A logistics rapid verification method and system based on data matching

Abstract

The present invention discloses a method and system for rapid logistics verification based on data matching, which belongs to the technical field of big data storage. The method comprises: generating a standard logistics route; establishing a storage network, the storage network comprising a plurality of storage nodes, splitting the standard logistics route into a plurality of sub-data, and storing the sub-data in different storage nodes; defining the storage node storing the sub-data as a first node, converting the sub-data into a fingerprint code based on a conversion algorithm, and storing the fingerprint code of the sub-data in a plurality of storage nodes other than the first node, which are defined as a second node; obtaining the identity code of the target item and the logistics information of the current site, locating the corresponding first node and second node; converting the logistics information into a verification code based on a conversion algorithm, and verifying the verification code with the fingerprint code, and if the number of fingerprint codes identical to the verification code exceeds a first threshold, the verification is passed. The present invention can disperse the storage of logistics data, thereby quickly feeding back the logistics verification result.

Description

Technical Field

[0001] The present invention belongs to the technical field of big data storage, and in particular relates to a logistics rapid verification method and system based on data matching. Background Art

[0002] With the rapid development of e-commerce, more and more people choose to shop online. The process of online shopping will inevitably involve the transportation of goods. During the transportation of goods, the logistics information needs to be continuously monitored to ensure the accuracy and traceability of the transportation process. For example, Chinese patent document CN109933486B discloses a monitoring and processing method, device and system for logistics data. The method automatically detects order data through a program. If a problem order is found, the data corresponding to the problem order is re-acquired, and the order obtained again is used as a pending order, and then the logistics data in the pending order is verified, and finally the logistics data is sent to a logistics server for data distribution and verification. For example, Chinese patent document CN117194486A discloses a cold chain traceability method and system based on blockchain and a verifiable database. After the cold chain product factory completes the production of the product, the method generates a product batch for the product, and uses the product batch as the unique commodity identifier in the first verifiable database to manage the product; when the cold chain logistics company hands over the product to the cold chain product factory, a transport order number for the product is generated, and the transport order number is used as the unique commodity identifier in the second verifiable database to manage the product; when the cold chain product seller hands over the product to the cold chain logistics company, an order number for the product is generated, and the order number is used as the unique commodity identifier in the third verifiable database to manage the product; the method can perform traceability query and verification on the product by obtaining the order number.

[0003] In actual logistics transportation, every time the goods arrive at a transit point, relevant personnel are required to scan and verify the logistics information of the goods to ensure that the goods are transported along the correct transportation route. However, as time goes by, the logistics data stored in the server will increase, which will make the server query speed slower and slower. Therefore, how to better store the logistics data and quickly feedback the verification results to the site has become a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a logistics rapid verification method and system based on data matching to solve the problems in the prior art.

[0005] In order to achieve the above-mentioned object of the invention, the present invention proposes a method for generating a virtual building model, comprising:

[0006] Setting transportation rules, inputting the origin and destination of the target item, and generating a standard logistics route based on the origin, the destination and the transportation rules, wherein the standard logistics route includes multiple transit points;

[0007] Establishing a storage network, the storage network comprising a plurality of storage nodes, splitting the standard logistics route into a plurality of sub-data based on the origin, the destination and the transit point, each of the sub-data comprising an identity code of the target item, and storing the sub-data in different storage nodes;

[0008] The storage node storing the sub-data is defined as a first node, the sub-data is converted into a fingerprint code based on a conversion algorithm, the fingerprint code of the sub-data is stored in a plurality of the storage nodes other than the first node, which are defined as second nodes, and an association rule addressing the second node is stored in the first node;

[0009] Acquire the identity code of the target item and the logistics information of the current site, locate the corresponding first node based on the identity code and the logistics information, and locate the second node based on the association rule in the first node;

[0010] The logistics information is converted into a verification code based on the conversion algorithm, and the verification code is verified with the fingerprint code in the second node. If the number of fingerprint codes that are the same as the verification code exceeds a first threshold, the verification is passed.

[0011] Further, storing the sub-data in different storage nodes comprises the following steps:

[0012] The sub-data includes first data to Nth data, N is the sum of the number of the origin, the transit point and the destination, a management layer and a plurality of network layers 1 to M are established in the storage network, the management layer includes a management node, and the network layer includes a plurality of the storage nodes;

[0013] The management node stores the standard logistics route as the first data in the storage node in network layer 1. After removing the destination from the first data, the management node obtains the second data, and stores the second data in the storage node in network layer 2. After removing the transit point from the second data, the management node obtains the third data, and stores the third data in the storage node in network layer 3. This step is repeated until the storage of the Nth data is completed, and only the origin exists in the Nth data.

[0014] Furthermore, an index is set in each storage node, and after obtaining the first to Nth data of the plurality of target items, in each network layer, the first to Nth data are stored in the storage node based on the index.

[0015] Further, if the sub-data in the storage nodes of the adjacent network layers have a containment relationship, a pointing mark is stored in the storage node.

[0016] Further, locating the corresponding first node based on the logistics information includes the following steps:

[0017] Based on the identity code, the origin of the target item is obtained, and a starting node is located in the network layer M, where the starting node is the storage node including the origin and the identity code corresponding to the target item. If the storage node does not exist, the search continues in the network layer M-1, and this step is repeated until the starting node is located.

[0018] Define the starting node in network layer J, locate the transit node in network layer J-1 based on the pointing mark, the transit node includes the identity code and the place of origin of the target item, locate the transit node in network layer J-2 based on the pointing mark, repeat this step until the logistics information is located in the storage node, and define the transit node that locates the logistics information for the first time as the first node.

[0019] Furthermore, if the starting node is not located after traversing all network layers, the storage node containing the identity code and the origin is located and defined as the upper-level node. The origin is extracted from the upper-level node as the Nth data, the Nth data is restored to the storage node of the corresponding network layer, and the storage node is defined as the starting node.

[0020] Further, the transit place or the destination to which the target item is to arrive after the current logistics information is defined as the target address, and after completing the verification of the current logistics information, the predicted time for the target item to arrive at the target address is calculated based on the transportation method of the target item and the distance from the target address;

[0021] The first node storing the target address is located, and the corresponding second node is located based on the association rule. The operation load of each second node at the prediction time is predicted based on the historical operation data of the second node, and the second node whose operation load exceeds a second threshold is defined as a migration node. The fingerprint code in the migration node is migrated to the other storage nodes whose operation load is lower than the second threshold as the new second node, and the association rule is updated based on the migrated second node.

[0022] Further, predicting the operating load of the second node at the prediction time includes the following steps:

[0023] A BP neural network model is established, and a training set is constructed based on the operating load of the storage node and the corresponding occurrence time point, wherein the occurrence time point is the input data and the operating load is the output data. After the BP neural network model is trained based on the training set, the predicted time obtained this time is input into the trained BP neural network model to obtain the operating load of the storage node at the predicted time.

[0024] Furthermore, the conversion algorithm is a hash algorithm.

[0025] The present invention also provides a logistics rapid verification system based on data matching, which is used to implement the above-mentioned logistics rapid verification method based on data matching, and the system includes:

[0026] A generation module is provided with a transportation rule, and an origin and a destination of a target item are inputted. The generation module generates a standard logistics route based on the origin, the destination and the transportation rule, and the standard logistics route includes a plurality of transit points;

[0027] A storage module, wherein there is a storage network, the storage network includes a plurality of storage nodes, the standard logistics route is split into a plurality of sub-data based on the origin, the destination and the transit point, each of the sub-data includes the identity code of the target item, the sub-data are stored in different storage nodes, the storage node storing the sub-data is defined as a first node, the sub-data is converted into a fingerprint code based on a conversion algorithm, the fingerprint code of the sub-data is stored in a plurality of the storage nodes except the first node, which are defined as a second node, and an association rule addressing the second node is stored in the first node;

[0028] a tracing module, which obtains the identity code of the target item and the logistics information of the current site, locates the corresponding first node based on the identity code and the logistics information, and locates the second node based on the association rule in the first node;

[0029] The verification module converts the logistics information into a verification code based on the conversion algorithm, and verifies the verification code with the fingerprint code in the second node. If the number of fingerprint codes that are the same as the verification code exceeds a first threshold, the verification is passed.

[0030] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0031] The present invention first generates a standard logistics route according to the origin and destination of the goods to be transported, and then splits the standard logistics route into multiple sub-data, which are stored in different storage nodes respectively, so as to avoid storing the entire logistics data in a single storage node, resulting in a situation where the storage node is overloaded and the reading is too slow. In addition, the decentralized storage reduces the size of each data, increases the data reading speed, and improves the efficiency of logistics information query. After the goods arrive at the transit station, the intermediate station site is uploaded as logistics information and checked with the stored standard logistics route to verify the correctness of the logistics information.

[0032] After storing the sub-data, the present invention also uses a hash algorithm to convert the sub-data into a fingerprint code and stores it in different storage nodes. After the logistics information is verified, the same hash algorithm is used to convert the logistics information into a verification code. By comparing the fingerprint code and the verification code, it can be determined whether the sub-data in the sub-data has been tampered with after storage, thereby further improving the accuracy of logistics verification. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a flow chart of the steps of a method for rapid logistics verification based on data matching of the present invention;

[0034] Figure 2 A schematic diagram of a storage network of the present invention;

[0035] Figure 3 The present invention is a structural schematic diagram of a rapid logistics verification system based on data matching. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0037] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0038] like Figure 1 As shown, a logistics rapid verification method based on data matching includes:

[0039] Step S1: Set the transportation rules, input the origin and destination of the target item, and generate a standard logistics route based on the origin, destination and transportation rules. The standard logistics route includes multiple transit points.

[0040] The transportation rules are set by the user based on the item transfer stations deployed by the user. The target items are the goods that need to be transported. When the recipient enters the origin and destination of the target items, a standard logistics route can be generated based on the distance between the two, the transportation method selected by the user, and the transfer station. In the standard logistics route, all transit points except the origin and destination are transit points.

[0041] Step S2: Establish a storage network, which includes multiple storage nodes. The standard logistics route is split into multiple sub-data based on the origin, destination and transit point. Each sub-data includes the identity code of the target item, and the sub-data is stored in different storage nodes.

[0042] Specifically, first deploy multiple storage servers, each storage server serves as a storage node, and then connect the storage nodes to form a storage network as needed; split each piece of logistics information into multiple sub-data, so that the standard logistics route can be stored as multiple data in a dispersed manner to avoid storage in a single storage node, which may cause the storage node to be overloaded and result in slow reading; dispersed storage reduces the size of each piece of data and increases the data reading speed. This step improves the timeliness of logistics information query; in addition, an identity code is generated based on the target item's delivery date, recipient's phone number, etc. when receiving the item. The identity code is a string of characters, and each target item has a unique identity code.

[0043] Step S3: define the storage node storing the sub-data as the first node, convert the sub-data into a fingerprint code based on a conversion algorithm, store the fingerprint code of the sub-data in a plurality of storage nodes other than the first node, define them as the second node, and store the association rule addressing the second node in the first node;

[0044] For example, the standard logistics route is split into 5 sub-data 1-5, and the sub-data 1-5 are stored in 5 storage nodes respectively, then these 5 storage nodes are defined as the first nodes 1-5; the conversion algorithm is the hash algorithm, and the sub-data stored in the first node 1 is input into the hash algorithm to obtain a string, which is the fingerprint code; the fingerprint code is stored in other storage nodes except the first node 1, here three storage nodes are selected to store them respectively, defined as the second nodes 1-3, and then the association rules addressing the second nodes 1-3 are stored in the first node 1.

[0045] Step S4: Obtain the identity code of the target item and the logistics information of the current site, locate the corresponding first node based on the identity code and the logistics information, and locate the second node based on the association rule in the first node.

[0046] Step S5: convert the logistics information into a verification code based on the conversion algorithm, and verify the verification code with the fingerprint code in the second node. If the number of fingerprint codes that are identical to the verification code exceeds a first threshold, the verification is successful.

[0047] When the target item arrives at the transfer site, the identification code is obtained by scanning the QR code pasted on the target item through the scanning terminal. The logistics information of the current site is set in the scanning terminal. The scanning terminal uploads the logistics information and identity code of the current site. If the first node including the logistics information and the identity code is located, it indicates that the target item is transported according to the standard route. If the first node including the logistics information and the identity code is not located, it indicates that the target item has entered the wrong transfer site, thereby realizing the verification of the logistics information.

[0048] In particular, in order to ensure that the sub-data in the storage node is not maliciously modified, after confirming that the logistics information is correct, the logistics information is converted into a verification code using a hash algorithm and compared with the fingerprint code stored in the second node. If it is completely consistent with all or most of the fingerprint codes, it indicates that the sub-data in the first node has not been modified, which further improves the reliability of the logistics information.

[0049] The present invention first generates a standard logistics route according to the origin and destination of the goods to be transported, and then splits the standard logistics route into multiple sub-data, which are stored in different storage nodes respectively, so as to avoid storing the entire logistics data in a single storage node, resulting in a situation where the storage node is overloaded and the reading is too slow. In addition, the decentralized storage reduces the size of each data, increases the data reading speed, and improves the efficiency of logistics information query. After the goods arrive at the transit station, the intermediate station site is uploaded as logistics information and checked with the stored standard logistics route to verify the correctness of the logistics information.

[0050] After storing the sub-data, the present invention also uses a hash algorithm to convert the sub-data into a fingerprint code and stores it in different storage nodes. After the logistics information is verified, the same hash algorithm is used to convert the logistics information into a verification code. By comparing the fingerprint code and the verification code, it can be determined whether the sub-data in the sub-data has been tampered with after storage, thereby further improving the accuracy of logistics verification.

[0051] It is particularly noteworthy that the present invention can store logistics data in a decentralized manner, thereby quickly feeding back logistics verification results to the site.

[0052] In this embodiment, storing sub-data in different storage nodes includes the following steps:

[0053] The sub-data includes first data to Nth data, N is the sum of the number of origins, transit points and destinations, a management layer and multiple network layers 1 to M are established in the storage network, the management layer includes a management node, and the network layer includes multiple storage nodes;

[0054] The management node stores the standard logistics route as the first data in the storage node in network layer 1. After removing the destination from the first data, the management node obtains the second data, and stores the second data in the storage node in network layer 2. After removing the transit point from the second data, the management node obtains the third data, and stores the third data in the storage node in network layer 3. This step is repeated until the storage of the Nth data is completed, and only the origin exists in the Nth data.

[0055] If the target item has one transit point, then the sum of the origin and destination is 3, that is, N = 3. The number of network layers M is set manually, such as Figure 2 As shown, for the convenience of explanation, only three network layers are set here. Network layer 1 has 2 nodes, network layer 2 has 4 storage nodes, and network layer 3 has 8 storage nodes. Management node 0 of the management layer is used to manage and monitor each storage node.

[0056] When storing, first store the complete standard logistics route as the first data in node 1-1, then remove the destination to obtain the second data, which will be smaller than the first data, and store the second data in node 2-1, and then remove the last transit point from the destination to obtain the third data, which only has the departure point, and store the third data in node 3-1. In this implementation, since there are fewer storage nodes at the front network layer, the more complete data will be stored more centrally, so when the complete logistics data needs to be queried, the number of storage nodes that need to be retrieved is reduced.

[0057] An index is set at each storage node, and after obtaining the first to Nth data of multiple target items, in each network layer, the first to Nth data are stored in the storage node based on the index.

[0058] For example, indexes a to n are set in node 1-1 of network layer 1, and the first letter of the first character of the destination in a to n is stored in node 1-1, and the first letter of the first character of the destination in o to z is stored in node 1-2. This step facilitates subsequent retrieval.

[0059] In this embodiment, if the sub-data in the storage nodes of the adjacent network layers have a containment relationship, a pointing mark is stored in the storage node.

[0060] If the second data in the storage node 2-1 is obtained based on the elimination of the storage node 1-1, the storage node 2-1 stores a pointing mark pointing to the storage node 1-1. Through this step, the logistics information of the target item can be quickly traced.

[0061] This embodiment locates the corresponding first node based on logistics information, including the following steps:

[0062] Based on the identity code, the origin of the target item is obtained, and the starting node is located in the network layer M. The starting node is a storage node including the origin and the identity code of the corresponding target item. If the storage node does not exist, continue to search in the network layer M-1 and repeat this step until the starting node is located;

[0063] Define the starting node in network layer J, locate the transit node in network layer J-1 based on the pointing mark, the transit node includes the identity code and origin of the target item, locate the transit node in network layer J-2 based on the pointing mark, repeat this step until the logistics information is located in the storage node, and define the transit node that locates the logistics information for the first time as the first node.

[0064] After scanning and obtaining the identity code of the target item, the place of origin is obtained based on the identity code, and then a search is performed in the network layer M. During the search, the corresponding storage node can be quickly located based on the initial pinyin letter of the first character of the place of origin. If the place of origin is retrieved in the storage node and the place of origin corresponds to the correct identity code, it is considered that the starting node is located.

[0065] If the length of the standard logistics route is less than the number of network layers, it is impossible to find the sub-data that only includes the origin and the identity code in the network layer M, so it is necessary to search in the network layer M-1. Here, it is assumed that the starting node is located in the network layer 3. Since there is a pointing mark in the starting node, the transit node containing the same identity code can be quickly located in the network layer 2. The transit point and the origin are stored in the transit node, and since it is the first time that the transit point appears, the logistics information is checked with the transit point to know whether the logistics information is correct. In addition, since the search is carried out from the last network layer forward, the positive order search from the origin is realized, and the previous address can be checked again during the positioning process to see if it is correct.

[0066] In this embodiment, if the starting node is not located after traversing all network layers, the storage node containing the identity code and the origin is located and defined as the parent node. The origin is extracted from the parent node as the Nth data, the Nth data is restored to the storage node of the corresponding network layer, and the storage node is defined as the starting node.

[0067] If the starting node that stores the origin separately is not found, the possible reason is that the data in the storage node is lost. In this case, search for the storage node that includes the origin in the network layer, for example, search in network layer 1. The storage node in network layer 1 stores complete data, and then restore the searched data to the original storage node.

[0068] In this embodiment, the transit place or destination to which the target item is to arrive after the current logistics information is defined as the target address. After completing the verification of the current logistics information, the predicted time for the target item to arrive at the target address is calculated based on the transportation method of the target item and the distance from the target address.

[0069] Locate the first node storing the target address, locate the corresponding second node based on the association rule, predict the operating load of each second node at the prediction time based on the historical operating data of the second node, define the second node whose operating load exceeds the second threshold as a migration node, migrate the fingerprint code in the migration node to other storage nodes whose operating load is lower than the second threshold as the new second node, and update the association rule based on the migrated second node.

[0070] The modes of transportation include road transportation, truck transportation and air transportation. According to the distance between the current transit point and the next transit point, or the destination, plus the mode of transportation, the estimated arrival time from the current transit point to the next transit point can be calculated; and because the address of the next transit point is known, the first node storing the next transit point can be known in advance, and then the second node can be obtained according to the located first node; after locating the second node, the operating load of the second node at the predicted time is predicted. If the operating load is too large, the fingerprint code in the second node is migrated to other storage nodes. Through this step, the second node used to verify the first node can be replaced according to the operating load, so as to avoid the excessive load of some second nodes, which affects the comparison speed of the verification code and the fingerprint code, thereby ensuring the verification speed of the logistics information.

[0071] In this embodiment, predicting the operating load of the second node at the prediction time includes the following steps:

[0072] A BP neural network model is established, and a training set is constructed based on the operating load of the storage node and the corresponding occurrence time point, where the occurrence time point is the input data and the operating load is the output data. After the BP neural network model is trained based on the training set, the predicted time obtained this time is input into the trained BP neural network model to obtain the operating load of the storage node at the predicted time.

[0073] like Figure 3 As shown, the present invention also provides a logistics rapid verification system based on data matching, which is used to implement the above-mentioned logistics rapid verification method based on data matching, and the system includes:

[0074] A generation module is provided with transportation rules. The origin and destination of the target item are input. The generation module generates a standard logistics route based on the origin, destination and transportation rules. The standard logistics route includes multiple transit points.

[0075] A storage module, wherein there is a storage network, the storage network includes a plurality of storage nodes, a standard logistics route is split into a plurality of sub-data based on an origin, a destination, and a transit point, each sub-data includes an identity code of a target item, the sub-data are stored in different storage nodes, a storage node storing the sub-data is defined as a first node, the sub-data is converted into a fingerprint code based on a conversion algorithm, the fingerprint code of the sub-data is stored in a plurality of storage nodes other than the first node, which are defined as a second node, and an association rule addressing the second node is stored in the first node;

[0076] The tracing module obtains the identity code of the target item and the logistics information of the current site, locates the corresponding first node based on the identity code and the logistics information, and locates the second node based on the association rule in the first node;

[0077] The verification module converts the logistics information into a verification code based on a conversion algorithm, and verifies the verification code with the fingerprint code in the second node. If the number of fingerprint codes that are identical to the verification code exceeds a first threshold, the verification is passed.

[0078] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0079] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0080] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for those of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A rapid logistics verification method based on data matching, characterized in that: include: Setting transportation rules, inputting the origin and destination of the target item, and generating a standard logistics route based on the origin, the destination and the transportation rules, wherein the standard logistics route includes multiple transit points; Establishing a storage network, the storage network comprising a plurality of storage nodes, splitting the standard logistics route into a plurality of sub-data based on the origin, the destination and the transit point, each sub-data comprising the identity code of the target item, and storing different sub-data in different storage nodes respectively; For any sub-data, define the storage node storing the sub-data as the first node, convert the sub-data into a fingerprint code based on a conversion algorithm, store the fingerprint code of the sub-data in a plurality of storage nodes other than the first node, define them as the second node, and store an association rule addressing the second node in the first node; Acquire the identity code of the target item and the logistics information of the current site, locate the corresponding first node based on the identity code and the logistics information, and locate the second node based on the association rule in the first node; Convert the logistics information into a verification code based on the conversion algorithm, and verify the verification code with the fingerprint code in the second node. If the number of fingerprint codes that are identical to the verification code exceeds a first threshold, the verification is successful. Storing different sub-data in different storage nodes includes the following steps: The plurality of sub-data include first data to Nth data, N being the sum of the number of the origin, the transit point and the destination, and establishing a management layer and a plurality of network layers 1 to M in the storage network, the management layer including a management node, and the network layer including a plurality of the storage nodes; The management node stores the standard logistics route as the first data in the storage node in network layer 1. After removing the destination from the first data, the management node obtains the second data, and stores the second data in the storage node in network layer 2. After removing the transit point from the second data, the management node obtains the third data, and stores the third data in the storage node in network layer 3. This step is repeated until the storage of the Nth data is completed, and only the origin exists in the Nth data.

2. The method according to claim 1, characterized in that An index is set in each storage node. After obtaining the first to Nth data of multiple target items, in each network layer, the first to Nth data are stored in the storage node based on the index. When setting, indexes a to n are set in node 1-1 of network layer 1, and the first letter of the first character of the destination in the first data is stored in node 1-1 in a to n, and the first letter of the first character of the destination is stored in node 1-2 in o to z. Repeat this step until the storage of the Nth data is completed.

3. The method according to claim 1 or 2, characterized in that: If the sub-data in the storage nodes of the adjacent network layers have a containment relationship, a pointing mark is stored in the storage nodes.

4. The method according to claim 3, characterized in that Locating the first node corresponding to the logistics information includes the following steps: Based on the identity code, the origin of the target item is obtained, and a starting node is located in the network layer M, where the starting node is the storage node that includes the origin and the identity code corresponding to the target item. If the storage node does not exist, the search continues in the network layer M-1, and this step is repeated until the starting node is located. Define the starting node in network layer J, locate the transit node in network layer J-1 based on the pointing mark, the transit node includes the identity code and the place of origin of the target item, locate the transit node in network layer J-2 based on the pointing mark, repeat this step until the logistics information is located in the storage node, and define the transit node that locates the logistics information for the first time as the first node.

5. The method according to claim 4, characterized in that If the starting node is not located after traversing all network layers, the storage node that at least includes the identity code and the origin is located and defined as the upper-level node. The origin is extracted from the upper-level node as the Nth data, the Nth data is restored to the storage node of the corresponding network layer, and the storage node is defined as the starting node.

6. The method according to claim 1, characterized in that The transit place or the destination to which the target item is to arrive after the current logistics information is defined as the target address, and after completing the verification of the current logistics information, the predicted time for the target item to arrive at the target address is calculated based on the transportation method of the target item and the distance from the target address; The first node storing the target address is located, and the corresponding second node is located based on the association rule. The operation load of each second node at the prediction time is predicted based on the historical operation data of the second node, and the second node whose operation load exceeds a second threshold is defined as a migration node. The fingerprint code in the migration node is migrated to the other storage nodes whose operation load is lower than the second threshold as the new second node, and the association rule is updated based on the migrated second node.

7. The method according to claim 6, characterized in that Predicting the operating load of the second node at the prediction time comprises the following steps: A BP neural network model is established, and a training set is constructed based on the operating load of the storage node and the corresponding occurrence time point, wherein the occurrence time point is the input data and the operating load is the output data. After the BP neural network model is trained based on the training set, the predicted time obtained this time is input into the trained BP neural network model to obtain the operating load of the storage node at the predicted time.

8. The method according to claim 1, characterized in that The conversion algorithm is a hash algorithm.

9. A logistics rapid verification system based on data matching, used to implement the method according to any one of claims 1 to 8, characterized in that: include: A generation module is provided with a transportation rule, and an origin and a destination of a target item are inputted. The generation module generates a standard logistics route based on the origin, the destination and the transportation rule, and the standard logistics route includes a plurality of transit points; A storage module, wherein there is a storage network, the storage network includes a plurality of storage nodes, the standard logistics route is split into a plurality of sub-data based on the origin, the destination and the transit point, each sub-data includes the identity code of the target item, and different sub-data are respectively stored in different storage nodes; The plurality of sub-data include first data to Nth data, N is the sum of the number of the origin, the transit point and the destination, a management layer and a plurality of network layers 1 to M are established in the storage network, the management layer includes a management node, and the network layer includes a plurality of the storage nodes; The management node stores the standard logistics route as the first data in the storage node in the network layer 1. After the management node removes the destination in the first data, it obtains the second data, and stores the second data in the storage node in the network layer 2. After the management node removes the transit point in the second data, it obtains the third data, and stores the third data in the storage node in the network layer 3. The above process is repeated until the storage of the Nth data is completed, and only the origin exists in the Nth data; For any sub-data, define the storage node storing the sub-data as the first node, convert the sub-data into a fingerprint code based on a conversion algorithm, store the fingerprint code of the sub-data in a plurality of storage nodes other than the first node, define them as the second node, and store an association rule addressing the second node in the first node; a tracing module, which obtains the identity code of the target item and the logistics information of the current site, locates the corresponding first node based on the identity code and the logistics information, and locates the second node based on the association rule in the first node; The verification module converts the logistics information into a verification code based on the conversion algorithm, and verifies the verification code with the fingerprint code in the second node. If the number of fingerprint codes that are the same as the verification code exceeds a first threshold, the verification is passed.

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