A method and system for switching emergency command and dispatch interface

Abstract

The invention provides a method and system for switching an emergency command and dispatch interface, and relates to the technical field of management systems. The method comprises: using the top-level container of the interface as a root function module and the function modules required by the interface as sub-function modules to construct an interface tree structure; using the root function module as a basic coordinate system and using a layered mounting technology to mount other sub-function modules on the root function module with relative coordinates; obtaining a switching instruction for an emergency command and dispatch scene interface; loading a target root function module corresponding to a target scene interface of the emergency command and dispatch, and updating a reference path of the target root function module; using a dynamic detail level strategy to dynamically adjust the data sampling frequency of each sensor in each sub-function module according to the distance from the place where the emergency event occurs; loading the underlying data required by each sub-function module in real time according to the data sampling frequency of each sensor; and displaying each sub-function module in the target scene interface of the emergency command and dispatch.

Description

Technical Field

[0001] The present invention relates to the technical field of management systems, and in particular to a method and system for switching emergency command and dispatch interfaces. Background Art

[0002] The emergency command and dispatch system, which integrates video conferencing, professional information systems, video surveillance systems, and network communication technologies, plays a vital role in responding to emergencies and is increasingly being used by government departments at all levels and in various industries. However, different application scenarios have different requirements for the emergency command and dispatch system.

[0003] Existing emergency command and dispatch systems often have problems with switching between different scenarios, such as slow switching speeds, inaccurate information display, and complex operations, which may lead to the inability to conduct command and dispatch in a timely and effective manner in emergency situations. Summary of the invention

[0004] In order to solve the technical problems that the current emergency command and dispatch system often has slow switching speed, inaccurate display information, and complex operation when switching between different scenes, which may lead to the inability to conduct command and dispatch in an emergency in an effective manner, delay rescue opportunities, and cause greater losses, the present invention provides a switching method and system for an emergency command and dispatch interface.

[0005] The technical solution provided by the embodiment of the present invention is as follows:

[0006] First aspect:

[0007] An embodiment of the present invention provides a method for switching an emergency command and dispatch interface, comprising:

[0008] S1: Take the top-level container of the interface as the root functional module and the functional modules required by the interface as sub-functional modules to build the tree structure of the interface;

[0009] S2: According to the tree structure of the interface, with the root function module as the basic coordinate system, using the layered mounting technology, other sub-function modules are mounted on the root function module with relative coordinates;

[0010] S3: Obtain the switching instruction of the emergency command and dispatch scene interface;

[0011] S4: In response to the interface switching instruction, load the target root function module corresponding to the emergency command and dispatch target scene interface, update the reference path of the target root function module, and determine the sub-function module mounted on the target root function module;

[0012] S5: Use a dynamic level of detail strategy to dynamically adjust the data sampling frequency of each sensor in each sub-functional module according to the distance from the emergency site;

[0013] S6: Load the underlying data required by each sub-functional module in real time according to the data sampling frequency of each sensor;

[0014] S7: In the emergency command and dispatch target scene interface, various sub-function modules are displayed.

[0015] Second aspect:

[0016] An embodiment of the present invention provides a switching system for an emergency command and dispatch interface, which is applied to an unmanned ship and includes:

[0017] processor;

[0018] A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method for switching the emergency command and dispatch interface as described in the first aspect is implemented.

[0019] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0020] (1) In the present invention, the root function module is used as the basic coordinate system, and the layered mounting technology is used to mount other sub-function modules on the root function module with relative coordinates. Different modules are independent and collaborative. When switching scenes, it is only necessary to load the reference path of the target root function module and its sub-modules without reloading the entire system, which significantly shortens the switching time, ensures timely and effective command and dispatch in emergency situations, and improves the timeliness of rescue.

[0021] (2) In the present invention, a dynamic level of detail strategy is used to dynamically adjust the data sampling frequency of each sensor in each sub-functional module according to the distance from the emergency site. According to the data sampling frequency of each sensor, the underlying data required by each sub-functional module is loaded in real time, thereby avoiding redundant data transmission, saving computing resources and communication bandwidth, and further shortening the switching time. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 A schematic diagram of a flow chart of a method for switching an emergency command and dispatch interface provided by an embodiment of the present invention;

[0024] Figure 2A structural schematic diagram of a switching system for an emergency command and dispatch interface provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0026] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0027] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0028] Reference Manual Attached Figure 1 , showing a flow chart of a method for switching an emergency command and dispatch interface provided by an embodiment of the present invention.

[0029] The embodiment of the present invention provides a method for switching an emergency command and dispatch interface, comprising the following steps:

[0030] S1: Take the top-level container of the interface as the root functional module and the functional modules required by the interface as sub-functional modules to build a tree structure of the interface.

[0031] Among them, the top-level container of the interface is the core parent container of the entire emergency command and dispatch system interface. It serves as the basic carrier and organizational framework for all functional modules. The top-level container defines the overall layout, structure, interaction logic, and mounting rules of each sub-functional module of the interface. The top-level container is the root node of the system interface. Through a unified coordinate system and hierarchical mounting technology, it manages all sub-functional modules and is responsible for coordinating the interaction and data flow between modules.

[0032] Taking the natural disaster scene interface as an example, the root function module is the root node, and four sub-nodes can be set below it. Each sub-node corresponds to the earthquake monitoring module, the disaster-affected personnel evacuation module, the rescue team dispatch module and the meteorological information module. The earthquake monitoring module displays the location of the earthquake epicenter, the magnitude distribution, and the disaster-affected area, and provides real-time monitoring data, such as magnitude, focal depth, and aftershock activity. The disaster-affected personnel evacuation module displays a heat map of the distribution of personnel in the disaster-affected area, and provides evacuation route planning and dynamic adjustment functions. The rescue team dispatch module displays the real-time location, current status and dispatch plan of each rescue team, and supports the dynamic allocation of rescue forces and resource coordination. The meteorological information module provides real-time weather data (such as wind speed and rainfall) in the disaster-affected area, predicts meteorological changes in the next few hours, and assists in rescue decision-making.

[0033] In the present invention, modular design makes the system clearly structured and easy to develop and maintain functional modules independently. The independence and collaboration between modules are enhanced, avoiding the coupling problem between modules. When switching scenes, only the root functional module and its related submodules need to be loaded, without reloading the entire system, which significantly improves the switching speed and system response efficiency.

[0034] S2: According to the tree structure of the interface, with the root function module as the basic coordinate system, using the layered mounting technology, other sub-function modules are mounted on the root function module with relative coordinates.

[0035] Specifically, the tree structure of the interface uses the top-level container (root function module) as the basic coordinate system, and each sub-function module defines its own relative coordinates based on the coordinates of the parent node (the upper module). The layout and position of the modules are determined by the hierarchical relationship, which ensures the stability of the overall interface structure and the independence of the modules. The coordinates, size and arrangement of the sub-function modules are not based on the entire interface, but on the root function module or its parent node. The mounted sub-module automatically inherits the transformation operations such as scaling, rotation and movement of the parent module. The layered mounting technology ensures that the root module and important sub-modules are loaded first through rendering priority, ensuring that users can quickly see key content.

[0036] In the present invention, the hierarchical mounting technology is used to facilitate dynamic loading and unloading, significantly improving the flexibility and response speed of the system. By using relative coordinates, the module layout is more flexible and adapts to the switching requirements of different scenarios. The hierarchical structure reduces the consumption of system resources, only the necessary modules need to be updated, and the complexity of maintenance and expansion is reduced, while ensuring that the interface structure is clear and easy to expand and manage.

[0037] S3: Obtain the switching instruction of the emergency command and dispatch scene interface.

[0038] Optionally, the emergency command and dispatch scenario interface includes: a natural disaster scenario interface, a public health event scenario interface, an accident and disaster scenario interface, and a social security event scenario interface.

[0039] S4: In response to the interface switching instruction, load the target root function module corresponding to the emergency command and dispatch target scene interface, update the reference path of the target root function module, and determine the sub-function module mounted on the target root function module.

[0040] S5: Use a dynamic level of detail strategy to dynamically adjust the data sampling frequency of each sensor in each sub-functional module according to the distance from the emergency site.

[0041] In a possible implementation, S5 specifically includes: dynamically adjusting the data sampling frequency of each sensor in each sub-functional module according to the following formula:

[0042]

[0043] in, f Indicates the data sampling frequency of the sensor, d Indicates the distance between the sensor location and the emergency event location. m Indicates meters.

[0044] In the present invention, through the dynamic detail level strategy, the data sampling frequency of each sensor is dynamically adjusted according to the distance from the emergency site, so as to prioritize the high real-time and accuracy of the core area information, maintain a high sampling frequency in the key area (close distance), and ensure accurate support for command decision-making; at the same time, the sampling frequency is reduced in the long-distance area to avoid unnecessary data redundancy, effectively save the system's computing resources and communication bandwidth, improve the performance and response speed of the overall system, and meet the resource optimization and rapid response requirements in emergency scenarios.

[0045] Furthermore, different types of emergency events have different requirements and importance for data sampling frequency. High-emergency events (such as fires and chemical leaks) require higher sampling frequencies to monitor changes in the core area in real time, such as the spread of fire sources or changes in the concentration of toxic substances. Low-emergency events (such as aftershock monitoring after an earthquake) require data that changes relatively slowly, so the sampling frequency can be appropriately reduced to reduce resource waste.

[0046] In order to make the data sampling frequency more accurately meet the needs of different emergency scenarios, the present invention introduces an emergency event type weight factor in the process of determining the data sampling frequency.

[0047] In a possible implementation, S5 specifically includes: dynamically adjusting the data sampling frequency of each sensor in each sub-functional module according to the following formula:

[0048]

[0049] in, f Indicates the data sampling frequency of the sensor, f m represents the base sampling frequency, α Represents the weight factor of the emergency event type. Different types of emergency events have different weight factors. d Indicates the distance between the sensor location and the emergency event location. d m Indicates the maximum distance, f 0 means fixed sampling frequency.

[0050] Optionally, the reference sampling frequency is generally 100% (full sampling), and those skilled in the art may set the reference sampling frequency according to actual conditions, which is not limited in the present invention.

[0051] In the present invention, by introducing emergency event type weight factors, the data sampling frequency of the sensor is dynamically adjusted according to different types of emergency events, so that the sampling frequency can more accurately meet the needs of different emergency scenarios. According to the urgency and information needs of the events, the real-time data of high-emergency events (such as fires, chemical leaks) can be prioritized and the monitoring accuracy of core areas can be improved. At the same time, unnecessary resource consumption can be reduced in low-priority or low-emergency events, the system's computing and communication resource allocation can be optimized, and the overall performance and response efficiency can be improved, thereby achieving more intelligent and precise resource management and decision support in multi-scenario emergency command.

[0052] S6: According to the data sampling frequency of each sensor, the underlying data required by each sub-functional module is loaded in real time.

[0053] In a possible implementation, S6 specifically includes sub-steps S601 to S604:

[0054] S601: updating the loading task list in real time according to the determined data sampling frequency.

[0055] S602: Calculate the load balancing factor between the current CPU and GPU:

[0056]

[0057] in, s represents the load factor, s represents the speedup ratio, m Indicates the number of CPU collaborative computing cores, T CPU represents the execution time of the CPU serial algorithm, T GPURepresents the execution time of GPU serial algorithm.

[0058] It should be noted that the load balancing factor is a dynamic parameter used to measure and optimize the task distribution ratio between the CPU and GPU. By calculating the performance of the CPU and GPU in the system and the current task execution time, it ensures that the two can work together efficiently, thereby achieving optimal load distribution and resource utilization.

[0059] S603: Allocate loading tasks to the CPU and GPU according to the load balancing factor:

[0060]

[0061] in, L CPU Indicates the amount of loading tasks assigned to the CPU. L GPU Indicates the amount of loading tasks assigned to the GPU, L Indicates the total loading task amount.

[0062] S604: Load the underlying data in parallel through the CPU and GPU.

[0063] In the present invention, by introducing a load balancing factor, the loading task amount is dynamically allocated according to the performance of the CPU and GPU and the current load status, so that the loading task of the underlying data can be efficiently and collaboratively processed in parallel between the CPU and GPU. The computing advantages of the CPU and GPU can be fully utilized to avoid resource waste or performance bottlenecks caused by uneven task allocation; by dynamically adjusting the task allocation ratio, the overall data loading efficiency of the system is improved, ensuring that the loading and processing of the underlying data can be completed in real time in high-load emergency scenarios, providing strong support for the rapid response and accurate display of sub-functional modules.

[0064] S7: In the emergency command and dispatch target scenario interface, each sub-function module is displayed.

[0065] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0066] (1) In the present invention, the root function module is used as the basic coordinate system, and the layered mounting technology is used to mount other sub-function modules on the root function module with relative coordinates. Different modules are independent and collaborative. When switching scenes, it is only necessary to load the reference path of the target root function module and its sub-modules without reloading the entire system, which significantly shortens the switching time, ensures timely and effective command and dispatch in emergency situations, and improves the timeliness of rescue.

[0067] (2) In the present invention, a dynamic level of detail strategy is used to dynamically adjust the data sampling frequency of each sensor in each sub-functional module according to the distance from the emergency site. According to the data sampling frequency of each sensor, the underlying data required by each sub-functional module is loaded in real time, thereby avoiding redundant data transmission, saving computing resources and communication bandwidth, and further shortening the switching time.

[0068] In a possible implementation, the method for switching the emergency command and dispatch interface further includes S8 to S10:

[0069] S8: Calculate the matching degree between the current emergency event and each historical emergency event based on the underlying data of the current emergency event.

[0070] Optionally, S8 specifically includes sub-steps S801 and S802:

[0071] S801: Extracting event features of the current emergency event based on the underlying data of the current emergency event.

[0072] Optionally, the event characteristics specifically include: geographical location, terrain features, distance from key facilities, event coverage, event type, event scale, event occurrence time, event duration, season, weather conditions, required rescue personnel, required equipment, required supplies, required transportation, injuries, number of trapped people, and distribution of trapped people.

[0073] S802: Use weighted Euclidean distance to calculate the matching degree between the current emergency event and each historical emergency event:

[0074]

[0075] in, s k Indicates the current emergency and k The matching degree between historical emergency events, x i Indicates the current emergency event i Event characteristics, x ki Indicates k The first historical emergency i Event characteristics, l i Indicates i The weight coefficient of each event feature, n Represents the total number of event features.

[0076] In the present invention, by assigning weights to different event features, the impact of each feature on the matching results can be flexibly adjusted to make the calculation more accurate and in line with actual needs; the weighting mechanism can highlight the importance of key features (such as geographic location, event type, etc.) to the matching degree, reduce the interference of secondary features, thereby improving the accuracy and credibility of the matching results, and helping to quickly and scientifically extract the most relevant events from historical data, providing more reliable reference and disposal support for current emergency events.

[0077] Optionally, the weight coefficient of each event feature is determined in the following manner: with the goal of improving the rationality of the matching degree, the weight coefficient of each event feature is determined by a bat optimization algorithm.

[0078] Specifically, historical events can be sorted according to the matching degree, with events with higher matching degrees being ranked first, and then the ranking of the real disposal effects of historical events can be obtained. According to the similarity between the matching degree ranking and the real disposal effect ranking, a fitness function can be constructed to quantify the rationality of the matching degree. The higher the similarity between the matching degree ranking and the real disposal effect ranking, the more reasonable the matching degree calculation method is.

[0079] Optionally, the Spearman rank correlation coefficient or the Kendall rank correlation coefficient may be used to measure the similarity between two rankings.

[0080] Initialize the bat individuals, each bat individual represents a feasible set of weight coefficients, each bat individual is composed of multiple dimensional components, and each component represents the weight coefficient of an event feature.

[0081] In the global search phase, update the flight speed and position of individual bats:

[0082]

[0083] in, f i Indicates i The pulse emission frequency of individual bats, f min Indicates the minimum value of pulse transmission frequency, f max Indicates the maximum value of pulse emission frequency, β t express t The nonlinear arccosine acceleration factor for the iteration, express t +1 iteration i The speed of individual bats, r 1. r 2 represents a random number between 0 and 1, oh t expresst The inertia weight factor at the iteration, express t The iteration i The speed of individual bats, represents the individual optimal solution, c i represents the learning factor, x * represents the global optimal solution, express t The iteration i The location of individual bats, express t +1 iteration i The position of each bat individual, Levy Represents the Levy flight step length.

[0084] It should be noted that the combination of global search and random optimization strategies enhances the algorithm's exploration ability, enables it to jump out of local optimality and quickly locate potential high-quality solutions in the solution space. At the same time, through the adjustment of learning factors and inertia weights, it focuses on fine search around the optimal solution in the later convergence process, thereby improving the algorithm's convergence speed and solution accuracy, providing a more stable and efficient solution to complex optimization problems.

[0085] Optionally, the inertia weight factor is specifically:

[0086]

[0087] in, oh t express t The inertia weight factor at the iteration, oh min represents the minimum inertia weight factor, oh max represents the maximum inertia weight factor, t Indicates the current iteration number, T Indicates the maximum number of iterations.

[0088] It should be noted that in the early stage of the algorithm (exploration stage), a larger inertia weight factor provides stronger global search capabilities, which helps to explore potential high-quality solutions in a wide solution space; in the later stage of the algorithm (convergence stage), a smaller inertia weight factor enhances local search capabilities and helps the algorithm focus on fine optimization around the optimal solution. The advantage of this is that it can effectively prevent the algorithm from falling into the local optimum, while accelerating the convergence speed and improving the accuracy and stability of the optimization results.

[0089] Optionally, the nonlinear arccosine acceleration factor is specifically:

[0090]

[0091] Among them, arccos represents the inverse cosine function, t Indicates the current iteration number, T Indicates the maximum number of iterations.

[0092] It should be noted that by introducing the nonlinear arccosine acceleration factor, the nonlinear change in the optimization process gradually accelerates from the initial slow growth and finally stabilizes. Maintaining a relatively slow change in the early stage of the algorithm ensures that the solution space can be fully explored in the global search stage; accelerating the search in the middle and late stages to improve the convergence speed of the algorithm and gradually focus on the optimal solution; finally completing the iteration in a stable state to avoid missing the global optimal solution due to too fast convergence.

[0093] Optionally, the learning factor is specifically:

[0094]

[0095] in, c i Indicates i The learning factor of each bat, c max represents the maximum learning factor, c min Represents the minimum learning factor.

[0096] It should be noted that in the early stage of the algorithm, a larger learning factor can enhance the individual's ability to learn the global optimal solution and speed up the global search; in the later stage, as the learning factor gradually decreases, the individual pays more attention to the local search around its own optimal solution, improves the search accuracy, and avoids skipping the optimal solution.

[0097] Optionally, the Levy flight step length is specifically:

[0098]

[0099] Where Γ represents the standard Gamma function, l represents the exponential parameter, s Represents a size parameter.

[0100] It should be noted that by introducing the Levy flight step and utilizing its random search method with long jump characteristics, it is possible to achieve a combination of long-distance jumps and local fine-tuning in the solution space. This allows individuals to perform local searches in the solution space and have a high probability of jumping to a position far away from the current solution, thus avoiding falling into the local optimal solution.

[0101] Randomly generate a number between 0 and 1 r 3. Determine the random number r3 is greater than the pulse rate. If so, enter the local search phase. Otherwise, enter the update pulse rate and pulse average loudness.

[0102] In the local search phase, a solution is selected from the optimal solution set to generate a new local solution:

[0103]

[0104] in, express t The iteration i The average loudness of the pulses emitted by individual bats, e Represents a random number between 0 and 1. express t The iteration i The average loudness of the pulses emitted by individual bats.

[0105] It should be noted that by randomly fine-tuning, potential better solutions are explored near the optimal solution to avoid the search process from falling into premature convergence. At the same time, the dynamic change of pulse loudness is used to gradually reduce the search amplitude, thereby improving the accuracy of the solution. While maintaining the search diversity, the ability of local search is enhanced, which helps to improve the optimization effect of the algorithm and the quality of the solution.

[0106] Calculate the fitness value of the new local solution and generate a random number between 0 and 1 r 4. Determine whether it is satisfied and If yes, accept the new local solution. Otherwise, do not accept the new local solution.

[0107] Update the pulse rate and average loudness of the pulses:

[0108]

[0109] in, express t +1 iteration i The pulse rate emitted by individual bats, Indicates i The initial pulse rate emitted by individual bats, e represents a natural constant, c represents the pulse rate enhancement factor, express t The iteration i The average loudness of the pulses emitted by individual bats, α Represents the pulse loudness attenuation coefficient.

[0110] Determine whether the current number of iterations has reached the maximum number of iterations; if so, output the weight coefficient set representing the bat individual with the highest current fitness; otherwise, return to continue iterating.

[0111] In the present invention, determining the weight coefficients of event features through a bat optimization algorithm can effectively explore the optimal weight combination to maximize the accuracy of the matching degree.

[0112] S9: Determine the recommended emergency response plan based on the handling method of the historical emergency events with the highest matching degree.

[0113] S10: In the emergency command and dispatch target scenario interface, the recommended emergency response plan is displayed.

[0114] In the present invention, historical emergency event data is matched with the current event, and a recommended emergency response plan is generated based on the handling method of the historical event with the highest matching degree, and intuitively displayed in the target scenario interface. The experience and handling plans of historical events are used to quickly provide scientific and practical decision-making support for the current event, reduce the analysis time of commanders, and improve the efficiency and accuracy of emergency response. At the same time, the data-driven matching method can improve the reliability and pertinence of the plan, ensure that command and dispatch are carried out more efficiently and accurately, thereby minimizing the losses of emergencies.

[0115] Reference Manual Attached Figure 2 , showing a structural schematic diagram of a switching system for an emergency command and dispatch interface provided by an embodiment of the present invention.

[0116] The present invention also provides a switching system 20 for an emergency command and dispatch interface, comprising:

[0117] Processor 201;

[0118] The memory 202 stores computer-readable instructions, and when the computer-readable instructions are executed by the processor 201, the method for switching the emergency command and dispatch interface as described in the method embodiment is implemented.

[0119] The emergency command and dispatch interface switching system 20 provided by the present invention can execute the above-mentioned emergency command and dispatch interface switching method and achieve the same or similar technical effects. To avoid repetition, the present invention will not go into details.

[0120] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0121] (1) In the present invention, the root function module is used as the basic coordinate system, and the layered mounting technology is used to mount other sub-function modules on the root function module with relative coordinates. Different modules are independent and collaborative. When switching scenes, it is only necessary to load the reference path of the target root function module and its sub-modules without reloading the entire system, which significantly shortens the switching time, ensures timely and effective command and dispatch in emergency situations, and improves the timeliness of rescue.

[0122] (2) In the present invention, a dynamic level of detail strategy is used to dynamically adjust the data sampling frequency of each sensor in each sub-functional module according to the distance from the emergency site. According to the data sampling frequency of each sensor, the underlying data required by each sub-functional module is loaded in real time, thereby avoiding redundant data transmission, saving computing resources and communication bandwidth, and further shortening the switching time.

[0123] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0124] There are a few points to note:

[0125] (1) The drawings of the embodiments of the present invention only involve structures related to the embodiments of the present invention. Other structures may refer to conventional designs.

[0126] (2) For the sake of clarity, in the drawings used to describe the embodiments of the present invention, the thickness of the film or region is exaggerated or reduced, that is, these drawings are not drawn according to the actual scale. It is understood that when an element such as a film, a region or a substrate is referred to as being "on" or "under" another element, the element may be "directly" "on" or "under" the other element or there may be intermediate elements.

[0127] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to obtain new embodiments.

[0128] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for switching an emergency command and dispatch interface, characterized in that: include: S1: Take the top-level container of the interface as the root functional module and the functional modules required by the interface as sub-functional modules to build the tree structure of the interface; S2: According to the tree structure of the interface, with the root function module as the basic coordinate system, using the layered mounting technology, other sub-function modules are mounted on the root function module with relative coordinates; S3: Obtain the switching instruction of the emergency command and dispatch scene interface; S4: In response to the interface switching instruction, load the target root function module corresponding to the emergency command and dispatch target scene interface, update the reference path of the target root function module, and determine the sub-function module mounted on the target root function module; S5: Use a dynamic level of detail strategy to dynamically adjust the data sampling frequency of each sensor in each sub-functional module according to the distance from the emergency site; S6: Load the underlying data required by each sub-functional module in real time according to the data sampling frequency of each sensor; S7: In the emergency command and dispatch target scene interface, various sub-function modules are displayed.

2. The method for switching the emergency command and dispatch interface according to claim 1, characterized in that: The emergency command and dispatch scenario interface includes: a natural disaster scenario interface, a public health event scenario interface, an accident and disaster scenario interface, and a social security event scenario interface.

3. The method for switching the emergency command and dispatch interface according to claim 1, characterized in that: The S5 is specifically: According to the following formula, the data sampling frequency of each sensor in each sub-function module is dynamically adjusted: in, f Indicates the data sampling frequency of the sensor, d Indicates the distance between the sensor location and the emergency event location. m Indicates meters.

4. The method for switching the emergency command and dispatch interface according to claim 1, characterized in that: The S5 is specifically: According to the following formula, the data sampling frequency of each sensor in each sub-function module is dynamically adjusted: in, f Indicates the data sampling frequency of the sensor, f m represents the base sampling frequency, α Represents the weight factor of the emergency event type. Different types of emergency events have different weight factors. d Indicates the distance between the sensor location and the emergency event location. d m Indicates the maximum distance, f 0 means fixed sampling frequency.

5. The method for switching the emergency command and dispatch interface according to claim 1, characterized in that: The S6 specifically includes: S601: updating the loading task list in real time according to the determined data sampling frequency; S602: Calculate the load balancing factor between the current CPU and GPU: in, σ represents the load factor, s represents the speedup ratio, m Indicates the number of CPU collaborative computing cores, T CPU represents the execution time of the CPU serial algorithm, T GPU Represents the execution time of GPU serial algorithm; S603: Allocate loading tasks to the CPU and GPU according to the load balancing factor: in, L CPU Indicates the amount of load tasks assigned to the CPU. L GPU Indicates the amount of loading tasks assigned to the GPU, L Indicates the total loading task volume; S604: Load the underlying data in parallel through the CPU and GPU.

6. The method for switching the emergency command and dispatch interface according to claim 1, characterized in that: Also includes: S8: Calculate the matching degree between the current emergency event and each historical emergency event based on the underlying data of the current emergency event; S9: Determine the recommended emergency response plan based on the historical emergency response method with the highest matching degree; S10: Displaying the recommended emergency response plan in the emergency command and dispatch target scenario interface.

7. The method for switching the emergency command and dispatch interface according to claim 6, characterized in that: The S8 specifically includes: S801: extracting event features of the current emergency event based on the underlying data of the current emergency event; S802: Use weighted Euclidean distance to calculate the matching degree between the current emergency event and each historical emergency event: in, σ k Indicates the current emergency and k The matching degree between historical emergency events, x i Indicates the current emergency event i Event characteristics, x ki Indicates k The first historical emergency i Event characteristics, λ i Indicates i The weight coefficient of each event feature, n Represents the total number of event features.

8. The method for switching the emergency command and dispatch interface according to claim 7, characterized in that: The event characteristics specifically include: geographical location, terrain features, distance from key facilities, event coverage, event type, event scale, event occurrence time, event duration, season, weather conditions, required rescue personnel, required equipment, required materials, required transportation, injuries, number of trapped people, and distribution of trapped people.

9. The method for switching the emergency command and dispatch interface according to claim 7, characterized in that: The weight coefficients of the event features are determined as follows: With the goal of improving the rationality of the matching degree, the weight coefficients of the characteristics of each event are determined through the bat optimization algorithm.

10. A switching system for emergency command and dispatch interface, characterized in that: include: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method for switching the emergency command and dispatch interface according to any one of claims 1 to 9 is implemented.

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