Soil remediation monitoring method and system

Abstract

The invention discloses a soil remediation monitoring method and system, and the method comprises the steps: inputting a historical soil image and a real-time soil image into a pre-constructed image recognition model, and judging whether at least one pixel point in the real-time soil image is the same as a pixel point at a corresponding position in the historical soil image or not according to the image recognition model, if at least one pixel point in the real-time soil image is the same as a pixel point at a corresponding position in the historical soil image, marking the at least one pixel point in the real-time soil image as an abnormal pixel point, and clustering at least two adjacent abnormal pixel points to obtain at least one abnormal region, and correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time pollution area map at the current acquisition moment. The precision of determining the soil remediation range can be improved while the soil data acquisition amount is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of soil contaminated areas, and in particular relates to a soil remediation monitoring method and system. Background Art

[0002] Since soil pollutants are of many types and complex conditions, different measures need to be taken in the process of soil remediation and the remediation methods need to be adjusted in time according to the conditions of soil pollution remediation. This requires monitoring of the soil pollution remediation effect.

[0003] At present, in the process of soil pollution remediation, grid monitoring points are often set up in the monitoring area, and soil data of all grid monitoring points are collected based on the preset collection frequency, and the soil remediation range is obtained based on the soil data analysis. However, this monitoring method is inefficient, and each monitoring requires a large amount of soil data to support, which increases the complexity of monitoring. Summary of the invention

[0004] The present invention provides a soil remediation monitoring method and system, which are used to solve the technical problem that the existing monitoring method is inefficient and each monitoring requires a large amount of soil data to support, thereby increasing the complexity of monitoring.

[0005] In a first aspect, the present invention provides a soil remediation monitoring method, comprising: Obtain a historical pollution area map of the area to be monitored at the last collection time, wherein the historical pollution area map includes historical pollution areas; Acquire a historical soil image of the area to be monitored at a previous acquisition moment and a real-time soil image at a current acquisition moment, and input the historical soil image and the real-time soil image into a pre-built image recognition model, and determine whether at least one pixel point in the real-time soil image is identical to a pixel point at a corresponding position in the historical soil image according to the image recognition model; If at least one pixel in the real-time soil image is the same as a pixel at a corresponding position in the historical soil image, at least one pixel in the real-time soil image is marked as an abnormal pixel, and at least two adjacent abnormal pixels are clustered to obtain at least one abnormal area; Determine whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region; If the distance is not greater than a preset distance threshold, the first abnormal area and the second abnormal area are merged based on a preset fusion strategy, and the fused area is defined as a risk area; Correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area; The historical pollution area is subtracted from the real-time pollution area to obtain soil remediation.

[0006] In a second aspect, the present invention provides a soil remediation monitoring system, comprising: An acquisition module is configured to acquire a historical pollution area map of the area to be monitored at a previous collection time, wherein the historical pollution area map includes historical pollution areas; A first judgment module is configured to obtain a historical soil image of the monitored area at a previous acquisition time and a real-time soil image at a current acquisition time, and input the historical soil image and the real-time soil image into a pre-built image recognition model, and judge whether at least one pixel point in the real-time soil image is the same as a pixel point at a corresponding position in the historical soil image according to the image recognition model; A clustering module, configured to mark at least one pixel in the real-time soil image as an abnormal pixel if at least one pixel in the real-time soil image is the same as a pixel at a corresponding position in the historical soil image, and cluster at least two adjacent abnormal pixels to obtain at least one abnormal region; A second judgment module is configured to judge whether the distance between the first center point of the first abnormal area and the second center point of the second abnormal area is greater than a preset distance threshold, wherein the first abnormal area and the second abnormal area are both abnormal areas in the at least one abnormal area; a fusion module, configured to fuse the first abnormal area and the second abnormal area based on a preset fusion strategy if the distance is not greater than a preset distance threshold, and define the fused area as a risk area; A correction module, configured to correct at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at a current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area; The output module is configured to subtract the historical pollution area from the real-time pollution area to obtain soil remediation.

[0007] According to a third aspect, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the steps of the soil remediation monitoring method according to any embodiment of the present invention.

[0008] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor executes the steps of the soil remediation monitoring method of any embodiment of the present invention.

[0009] The soil remediation monitoring method and system of the present application obtain a historical soil image of the monitored area at the last acquisition moment and a real-time soil image at the current acquisition moment, and input the historical soil image and the real-time soil image into a pre-constructed image recognition model, and determine whether at least one pixel point in the real-time soil image is the same as a pixel point at a corresponding position in the historical soil image according to the image recognition model; if at least one pixel point in the real-time soil image is the same as a pixel point at a corresponding position in the historical soil image, at least one pixel point in the real-time soil image is marked as an abnormal pixel point, and at least two adjacent abnormal pixels are clustered to obtain at least one abnormal area, and at least one risk area in the real-time soil image is corrected based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, which can improve the accuracy of determining the scope of soil remediation while reducing the amount of soil data collected. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of 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 some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 A flow chart of a soil remediation monitoring method provided by one embodiment of the present invention; Figure 2 A structural block diagram of a soil remediation monitoring system provided by an embodiment of the present invention; Figure 3 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0012] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0013] See also Figure 1, which shows a flow chart of a soil remediation monitoring method of the present application.

[0014] like Figure 1 As shown, the monitoring method for soil remediation specifically includes the following steps: Step S101, obtaining a historical pollution area map of the area to be monitored at the last collection time, wherein the historical pollution area map includes historical pollution areas.

[0015] Step S102, obtaining a historical soil image of the monitored area at the last acquisition moment and a real-time soil image at the current acquisition moment, and inputting the historical soil image and the real-time soil image into a pre-constructed image recognition model, and judging whether at least one pixel point in the real-time soil image is the same as a pixel point at a corresponding position in the historical soil image according to the image recognition model.

[0016] In this step, the image recognition model can be obtained by training a convolutional neural network. For example, the training sample containing the annotation box is input into the convolutional neural network for training.

[0017] It should be noted that after determining whether at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image according to the image recognition model, if at least one pixel point in the real-time soil image is not the same as the pixel point at the corresponding position in the historical soil image, at least one pixel point in the real-time soil image is marked as a normal pixel point, and at least two adjacent normal pixels are clustered to obtain a normal area.

[0018] For example, after restoration, vegetation may grow on the surface of the soil, and the area with vegetation can be defined as a normal area; however, the soil surface may not have undergone substantial changes after restoration, and therefore steps S103 to S107 need to be executed to further determine the scope of soil restoration.

[0019] Step S103: If at least one pixel in the real-time soil image is the same as a pixel at a corresponding position in the historical soil image, at least one pixel in the real-time soil image is marked as an abnormal pixel, and at least two adjacent abnormal pixels are clustered to obtain at least one abnormal area.

[0020] Step S104, determining whether the distance between the first center point of the first abnormal region and the second center point of the second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region.

[0021] In a specific embodiment, after determining whether the distance between the first center point of the first abnormal area and the second center point of the second abnormal area is greater than a preset distance threshold, if it is greater than the preset distance threshold, the first abnormal area and the second abnormal area are directly defined as risk areas respectively.

[0022] Step S105: If the distance is not greater than a preset distance threshold, the first abnormal area and the second abnormal area are fused based on a preset fusion strategy, and the fused area is defined as a risk area.

[0023] In this step, the first center point of the first abnormal area and the second center point of the second abnormal area are obtained, and the first center point and the second center point are connected to obtain a target line segment; it is determined whether the distance from the third center point of the normal area to the target line segment is greater than the length of the target line segment; if greater, a preset sliding window is slid on the target line segment, the area covered by the sliding window, the first abnormal area and the second abnormal area are fused, and the fused area is defined as a risk area, wherein the radius of the sliding window is the length of the target line segment; if not greater, the first abnormal area and the second abnormal area are directly defined as risk areas.

[0024] It should be noted that if the distance from the third center point of the normal area to the target line segment is greater than the length of the target line segment, it means that the first abnormal area and the second abnormal area are far away from the center point of the normal area. In actual application scenarios, this phenomenon indicates that a part of the normal area between the first abnormal area and the second abnormal area is in the recovery stage, that is, the pollutant concentration is gradually decreasing, but it does not mean that the pollutant concentration has dropped below the preset concentration. Therefore, it is necessary to merge this part of the normal area with the abnormal area to facilitate subsequent soil data collection and analysis. In this way, the polluted area at the current moment can be obtained more accurately.

[0025] Step S106, correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area.

[0026] In this step, first soil sample data of each monitoring point in a certain risk area is obtained; the certain risk area is corrected according to each first soil sample data to obtain at least one target risk area.

[0027] Specifically, soil data is obtained through field soil sampling and experimental analysis of the sampled soil. Soil data reflects the concentration of pollutants in the soil. By measuring the concentration of pollutants in risk areas, the amount of data collected can be reduced as much as possible, while the scope of pollution can be determined more accurately.

[0028] Step S107, subtracting the historical pollution area from the real-time pollution area to obtain soil remediation.

[0029] In this step, the historical pollution area map and the real-time pollution area map are input into a pre-built image deduplication model, and the image deduplication model removes the real-time pollution area on the historical pollution area map, and outputs soil remediation.

[0030] It should be noted that the image deduplication model can be trained by a residual neural network.

[0031] In summary, the method of the present application obtains the historical soil image of the monitored area at the last acquisition moment and the real-time soil image at the current acquisition moment, and inputs the historical soil image and the real-time soil image into a pre-constructed image recognition model, and judges whether at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image according to the image recognition model; if at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image, at least one pixel point in the real-time soil image is marked as an abnormal pixel point, and at least two adjacent abnormal pixels are clustered to obtain at least one abnormal area, and at least one risk area in the real-time soil image is corrected based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, which can improve the accuracy of determining the scope of soil remediation while reducing the amount of soil data collected.

[0032] See also Figure 2 , which shows a structural block diagram of a soil remediation monitoring system of the present application.

[0033] like Figure 2 As shown, the soil remediation monitoring system 200 includes an acquisition module 210, a first judgment module 220, a clustering module 230, a second judgment module 240, a fusion module 250, a correction module 260 and an output module 270.

[0034] Among them, the acquisition module 210 is configured to obtain a historical pollution area map of the monitored area at the last acquisition time, wherein the historical pollution area map contains historical pollution areas; the first judgment module 220 is configured to obtain a historical soil image of the monitored area at the last acquisition time, and a real-time soil image at the current acquisition time, and input the historical soil image and the real-time soil image into a pre-constructed image recognition model, and judge whether at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image according to the image recognition model; the clustering module 230 is configured to mark at least one pixel point in the real-time soil image as an abnormal pixel point if at least one pixel point in the real-time soil image is the same as the pixel point at the corresponding position in the historical soil image, and cluster at least two adjacent abnormal pixels to obtain to at least one abnormal area; a second judgment module 240 is configured to judge whether the distance between the first center point of the first abnormal area and the second center point of the second abnormal area is greater than a preset distance threshold, wherein the first abnormal area and the second abnormal area are both abnormal areas in the at least one abnormal area; a fusion module 250 is configured to fuse the first abnormal area and the second abnormal area based on a preset fusion strategy if it is not greater than the preset distance threshold, and define the fused area as a risk area; a correction module 260 is configured to correct at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition time, wherein the real-time contaminated area is included in the real-time contaminated area map; an output module 270 is configured to subtract the historical contaminated area from the real-time contaminated area to obtain soil remediation.

[0035] It should be understood that Figure 2 Modules and references documented in Figure 1 Therefore, the operations and features described above for the method and the corresponding technical effects are also applicable to Figure 2 The modules in it will not be described in detail here.

[0036] In other embodiments, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor executes the soil remediation monitoring method in any of the above method embodiments; As an implementation mode, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are configured as follows: Obtain a historical pollution area map of the area to be monitored at the last collection time, wherein the historical pollution area map includes historical pollution areas; Acquire a historical soil image of the area to be monitored at a previous acquisition moment and a real-time soil image at a current acquisition moment, and input the historical soil image and the real-time soil image into a pre-built image recognition model, and determine whether at least one pixel point in the real-time soil image is identical to a pixel point at a corresponding position in the historical soil image according to the image recognition model; If at least one pixel in the real-time soil image is the same as a pixel at a corresponding position in the historical soil image, at least one pixel in the real-time soil image is marked as an abnormal pixel, and at least two adjacent abnormal pixels are clustered to obtain at least one abnormal area; Determine whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region; If the distance is not greater than a preset distance threshold, the first abnormal area and the second abnormal area are merged based on a preset fusion strategy, and the fused area is defined as a risk area; Correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area; The historical pollution area is subtracted from the real-time pollution area to obtain soil remediation.

[0037] The computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the monitoring system for soil remediation, etc. In addition, the computer-readable storage medium may include a high-speed random access memory, and may also include a memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer-readable storage medium may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the monitoring system for soil remediation 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.

[0038] Figure 3 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, such as Figure 3 As shown, the device includes: a processor 310 and a memory 320. The electronic device may also include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330 and the output device 340 may be connected via a bus or other means. Figure 3In the example, the bus connection is used. The memory 320 is the above-mentioned computer-readable storage medium. The processor 310 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory 320, that is, the soil remediation monitoring method of the above-mentioned method embodiment is realized. The input device 330 can receive input digital or character information, and generate key signal input related to user settings and function control of the soil remediation monitoring system. The output device 340 may include a display device such as a display screen.

[0039] The electronic device can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0040] As an embodiment, the electronic device is applied to a soil remediation monitoring system and is used for a client, and includes: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can: Obtain a historical pollution area map of the area to be monitored at the last collection time, wherein the historical pollution area map includes historical pollution areas; Acquire a historical soil image of the area to be monitored at a previous acquisition moment and a real-time soil image at a current acquisition moment, and input the historical soil image and the real-time soil image into a pre-built image recognition model, and determine whether at least one pixel point in the real-time soil image is identical to a pixel point at a corresponding position in the historical soil image according to the image recognition model; If at least one pixel in the real-time soil image is the same as a pixel at a corresponding position in the historical soil image, at least one pixel in the real-time soil image is marked as an abnormal pixel, and at least two adjacent abnormal pixels are clustered to obtain at least one abnormal area; Determine whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region; If the distance is not greater than a preset distance threshold, the first abnormal area and the second abnormal area are merged based on a preset fusion strategy, and the fused area is defined as a risk area; Correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area; The historical pollution area is subtracted from the real-time pollution area to obtain soil remediation.

[0041] Through the description of the above implementation modes, those skilled in the art can clearly understand that each implementation mode can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on such an understanding, the above technical solution can essentially or in other words be embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention 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 described 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 invention.

Claims

1. A soil remediation monitoring method, characterized in that: include: Obtain a historical pollution area map of the area to be monitored at the last collection time, wherein the historical pollution area map includes historical pollution areas; Acquire a historical soil image of the area to be monitored at a previous acquisition moment and a real-time soil image at a current acquisition moment, and input the historical soil image and the real-time soil image into a pre-built image recognition model, and determine whether at least one pixel point in the real-time soil image is identical to a pixel point at a corresponding position in the historical soil image according to the image recognition model; If at least one pixel in the real-time soil image is the same as a pixel at a corresponding position in the historical soil image, at least one pixel in the real-time soil image is marked as an abnormal pixel, and at least two adjacent abnormal pixels are clustered to obtain at least one abnormal area; Determine whether a distance between a first center point of a first abnormal region and a second center point of a second abnormal region is greater than a preset distance threshold, wherein the first abnormal region and the second abnormal region are both abnormal regions in the at least one abnormal region; If the distance is not greater than a preset distance threshold, the first abnormal area and the second abnormal area are merged based on a preset fusion strategy, and the fused area is defined as a risk area; Correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area; The historical pollution area is subtracted from the real-time pollution area to obtain soil remediation.

2. A soil remediation monitoring method according to claim 1, characterized in that: After determining whether at least one pixel point in the real-time soil image is identical to a pixel point at a corresponding position in the historical soil image according to the image recognition model, the method further includes: If at least one pixel point in the real-time soil image is different from the pixel point at the corresponding position in the historical soil image, at least one pixel point in the real-time soil image is marked as a normal pixel point, and at least two adjacent normal pixels are clustered to obtain a normal area.

3. A soil remediation monitoring method according to claim 1, characterized in that: After determining whether the distance between the first center point of the first abnormal area and the second center point of the second abnormal area is greater than a preset distance threshold, the method further includes: If it is greater than a preset distance threshold, the first abnormal area and the second abnormal area are directly defined as risk areas respectively.

4. A soil remediation monitoring method according to claim 2, characterized in that: The fusing the first abnormal area and the second abnormal area based on a preset fusion strategy, and defining the fused area as a risk area includes: Obtaining a first center point of the first abnormal area and a second center point of the second abnormal area, and connecting the first center point with the second center point to obtain a target line segment; Determining whether the distance from the third center point of the normal area to the target line segment is greater than the length of the target line segment; If it is greater than, sliding a preset sliding window on the target line segment, fusing the area covered by the sliding window, the first abnormal area and the second abnormal area, and defining the fused area as a risk area, wherein the radius of the sliding window is the length of the target line segment; If not, the first abnormal area and the second abnormal area are directly defined as risk areas.

5. A soil remediation monitoring method according to claim 1, characterized in that: The method of correcting at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at the current acquisition time includes: Acquire first soil sample data of each monitoring point in a risk area; The certain risk area is corrected according to each first soil sample data to obtain at least one target risk area.

6. A soil remediation monitoring method according to claim 1, characterized in that: Subtracting the historical pollution area from the real-time pollution area to obtain soil remediation includes: The historical pollution area map and the real-time pollution area map are input into a pre-built image deduplication model, and the image deduplication model removes the real-time pollution area on the historical pollution area map, and outputs soil remediation.

7. A soil remediation monitoring system, characterized in that: include: An acquisition module is configured to acquire a historical pollution area map of the area to be monitored at a previous collection time, wherein the historical pollution area map includes historical pollution areas; A first judgment module is configured to obtain a historical soil image of the monitored area at a previous acquisition time and a real-time soil image at a current acquisition time, and input the historical soil image and the real-time soil image into a pre-built image recognition model, and judge whether at least one pixel point in the real-time soil image is the same as a pixel point at a corresponding position in the historical soil image according to the image recognition model; A clustering module, configured to mark at least one pixel in the real-time soil image as an abnormal pixel if at least one pixel in the real-time soil image is the same as a pixel at a corresponding position in the historical soil image, and cluster at least two adjacent abnormal pixels to obtain at least one abnormal region; A second judgment module is configured to judge whether the distance between the first center point of the first abnormal area and the second center point of the second abnormal area is greater than a preset distance threshold, wherein the first abnormal area and the second abnormal area are both abnormal areas in the at least one abnormal area; a fusion module, configured to fuse the first abnormal area and the second abnormal area based on a preset fusion strategy if the distance is not greater than a preset distance threshold, and define the fused area as a risk area; A correction module, configured to correct at least one risk area in the real-time soil image based on a preset correction strategy to obtain a real-time contaminated area map at a current acquisition moment, wherein the real-time contaminated area map includes a real-time contaminated area; The output module is configured to subtract the historical pollution area from the real-time pollution area to obtain soil remediation.

8. An electronic device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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