A method, device and medium for driving construction progress of a building by a drone

Abstract

The application relates to a progress management method, equipment and medium for unmanned aerial vehicle driving building construction, which comprises the following steps: establishing a theoretical model of a target building according to construction drawings; the unmanned aerial vehicle flies around the target building and establishes a real scene model based on image data collected through oblique photography; a first model area representing current construction progress and a second model area representing completed construction are framed in the real scene model, the first image features of the first model area and the second image features of the second model area are memorized, when the unmanned aerial vehicle flies around the target building again to collect image data, the first image features and the second image features are matched in the newly established real scene model, and the matched first model area and second model area are mapped to the theoretical model, in the implementation process, a large number of algorithm recognitions are not required, only simple image feature extraction and comparison are needed, progress management can be simply realized, the implementation cost is low, and the implementation process is simpler.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) and image processing technology, and in particular to a method, equipment and medium for UAV-driven construction progress management. Background Technology

[0002] Construction progress is a crucial factor in evaluating project quality and cost. Due to the complexity and variability of construction sites, and the time-consuming and labor-intensive nature of traditional manual progress monitoring, project progress control is challenging. With the development of smart mobile terminals and drone technology, some scholars have proposed construction progress monitoring methods based on oblique photogrammetry and drone technology, such as patents N115526450A and CN202210966642.1. The core idea is to use drone-acquired images to construct a 3D reality model, which is then compared with a BIM model containing a time dimension to determine construction progress. However, while this method boasts a high degree of intelligence, it requires four-dimensional modeling based on time series, making implementation complex, costly, and difficult to widely adopt. Therefore, it is necessary to provide a simple and easily implemented method, equipment, and medium for drone-driven construction progress management. Summary of the Invention

[0003] The purpose of this application is to provide a simple and easy-to-implement method, equipment, and medium for schedule management of construction based on drone-driven building construction.

[0004] According to one aspect of this application, a method for schedule management of unmanned aerial vehicle (UAV) driven construction is provided, comprising the steps of: Establish a theoretical model of the target building based on the construction drawings; The drone flew around the target building and collected image data based on oblique photography, and built a real-world model based on the image data; In the real-world model, select the first model area representing the current construction in progress and the second model area representing the completed construction, and establish a mapping between the first and second model areas in the theoretical model; The system memorizes the first image features of the first model region and the second image features of the second model region. When the drone flies around the target building again to collect image data, it matches the first and second image features in the newly established real-world model and maps the matched first and second model regions to the theoretical model. The update of the first and second model regions in the theoretical model reflects the construction progress.

[0005] More preferably, the step of establishing a theoretical model of the target building based on the construction drawings specifically includes the following steps: Establish a spatial coordinate system; Establish a theoretical model of the target building in a spatial coordinate system based on the construction drawings; Multiple phase progress coordinates representing the construction progress of the target building are selected in the theoretical model; In the step of reflecting the construction progress by updating the first and second model regions in the theoretical model, it is determined whether the second model region, which represents the completion of construction, covers the stage progress coordinates. If it does, it means that the construction of the target building at that stage has been completed; otherwise, it has not been completed.

[0006] More preferably, the step of establishing a theoretical model of the target building based on the construction drawings specifically includes the following steps: Establish a spatial coordinate system; Establish a theoretical model of the target building in a spatial coordinate system based on the construction drawings; Multiple phase progress coordinates representing the construction progress of the target building are selected in the theoretical model; In the step of reflecting the construction progress through the updating of the first model region and the second model region in the theoretical model, it is identified whether the first model region, which represents the current construction in progress, and the second model region, which represents the completed construction, cover the stage progress coordinates. If they do, it means that the construction of the target building at that stage is at least in progress; if not, it means that the construction of that stage has not yet started.

[0007] More preferably, the drone flies around the target building and collects image data based on oblique photography, and builds a real-world model based on the image data, specifically including the following steps: The drone flies around the target building and collects image data based on oblique photography, and flies around the target building at least once; The theoretical model of the target building, established in a spatial coordinate system, is invoked, and the collected image data is mapped onto the theoretical model as a texture to obtain a real-world model.

[0008] More preferably, in the step where the drone flies around the target building and acquires image data based on oblique photography, and at least flies around the target building once, The drone flies to at least the same height as the target building and acquires the current actual height of the target building, and the acquired image data at least covers the current actual height of the target building; The step of calling the theoretical model of the target building established in the spatial coordinate system and mapping the collected image data as textures onto the theoretical model. First, the image data is processed into a panoramic texture. Based on the actual height of the target building, the part representing the target building in the panoramic texture is completely mapped to the part in the theoretical model that corresponds to the actual height.

[0009] More preferably, in the step of selecting a first model area representing the current construction in progress and a second model area representing the completed construction in the real-world model, and establishing a mapping between the first and second model areas in the theoretical model, Users can select a first model area representing the current construction in progress and a second model area representing the completed construction in the real-world model. The selected first model area and second model area include at least the corresponding coordinate information in the real-world model and the graphic feature information in the panoramic texture. Based on the coordinate information in the real-world model, coordinate mappings corresponding to the first and second model regions are established in the theoretical model.

[0010] More preferably, in the step of memorizing the first image features of the first model region and the second image features of the second model region, Based on the graphic feature information in the panoramic texture, first image features representing the current construction in progress are extracted from the first model region, and second image features representing the current construction completed are extracted from the second model region. The first image feature representing the current construction in progress is either a graphic feature manually selected by the user, or a combination of one or more of the following pre-stored features in the image library: green netting, steel scaffolding, construction equipment, material stockpiles, protective equipment, and construction signs. The second image feature representing the completion of the current construction is either a graphic feature manually selected by the user, or a combination of one or more of the following features pre-stored in the image library: a topped-off building, exterior decoration, construction completion sign, doors and windows, railings, and bricked walls.

[0011] Even better, when the drone flies around the target building again to collect image data, the step of matching the first image features and the second image features in the newly established reality model, and mapping the matched first model region and the second model region to the theoretical model, is as follows: In the newly established real-world model, the first image feature represents the first model area where construction is currently underway, and the second image feature corresponds to the second model area where construction has been completed. The model region that matches the first image feature in the newly established real-world model is identified as the first model region, and the model region that matches the second image feature in the newly established real-world model is identified as the second model region. The first model region and the second model region are then mapped and updated to the theoretical model.

[0012] According to another aspect of this application, a computer device is provided, including a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method.

[0013] A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method.

[0014] This application has the following beneficial effects: A theoretical model of the target building is created using construction drawings, and a real-world model is built by collecting image data through oblique photography using drones. When the drone first creates the real-world model, the user selects a first model area representing ongoing construction and a second model area representing completed construction within the model. The system memorizes the first image features of the first model area and the second image features of the second model area. Updates to the corresponding model areas reflect the construction progress. This approach requires only simple image feature extraction and comparison, eliminating the need for extensive algorithmic recognition. It achieves simple progress management at a low cost and with a simpler implementation process. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating the steps of a construction progress management method based on unmanned aerial vehicle (UAV) driven construction, as described in an embodiment of this application. Figure 2 This is a structural block diagram of a computer device according to an embodiment of this application; Icon labels: 100. Computer equipment. Detailed Implementation

[0017] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings. Preferred embodiments of this application are shown in the drawings. However, this application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of this application.

[0018] It should be noted that when a component is said to be "fixed to" another component, it can be directly attached to the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0020] Please refer to Figure 1 One embodiment of this application provides a method for managing the progress of unmanned aerial vehicle (UAV)-driven construction, including the following steps: Step S10: Establish a theoretical model of the target building based on the construction drawings.

[0021] The purpose of this application is to provide a method for managing construction progress based on drone oblique photography, which aims to enable managers to achieve highly visualized monitoring of construction progress with minimal manpower costs.

[0022] First, establish a spatial coordinate system. Then, based on the construction drawings, establish a theoretical model of the target building on the spatial coordinate system. Finally, select multiple stage progress coordinates representing the construction progress of the target building on the theoretical model.

[0023] For example, if the target building is located in a central urban area, the UTM coordinate system (WGS84 projection) is chosen as the reference coordinate system for subsequent integration with topographic maps and geographic information systems. The origin is set at the southwest corner of the construction site as the reference point (0,0,0). The X-axis extends eastward along the long side of the site, the Y-axis extends northward along the wide side, and the Z-axis represents vertical height. GNSS reference points are placed at the four corners of the site, and high-precision spatial coordinates are obtained through RTK measurements. The distances and angles between the coordinate points are verified using a total station to ensure the accuracy of the coordinate system.

[0024] Next, import the architectural construction drawings (such as CAD files), ensuring that the drawings include the foundation, column grid layout, floor structure, and exterior details. Use architectural design software (such as Revit, SketchUp, or Rhino) to create a 3D BIM model. The model should include: the foundation structure, the floor plan of each floor, the elevation design, and the exterior decorative features. Then, align the origin of the digital model to (0,0,0) in the site coordinate system to ensure that the model's dimensions and scale are consistent with the actual construction design.

[0025] According to the construction plan, the construction progress of the target building is divided into three stages: Phase 1: Foundation construction completed.

[0026] Phase 2: Main structure capping.

[0027] Phase 3: Facade completed.

[0028] Key node annotation: In the theoretical model at each stage, representative coordinate points are selected: Foundation construction: Coordinates of the four corner points and the center point of the foundation (e.g., A1=(0,0,-3), A2=(50,0,-3)).

[0029] Main structure: Coordinates of the four corner column tops of each floor (e.g., B1=(0,0,3), B2=(50,0,3)).

[0030] Exterior facade: Coordinates of the midpoint of each wall (e.g., C1=(25,0,12)).

[0031] These coordinate points will be used for comparative analysis of subsequent data collected by the drone.

[0032] Therefore, by decomposing the progress into stages, the theoretical model is divided into multiple construction phases, with clear progress targets for each phase, facilitating rapid location of construction progress. The precisely labeled coordinates of key nodes provide a standardized basis for subsequent automatic matching of the UAV reality model.

[0033] Step S20: The drone flies around the target building and collects image data based on oblique photography, and builds a real-world model based on the image data.

[0034] First, the drone flies around the target building, collecting image data using oblique photography, and completes at least one full orbit. Then, a theoretical model of the target building, established in a spatial coordinate system, is invoked, and the collected image data is mapped onto this theoretical model as textures to obtain a real-world model. The drone flies to at least the same height as the target building and acquires its current actual height, with the collected image data covering at least this current height. This image data is then processed into a panoramic texture map, and based on the target building's current actual height, the portion of the panoramic texture representing the target building is completely mapped onto the corresponding portion of the theoretical model at that height.

[0035] Furthermore, the image data acquired through oblique photography is processed into panoramic textures, which can be mapped onto the theoretical model to ensure precise alignment between the real-world model and the theoretical model in the construction drawings. By combining the calibration point information in the images with the actual coordinates of the building's location, the real-world model becomes a dynamic reflection that matches the actual progress.

[0036] As the drone flies, the image data is dynamically updated based on the building's current actual height and construction stage, ensuring that the building's status reflected in the reality model is always up-to-date and supports real-time progress monitoring.

[0037] In this embodiment, based on the construction schedule, the drone needs to fly to the current actual height of the target building (assuming the current main structure height is 30 meters). The drone flies around the target building, starting from the ground and gradually ascending to a height equal to or slightly higher than 30 meters. The drone's camera is tilted at a certain angle (usually 45°~60°) to acquire multi-angle images, ensuring that the building's vertical facade and top are captured. The drone must fly around the target building at least once, possibly using a spiral ascent flight path to cover different heights and angles of the building. High resolution (e.g., 20MP) can be used to ensure clear details. Images should have at least 60% horizontal overlap and at least 40% vertical overlap to ensure the accuracy of subsequent modeling. This can be done on a sunny day to avoid shadows affecting data quality.

[0038] The drone uses a laser rangefinder or barometer to obtain the actual height of the building's top, and combines this with a preset ground elevation to determine the building's current actual height as 30 meters. The acquired images are then processed using photogrammetry software (such as Pix4D or Agisoft Metashape), and the following steps are performed: Image distortion correction: Correcting geometric distortion of the lens.

[0039] Image registration: Feature points are matched based on overlapping regions of images to generate point cloud data.

[0040] Image stitching: Stitching multiple images together to create a panoramic texture. The panoramic texture is a complete texture map of the building's surface, containing details of the building at its current actual height.

[0041] Step S30: In the real-world model, select the first model area representing the current construction in progress and the second model area representing the completed construction, and establish a mapping between the first model area and the second model area in the theoretical model.

[0042] By selecting and distinguishing between the "first model area currently under construction" and the "second model area where construction is completed" within the real-world model, the current construction progress of the target building can be intuitively displayed. Users can clearly see the different construction stages and their progress status within the real-world model, such as the completion status of construction blocks like the foundation, main structure, and facade. Users can not only see the actual construction status of the building but also track the construction progress in real time through clear area divisions, reducing the errors and uncertainties caused by vague progress reports.

[0043] Users can select a first model area representing the current construction in progress and a second model area representing the completed construction in the real-world model. The selected first and second model areas include at least the corresponding coordinate information in the real-world model and the graphic feature information in the panoramic texture.

[0044] When establishing the mapping between the theoretical model and the first and second model regions, the coordinate mapping between the theoretical model and the first and second model regions is established based on the corresponding coordinate information in the real-world model.

[0045] After selecting the model area, these areas can be compared with the theoretical model on the construction drawings using image features and coordinate information to ensure that the construction progress matches the design schedule. This operation reduces manual intervention and provides automated progress comparison and update functions.

[0046] By comparing the real-world model with the theoretical model in real time, the actual construction progress of the target building can be dynamically reflected. For example, as construction progresses, the first model area (under construction) may gradually expand into the second model area (completed construction). This update is clearly visible on the graphics, helping management to accurately grasp the construction progress.

[0047] Step S40: Memorize the first image features of the first model region and the second image features of the second model region. When the UAV flies around the target building again to collect image data, match the first image features and the second image features in the newly established real-world model, and map the matched first model region and the second model region to the theoretical model. The update of the first model region and the second model region in the theoretical model reflects the construction progress of the building.

[0048] Specifically, based on the graphic feature information in the panoramic texture, a first image feature representing the current construction in progress in the first model area, and a second image feature representing the current construction completed in the second model area, can be extracted. The first image feature representing the current construction in progress is a graphic feature manually selected by the user, or a combination of one or more pre-stored features from the image library representing the current construction in progress, such as green netting, steel scaffolding, construction equipment, material stockpiles, protective equipment, and construction signs. The second image feature representing the current construction completed is a graphic feature manually selected by the user, or a combination of one or more pre-stored features from the image library representing the current construction completed, such as a topped-out building, exterior decoration, construction completion signs, doors and windows, railings, and bricked walls.

[0049] In the newly established real-world model, the first image feature matched represents the first model region currently under construction, and the second image feature corresponds to the second model region currently under construction. The model region in the newly established real-world model that matches the first image feature is identified as the first model region, and the model region in the newly established real-world model that matches the second image feature is identified as the second model region. The first and second model regions are then mapped and updated in the theoretical model.

[0050] This image feature memorization and matching method allows for automated updates to construction progress, requiring minimal manual intervention. Managers can track construction progress in real time simply by relying on images captured by drones and pre-set image feature information. This significantly reduces the cost of manual calculations and judgments, greatly improving the efficiency of construction progress management.

[0051] After each drone flight collects data, an automated progress feedback mechanism rapidly updates the relationship between the theoretical model and the real-world model. If construction delays or other problems occur, managers can immediately identify and take appropriate measures. This automation significantly improves the responsiveness of progress control.

[0052] Depending on the specific needs, progress can be managed by checking the completion progress of the target building, or by checking whether a specific part of the target building has been completed or is in progress.

[0053] As one implementation method, it is possible to identify whether the second model area representing the completed construction covers the stage progress coordinates. If it does, it means that the construction of the target building at that stage has been completed; otherwise, it has not been completed.

[0054] As another implementation method, it is possible to identify whether the first model area representing the current construction in progress and the second model area representing the completed construction cover the stage progress coordinates. If they do, it means that the construction of the target building at that stage is at least in progress; if not, it means that the construction of that stage has not yet started.

[0055] In construction progress management, a "stage progress coordinate" is usually defined for each stage of a building project (such as foundation construction, main structure topping out, facade completion, etc.). These coordinates are usually representative points or area coordinates of the building at a specific construction stage, and can be key structural nodes (such as the four corners of the foundation, column tops, the midpoint of the facade, etc.).

[0056] During each drone flight and image data collection, image matching and feature extraction can identify different areas of the target building and determine which areas have been completed. For example, completed building areas may be represented by a roof that has been capped or finished exterior facade decoration.

[0057] If the identified completed second model area completely coincides with or covers the stage progress coordinates, it indicates that the construction of that stage is complete. If the completed area does not completely coincide with or cover the stage progress coordinates, it indicates that the construction of that stage is not yet complete.

[0058] If the completed area completely overlaps with the stage progress coordinates, it indicates that the construction of that stage is complete and can be marked as completed. If the completed area does not completely cover the stage progress coordinates, it means that the construction of that stage is not yet complete, and the management can take timely measures to accelerate the progress.

[0059] See Figure 2 This specific embodiment also provides a computer device 100, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the method described above.

[0060] This specific embodiment also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method described above.

[0061] Figure 2 An internal structural diagram of a computer device 100 in one embodiment is shown. This computer device 100 can specifically be a terminal or a server. Figure 2 As shown, the computer device 100 includes a processor, a memory, and a network interface connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium of the computer device 100 stores an operating system and may also store a computer program. When the computer program is executed by the processor, it causes the processor to implement the methods described in this embodiment. The internal memory may also store a computer program, which, when executed by the processor, causes the processor to perform the methods described in this embodiment. Those skilled in the art will understand that... Figure 2 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 100 to which the present application is applied. The specific computer device 100 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0062] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0063] This method involves establishing a theoretical model of the target building using construction drawings and creating a real-world model by collecting image data through oblique photography using drones. When the drone first creates the real-world model, the user selects a first model area representing ongoing construction and a second model area representing completed construction within the model. The system memorizes the first image features of the first model area and the second image features of the second model area. Updates to the corresponding model areas reflect the construction progress. This approach requires minimal algorithmic recognition; simple image feature extraction and comparison are sufficient for simple progress management, resulting in lower costs and a simpler implementation process.

[0064] The embodiments described above are merely examples of several implementations of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the scope of protection of this application.

Claims

1. A method for managing the progress of construction driven by unmanned aerial vehicles (UAVs), characterized in that, Including the following steps: The theoretical model of the target building is established based on the construction drawings. The specific steps of establishing the theoretical model of the target building based on the construction drawings include: establishing a spatial coordinate system; establishing the theoretical model of the target building on the spatial coordinate system based on the construction drawings; and selecting multiple stage progress coordinates representing the construction progress of the target building on the theoretical model. The drone flew around the target building and collected image data based on oblique photography, and built a real-world model based on the image data; In the real-world model, a first model area representing the current construction in progress and a second model area representing the completed construction are selected. A mapping between the first and second model areas is established in the theoretical model. The first and second model areas selected by the user in the real-world model include at least the corresponding coordinate information in the real-world model and the graphic feature information in the panoramic texture. Based on the coordinate information in the real-world model, coordinate mappings corresponding to the first and second model regions are established in the theoretical model; The system memorizes the first image features of the first model area and the second image features of the second model area. Based on the graphic feature information in the panoramic texture, it extracts the first image features representing the current construction in progress in the first model area and the second image features representing the current construction completed in the second model area. The first image features representing the current construction in progress are either manually selected by the user or a combination of one or more of the following pre-stored features in the image library: green netting, steel scaffolding, construction equipment, material stacking, protective equipment, and construction signs. The second image features representing the current construction completed are either manually selected by the user or a combination of one or more of the following pre-stored features in the image library: topped-out buildings, exterior decoration, construction completion signs, doors and windows, railings, and brick walls. When the drone flies around the target building again to collect image data, it matches the first image feature and the second image feature in the newly established real-world model, and maps the matched first and second model regions to the theoretical model. In the newly established real-world model, the first image feature matched represents the first model region where construction is currently underway, and the second image feature corresponds to the second model region where construction has been completed. The model region in the newly established real-world model that matches the first image feature is identified as the first model region, and the model region in the newly established real-world model that matches the second image feature is identified as the second model region. The first and second model regions are then mapped and updated in the theoretical model. The construction progress is reflected by updating the first and second model regions in the theoretical model. It is identified whether the second model region, which represents the completion of construction, covers the stage progress coordinates. If it does, it means that the construction of the target building at that stage has been completed; otherwise, it has not been completed. It is also identified whether the first model region, which represents the current construction in progress, and the second model region, which represents the completion of construction, cover the stage progress coordinates. If they do, it means that the construction of the target building at that stage is at least in progress; otherwise, it means that the construction of that stage has not yet started.

2. The method for managing the progress of unmanned aerial vehicle-driven building construction according to claim 1, characterized in that, The drone flies around the target building and collects image data based on oblique photography, and builds a real-world model based on the image data, specifically including the following steps: The drone flies around the target building and collects image data based on oblique photography, and flies around the target building at least once; The theoretical model of the target building, established in a spatial coordinate system, is invoked, and the collected image data is mapped onto the theoretical model as a texture to obtain a real-world model.

3. The method for managing the progress of unmanned aerial vehicle-driven building construction according to claim 2, characterized in that, In the step where the drone flies around the target building and acquires image data based on oblique photography, and at least flies around the target building once, The drone flies to at least the same height as the target building and acquires the current actual height of the target building, and the acquired image data at least covers the current actual height of the target building; The step of calling the theoretical model of the target building established in the spatial coordinate system and mapping the collected image data as textures onto the theoretical model. First, the image data is processed into a panoramic texture. Based on the actual height of the target building, the part representing the target building in the panoramic texture is completely mapped to the part in the theoretical model that corresponds to the actual height.

4. A computer device, characterized in that, It includes a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method as described in any one of claims 1 to 3.

5. A computer-readable storage medium, characterized in that, The system contains a computer program that, when executed by a processor, causes the processor to perform the steps of the method as described in any one of claims 1 to 3.

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