Digital twin construction method and system applied to customs supervision

Abstract

The present application discloses a digital twin construction method and system for customs supervision, which relates to the field of data processing technology. The digital twin construction method for customs supervision includes: obtaining multiple historical digital twin three-dimensional models of customs supervision; dividing the three-dimensional model into multiple area blocks based on each historical digital twin three-dimensional model; obtaining multiple key values based on each area block; configuring the detail level of the corresponding area block based on each key value; rendering and generating the current digital twin three-dimensional model based on the detail level of each area block. The present application identifies the frequency of cargo transportation in different areas of the digital twin three-dimensional model, and then divides the three-dimensional model into multiple area blocks, and then determines the density of cargo stacking in each area block, and configures a high level of detail for areas with high cargo stacking density, and configures a low level of detail for areas with low cargo stacking density.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and specifically to a method and system for constructing a digital twin for customs supervision. Background Art

[0002] Digital twins for customs supervision are a technology that clones physical entities in digital space and enables interoperability between the virtual and the real. This technology aims to improve customs supervision efficiency, optimize management processes, and enhance decision-making capabilities. In other words, digital twins for customs supervision utilize technologies such as 3D modeling, dynamic simulation, multi-dimensional visualization, and cross-departmental collaboration to comprehensively monitor and optimize the management of customs logistics processes. This not only improves the efficiency and security of customs supervision but also lays the foundation for the future development of smart customs.

[0003] During the construction of digital twins for customs supervision, different areas of the 3D model often require different levels of detail (LOD). Inaccurate LOD configuration can easily result in non-critical areas using a high LOD, wasting computing resources, or critical areas using a low LOD, reducing the quality of the digital twin 3D model. Summary of the Invention

[0004] The purpose of this application is to provide a digital twin construction method and system for customs supervision, so as to solve the technical problem that it is difficult to accurately configure the detail level for different area blocks in the digital twin construction process of customs supervision.

[0005] To achieve the above objectives, this application provides the following technical solutions:

[0006] In a first aspect, this application proposes a method for constructing a digital twin for customs supervision, which includes:

[0007] Obtain multiple historical digital twin 3D models of customs supervision;

[0008] Based on each historical digital twin 3D model, the 3D model is divided into multiple area blocks;

[0009] Based on each area block, a plurality of criticality values are obtained; the area blocks correspond to the criticality values one by one; the criticality values are used to at least characterize the density of the goods stacked in the corresponding area block;

[0010] Based on each criticality value, configure the level of detail of the corresponding area block;

[0011] Based on the level of detail of each area block, the current digital twin 3D model is rendered and generated.

[0012] As a specific solution in the technical solution of this application, the three-dimensional model is divided into multiple area blocks based on each historical digital twin three-dimensional model, including:

[0013] Based on the three-dimensional model, a first regional plane is obtained; the first regional plane is a regional plane formed by the projection of the three-dimensional model along the z-axis direction; the z-axis of the three-dimensional model is parallel to the vertical direction in reality;

[0014] Based on the first regional plane, obtaining a first coordinate point; the first coordinate point is an arbitrary coordinate point in the first regional plane;

[0015] Based on each historical digital twin three-dimensional model, obtaining each sequence segment corresponding to the first coordinate point; each sequence segment is used to at least indicate whether the first coordinate point in the corresponding historical digital twin three-dimensional model has goods deposited or withdrawn;

[0016] Based on each sequence segment, a transport frequency value is obtained; the transport frequency value is used to at least represent the frequency of cargo transportation at the first coordinate point;

[0017] Based on the transportation frequency value, the three-dimensional model is divided into a plurality of area blocks.

[0018] As a specific solution in the technical solution of this application, the sequence segments include 00, 10 and 01; 01 is used to indicate that no goods are deposited or taken out from the first coordinate point in the corresponding historical digital twin three-dimensional model; 10 is used to indicate that goods are deposited into the first coordinate point in the corresponding historical digital twin three-dimensional model; 00 is used to indicate that goods are taken out from the first coordinate point in the corresponding historical digital twin three-dimensional model.

[0019] As a specific solution in the technical solution of this application, obtaining the transport frequency value based on each sequence segment includes:

[0020] Based on each sequence segment, a first sequence segment is acquired; the first sequence segment is the last sequence segment in the time sequence of each sequence segment;

[0021] Based on the first sequence segment, obtaining a height value and a timing value; the height value is the sum of the values of the first sequence segment and the sequence segment preceding the first sequence segment; the timing value is the sequence number corresponding to the first sequence segment;

[0022] The transportation frequency value is obtained based on the altitude value and the time sequence value.

[0023] As a specific solution in the technical solution of this application, the calculation formula for obtaining the transportation frequency value based on the altitude value and the time sequence value is as follows:

[0024]

[0025] Where P represents the transport frequency value; S represents the height value; n represents the number of each sequence segment; Indicates that the value in the brackets is mapped to the interval [0, 1]; Indicates finding the absolute value.

[0026] As a specific solution in the technical solution of this application, the three-dimensional model is divided into multiple area blocks based on the transportation frequency value, including:

[0027] Obtaining a first feature vector based on the first coordinate point; the first feature vector is the transportation frequency value corresponding to the first coordinate point and the coordinate value corresponding to the first coordinate point located in the first area plane;

[0028] Based on a clustering algorithm, clustering each first coordinate point using the first feature vector to obtain a plurality of first clusters;

[0029] Based on each first cluster, the three-dimensional model is divided into a plurality of area blocks.

[0030] As a specific solution in the technical solution of this application, the method of obtaining multiple criticality values based on each area block includes:

[0031] Based on each area block, a first area block is obtained; the first area block is any one of the area blocks;

[0032] Based on the first area block, a plurality of second coordinate points are acquired; the second coordinate points are any coordinate points located in the first area block;

[0033] Based on each second coordinate point, a second eigenvector corresponding to each second coordinate point is obtained; the second eigenvector is a transport frequency difference value corresponding to each second coordinate point and a coordinate value corresponding to the plane of the first region; the transport frequency difference value is a difference between a current transport frequency value and a historical transport frequency value of the corresponding second coordinate point;

[0034] Based on the clustering algorithm, clustering each second coordinate point by the second eigenvector to obtain a plurality of second clusters;

[0035] Based on each second cluster, a criticality value corresponding to the first region block is obtained.

[0036] As a specific solution in the technical solution of this application, the calculation formula for obtaining the criticality value corresponding to the first region block based on each second cluster is as follows:

[0037]

[0038] Wherein, M represents the criticality value corresponding to the first region block; m represents the number of second clusters corresponding to the first region block; Represents the sum of the height values of each second coordinate point corresponding to the i-th second cluster; Represents the number of each second coordinate point in the i-th second cluster; Indicates the area corresponding to the first region block; represents the area corresponding to the first region plane; Indicates that the value in the brackets is mapped to the range [0, 1].

[0039] As a specific solution in the technical solution of this application, configuring the level of detail of the corresponding area block based on each criticality value includes:

[0040] If the criticality value corresponding to the first area block is greater than or equal to a preset value, the detail level of the first area block is configured as a high detail level; otherwise, the detail level of the first area block is configured as a low detail level.

[0041] In a second aspect, the present application proposes a digital twin construction system for customs supervision, which includes:

[0042] Reader for acquiring multiple historical digital twin 3D models under customs supervision;

[0043] A server is used to divide the three-dimensional model into multiple area blocks based on each historical digital twin three-dimensional model;

[0044] And, based on each area block, a plurality of criticality values are obtained; the area blocks correspond to the criticality values one by one; the criticality values are used to at least characterize the density of the goods stacked in the corresponding area block;

[0045] and, based on each criticality value, configuring a level of detail of the corresponding area block;

[0046] And, based on the level of detail of each area block, the current digital twin three-dimensional model is rendered and generated.

[0047] As a specific solution of the technical solution of the present application, the server is further configured to obtain a first regional plane based on the three-dimensional model; the first regional plane is a regional plane formed by the projection of the three-dimensional model along the z-axis; the z-axis of the three-dimensional model is parallel to the vertical direction in reality;

[0048] And, based on the first area plane, obtaining a first coordinate point; the first coordinate point is an arbitrary coordinate point in the first area plane;

[0049] and, based on each historical digital twin three-dimensional model, obtaining each sequence segment corresponding to the first coordinate point; each sequence segment is used to at least indicate whether the first coordinate point in the corresponding historical digital twin three-dimensional model has goods deposited or withdrawn;

[0050] And, based on each sequence segment, obtaining a transport frequency value; the transport frequency value is used to at least represent the frequency of cargo transportation at the first coordinate point;

[0051] And, based on the transportation frequency value, the three-dimensional model is divided into a plurality of area blocks.

[0052] As a specific solution in the technical solution of this application, the sequence segments include 00, 10 and 01; 01 is used to indicate that no goods are deposited or taken out from the first coordinate point in the corresponding historical digital twin three-dimensional model; 10 is used to indicate that goods are deposited into the first coordinate point in the corresponding historical digital twin three-dimensional model; 00 is used to indicate that goods are taken out from the first coordinate point in the corresponding historical digital twin three-dimensional model.

[0053] As a specific solution in the technical solution of the present application, the server is further configured to obtain a first sequence segment based on each sequence segment; the first sequence segment is the last sequence segment in the sequence of each sequence segment;

[0054] and, based on the first sequence segment, obtaining a height value and a timing value; the height value being the sum of the values of the first sequence segment and the sequence segment preceding the first sequence segment in time; and the timing value being the sequence number corresponding to the first sequence segment;

[0055] And, based on the altitude value and the time sequence value, the transportation frequency value is obtained.

[0056] As a specific solution in the technical solution of this application, the server obtains the transportation frequency value based on the altitude value and the time sequence value using the following calculation formula:

[0057]

[0058] Where P represents the transport frequency value; S represents the height value; n represents the number of each sequence segment; Indicates that the value in the brackets is mapped to the interval [0, 1]; Indicates finding the absolute value.

[0059] As a specific solution in the technical solution of the present application, the server is further configured to obtain a first feature vector based on the first coordinate point; the first feature vector is a transportation frequency value corresponding to the first coordinate point and a coordinate value corresponding to the first coordinate point located in the first area plane;

[0060] and, based on a clustering algorithm, clustering each first coordinate point using the first feature vector to obtain a plurality of first clusters;

[0061] And, based on each first cluster, the three-dimensional model is divided into a plurality of area blocks.

[0062] As a specific solution in the technical solution of the present application, the server is further configured to obtain a first regional block based on each regional block; the first regional block is any one of the regional blocks;

[0063] And, based on the first area block, a plurality of second coordinate points are acquired; the second coordinate points are any coordinate points located in the first area block;

[0064] and, based on each second coordinate point, obtaining a second eigenvector corresponding to each second coordinate point; the second eigenvector being a transport frequency difference value corresponding to each second coordinate point and a coordinate value corresponding to the plane of the first region; the transport frequency difference being a difference between a current transport frequency value and a historical transport frequency value of the corresponding second coordinate point;

[0065] And, based on a clustering algorithm, clustering each second coordinate point by the second eigenvector to obtain a plurality of second clusters;

[0066] And, based on each second cluster, a criticality value corresponding to the first region block is obtained.

[0067] As a specific solution in the technical solution of this application, the server obtains the criticality value corresponding to the first region block based on each second cluster using the following calculation formula:

[0068]

[0069] Wherein, M represents the criticality value corresponding to the first region block; m represents the number of second clusters corresponding to the first region block; Represents the sum of the height values of each second coordinate point corresponding to the i-th second cluster; Represents the number of each second coordinate point in the i-th second cluster; Indicates the area corresponding to the first region block; represents the area corresponding to the first region plane; Indicates that the value in the brackets is mapped to the range [0, 1].

[0070] As a specific solution in the technical solution of the present application, the server is further used to configure the detail level of the first area block to a high detail level if the criticality value corresponding to the first area block is greater than or equal to a preset value; otherwise, configure the detail level of the first area block to a low detail level.

[0071] Compared with the prior art, the present invention has the following advantages:

[0072] This application identifies the frequency of cargo transportation in different areas of a digital twin 3D model, divides the 3D model into multiple blocks, and then determines the density of cargo stacking in each block. It configures a high level of detail for areas with high cargo density and a low level of detail for areas with low cargo density. This allows for low-level rendering in areas that don't require high attention, reducing the rendering burden and improving system performance; while high-level rendering is used in areas that require high attention, resulting in better rendering effects and clearer visual information. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 A flowchart of a method for constructing a digital twin for customs supervision proposed in an embodiment of the present application;

[0074] Figure 2 This is a structural diagram of a digital twin construction system for customs supervision proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0075] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0076] The terms "first", "second", etc. in the description of the embodiments of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence, such as the first eigenvector and the second eigenvector proposed below, which belong to different eigenvectors. It should be understood that the names used in this way can be interchanged where appropriate so that the embodiments described herein can be implemented in an order other than the content illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or modules is not necessarily limited to those steps or modules clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. The configuration of the modules appearing in the embodiments of the present application is only a logical configuration. In actual application, there may be other configuration modes, such as multiple modules can be combined into or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, and the indirect coupling or communication connection between modules can be electrical or other similar forms, which are not limited in the embodiments of the present application. Moreover, the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed into multiple circuit modules, and some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiment of the present application.

[0077] Before understanding the embodiments of this application, it is important to understand that in computer graphics and 3D modeling, Level of Detail (LOD) is a term used to describe the degree of detail in a model. For example, LOD0, LOD1, and LOD2 are different levels of detail, each corresponding to a different number of faces or vertices, used to display models with the appropriate level of detail for different application requirements. In the embodiments of this application, the level of detail can be selected based on requirements. For example, in this embodiment, the high level of detail can be LOD0, which can have 5,000 faces, meaning that each container model in the 3D modeling consists of approximately 5,000 faces. Container models at this level of detail (i.e., LOD0) are very detailed and suitable for applications requiring a high level of detail. In this embodiment, the low level of detail can be LOD2, which can have 500 faces, meaning that each container model in the 3D modeling consists of approximately 500 faces. Container models at this level have fewer details and are suitable for applications requiring fast rendering. Using models at different levels of detail can optimize rendering performance and resource consumption while maintaining visual quality. Of course, in other embodiments of the present application, high detail levels and low detail levels different from those in the above embodiments may also be set according to needs.

[0078] It should be understood that the focus of customs and port supervision is cargo storage areas, which are planned and known areas. Therefore, subsequent analysis will only focus on the planned cargo storage areas in the digital twin 3D model. Non-cargo storage areas (for example, areas where immovable equipment is placed, or roads where vehicles travel) are directly configured for rendering at a low level of detail.

[0079] In order to solve the technical problem in the background technology that it is difficult to accurately configure the level of detail for different area blocks in the construction process of digital twins under customs supervision, this application proposes a digital twin construction method for customs supervision. Figure 1 As shown, the digital twin construction method applied to customs supervision includes steps S100 to S500.

[0080] Step S100: Acquire multiple historical digital twin 3D models under customs supervision.

[0081] It should be noted that during customs supervision, the historical digital twin 3D model must be updated to obtain the current digital twin 3D model. After the current digital twin 3D model is updated, the historical digital twin 3D model must also be stored (typically on a computer-readable storage medium). Retrieving these stored historical digital twin 3D models from a computer-readable storage medium is a mature technology and will not be elaborated on here.

[0082] Step S200: Based on each historical digital twin three-dimensional model, divide the three-dimensional model into multiple area blocks.

[0083] In the embodiments of the present application, the three-dimensional model can be divided into multiple regional blocks in any reasonable manner. For example, the historical digital twin three-dimensional model can be divided into multiple regional blocks using a spatial grid. It should be understood that dividing the historical digital twin three-dimensional model into multiple regional blocks using a spatial grid is a mature technology and will not be described in detail here.

[0084] It's important to note that at customs ports, shore-to-shore container cranes are typically used to unload containers from ships onto docks, or to load containers from docks onto ships. Straddle carriers are also used to transport containers from one side of the dock to the other, or from the dock to inland freight stations. Areas with frequent container turnover often require special attention to ensure the efficiency and safety of centralized transportation. Therefore, the more frequent container transportation in a particular area, the more attention it warrants. A higher level of detail should be assigned to this area when constructing the 3D model to ensure the accuracy of customs supervision. Using the aforementioned spatial grid to segment the 3D model into multiple blocks, it's likely that areas with frequent and infrequent transportation will be grouped into the same block. If a block contains both frequent and infrequent transportation areas, it will be impossible to configure an accurate level of detail for that area later on.

[0085] In order to divide the three-dimensional model into multiple suitable area blocks, and thus facilitate the subsequent configuration of detail levels for each area block, in one embodiment of the present application, step S200 divides the three-dimensional model into multiple area blocks based on each historical digital twin three-dimensional model, including steps S210 to S250.

[0086] Step S210: Acquire a first region plane based on the three-dimensional model.

[0087] In this embodiment, the first regional plane is the regional plane formed by the projection of the three-dimensional model along the z-axis. The z-axis of the three-dimensional model is parallel to the vertical direction in reality. That is, in this embodiment, the first regional plane can be any plane perpendicular to the z-axis. For example, the first regional plane can be the xoy plane (i.e., the plane with a z-axis value of 0).

[0088] Step S220: Acquire a first coordinate point based on the first area plane.

[0089] In this embodiment, the first coordinate point is any coordinate point in the first regional plane. In this embodiment, a grid method can be used to set each first coordinate point in the first regional plane; of course, each first coordinate point can also be selected from the first regional plane in a random selection manner.

[0090] Step S230: Based on each historical digital twin three-dimensional model, obtain each sequence segment corresponding to the first coordinate point.

[0091] In this embodiment, each sequence segment is at least used to represent whether the first coordinate point in the corresponding historical digital twin three-dimensional model has goods deposited or withdrawn.

[0092] It should be understood that, in the embodiments of the present application, any reasonable sequence segment may be used to record whether goods are deposited or withdrawn at the first coordinate point in the corresponding historical digital twin three-dimensional model. For example, in one embodiment of the present application, the sequence segment may include 00, 10, and 01. 01 is used to indicate that no goods are deposited or withdrawn from the first coordinate point in the corresponding historical digital twin three-dimensional model. 10 is used to indicate that goods are deposited at the first coordinate point in the corresponding historical digital twin three-dimensional model. 00 is used to indicate that goods are withdrawn from the first coordinate point in the corresponding historical digital twin three-dimensional model.

[0093] Step S240: Based on each sequence segment, obtain a transportation frequency value.

[0094] In this embodiment, the transportation frequency value is at least used to represent the frequency of cargo transportation at the first coordinate point.

[0095] It should be understood that, in the embodiments of the present application, any reasonable method can be used to obtain the transport frequency value based on each sequence segment. For example, the sum of the values of each sequence segment can be used as the transport frequency value. As can be seen from the foregoing, the more frequently goods are deposited at a certain coordinate point, the greater the sum of its sequence segments. The more frequently goods are taken out of a certain coordinate point, the closer the sum of its sequence segments is to 0. Specifically, the calculation formula for the sum of the values of each sequence segment (hereinafter referred to as the first calculation formula) can be as follows:

[0096]

[0097] Wherein, S represents the sum of the values of the sequence segments corresponding to the first coordinate point; n represents the number of the sequence segments corresponding to the first coordinate point; Indicates the value corresponding to the kth sequence segment. In binary, 00 represents the value 0; 10 represents the value 2; and 01 represents the value 1.

[0098] It should be clear that the frequency of transportation is not only related to the numerical value and the height value of each sequence segment (that is, the height value below), but also related to time (that is, the timing value below). In order to obtain accurate transportation frequency values, in one embodiment of the present application, step S240 obtains the transportation frequency value based on each sequence segment, including steps S241 to S243.

[0099] Step S241: Based on each sequence segment, obtain a first sequence segment.

[0100] In this embodiment, the first sequence segment is the last sequence segment in the sequence among all the sequence segments.

[0101] Step S242: Based on the first sequence segment, obtain a height value and a timing value.

[0102] In this embodiment, the height value is the sum of the values of the first sequence segment and the sequence segment preceding the first sequence segment (calculated using the first calculation formula). The sequence value is the sequence number corresponding to the first sequence segment.

[0103] Step S243: Based on the altitude value and the time sequence value, obtain the transportation frequency value.

[0104] In the embodiment of the present application, the transportation frequency value can be obtained based on the altitude value and the time sequence value in any reasonable manner. For example, the transportation frequency value can be the ratio of the altitude value to the time sequence value. Alternatively, in step S243, the calculation formula for obtaining the transportation frequency value based on the altitude value and the time sequence value is as follows:

[0105]

[0106] Where P represents the transport frequency value; S represents the height value; n represents the number of each sequence segment; Indicates that the value in the brackets is mapped to the interval [0, 1]; Indicates finding the absolute value.

[0107] In this embodiment, the faster the goods are deposited into the first coordinate point, the greater the transport frequency value; the faster the goods are taken out of the first coordinate point, the smaller the transport frequency value; if the goods are neither deposited nor taken out of the first coordinate point for a long time, the transport frequency value tends to 0.

[0108] Step S250: Divide the three-dimensional model into a plurality of area blocks based on the transportation frequency value.

[0109] In an embodiment of the present application, first coordinate points with similar transport frequency values can be divided into the same area block based on the transport frequency value, thereby making the features of the first coordinate points in the same area block similar, which is beneficial for subsequently accurately configuring the detail level for the area.

[0110] In the embodiment of the present application, any reasonable method can be used to divide the three-dimensional model into multiple blocks based on the transportation frequency value. For example, step S250, dividing the three-dimensional model into multiple blocks based on the transportation frequency value, includes steps S251 to S253.

[0111] Step S251: Obtain a first feature vector based on the first coordinate point.

[0112] In this embodiment, the first feature vector is the transportation frequency value corresponding to the first coordinate point and the coordinate value corresponding to the first coordinate point being located in the first area plane.

[0113] Step S252: Based on a clustering algorithm, cluster the first coordinate points using the first feature vector to obtain a plurality of first clusters.

[0114] It should be noted that a clustering algorithm is an unsupervised learning method in machine learning. Its goal is to divide samples in a dataset into several groups (or "clusters"), such that samples within the same cluster are highly similar, while samples between different clusters are less similar. In this embodiment, any reasonable clustering algorithm can be used to cluster the first coordinate points, such as the K-Means algorithm or the K-medoids algorithm. Both the K-Means algorithm and the K-medoids algorithm are mature technologies and are not described in detail here.

[0115] Step S253: Divide the three-dimensional model into a plurality of area blocks based on each first cluster.

[0116] It should be noted that, in this embodiment, a plurality of first coordinate points in each first cluster together form an area block.

[0117] Step S300: Based on each region block, a plurality of criticality values are obtained.

[0118] In an embodiment of the present application, the area blocks correspond to the criticality values in a one-to-one manner, and the criticality values are used to at least characterize the density of the goods stacked in the corresponding area blocks.

[0119] It's important to note that at customs terminals, containers are typically stacked layer by layer. As previously mentioned, the higher the stacking height of the containers in a block, the larger the height value at the corresponding first coordinate point. In other words, in this embodiment of the present application, the sum of the height values at each first coordinate point in each block can be used as the criticality value for that block.

[0120] It's important to note that the more containers stacked in a particular area, the more focus that area requires. This means that when creating a 3D model, a higher level of detail (LOD) must be configured for that area. Because containers vary in size, simply summing the heights of the first coordinate points in a given area is not sufficient to accurately represent the number of containers in that area. In other words, simply using the sum of the heights of the first coordinate points in a given area as the criticality value makes it difficult to subsequently configure an accurate LOD for that area based on that criticality.

[0121] In order to further configure an accurate level of detail for each area block, in one embodiment of the present application, step S300 obtains multiple criticality values based on each area block, including steps S310 to S350.

[0122] Step S310: Based on each area block, obtain a first area block.

[0123] In this embodiment, the first region block is any one of the region blocks. That is, in this application, the criticality values of the various region blocks can be obtained by referring to the first region block, which will not be described in detail later.

[0124] Step S320: Based on the first area block, obtain a plurality of second coordinate points.

[0125] In this embodiment, the second coordinate point is any coordinate point located in the first area block.

[0126] Step S330: Based on each second coordinate point, obtain a second eigenvector corresponding to each second coordinate point.

[0127] In this embodiment, the second feature vector is the difference between the transport frequency value corresponding to each second coordinate point and the coordinate value corresponding to the first area plane. The transport frequency difference is the difference between the current transport frequency value and the historical transport frequency value of the corresponding second coordinate point.

[0128] It's easy to understand that if two second coordinate points are located in the same stack of containers, then the transport frequency difference between these two second coordinate points at each time series must be the same (that is, the transport frequency difference between these two coordinate points at each time series must change synchronously), and the coordinate values of these two second coordinate points must be similar. In other words, in this embodiment, the number of containers in the first area block can be determined by determining whether the second coordinate points in the first area block are similar.

[0129] Step S340: Based on a clustering algorithm, cluster the second coordinate points using the second eigenvectors to obtain a plurality of second clusters.

[0130] In this embodiment, any reasonable clustering algorithm can be used to cluster the first coordinate points, such as a K-Means algorithm or a K-medoids algorithm, etc. The K-Means algorithm or the K-medoids algorithm are both mature technologies and will not be described in detail here.

[0131] Step S350: Based on each second cluster, obtain the criticality value corresponding to the first region block.

[0132] In this embodiment, the number of the second clusters is substantially the same as the number of container stacks in the first area block. Based on this, in step S350, based on each second cluster, the calculation formula for obtaining the criticality value corresponding to the first area block is as follows:

[0133]

[0134] Wherein, M represents the criticality value corresponding to the first region block; m represents the number of second clusters corresponding to the first region block; represents the sum of the height values of each second coordinate point corresponding to the i-th second cluster; Represents the number of each second coordinate point in the i-th second cluster; Indicates the area corresponding to the first region block; represents the area corresponding to the first region plane; Indicates that the value in the brackets is mapped to the range [0, 1].

[0135] In this embodiment, if the criticality value corresponding to the first area block is larger, it means that the number of containers in the first area block is larger, and more attention needs to be paid to the first area block; if the criticality value corresponding to the first area block is smaller, it means that the number of containers in the first area block is smaller, and the attention paid to the first area block can be reduced.

[0136] Step S400: configuring the level of detail of the corresponding area block based on each criticality value.

[0137] In an embodiment of the present application, any reasonable method can be used to configure the level of detail of the corresponding area block based on each criticality value. For example, the larger the criticality value corresponding to a certain area block, the higher the level of detail configured for that area can be. In a specific embodiment of the present application, step S400, configuring the level of detail of the corresponding area block based on each criticality value, includes: if the criticality value corresponding to the first area block is greater than or equal to a preset value, configuring the level of detail of the first area block to a high level of detail; otherwise, configuring the level of detail of the first area block to a low level of detail.

[0138] In the embodiment of the present application, the preset value may be any appropriate value, for example, the preset value may be 0.5 or 0.6.

[0139] Step S500: Based on the level of detail of each area block, render and generate the current digital twin three-dimensional model.

[0140] It should be understood that rendering corresponding area blocks based on pre-configured levels of detail and forming a three-dimensional model is a mature technology and will not be described in detail here.

[0141] It should be understood that the embodiment of the digital twin construction method for customs supervision proposed in this application identifies the frequency of cargo transportation in different areas of the digital twin three-dimensional model, and then divides the three-dimensional model into multiple regional blocks. The density of cargo stacking in each regional block is then determined, and a high level of detail is configured for areas with high cargo stacking density, and a low level of detail is configured for areas with low cargo stacking density. This allows low-level rendering to be used in areas that do not require high attention, which can reduce the rendering burden and improve system performance; while high-level rendering is used in areas that require high attention to achieve better rendering effects and provide clearer visual information.

[0142] After introducing the embodiment of the digital twin construction method for customs supervision proposed in the embodiment of this application, the following introduces an embodiment of the digital twin construction system for customs supervision proposed in this application. Specifically, Figure 2 As shown, the digital twin construction system 10 applied to customs supervision includes:

[0143] Reader 11, used to obtain multiple historical digital twin 3D models under customs supervision;

[0144] The server 12 is configured to divide the three-dimensional model into a plurality of area blocks based on each historical digital twin three-dimensional model;

[0145] And, based on each area block, a plurality of criticality values are obtained; the area blocks correspond to the criticality values one by one; the criticality values are used to at least characterize the density of the goods stacked in the corresponding area block;

[0146] and, based on each criticality value, configuring a level of detail of the corresponding area block;

[0147] And, based on the level of detail of each area block, the current digital twin three-dimensional model is rendered and generated.

[0148] As a specific embodiment of the present application, the server 12 is further configured to obtain a first regional plane based on the three-dimensional model; the first regional plane is a regional plane formed by the projection of the three-dimensional model along the z-axis; the z-axis of the three-dimensional model is parallel to the vertical direction in reality;

[0149] And, based on the first area plane, obtaining a first coordinate point; the first coordinate point is an arbitrary coordinate point in the first area plane;

[0150] and, based on each historical digital twin three-dimensional model, obtaining each sequence segment corresponding to the first coordinate point; each sequence segment is used to at least indicate whether the first coordinate point in the corresponding historical digital twin three-dimensional model has goods deposited or withdrawn;

[0151] And, based on each sequence segment, obtaining a transport frequency value; the transport frequency value is used to at least represent the frequency of cargo transport at the first coordinate point;

[0152] And, based on the transportation frequency value, the three-dimensional model is divided into a plurality of area blocks.

[0153] As a specific embodiment of the present application, the sequence segments include 00, 10 and 01; 01 is used to indicate that no goods are deposited or taken out from the first coordinate point in the corresponding historical digital twin three-dimensional model; 10 is used to indicate that goods are deposited into the first coordinate point in the corresponding historical digital twin three-dimensional model; 00 is used to indicate that goods are taken out from the first coordinate point in the corresponding historical digital twin three-dimensional model.

[0154] As a specific embodiment of the present application, the server 12 is further configured to obtain a first sequence segment based on each sequence segment; the first sequence segment is the last sequence segment in the sequence of each sequence segment;

[0155] and, based on the first sequence segment, obtaining a height value and a timing value; the height value being the sum of the values of the first sequence segment and the sequence segment preceding the first sequence segment in time; and the timing value being the sequence number corresponding to the first sequence segment;

[0156] And, based on the altitude value and the time sequence value, the transportation frequency value is obtained.

[0157] As a specific embodiment of the present application, the server 12 obtains the transportation frequency value based on the altitude value and the time sequence value using the following calculation formula:

[0158]

[0159] Where P represents the transport frequency value; S represents the height value; n represents the number of each sequence segment; Indicates that the value in the brackets is mapped to the interval [0, 1]; Indicates finding the absolute value.

[0160] As a specific embodiment of the present application, the server 12 is further configured to obtain a first feature vector based on the first coordinate point; the first feature vector is a transportation frequency value corresponding to the first coordinate point and a coordinate value corresponding to the first coordinate point being located on the first regional plane;

[0161] and, based on a clustering algorithm, clustering each first coordinate point using the first feature vector to obtain a plurality of first clusters;

[0162] And, based on each first cluster, the three-dimensional model is divided into a plurality of area blocks.

[0163] As a specific embodiment of the present application, the server 12 is further configured to obtain a first regional block based on each regional block; the first regional block is any one of the regional blocks;

[0164] And, based on the first area block, a plurality of second coordinate points are acquired; the second coordinate points are any coordinate points located in the first area block;

[0165] and, based on each second coordinate point, obtaining a second eigenvector corresponding to each second coordinate point; the second eigenvector being a transport frequency difference value corresponding to each second coordinate point and a coordinate value corresponding to the plane of the first region; the transport frequency difference being a difference between a current transport frequency value and a historical transport frequency value of the corresponding second coordinate point;

[0166] And, based on a clustering algorithm, clustering each second coordinate point by the second eigenvector to obtain a plurality of second clusters;

[0167] And, based on each second cluster, a criticality value corresponding to the first region block is obtained.

[0168] As a specific embodiment of the present application, the server 12 obtains the criticality value corresponding to the first region block based on each second cluster using the following calculation formula:

[0169]

[0170] Wherein, M represents the criticality value corresponding to the first region block; m represents the number of second clusters corresponding to the first region block; Represents the sum of the height values of each second coordinate point corresponding to the i-th second cluster; Represents the number of each second coordinate point in the i-th second cluster; Indicates the area corresponding to the first region block; represents the area corresponding to the first region plane; Indicates that the value in the brackets is mapped to the range [0, 1].

[0171] As a specific embodiment of the present application, the server 12 is further configured to configure the detail level of the first area block to a high detail level if the criticality value corresponding to the first area block is greater than or equal to a preset value; otherwise, configure the detail level of the first area block to a low detail level.

[0172] It should be understood that the embodiment of the digital twin construction system for customs supervision proposed in this application identifies the frequency of cargo transportation in different areas of the digital twin three-dimensional model, and then divides the three-dimensional model into multiple area blocks. The density of cargo stacking in each area block is then determined, and a high level of detail is configured for areas with high cargo stacking density, and a low level of detail is configured for areas with low cargo stacking density. This allows low-level rendering to be used in areas that do not require high attention, reducing the rendering burden and improving system performance; while high-level rendering is used in areas that require high attention, resulting in better rendering effects and providing clearer visual information.

[0173] It should be understood that computer-readable storage media in this application include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory, static random access memory, dynamic random access memory, other types of random access memory, read-only memory, electrically erasable programmable read-only memory, flash memory or other memory technology, read-only compact disc read-only memory, digital versatile disc or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media such as modulated data signals and carrier waves.

[0174] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0175] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the methods, devices and equipment described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0176] In the several embodiments provided in the embodiments of the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the configuration of the modules is merely a logical function configuration. In actual implementation, there may be other configurations, such as multiple modules or components that 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 an indirect coupling or communication connection of some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0177] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of the present embodiment according to actual needs.

[0178] In addition, the functional modules in each embodiment of the present application can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into a module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software functional modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0179] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0180] The computer program product includes one or more computer instructions. When the computer program is loaded and executed on a computer, the process or functions described in accordance with the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium may be any available medium that can be stored on a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., a floppy disk, hard disk, or magnetic tape), an optical medium (e.g., a digital versatile disk), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0181] Although the embodiments of the present application have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions, and alterations may be made to these embodiments without departing from the principles of the present application.

Claims

1. A digital twin construction method for customs supervision, characterized in that: include: Obtain multiple historical digital twin 3D models of customs supervision; Based on each historical digital twin 3D model, the 3D model is divided into multiple area blocks; Based on each area block, a plurality of criticality values are obtained; the area blocks correspond to the criticality values one by one; the criticality values are used to at least characterize the density of the goods stacked in the corresponding area block; Based on each criticality value, configure the level of detail of the corresponding area block; Based on the level of detail of each area block, render and generate the current digital twin 3D model; Based on each historical digital twin 3D model, the 3D model is divided into multiple area blocks, including: Based on the three-dimensional model, a first regional plane is obtained; the first regional plane is a regional plane formed by the projection of the three-dimensional model along the z-axis direction; the z-axis of the three-dimensional model is parallel to the vertical direction in reality; Based on the first regional plane, obtaining a first coordinate point; the first coordinate point is an arbitrary coordinate point in the first regional plane; Based on each historical digital twin three-dimensional model, obtaining each sequence segment corresponding to the first coordinate point; each sequence segment is used to at least indicate whether the first coordinate point in the corresponding historical digital twin three-dimensional model has goods deposited or withdrawn; Based on each sequence segment, a transport frequency value is obtained; the transport frequency value is used to at least represent the frequency of cargo transportation at the first coordinate point; Based on the transportation frequency value, the three-dimensional model is divided into a plurality of area blocks.

2. The digital twin construction method for customs supervision according to claim 1 is characterized in that: The sequence segments include 00, 10 and 01; 01 is used to indicate that no goods are deposited or taken out from the first coordinate point in the corresponding historical digital twin three-dimensional model; 10 is used to indicate that goods are deposited at the first coordinate point in the corresponding historical digital twin three-dimensional model; 00 is used to indicate that goods are taken out from the first coordinate point in the corresponding historical digital twin three-dimensional model.

3. The digital twin construction method for customs supervision according to claim 2 is characterized in that: The method of obtaining the transport frequency value based on each sequence segment includes: Based on each sequence segment, a first sequence segment is acquired; the first sequence segment is the last sequence segment in the time sequence of each sequence segment; Based on the first sequence segment, obtaining a height value and a timing value; the height value is the sum of the values of the first sequence segment and the sequence segment preceding the first sequence segment; the timing value is the sequence number corresponding to the first sequence segment; The transportation frequency value is obtained based on the altitude value and the time sequence value.

4. The digital twin construction method for customs supervision according to claim 3 is characterized in that: The calculation formula for obtaining the transportation frequency value based on the altitude value and the time sequence value is as follows: Where P represents the transport frequency value; S represents the height value; n represents the number of each sequence segment; Indicates that the value in the brackets is mapped to the interval [0, 1]; Indicates finding the absolute value.

5. The digital twin construction method for customs supervision according to claim 3 is characterized in that: The three-dimensional model is divided into a plurality of area blocks based on the transportation frequency value, including: Obtaining a first feature vector based on the first coordinate point; the first feature vector is the transportation frequency value corresponding to the first coordinate point and the coordinate value corresponding to the first coordinate point located in the first area plane; Based on a clustering algorithm, clustering each first coordinate point using the first feature vector to obtain a plurality of first clusters; Based on each first cluster, the three-dimensional model is divided into a plurality of area blocks.

6. The method for constructing a digital twin for customs supervision according to any one of claims 1 to 5, characterized in that: The method of obtaining multiple criticality values based on each region block includes: Based on each area block, a first area block is obtained; the first area block is any one of the area blocks; Based on the first area block, a plurality of second coordinate points are acquired; the second coordinate points are any coordinate points located in the first area block; Based on each second coordinate point, a second eigenvector corresponding to each second coordinate point is obtained; the second eigenvector is a transport frequency difference value corresponding to each second coordinate point and a coordinate value corresponding to the plane of the first region; the transport frequency difference value is a difference between a current transport frequency value and a historical transport frequency value of the corresponding second coordinate point; Based on the clustering algorithm, clustering each second coordinate point by the second eigenvector to obtain a plurality of second clusters; Based on each second cluster, a criticality value corresponding to the first region block is obtained.

7. The method for constructing a digital twin for customs supervision according to claim 6, characterized in that: The calculation formula for obtaining the criticality value corresponding to the first region block based on each second cluster is as follows: Wherein, M represents the criticality value corresponding to the first region block; m represents the number of second clusters corresponding to the first region block; Represents the sum of the height values of each second coordinate point corresponding to the i-th second cluster; Represents the number of each second coordinate point in the i-th second cluster; Indicates the area corresponding to the first region block; represents the area corresponding to the first region plane; Indicates that the value in the brackets is mapped to the range [0, 1].

8. The method for constructing a digital twin for customs supervision according to claim 7, characterized in that: The configuration of the level of detail of the corresponding area block based on each criticality value includes: If the criticality value corresponding to the first area block is greater than or equal to a preset value, the detail level of the first area block is configured as a high detail level; otherwise, the detail level of the first area block is configured as a low detail level.

9. The digital twin construction system applied to customs supervision is characterized by: include: Reader for acquiring multiple historical digital twin 3D models under customs supervision; A server is used to divide the three-dimensional model into multiple area blocks based on each historical digital twin three-dimensional model; And, based on each area block, a plurality of criticality values are obtained; the area blocks correspond to the criticality values one by one; the criticality values are used to at least characterize the density of the goods stacked in the corresponding area block; and, based on each criticality value, configuring a level of detail of the corresponding area block; And, based on the level of detail of each area block, render and generate the current digital twin 3D model; Based on each historical digital twin 3D model, the 3D model is divided into multiple area blocks, including: Based on the three-dimensional model, a first regional plane is obtained; the first regional plane is a regional plane formed by the projection of the three-dimensional model along the z-axis direction; the z-axis of the three-dimensional model is parallel to the vertical direction in reality; Based on the first regional plane, obtaining a first coordinate point; the first coordinate point is an arbitrary coordinate point in the first regional plane; Based on each historical digital twin three-dimensional model, obtaining each sequence segment corresponding to the first coordinate point; each sequence segment is used to at least indicate whether the first coordinate point in the corresponding historical digital twin three-dimensional model has goods deposited or withdrawn; Based on each sequence segment, a transport frequency value is obtained; the transport frequency value is used to at least represent the frequency of cargo transportation at the first coordinate point; Based on the transportation frequency value, the three-dimensional model is divided into a plurality of area blocks.

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