module; the 3D model corresponding to the laboratory is divided into several regions; each region has independent dynamic attributes, including the infection probability; the 3D models corresponding to the experimental equipment and the virtual personnel respectively have some or all interactive attributes; the interactive attributes include collidable and movable;
[0015] The user interacts with the 3D model through the interaction control module to conduct a simulation experiment;
[0016] When the leakage event is triggered, the transmission path and epidemiological investigation module simulates the transmission path and diffusion speed of the pathogen according to the infectious disease dynamics model and the geographical diffusion model, dynamically adjusts the infection probability of the region at different time points, and modifies the infection status of the virtual personnel according to the infection probability; the infection status includes uninfected and infected;
[0017] The warning and evaluation module monitors the data changes of the 3D model in real time; when the monitored data is within the preset threshold range, the system triggers an alarm, and the warning and evaluation module generates a multi-dimensional quantitative evaluation report, including the final possibility of pathogen / virus leakage from the laboratory, the number of infected people, and the affected range, etc.; the multi-dimensional quantitative evaluation report is displayed through the interaction control module;
[0018] Several items of data generated during the simulation experiment are stored in the data storage module.
[0019] An infectious disease dynamics model is a mathematical model for studying the spread of infectious diseases. Specifically, based on the characteristics of population growth, the occurrence and spread and development laws of diseases within the population, as well as related social factors, etc., a mathematical model that can reflect the dynamic characteristics of infectious diseases is established. Through qualitative, quantitative analysis and numerical simulation of the dynamic behavior of the model, the development process of the disease is analyzed, the epidemic law is revealed, the changing trend is predicted, and the causes and keys of the disease epidemic are analyzed. The infectious disease dynamics model relies on difference equations or partial differential equations and can evaluate the spatial distribution and infection situation of pathogens at different time nodes. Such as the SIR (Susceptible-Infected-Recovered) model, SEIR (Susceptible-Exposed-Infected-Recovered) model, etc.
[0020] The geographical diffusion model is a model based on statistical and mathematical methods and is used to describe the spatial diffusion process of geographical phenomena. This model usually considers the spatial dependence, temporal variation and other related factors in geographical data, so as to construct a mathematical model that can simulate and predict geographical phenomena. The commonly used one is the diffusion equation method. The diffusion equation is a partial differential equation used to describe the diffusion process of substances in space and can predict the diffusion process of geographical phenomena.
[0021] As a further optimization of the above solution, the data storage module stores a number of pre-set simulation data;
[0022] The data generation module randomly generates the simulation data, or directly loads the simulation data from the data storage module, or is a combination of both.
[0023] As a further optimization of the above solution, the data generation module has a sub-module, including a scenario setting module; the scenario setting module is used for the user to customize and set some or all of the simulation data;
[0024] The data generation module randomly generates the simulation data, or directly loads the simulation data from the data storage module, or the user customizes and sets the simulation data through the scenario setting module, or is any combination application of the three.
[0025] Users can select specific laboratory environments, operation procedures and types and conditions of leakage events to create unique experimental scenarios. This includes setting scenarios such as improper sample handling, equipment operation errors or non-compliance with protective measures to cover various leakage possibilities.
[0026] As a further optimization of the above solution, the experimental environment parameters also include personal protective equipment; in the 3D model, the virtual person interacts with the personal protective equipment to simulate wearing or removing the personal protective equipment;
[0027] When the leakage event is triggered, within the same area, the number of virtual personnel wearing the personal protective equipment increases, and the infection probability of the area decreases.
[0028] Personal protective equipment includes masks, protective clothing, etc.
[0029] As a further optimization of the above solution, the dynamic attributes of the virtual personnel include the infection probability; among them, when the leakage event is triggered, the infection probability of the virtual personnel wearing the personal protective equipment is greater than that of the virtual personnel not wearing the personal protective equipment;
[0030] The transmission path and epidemiological investigation module modify the infection status of the virtual personnel according to the infection probability and the infected probability.
[0031] Specifically, for the combined application of the two probabilities, weight calculation can be used. For example, a represents the infection probability, A is the first weight, b represents the infected probability, B is the second weight, A + B = 1, and the final random probability is a×A + b×B. The infection status is changed according to the final random probability;
[0032] Specifically, the infected probability can also be randomly increased or decreased according to the infection probability, and then the infection status is changed according to the final infected probability.
[0033] The two specific methods provided here illustrate the feasible influence methods and logical processing methods between the infection probability, the infected probability, and the infection status, and are not restrictive.
[0034] As a further optimization of the above solution, when an uninfected virtual person comes into contact with an infected virtual person, the infected probability of the uninfected virtual person increases, or the infection status of the uninfected virtual person is modified to infected.
[0035] During the simulation process, the infection status and the infected probability are dynamically modified according to the contact frequency, contact time, etc. between the uninfected and infected persons.
[0036] As a further optimization of the above solution, the virtual personnel include passive personnel directly controlled by the user and automatic personnel that walk and move automatically; the data generation module also generates the activity trajectories of the automatic personnel; the activity trajectories include the coordinates and actions of the virtual personnel at different time points;
[0037] The transmission path and epidemiological investigation module also tracks and records the activity trajectories of the passive personnel;
[0038] When the leakage event is triggered, the transmission path and epidemiological investigation module simulates the transmission path and diffusion speed of the pathogen according to the infectious disease dynamics model and the geographical diffusion model, in combination with the activity trajectories.
[0039] During the simulation process, key links include determining the initial leak location and source, establishing the transmission path, assessing the probability of infection, and ultimately assessing the consequences and controlling the risks. First, determining the specific location of the leak and the concentration of the pathogen is the basis for understanding the pathogen diffusion process. Next, to simulate the spread of pathogens within the laboratory through air and contact transmission pathways, it is necessary to comprehensively consider factors such as air flow, object contact, and the movement path of the experimenters in order to accurately depict the pathogen diffusion pattern.
[0040] In terms of infection probability and exposure assessment, the personnel exposure risk at each location is calculated based on the laboratory's airtightness, air circulation and frequency of personnel contact, and the number of people who may be infected at different time points is further predicted, providing an accurate estimate of the potential scale of the epidemic development.
[0041] As a further optimization of the above scheme, when an alarm is triggered, the early warning and assessment module performs a risk assessment according to a preset risk standard and generates an assessment report. At the same time, the interactive control module provides suggestions for emergency measures, such as increased protection, isolation, emergency evacuation, etc.
[0042] Specifically, a score range of 0 to 100 or 0 to 1 is used to characterize the possibility of leakage and the potential impact, and is divided into different risk levels / tiers. The model clearly quantifies the possibility of leakage and the scope of impact through multi-level risk division, so that the laboratory can take appropriate management and response measures in a targeted manner. The low risk level indicates that the possibility of leakage is extremely low, and even if a leakage occurs, the impact on the external environment is small. The medium risk level reflects that there is a certain possibility of leakage. If a leakage occurs, it will have an impact on the laboratory or limited personnel. The high risk level indicates that the possibility of leakage is high, and once the leakage occurs, it may have a wide range of impacts on the laboratory, personnel and even the external environment. The extremely high risk level indicates an extremely high possibility of leakage and serious consequences, and urgent risk reduction measures must be taken immediately to ensure the safety of the laboratory and the protection of the surrounding environment.
[0043] By analyzing the multiple impacts of possible infections, the scope of transmission, and the economic losses caused by leakage, specific risk control recommendations are provided to laboratories, such as strengthening the use of personal protective equipment (PPE), increasing ventilation efficiency, or upgrading safety equipment, so as to effectively reduce leakage risks and control the potential spread of pathogens.
[0044] As a further optimization of the above scheme, at the end of the simulation experiment, leakage data is obtained; the leakage data includes the infection status of the virtual personnel in each of the areas;
[0045] The leaked data is stored in the data storage module; the data storage module also collects the analog data according to a predefined collection frequency; the data storage module also records and stores the operation steps performed by the user through the interaction control module;
[0046] It further includes a data analysis module; the data analysis module analyzes the high-risk factors in the simulation experiment based on the leaked data and the operation steps, and dynamically modifies the risk assessment criteria according to the high-risk factors; the high-risk factors are the risk factors whose occurrence times exceed a preset number in several simulation experiments; the risk factors include the experimental environment parameters and the operation steps.
[0047] By evaluating the following factors, including but not limited to pathogen characteristics, that is, including the infectivity, pathogenicity, environmental stability, etc. of the pathogen. The characteristics of the pathogen directly affect the spread speed and range after leakage; operation behavior, that is, whether the operations of the experimental personnel conform to the standard procedures. Including sample processing, waste treatment and other links, especially paying attention to the leakage risks that may be caused by operation errors; experimental environment, that is, including the biosafety level of the laboratory, the types, operating conditions and sealing performance of safety equipment, etc., these factors will all affect the probability of leakage occurrence; personal protective equipment (PPE), that is, the types and quality of personal protective equipment used by the experimental personnel, such as the protection levels and correct usage of gloves, masks, protective clothing, etc. In addition, external environmental variables, such as environmental factors like temperature and humidity, which may affect the transmission ability of the pathogen, usually need to be considered in the model.
[0048] During the evaluation, several modeling methods such as the Bayesian network model based on probability, numerical simulation and infectious disease dynamics model, and Monte Carlo simulation are mainly used for quantitative evaluation. The Bayesian network model cleverly associates various risk factors by constructing conditional probabilities, and can perform dynamic risk prediction according to the changes of risk factors under specific operating conditions. For example, the probability of a certain operation error is significantly reduced when using personal protective equipment (PPE), and these conditions are systematically expressed in the Bayesian network, enabling the model to adapt to the probability changes between risk factors in real time, so as to provide a dynamic assessment of the leakage risk in the operation scenario.
[0049] The numerical simulation and infectious disease dynamics model mainly relies on difference equations or partial differential equations to establish a dynamic system of pathogen transmission, simulating the diffusion path of the pathogen in the air or experimental environment and variables such as the number of infected people, etc., which is especially suitable for dynamic tracking after a leakage event occurs. Through this type of model, the spatial distribution and infection situation of the pathogen can be evaluated at different time nodes, providing a scientific basis for the formulation of emergency treatment and prevention measures.
[0050] Monte Carlo simulation emphasizes multi - scenario prediction under uncertain conditions. It uses random numbers to generate a large number of leakage event scenarios, covering different operations, environmental variables and their interactions, and obtains the overall risk probability through a large number of iterative calculations. Such simulation can not only provide rich data support for complex experimental conditions, but also provide a robust risk assessment in scenarios with extremely high uncertainty.
[0051] As a further optimization of the above - mentioned solution, in the same simulation experiment, the passive personnel are one or more.
[0052] Multiple scientific research experimenters controlled by real users cooperate with each other, which can cultivate the communication and coordination abilities among team members in scientific research experiments and in the face of pathogen leakage scenarios.
[0053] Compared with the prior art, the present invention has the following beneficial effects:
[0054] (1) By customizing the laboratory environment, operation steps and specific leakage scenarios, this system can simulate leakage scenarios that may be caused by different operation mistakes or equipment failures, and dynamically quantify the assessment of their consequences. Scientific researchers can identify potential leakage risk points in the simulation experiment, enhance the awareness of accident prevention, formulate more rigorous safety measures, thereby reducing the leakage risk in actual experiments;
[0055] (2) Provide the dynamic transmission path, diffusion range and consequence assessment after virus leakage. Scientific researchers can clearly observe how the pathogen spreads after leakage, quantify the infection probability and the affected range, so as to make accurate risk predictions before the experiment. The refined path tracking and consequence analysis provide a reliable scientific basis for formulating prevention and control strategies for biosafety incidents;
[0056] (3) The equipment design of the present invention takes into account user - friendliness, simplifies the operation process, makes the risk assessment simple and fast, and helps to promote it to a wider range of application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS
[0057] Figure 1 is a schematic diagram of the module connection of a visual virus experiment simulation operation system provided by an embodiment of the present invention;
[0058] Figure 2 is a partial effect diagram of a three - dimensional model shown on the interactive control interface provided by an embodiment of the present invention;
[0059] Figure 3 is a partial effect diagram of another three - dimensional model shown on the interactive control interface provided by an embodiment of the present invention;
[0060] Figure 4It is a partial effect schematic diagram of another 3D model displayed by the interaction control interface provided in the embodiment of the present invention;
[0061] Figure 5 It is the experimental personnel setting interface view displayed by the scenario setting module provided in the embodiment of the present invention;
[0062] Figure 6 It is a partial setting interface view of virtual personnel displayed by the scenario setting module provided in the embodiment of the present invention;
[0063] Figure 7 It is the activity trajectory generation and jack function interface view of the scenario setting module provided in the embodiment of the present invention;
[0064] Figure 8 It is the data record display diagram of the activity trajectory tracking provided in the embodiment of the present invention;
[0065] Figure 9 It is the data record display diagram of the experimental steps provided in the embodiment of the present invention. Detailed implementation manners
[0066] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.
[0067] As Figure 1 shown, this embodiment provides a visual virus experiment simulation operation system, including an interaction control module, a simulation platform module, a data generation module, a transmission path and epidemiological investigation module, a warning and evaluation module, as well as a data storage module and a data analysis module.
[0068] In this embodiment, the data storage module stores a number of pre-set simulation data; the data generation module has sub-modules, including a scenario setting module; the scenario setting module is used for users to customize and set some or all of the simulation data.
[0069] The data generation module is used to generate simulation data, including experimental environment parameters, experimental step parameters and event parameters; as Figure 5 、 Figure 6As shown, in actual operation, users can either randomly generate simulated data through the data generation module or directly load simulated data from the data storage module, that is, directly load simulated data from the experimental case library and scenario library, or customize some or all of the simulated data through the scenario setting module. For example, users can select specific laboratory environments, operation steps, and types and conditions of leakage events, and can also customize the number of personnel participating in the experiment to create unique experimental scenarios. This includes setting scenarios such as improper sample handling, equipment operation errors, or non-compliance with protective measures to cover various leakage possibilities.
[0070] The experimental environment parameters include several types of objects, including laboratories, experimental equipment, virtual personnel, and personal protective equipment; the experimental equipment includes experimental instruments and sample containers, such as microscopes, computers, petri dishes, centrifuges, etc.
[0071] Objects have several attributes, including static attributes, dynamic attributes, and interactive attributes; dynamic attributes include coordinates; static attributes are fixed attributes that do not change, and dynamic attributes are attributes that change dynamically over time, interaction, and status.
[0072] In this embodiment, virtual personnel include passive personnel directly controlled by users and automatic personnel that walk and move automatically; the data generation module also generates the activity trajectories of the automatic personnel; the activity trajectories include the coordinates and actions of virtual personnel at different time points, as Figure 7 shown. The generated information includes the types / activity steps of the experiments participated by virtual personnel, such as "changing into isolation pants in the changing room", "experimental personnel enter the experimental work area and perform...", etc., as well as the time point and location coordinate information at that time.
[0073] The dynamic attributes of virtual personnel include the infection status and the probability of being infected, and the infection status includes uninfected and infected.
[0074] Personal protective equipment includes wearable equipment such as masks, goggles, and protective clothing, as well as equipment such as disinfectant.
[0075] The experimental step parameters include multiple experimental steps with a sequential relationship, and the duration of each experimental step;
[0076] The event parameters include the types of leakage events, such as improper sample handling, experimental instrument failures, etc., and the probability of the event occurring, such as the probability of pathogen leakage when operating improperly; the leakage event is randomly triggered according to the probability of the event occurring;
[0077] The simulation platform module models and renders a three-dimensional model based on the experimental environment parameters and displays the three-dimensional model through the interaction and control module.
[0078] In this embodiment, based on the Unity3D engine, a three-dimensional model of a virtual laboratory is built to digitally reproduce elements such as laboratory equipment, operation areas, and experimental personnel, as Figures 2 to 4 shown. The graphics rendering ability of the Unity3D engine enables the virtual laboratory to have a realistic visual effect and interactive experience.
[0079] The three-dimensional model corresponding to the laboratory is divided into several areas; each area has independent dynamic attributes, including the infection probability; the three-dimensional models corresponding to the experimental equipment and virtual personnel respectively have partial or all interactive attributes; the interactive attributes include being collidable and movable;
[0080] The user interacts with the three-dimensional model through the interaction control module to conduct simulation experiments; among them, the virtual personnel interact with personal protective equipment, and can simulate wearing or removing personal protective equipment, etc.
[0081] As Figure 8 shown, the transmission path and epidemiological investigation module also tracks and records the activity trajectories of passive personnel, that is, the activity trajectories of virtual personnel directly controlled by the user.
[0082] When a leakage event is triggered, the transmission path and epidemiological investigation module simulates the transmission path and diffusion speed of pathogens according to the infectious disease dynamics model and the geographical diffusion model, and combines the activity trajectories to dynamically adjust the infection probability of the area at different time points.
[0083] In this embodiment, within the same area, as the number of virtual personnel wearing personal protective equipment increases, the infection probability of the area decreases. And the infection probability of virtual personnel who have already worn personal protective equipment is greater than that of virtual personnel who have not worn personal protective equipment.
[0084] The transmission path and epidemiological investigation module modifies the infection status of virtual personnel according to the infection probability and the probability of being infected. Specifically, for the combined application of the two probabilities, weight calculation can be used. For example, a represents the infection probability, A is the first weight, b represents the probability of being infected, B is the second weight, A + B = 1, and the final random probability is a×A + b×B, and the infection status is changed according to the final random probability. It is also possible to randomly increase or decrease the probability of being infected according to the infection probability, and then change the infection status according to the final probability of being infected. The two specific methods provided here are to illustrate the feasible influence methods and logical processing methods between the infection probability, the probability of being infected, and the infection status, and are not restrictive.
[0085] In addition, when an uninfected virtual person comes into contact with an infected virtual person, the probability of the uninfected virtual person being infected increases, or the infection status of the uninfected virtual person is directly changed to infected. This can more realistically simulate the infection transmission process in the real environment.
[0086] The early warning and assessment module monitors the data changes of the 3D model in real time; when the monitored data is within the preset threshold range, the system triggers an alarm, and the early warning and assessment module generates a multi-dimensional quantitative assessment report, including the possibility of the final pathogen / virus leaking from the laboratory, the number of infected people, and the affected range, etc.; the multi-dimensional quantitative assessment report is displayed through the interactive control module.
[0087] In this embodiment, when an alarm is triggered, the early warning and assessment module conducts a risk assessment according to the preset risk standard, generates an assessment report, and at the same time provides suggestions for emergency measures through the interactive control module, such as increasing protection, isolation, emergency evacuation, etc. Different suggestions correspond to different risk levels. For example, after quantitative assessment, the obtained risk levels are level 1, level 2, and level 3 respectively. The higher the level, the greater the risk. When the risk is level 1, only personnel protection needs to be increased; when the risk is level 2, infected personnel need to be isolated separately; when the risk is level 3, uninfected personnel need to be evacuated urgently.
[0088] A number of data generated during the simulation experiment are stored in the data storage module. In this embodiment, when the simulation experiment ends, leakage data is obtained; the leakage data includes the infection status of virtual personnel in each area;
[0089] The leakage data is stored in the data storage module; the data storage module also collects simulation data according to the predefined collection frequency; the data storage module also records and stores the operation steps performed by the user through the interactive control module, such as Figure 9 shown.
[0090] The data analysis module analyzes the high-risk factors in the simulation experiment based on the leakage data and operation steps, and dynamically modifies the risk assessment criteria according to the high-risk factors; the high-risk factors are the risk factors that appear more than the preset number of times in several simulation experiments; the risk factors include experimental environment parameters and operation steps.
[0091] In this embodiment, the backend system is developed based on the Django framework. The data generation module, the transmission path and epidemiological investigation module, the early warning and assessment module, etc., which are involved in the background data logic processing, are all the content of the backend system. Using the Django framework, the backend system generates and manages the experimental events and leakage scenario data that may occur in the virtual experiment. The data storage module is a SQL database located in the cloud. Django connects to the SQL database and stores information such as experimental events and coordinates in the database to support real-time event calls and data interactions. The front-end Unity3D interface generates specific experimental events or simulation scenarios according to the backend data. When the experimental scenario changes or a new event needs to be triggered, the front-end can call the corresponding data from the backend to dynamically update the rendering and interaction of the experimental scenario.
[0092] Based on the disclosure and teachings of the above specification, those skilled in the art to which the present invention pertains can also make changes and modifications to the above embodiments. Therefore, the present invention is not limited to the specific embodiments disclosed and described above, and some modifications and changes to the present invention should also fall within the protection scope of the claims of the present invention. In addition, although some specific terms are used in this specification, these terms are only for convenience of description and do not constitute any limitation to the present invention.
Claims
1. A visual simulation operating system for virus experiments, characterized in that, It includes an interaction control module, a simulation platform module, a data generation module, a transmission path and epidemiological investigation module, a warning and assessment module, and a data storage module; The data generation module is used to generate simulation data, including experimental environment parameters, experimental step parameters, and event parameters; The experimental environment parameters include several types of objects, including laboratories, experimental equipment, and virtual personnel; the experimental equipment includes experimental instruments and sample containers; the objects have several attributes, including static attributes, dynamic attributes, and interactive attributes; the dynamic attributes include coordinates; the dynamic attributes of the virtual personnel include the infection status; The experimental step parameters include multiple experimental steps with a sequential relationship, and the duration of each experimental step; The event parameters include the type of leakage event and the event occurrence probability; the leakage event is randomly triggered according to the event occurrence probability; The simulation platform module models and renders a 3D model according to the experimental environment parameters, and displays the 3D model through the interaction and control module; the 3D model corresponding to the laboratory is divided into several regions; each region has independent dynamic attributes, including the infection probability; the 3D models corresponding to the experimental equipment and the virtual personnel respectively have some or all of the interactive attributes; the interactive attributes include collidable and movable; The user interacts with the 3D model through the interaction control module to conduct a simulation experiment; When the leakage event is triggered, the transmission path and epidemiological investigation module simulates the transmission path and diffusion speed of the pathogen according to the infectious disease dynamics model and the geographical diffusion model, dynamically adjusts the infection probability of the region at different time points, and modifies the infection status of the virtual personnel according to the infection probability; the infection status includes uninfected and infected; The warning and assessment module monitors the data changes of the 3D model in real time; when the monitored data is within the preset threshold range, the system triggers an alarm, and the warning and assessment module generates a multi-dimensional quantitative assessment report; the multi-dimensional quantitative assessment report is displayed through the interaction control module; Several items of data generated during the simulation experiment are stored in the data storage module.
2. The visual virus experiment simulation operating system according to claim 1, wherein The data storage module stores several items of pre-set simulation data; The data generation module randomly generates the simulation data, or directly loads the simulation data from the data storage module, or is a combination of both.
3. The visual virus experiment simulation operating system according to claim 2, characterized in that, The data generation module has a sub-module, including a scenario setting module; the scenario setting module is used for the user to customize some or all of the simulation data; The data generation module randomly generates the simulation data, or directly loads the simulation data from the data storage module, or the user customizes the simulation data through the scenario setting module, or is any combination application of the three.
4. A visual virus experiment simulation operating system according to claim 1, characterized in that, The experimental environment parameters also include personal protective equipment; in the 3D model, the virtual personnel interact with the personal protective equipment to simulate wearing or removing the personal protective equipment; When the leakage event is triggered, within the same area, the number of virtual personnel wearing the personal protective equipment increases, and the infection probability of the area decreases.
5. A visual virus experiment simulation operating system according to claim 4, characterized in that, The dynamic attributes of the virtual personnel include the probability of being infected; among them, when the leakage event is triggered, the probability of being infected of the virtual personnel wearing the personal protective equipment is greater than that of the virtual personnel not wearing the personal protective equipment; The transmission path and epidemiological investigation module modify the infection status of the virtual personnel according to the infection probability and the probability of being infected.
6. A visual virus experiment simulation operating system according to claim 1, characterized in that, When an uninfected virtual person comes into contact with an infected virtual person, the probability of the uninfected virtual person being infected increases, or the infection status of the uninfected virtual person is modified to infected.
7. A visual virus experiment simulation operating system according to claim 1, characterized in that The virtual personnel include passive personnel directly controlled by the user and automatic personnel that walk and move automatically; the data generation module also generates the activity trajectories of the automatic personnel; the activity trajectories include the coordinates and actions of the virtual personnel at different time points; The transmission path and epidemiological investigation module also tracks and records the activity trajectories of the passive personnel; When the leakage event is triggered, the transmission path and epidemiological investigation module simulates the transmission path and diffusion speed of the pathogen according to the infectious disease dynamics model and the geographical diffusion model, in combination with the activity trajectories.
8. A visual virus experiment simulation operating system according to claim 1, characterized in that, When an alarm is triggered, the early warning and assessment module conducts a risk assessment according to the preset risk criteria, generates an assessment report, and at the same time provides suggestions for emergency measures through the interactive control module.
9. A visual virus experiment simulation operating system according to claim 8, characterized in that, When the simulation experiment ends, leakage data is obtained; the leakage data includes the infection status of the virtual personnel in each area; The leakage data is stored in the data storage module; the data storage module also collects the simulation data at a predefined collection frequency; the data storage module also records and stores the operation steps performed by the user through the interactive control module; It also includes a data analysis module; the data analysis module analyzes the high-risk factors in the simulation experiment according to the leakage data and the operation steps, and dynamically modifies the risk assessment criteria according to the high-risk factors; the high-risk factors are the risk factors that appear more than the preset number of times in several simulation experiments; the risk factors include the experimental environment parameters and the operation steps.
10. A visual virus experiment simulation operating system according to claim 7, characterized in that, In the same simulation experiment, the number of passive personnel is one or more.