Personnel flow monitoring method and system, storage medium and electronic device

Abstract

The embodiment of the invention provides a personnel flow direction monitoring method, a storage medium and an electronic device, and the method comprises the following steps: S1, building a target 2D plane graph according to the structure of a target region, building a corresponding target 2D coordinate system, and dividing corresponding regions according to actual requirements; s2, deploying an evacuation indicating device comprising a Wi-Fi probe module or a Bluetooth probe module, and recording the two-dimensional coordinate position of each module; s3, after the person enters the target area, the probe obtains information of a Bluetooth beacon carried by the user or an intelligent device with a Wi-Fi connection function and uploads the information to the control host; s4, the control host cleans and combines the data from the probe, and then calculates the time of the personnel passing through each monitoring point on the path by using a personnel flow direction monitoring algorithm based on time point probability density estimation; and S5, the control host smoothly arranges the monitoring points through which the personnel pass according to time to obtain the flow track of the personnel in the target area.

Description

Technical Field

[0001] The present application relates to the technical field of personnel flow monitoring, and in particular to a personnel flow monitoring method, system, storage medium and electronic device. Background Art

[0002] People flow monitoring technology can track and analyze people's movement trajectories in real time. Currently, commonly used people flow monitoring technologies include infrared sensors, video surveillance, RFID technology, etc. These technologies can monitor the flow of people to a certain extent, but in complex indoor environments, especially public areas, due to factors such as building occlusion and light changes, the accuracy of these monitoring technologies may be affected. Public areas are usually densely populated, with complex building structures and diverse flow paths. Traditional flow monitoring technology is difficult to fully meet the needs of real-time monitoring and analysis of people flow.

[0003] Therefore, there is still a lack of an efficient and stable technical system that can accurately monitor the flow of people in real time and provide corresponding data support in case of fire or other emergencies to help analyze the behavior patterns and flow trends of the crowd. Summary of the invention

[0004] Each exemplary embodiment of the present application provides a method, system, storage medium and electronic device for monitoring the flow of people, so as to at least have the technical effect of solving the trends and behavior patterns of people in emergency situations with the advantages of low cost, anti-interference and easy deployment.

[0005] Each exemplary embodiment of the present application provides a method for monitoring the flow of people, comprising the following steps:

[0006] S1, establish a target 2D plane map according to the structure of the target area, establish a corresponding target two-dimensional coordinate system, and divide the corresponding area according to actual requirements;

[0007] S2, deploying an evacuation indication device including a Wi-Fi probe module or a Bluetooth probe module in the target area, and recording the two-dimensional coordinate position of each module on the target two-dimensional coordinate system;

[0008] S3, when a person enters the target area, the probe obtains information of a Bluetooth beacon or a smart device with a Wi-Fi connection function carried by the user and uploads it to the control host;

[0009] S4, the control host cleans and merges the data from the probes, and then uses a personnel flow monitoring algorithm based on time point probability density estimation to calculate the time when the personnel pass through each monitoring point on their path;

[0010] S5, the control host smoothly arranges the monitoring points where the personnel pass by according to time to obtain the flow trajectory of the personnel in the target area.

[0011] In one embodiment of the present application, a personnel flow monitoring system is also proposed, including:

[0012] The probe module is configured to establish a target 2D plane map according to the structure of the target area, establish a corresponding target two-dimensional coordinate system, and divide the corresponding area according to actual requirements; deploy an evacuation indication device including a Wi-Fi probe module or a Bluetooth probe module in the target area, and record the two-dimensional coordinate position of each module on the target two-dimensional coordinate system;

[0013] And control host module, including:

[0014] Data acquisition module: when a person enters the target area, the probe acquires the information of the Bluetooth beacon or smart device with Wi-Fi connection function carried by the user and uploads it to the control host;

[0015] The data processing module, the control host cleans and merges the data from the probes, and then uses a personnel flow monitoring algorithm based on time point probability density estimation to calculate the time when a person passes each monitoring point on his path;

[0016] The trajectory analysis module, the control host smoothly arranges the monitoring points passed by the personnel according to time to obtain the flow trajectory of the personnel in the target area.

[0017] In one embodiment of the present application, a computer-readable storage medium is further provided, wherein a computer program is stored in the storage medium, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0018] In one embodiment of the present application, an electronic device is also proposed, including a memory and a processor, characterized in that a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any of the above method embodiments.

[0019] The present application has the following beneficial effects: compared with the traditional monitoring method based on signal strength (RSSI), the personnel flow monitoring method based on time point probability density estimation is more applicable in underground parking lots, subway stations and other complex building environments. When the time window length is appropriate, it is not easily affected by signal electromagnetic wave reflection, diffraction and attenuation, and the monitoring efficiency is higher; the personnel flow monitoring method based on time point probability density estimation can know the time when a person passes through the monitoring point only by relying on the data of a single probe, and can be combined with the personnel evacuation indication sign in the building. Compared with the traditional monitoring method based on signal strength, the probe deployment cost is lower and the deployment method is simpler; the Gaussian kernel function processing, adaptive bandwidth and number of estimation points used in the monitoring algorithm are obtained by experiments based on different building environments, and the obtained personnel passing time is more accurate; the personnel flow trajectory information output by the method can track a single person, and can also reflect the flow of the crowd, and can perform human flow control and dangerous behavior identification, which is more efficient than traditional video tracking; the present invention realizes public area human flow management through the personnel flow monitoring method based on time point probability density estimation, and improves the management ability and risk identification ability of public areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0021] Figure 1 Schematic diagram of the steps for implementing the flow direction monitoring method of the present invention;

[0022] Figure 2 It is a structural schematic diagram of a method for monitoring the flow of people based on time point probability density estimation of the present invention;

[0023] Figure 3 It is a schematic diagram of the workflow of the personnel flow monitoring method based on time point probability density estimation of the present invention;

[0024] Figure 4 It is a schematic diagram of the workflow of the personnel flow monitoring algorithm based on time point probability density estimation of the present invention;

[0025] Figure 5 It is a schematic diagram of an optional electronic device structure according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the preferred embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0027] like Figures 1 to 3 As shown, a personnel flow monitoring method structure based on time point probability density estimation and its workflow are characterized by comprising the following steps:

[0028] S1, establish a target 2D plane map according to the structure of the target area, establish a corresponding target two-dimensional coordinate system, and divide the corresponding area according to actual requirements;

[0029] S2, deploying an evacuation indication device including a Wi-Fi probe module or a Bluetooth probe module in the target area, and recording the two-dimensional coordinate position of each module on the target two-dimensional coordinate system;

[0030] S3, when a person enters the target area, the probe obtains information of a Bluetooth beacon or a smart device with a Wi-Fi connection function carried by the user and uploads it to the control host;

[0031] S4, the control host cleans and merges the data from the probes, and then uses a personnel flow monitoring algorithm based on time point probability density estimation to calculate the time when the personnel pass each monitoring point on their path;

[0032] S5, the control host smoothly arranges the monitoring points where the personnel pass by according to time to obtain the flow trajectory of the personnel in the target area.

[0033] It should be noted that the target area is the monitoring area, in which the control host cleans and merges the data from the probes, and then judges the time interval when each MAC address information is received. If the time interval is uniform in the entire calculation area and its RSSI information is relatively stable, it is considered that the monitoring target represented by the MAC address remains stationary at a point near the probe, and then the trajectory information of the MAC address is output as being stationary near a certain probe; otherwise, it is considered to be moving in the monitoring area; the personnel flow monitoring algorithm based on time point probability density estimation is used to calculate the time when personnel pass each monitoring point on their path.

[0034] In an optional implementation, the personnel flow monitoring algorithm based on time point probability density estimation in step S4 includes: when a person enters the target area and passes through an evacuation indication device containing a Wi-Fi probe module or a Bluetooth probe module, the probe continuously obtains information from the Bluetooth beacon carried by the user or the smart device with a Wi-Fi connection function, and obtains the precise time when the person passes through the monitoring point through the personnel flow monitoring algorithm based on time point probability density estimation, and uploads it to the control host; wherein, the time period from the first time the probe detects a new MAC address to the time when the MAC address is no longer monitored is the calculation area of ​​the algorithm, and the probability density function of all time points monitored in the area is calculated.

[0035] refer to Figure 4 In an optional implementation, a schematic diagram of the workflow of a personnel flow monitoring algorithm based on time point probability density estimation adopts a passive positioning method, and the information required for trajectory monitoring can be obtained without the need for smart devices to operate, and then a more accurate elapsed time is obtained through probability function estimation calculation. Step S4 includes:

[0036] S4.1, cleaning the data format received from each probe and merging the data of each probe into one file for subsequent calculation;

[0037] S4.2, the time interval when each MAC address information is received is judged. If the time interval is uniform in the entire calculation area and its RSSI information is relatively stable, it is considered that the monitoring target represented by the MAC address remains stationary at a point near the probe, and then the trajectory information of the MAC address is output as being stationary near a certain probe; otherwise, it is considered to be moving in the monitoring area;

[0038] S4,3, divide the calculation area into time windows, and determine the time window length according to the normal walking speed of adults and the distance between adjacent probes;

[0039] S4.4, treat the data information obtained by the probe as a random event (x 1 , x 2 , …, x n ), using the kernel function to estimate (the formula is ) estimates the probability density function of the time point in the time window, where the kernel function K takes the Gaussian kernel function (formula is ), the bandwidth h uses an adaptive bandwidth, and the number of estimated points in each time window is 100; after estimating its probability density function using the kernel density estimation method with parameters set as above, the two-dimensional curve image of the function has at least one peak structure;

[0040] S4.5, the control host identifies all the peaks of the probability density function and saves them into a new file.

[0041] In an optional implementation manner, in step S5,

[0042] S5.1, the control host screens the calculated points under the same MAC address in the calculated file;

[0043] S5.2, the control host sorts the screened points in chronological order to obtain the movement trajectory of the personnel in the monitoring area.

[0044] Based on the above personnel flow monitoring method, the present invention discloses a personnel flow monitoring system, which uses the above personnel flow monitoring method and includes:

[0045] The probe module is configured to establish a target 2D plane map according to the structure of the target area, establish a corresponding target two-dimensional coordinate system, and divide the corresponding area according to actual requirements; deploy an evacuation indication device including a Wi-Fi probe module or a Bluetooth probe module in the target area, and record the two-dimensional coordinate position of each module on the target two-dimensional coordinate system;

[0046] And control host module, including:

[0047] Data acquisition module: when a person enters the target area, the probe acquires the information of the Bluetooth beacon or smart device with Wi-Fi connection function carried by the user and uploads it to the control host;

[0048] The data processing module, the control host cleans and merges the data from the probes, and then uses a personnel flow monitoring algorithm based on time point probability density estimation to calculate the time when a person passes each monitoring point on his path;

[0049] The trajectory analysis module, the control host smoothly arranges the monitoring points passed by the personnel according to time to obtain the flow trajectory of the personnel in the target area.

[0050] Specifically, it includes an evacuation sign containing a Wi-Fi probe module or a Bluetooth probe module in a public area, which is powered by a fire power supply and includes a receiving antenna and a transmitting antenna or a transmission line; the control host includes a receiving processor, a receiving module, a data cleaning, a merging processing module, a probability density function estimation module, a function data processing module, a display module and an output module, and finally the control host outputs personnel flow information to the outside world.

[0051] The receiving antenna of the Wi-Fi probe module or the Bluetooth probe can obtain information of the Bluetooth beacon carried by the user or the smart device with Wi-Fi connection function, and the transmitting antenna or the transmission line can transmit the obtained information to the control host.

[0052] The receiving module of the control host can receive information obtained by the Bluetooth beacon carried by the user or the smart device with Wi-Fi connection function. The processing module processes the information, outputs the image through the display module, and outputs the personnel flow trajectory information to the management personnel or other devices through the output module.

[0053] According to another aspect of the embodiment of the present application, an electronic device for implementing the above-mentioned personnel flow monitoring method is also provided, and the above-mentioned electronic device can be but is not limited to being applied in a server. Figure 5 As shown, the electronic device includes a memory 402 and a processor 404. The memory 402 stores a computer program, and the processor 404 is configured to execute the steps in any of the above method embodiments through the computer program.

[0054] Optionally, in this embodiment, the electronic device may be located in at least one network device among a plurality of network devices of a computer network.

[0055] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0056] S1, establish a target 2D plane map according to the structure of the target area, establish a corresponding target two-dimensional coordinate system, and divide the corresponding area according to actual requirements;

[0057] S2, deploying an evacuation indication device including a Wi-Fi probe module or a Bluetooth probe module in the target area, and recording the two-dimensional coordinate position of each module on the target two-dimensional coordinate system;

[0058] S3, when a person enters the target area, the probe obtains information of a Bluetooth beacon or a smart device with a Wi-Fi connection function carried by the user and uploads it to the control host;

[0059] S4, the control host cleans and merges the data from the probes, and then uses a personnel flow monitoring algorithm based on time point probability density estimation to calculate the time when the personnel pass through each monitoring point on their path;

[0060] S5, the control host smoothly arranges the monitoring points where the personnel pass by according to time to obtain the flow trajectory of the personnel in the target area.

[0061] Alternatively, a person skilled in the art may understand that: Figure 5 The structure shown is for illustration only, and the electronic device may also be a terminal device such as a mobile Internet device (MID) or a PAD. Figure 5 The structure of the electronic device is not limited. Figure 5More or fewer components (such as network interfaces, etc.) as shown in, or with Figure 5 Different configurations shown.

[0062] Among them, the memory 402 can be used to store software programs and modules, such as the method for determining the probability of occurrence of an event in the embodiment of the present application and the training method and device of the neural network model used therein, and the processor 404 executes various functional applications and data processing by running the software programs and modules stored in the memory 402, that is, to achieve the above-mentioned determination of the probability of occurrence of the event. The memory 402 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 402 may further include a memory remotely arranged relative to the processor 404, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof. Among them, the memory 402 may specifically be, but is not limited to, a program step for storing the determination of the probability of occurrence of an event.

[0063] Optionally, the transmission device 406 is used to receive or send data via a network. Specific examples of the network may include a wired network and a wireless network. In one example, the transmission device 406 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices and routers via a network cable so as to communicate with the Internet or a local area network. In one example, the transmission device 406 is a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0064] In addition, the electronic device further includes: a display 408 for displaying the operation status or fault display of the rectifier side or the inverter side; and a connection bus 410 for connecting various module components in the electronic device.

[0065] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when run.

[0066] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0067] S1, establish a target 2D plane map according to the structure of the target area, establish a corresponding target two-dimensional coordinate system, and divide the corresponding area according to actual requirements;

[0068] S2, deploying an evacuation indication device including a Wi-Fi probe module or a Bluetooth probe module in the target area, and recording the two-dimensional coordinate position of each module on the target two-dimensional coordinate system;

[0069] S3, when a person enters the target area, the probe obtains information of a Bluetooth beacon or a smart device with a Wi-Fi connection function carried by the user and uploads it to the control host;

[0070] S4, the control host cleans and merges the data from the probes, and then uses a personnel flow monitoring algorithm based on time point probability density estimation to calculate the time when the personnel pass through each monitoring point on their path;

[0071] S5, the control host smoothly arranges the monitoring points where the personnel pass by according to time to obtain the flow trajectory of the personnel in the target area.

[0072] Optionally, the storage medium is also configured to store a computer program for executing the steps included in the method in the above embodiment, which will not be described in detail in this embodiment.

[0073] Optionally, in this embodiment, a person of ordinary skill in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing hardware related to the terminal device through a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0074] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0075] If the integrated units in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in the above computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling one or more computer devices (which may be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application.

[0076] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0077] In the several embodiments provided in the present application, it should be understood that the disclosed client can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0078] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0079] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0080] The above is only a preferred embodiment of the present application. It should be noted that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present application, and these improvements and modifications should also be regarded as the scope of protection of the present application.

[0081] Although the preferred embodiments of the present application have been described, those skilled in the art, once knowing the basic creative concept, can make other changes and modifications according to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for monitoring personnel flow, characterized in that: The steps include: S1, establish a target 2D plane map according to the structure of the target area, establish a corresponding target two-dimensional coordinate system, and divide the corresponding area according to actual requirements; S2, deploying an evacuation indication device including a Wi-Fi probe module or a Bluetooth probe module in the target area, and recording the two-dimensional coordinate position of each module on the target two-dimensional coordinate system; S3, when a person enters the target area, the probe obtains information of a Bluetooth beacon or a smart device with a Wi-Fi connection function carried by the user and uploads it to the control host; S4, the control host cleans and merges the data from the probes, and then uses a personnel flow monitoring algorithm based on time point probability density estimation to calculate the time when the personnel pass through each monitoring point on their path; S5, the control host smoothly arranges the monitoring points where the personnel pass by according to time to obtain the flow trajectory of the personnel in the target area.

2. A method for monitoring personnel flow according to claim 1, characterized in that: The personnel flow monitoring algorithm based on time point probability density estimation in step S4 includes: when a person enters the target area and passes through an evacuation indication device containing a Wi-Fi probe module or a Bluetooth probe module, the probe continuously obtains information from a Bluetooth beacon carried by the user or a smart device with a Wi-Fi connection function, and obtains the precise time when the person passes through the monitoring point through the personnel flow monitoring algorithm based on time point probability density estimation, and uploads it to the control host; wherein, the time period from the first time the probe detects a new MAC address to the time when the MAC address is no longer monitored is the calculation area of ​​the algorithm, and the probability density function of all time points monitored in the area is calculated.

3. A method for monitoring personnel flow according to claim 2, characterized in that: The step S4 comprises: S4.1, cleaning the data format received from each probe and merging the data of each probe into one file for subsequent calculation; S4.2, the time interval when each MAC address information is received is judged. If the time interval is uniform in the entire calculation area and its RSSI information is relatively stable, it is considered that the monitoring target represented by the MAC address remains stationary at a point near the probe, and then the trajectory information of the MAC address is output as being stationary near a certain probe; otherwise, it is considered to be moving in the monitoring area; S4,3, divide the calculation area into time windows, and determine the time window length according to the normal walking speed of adults and the distance between adjacent probes; S4.4, treat the data information obtained by the probe as a random event (x1, x2, ..., x n ), using the kernel function to estimate (the formula is ) estimates the probability density function of the time point in the time window, where the kernel function K takes the Gaussian kernel function (formula is ), the bandwidth h uses an adaptive bandwidth, and the number of estimated points in each time window is 100; after estimating its probability density function using the kernel density estimation method with parameters set as above, the two-dimensional curve image of the function has at least one peak structure; S4.5, the control host identifies all the peaks of the probability density function and saves them into a new file.

4. A method for monitoring personnel flow according to claim 3, characterized in that: The step S5 comprises: S5.1, the control host screens the calculated points under the same MAC address in the calculated file; S5.2, the control host sorts the screened points in chronological order to obtain the movement trajectory of the personnel in the monitoring area.

5. A personnel flow monitoring system, using the personnel flow monitoring method according to claims 1-4, characterized in that: The probe module is configured to establish a target 2D plane map according to the structure of the target area, establish a corresponding target two-dimensional coordinate system, and divide the corresponding area according to actual requirements; deploy an evacuation indication device including a Wi-Fi probe module or a Bluetooth probe module in the target area, and record the two-dimensional coordinate position of each module on the target two-dimensional coordinate system; And control host module, including: Data acquisition module: when a person enters the target area, the probe acquires the information of the Bluetooth beacon or smart device with Wi-Fi connection function carried by the user and uploads it to the control host; The data processing module, the control host cleans and merges the data from the probes, and then uses a personnel flow monitoring algorithm based on time point probability density estimation to calculate the time when a person passes each monitoring point on his path; The trajectory analysis module, the control host smoothly arranges the monitoring points passed by the personnel according to time to obtain the flow trajectory of the personnel in the target area.

6. The personnel flow monitoring system according to claim 5, characterized in that: The data processing module is specifically configured to clean the data format received from each probe and merge the data of each probe into a file for subsequent calculation; The time interval when each MAC address information is received is judged. If the time interval is uniform in the entire calculation area and its RSSI information is relatively stable, it is considered that the monitoring target represented by the MAC address remains stationary at a point near the probe, and then the trajectory information of the MAC address is output as being stationary near a certain probe; otherwise, it is considered to be moving in the monitoring area; The calculation area is divided into time windows, and the length of the time window is determined according to the normal walking speed of adults and the distance between adjacent probes; The data information obtained by the probe is regarded as a random event (x1, x2, ..., x n ), using the kernel function to estimate (the formula is ) estimates the probability density function of the time point in the time window, where the kernel function K takes the Gaussian kernel function (formula is ), the bandwidth h uses an adaptive bandwidth, and the number of estimated points in each time window is 100; after estimating its probability density function using the kernel density estimation method with parameters set as above, the two-dimensional curve image of the function has at least one peak structure; The control host identifies all the peaks of the probability density function and saves them in a new file.

7. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 4 when executed.

8. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 4.

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