Blockchain-based logistics supervision methods, devices, electronic equipment, and storage media

Abstract

This disclosure provides a blockchain-based logistics supervision method, apparatus, electronic device, and storage medium, applicable to the field of blockchain technology. The method includes: processing initial feature data of acquired target goods on the blockchain to generate first data, the first data including a first hash value associated with the initial feature data, the initial feature data being obtained based on a first image of the target goods at a first location; monitoring the status information of the target goods in real time through an electronic lock, processing acquired abnormal status information on the blockchain to generate second data; processing the acquired end feature data of the target goods on the blockchain to generate third data, the third data including a second hash value associated with the end feature data, the end feature data being obtained based on a second image of the target goods at a second location; and determining a supervision strategy for the target goods based on the comparison result of the acquired first data and third data and / or the second data.

Description

Technical Field

[0001] This disclosure relates to the field of blockchain technology, and specifically to a blockchain-based logistics supervision method, apparatus, electronic device, and readable storage medium. Background Technology

[0002] With the development of economic globalization, the volume and quantity of logistics and goods have grown rapidly. Various situations may arise during transportation, leading to changes in the goods and quantities transported. After goods arrive at their destination, it's impossible to determine whether these changes occurred during transit, necessitating manual inspection, which is inefficient and detrimental to efficient transportation. Furthermore, due to different carriers and cargo locations, carriers, consignees, and suppliers cannot obtain timely information on the logistics status of goods during transport. Current technologies cannot accurately assess the status of goods during logistics, and all parties involved in logistics cannot effectively and accurately obtain logistics information. Summary of the Invention

[0003] In view of this, this disclosure provides a blockchain-based logistics supervision method, device, electronic device, and storage medium, which at least partially solves the problems of being unable to judge the status of goods during the logistics process and being unable to accurately obtain goods logistics information.

[0004] A first aspect of this disclosure provides a blockchain-based logistics supervision method, comprising: processing initial characteristic data of acquired target goods on the blockchain to generate first data, the first data including a first hash value associated with the initial characteristic data, the initial characteristic data being acquired based on a first image of the target goods at a first location; monitoring the status information of the target goods in real time via an electronic lock, processing acquired abnormal status information on the blockchain to generate second data; processing the acquired end characteristic data of the target goods on the blockchain to generate third data, the third data including a second hash value associated with the end characteristic data, the end characteristic data being acquired based on a second image of the target goods at a second location; and determining a supervision strategy for the target goods based on a comparison result between the acquired first data and the third data and / or the second data.

[0005] In an exemplary embodiment of this disclosure, the method further includes: when the target goods are located at the first location, performing on-chain processing on the acquired initial business data of the target goods to generate initial logistics information of the target goods; and when the target goods are located at the second location, performing on-chain processing on the acquired end business data of the target goods to generate end logistics information of the target goods, wherein the initial business data and the end business data are acquired from an Internet of Things data server.

[0006] In an exemplary embodiment of this disclosure, the method further includes: before performing on-chain processing on the initial feature data of the acquired target goods to generate first data, taking a picture of the target goods at the first location to obtain a first image of the target goods; and performing feature extraction on the first image of the target goods to generate the initial feature data of the target goods.

[0007] In an exemplary embodiment of this disclosure, the step of uploading the initial feature data of the acquired target goods to the blockchain to generate the first data includes: performing a hash calculation on the initial feature data using a preset algorithm to generate a first hash value; and signing the first hash value to generate the first data.

[0008] In an exemplary embodiment of this disclosure, the method further includes: before performing on-chain processing on the acquired end feature data of the target goods to generate third data, taking a picture of the target goods at the second location to obtain a second image of the target goods; and performing feature extraction on the second image of the target goods to generate end feature data of the target goods.

[0009] In an exemplary embodiment of this disclosure, the step of uploading the acquired end feature data of the target goods to the blockchain to generate third data includes: performing a hash calculation on the end feature data using a preset algorithm to generate a second hash value; and signing the second hash value to generate third data.

[0010] In an exemplary embodiment of this disclosure, the method further includes: before determining the regulatory strategy for the target cargo based on the comparison result of the acquired first data and the third data and / or the second data, the method includes: decrypting the first data to generate a first hash value; decrypting the third data to generate a second hash value; and determining the comparison result based on the first hash value and the second hash value, wherein when the first hash value and the second hash value are the same, the comparison result is determined to be normal logistics, and when the first hash value and the second hash value are different, the comparison result is determined to be abnormal logistics.

[0011] In an exemplary embodiment of this disclosure, determining the regulatory strategy for the target goods based on the comparison result of the first data and the third data and / or the second data includes: when the comparison result indicates abnormal logistics, or when the comparison result indicates normal logistics and the second data is present, determining that the regulatory strategy for the target goods is to require unpacking and inspection.

[0012] In an exemplary embodiment of this disclosure, the step of real-time monitoring of the status information of the target goods through an electronic lock, and uploading the acquired abnormal status information to the blockchain to generate second data includes: acquiring the status information of the target goods through the electronic lock, wherein the status information includes at least one of sealing status information, geographical location information, and time information; determining whether the status information of the target goods is abnormal through an IoT data server; and uploading the abnormal status information to the blockchain to generate second data.

[0013] In an exemplary embodiment of this disclosure, the method further includes: responding to a cross-chain synchronization instruction by synchronizing the first data, the second data, and the third data from a source blockchain to at least one target blockchain via a synchronization component.

[0014] In an exemplary embodiment of this disclosure, the method further includes: responding to a query instruction to obtain at least one of the logistics initial information, the logistics end information, the first data, the second data, and the third data from the source blockchain and the at least one target blockchain.

[0015] A second aspect of this disclosure provides a blockchain-based logistics monitoring device, comprising: a first generation module configured to perform on-chain processing on initial feature data of acquired target goods to generate first data, the first data including a first hash value associated with the initial feature data, the initial feature data being acquired based on a first image of the target goods at a first location; a second generation module configured to perform real-time monitoring of the status information of the target goods via an electronic lock, and perform on-chain processing on acquired abnormal status information to generate second data; a third generation module configured to perform on-chain processing on final feature data of acquired target goods to generate third data, the third data including a second hash value associated with the final feature data, the final feature data being acquired based on a second image of the target goods at a second location; and a determination module configured to determine a monitoring strategy for the target goods based on a comparison result between the acquired first data and the third data and / or the second data.

[0016] A third aspect of this disclosure provides an electronic device, including: one or more processors; and a storage device for storing executable instructions, which, when executed by the processor, implement the method described above.

[0017] A fourth aspect of this disclosure provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, implement the method described above.

[0018] A fifth aspect of this disclosure provides a computer program product including a computer program that, when executed by a processor, implements the method described above.

[0019] According to embodiments of this disclosure, by comparing the initial characteristic data of the target cargo obtained at a first location and the final characteristic data of the target cargo obtained at a second location, and by determining the regulatory strategy for the target cargo based on second data generated from abnormal status information during the logistics process, the efficiency of logistics supervision can be effectively improved. Furthermore, by uploading the acquired initial characteristic data, final characteristic data, and abnormal status information to the blockchain, relevant logistics users can easily obtain detailed logistics information of the target cargo from the blockchain, and due to the immutability of information in the blockchain, the obtained logistics information is more accurate. Attached Figure Description

[0020] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0021] Figure 1 The illustration schematically depicts an exemplary system architecture for applying a blockchain-based logistics monitoring method according to embodiments of this disclosure;

[0022] Figure 2 A flowchart illustrating a blockchain-based logistics supervision method according to an embodiment of this disclosure is shown schematically.

[0023] Figure 3 The flowchart illustrating the blockchain-based logistics supervision method according to an embodiment of the present disclosure in operation S250 is shown.

[0024] Figure 4 The flowchart illustrating operation S300 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure before the generation of first data is shown.

[0025] Figure 5 The flowchart illustrating the operation S210 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown in the illustration.

[0026] Figure 6 The flowchart illustrating the operation S220 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown in the illustration.

[0027] Figure 7 The flowchart illustrating operation S400 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure before the generation of second data is shown.

[0028] Figure 8 The flowchart illustrating the blockchain-based logistics supervision method according to an embodiment of the present disclosure in operation S230 is shown in the diagram.

[0029] Figure 9 The flowchart illustrates an operation S500 of a blockchain-based logistics monitoring method according to an embodiment of the present disclosure before determining the monitoring strategy for target goods.

[0030] Figure 10 The schematic diagram illustrates a specific flowchart of the blockchain-based logistics supervision method according to an embodiment of the present disclosure in operation S240;

[0031] Figure 11 The flowchart illustrating the operation S260 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown in the illustration.

[0032] Figure 12 The flowchart illustrating the blockchain-based logistics supervision method according to an embodiment of the present disclosure in operation S270 is shown in the diagram.

[0033] Figure 13 A block diagram of a blockchain-based logistics monitoring device according to an embodiment of the present disclosure is shown schematically.

[0034] Figure 14 A block diagram of an electronic device for implementing a blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0035] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0036] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0037] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0038] When using expressions such as "at least one of A, B, or C," it should generally be interpreted in accordance with the meaning commonly understood by those skilled in the art (e.g., "a system having at least one of A, B, or C" should include, but is not limited to, systems having A alone, having B alone, having C alone, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.). The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, features defined with "first" or "second" may explicitly or implicitly include one or more features.

[0039] In the technical solution disclosed herein, the acquisition, storage, and application of user personal information comply with relevant laws and regulations, necessary confidentiality measures have been taken, and there is no violation of public order and good morals. All operations involving the acquisition, storage, and application of user personal information in the technical solution disclosed herein have been authorized by the user.

[0040] To address the problems in related technologies such as the inability to determine the status of goods during the logistics process and the inability of logistics stakeholders to effectively and accurately obtain logistics information, embodiments of this disclosure provide a blockchain-based logistics monitoring method, apparatus, electronic device, and readable storage medium. The blockchain-based logistics monitoring method includes: processing initial feature data of the acquired target goods on the blockchain to generate first data, the first data including a first hash value associated with the initial feature data, which is obtained from a first image of the target goods at a first location; monitoring the status information of the target goods in real time using an electronic lock, processing abnormal status information on the blockchain to generate second data; processing the acquired end feature data of the target goods on the blockchain to generate third data, the third data including a second hash value associated with the end feature data, which is obtained from a second image of the target goods at a second location; and determining a monitoring strategy for the target goods based on the comparison result of the acquired first data and third data and / or the second data.

[0041] According to embodiments of this disclosure, by comparing the initial characteristic data of the target cargo obtained at a first location and the final characteristic data of the target cargo obtained at a second location, and by determining the regulatory strategy for the target cargo based on second data generated from abnormal status information during the logistics process, the efficiency of logistics supervision can be effectively improved. Furthermore, by uploading the acquired initial characteristic data, final characteristic data, and abnormal status information to the blockchain, relevant logistics users can easily obtain detailed logistics information of the target cargo from the blockchain, and due to the immutability of information in the blockchain, the obtained logistics information is more accurate.

[0042] Figure 1 This illustration schematically depicts an exemplary system architecture to which a blockchain-based logistics monitoring method can be applied according to embodiments of this disclosure. It should be noted that... Figure 1 The examples shown are merely examples of system architectures applicable to the embodiments of this disclosure, intended to help those skilled in the art understand the technical content of this disclosure. However, they do not imply that the embodiments of this disclosure cannot be used in other devices, systems, environments, or scenarios. It should be noted that the logistics monitoring methods, devices, electronic devices, and readable storage media provided in the embodiments of this disclosure can be used in relevant aspects of the logistics field, as well as in various fields other than logistics. The logistics monitoring methods, devices, electronic devices, and readable storage media provided in the embodiments of this disclosure do not limit the application field.

[0043] like Figure 1 As shown, the system architecture applicable to blockchain-based logistics supervision methods in this disclosure includes a first image acquisition device 101, an electronic lock 102, a second image acquisition device 103, a user 104, an Internet of Things data server 105, a blockchain 106, and a network 107.

[0044] The first image acquisition device 101 and the second image acquisition device 102 are used to acquire images of target goods in logistics at different locations or positions. For example, they can be X-ray image acquisition devices used to acquire X-ray images of the target goods.

[0045] The electronic lock 102 can be a lock that detects the status information of the target goods. The electronic lock can be set to be legally opened at a set location by a specific key or command. When the opening conditions of the electronic lock are not met, abnormal information of the electronic lock being illegally opened can be recorded, and the status of the target goods during logistics transportation can be judged by the abnormal information.

[0046] User 104 could be a cargo carrier, consignee, cargo supplier, customs officer, etc., who can obtain data from blockchain 106 through network 107 and view it or write data to the blockchain, thereby viewing and judging the logistics information and status of the target goods.

[0047] The Internet of Things (IoT) data server 105 can be, for example, a server that provides various logistics information services, such as a server that inputs, analyzes, or manages information about carriers, consignees, and cargo suppliers.

[0048] Blockchain 106 is, for example, a consortium blockchain for use by specific groups or organizations, such as a blockchain for cargo carriers, consignees, cargo suppliers, customs officials, etc., so that relevant users can obtain data information from blockchain 106.

[0049] Network 107 serves as a medium for providing communication links between the first image acquisition device 101, electronic lock 102, second image acquisition device 103, user 104, IoT data server 105, and blockchain 106. Network 107 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0050] pass Figure 1 The system architecture shown can implement the blockchain-based logistics monitoring method of this disclosure. For example, the target goods are imaged at the initial location by a first image acquisition device 101, and the status information of the target goods during transportation is monitored in real time by an electronic lock 102. After the target goods arrive at the destination, the target goods are imaged again by a second image acquisition device 103. The acquired images are processed and uploaded to the blockchain 106, making it convenient for other users 104 or the Internet of Things 105 to view or access the information.

[0051] It should be understood that Figure 1 The number of the first image acquisition device, electronic lock, second image acquisition device, user, IoT data server, blockchain, and network in the diagram is merely illustrative. Depending on the implementation requirements, any number of the first image acquisition device, electronic lock, second image acquisition device, user, IoT data server, blockchain, and network can be included.

[0052] Figure 2 A flowchart illustrating a blockchain-based logistics supervision method according to an embodiment of this disclosure is shown.

[0053] like Figure 2 As shown, the process 200 of the blockchain-based logistics supervision method disclosed herein includes operations S210 to S240.

[0054] In operation S210, the initial feature data of the acquired target cargo is processed on the blockchain to generate first data. The first data includes a first hash value associated with the initial feature data, which is obtained based on a first image of the target cargo at a first location.

[0055] In operation S220, the status information of the target goods is monitored in real time through electronic locks, and abnormal status information is processed on the blockchain to generate second data.

[0056] In operation S230, the acquired end feature data of the target cargo is processed on the blockchain to generate third data. The third data includes a second hash value associated with the end feature data, which is obtained based on a second image of the target cargo at a second location.

[0057] In operation S240, a regulatory strategy for the target cargo is determined based on the comparison results of the first data and the third data and / or the second data.

[0058] The following combination Figures 2 to 12 The blockchain-based logistics supervision method of this disclosure will be described in detail.

[0059] In embodiments of this disclosure, the target goods may be, for example, goods requiring logistics monitoring. The first location may be, for example, the shipping location of the target goods, or the initial location where logistics monitoring of the target goods is required. The second location may be, for example, the receiving location of the target goods, or the ending location where logistics monitoring of the target goods ends.

[0060] During transit, goods may be opened or unsealed. If the parties involved, from one location to another, or who require inspection, do not check the goods, they cannot effectively determine whether the goods have been altered during transit. Furthermore, opening and inspecting the goods is time-consuming and labor-intensive, hindering efficiency in the logistics process. Conversely, if the goods remain unchanged during transit, the opening and inspection process results in a significant amount of wasted work.

[0061] By comparing the characteristic data of the target goods at the first and second locations, it is determined whether the target goods have changed during the logistics process. In addition, the logistics supervision method disclosed herein also includes operation S250.

[0062] Figure 3 The flowchart illustrating the operation S250 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown.

[0063] like Figure 3As shown, operation S250 includes operations S251 to S252.

[0064] In operation S251, when the target goods are in the first position, the initial business data of the acquired target goods are processed on the blockchain to generate the initial logistics information of the target goods.

[0065] For example, initial business data may include information related to the logistics of the target goods, such as the origin of the goods, driver information, cargo information, carrier information, shipper information, manufacturer information, trunk transporter information, and first-end receiving information. After obtaining the initial business data, one or more of the initial business data can be processed on the blockchain to generate initial logistics information for the target goods. For example, the on-chain data can be verified, and after successful verification, it can be recorded in a block on the blockchain. Relevant users can obtain the initial logistics information of the target goods by consulting the information in this block.

[0066] In operation S252, when the target goods are located at the second position, the acquired end-of-business data of the target goods is processed on the blockchain to generate logistics end information for the target goods.

[0067] For example, the data indicating the end of a business transaction can be business data related to the logistics of the target goods, such as the destination information, driver information, cargo information, carrier information, shipper information, manufacturer information, trunk transporter information, and last-mile delivery information. Following the same process as putting the initial business data on the blockchain, the data indicating the end of a business transaction is also put on the blockchain, making it convenient for users to view the logistics completion information of the target goods recorded in the blockchain.

[0068] In the embodiments of this disclosure, initial and final business data are obtained from an IoT data server. For example, before the target goods enter the logistics process, during the logistics process, and after the logistics completion, information such as the origin, destination, driver, cargo, carrier, shipper, manufacturer, trunk transporter, first-end receiver, and last-end delivery provider of the target goods is collected through various data collection devices and stored in the IoT data server. When using blockchain, the information that each party needs to upload to the blockchain is defined, and according to the corresponding on-chain rules, the initial and final business data are uploaded to the blockchain to generate the initial and final logistics information of the target goods stored in the blockchain.

[0069] In embodiments of this disclosure, operation S300 is included before the initial feature data of the acquired target goods is processed on-chain to generate the first data.

[0070] Figure 4 The flowchart illustrating operation S300 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure before the generation of first data is shown.

[0071] like Figure 4 As shown, operation S300 includes operations S310 to S320.

[0072] In operation S310, a photograph is taken of the target cargo at the first location to obtain the first image of the target cargo.

[0073] In the embodiments of this disclosure, after the target goods arrive at the first location, a logistics process is initiated, and the target goods are photographed, for example, by using an X-ray device to generate an X-ray image of the target goods. In other optional embodiments, images of the target goods may be acquired through other photographic methods. The first image is the image acquired by the photographic device, such as an X-ray image of the target goods or a photograph of the target goods' appearance.

[0074] In operation S320, feature extraction is performed on the first image of the target cargo to generate initial feature data of the target cargo.

[0075] For example, feature extraction of the first image of the target cargo can be performed using a specific algorithm, such as the HOG (Histogram of Oriented Gradient) algorithm, to extract features of the first image and generate initial feature data of the target cargo.

[0076] Figure 5 The flowchart illustrating the operation S210 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown.

[0077] After obtaining the initial characteristic data of the target goods, operation S210 is executed, such as... Figure 5 As shown, operation S210 includes operations S211 to S212.

[0078] In operation S211, the initial feature data is hashed using a preset algorithm to generate a first hash value.

[0079] For example, the preset algorithm may be a specific hash function, which calculates a hash value of a specific length on the initial feature data.

[0080] In operation S212, the first hash value is signed to generate the first data.

[0081] For example, the first hash value is signed using the user's private key to generate the first data.

[0082] In embodiments of this disclosure, the first data may be recorded in a blockchain, for example, to facilitate a user's retrieval of the first data.

[0083] In the embodiments of this disclosure, after taking a picture of the target cargo at a first location and obtaining the initial feature data of the first image of the target cargo at the first location, the target cargo is sealed, that is, after the target cargo is loaded into a container or a logistics vehicle, the container door is closed and an electronic lock is applied by a specific person, so that the status of the target cargo can be monitored in real time.

[0084] Figure 6 The flowchart illustrating the operation S220 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown.

[0085] like Figure 6 As shown, operation S220 includes operations S221 to S223.

[0086] In operation S221, the status information of the target goods is obtained through electronic lock, and the status information includes at least one of the following: sealing status information, geographical location information, and time information.

[0087] In embodiments of this disclosure, during the logistics of the target goods, the electronic lock can acquire the status information of the target goods, which may be sealing status information, geographical location information, or time information.

[0088] For example, real-time acquisition of the target cargo's geographical location information can determine its logistics trajectory and whether it has deviated from the set trajectory. Based on the sealing status information, it can be determined whether the target cargo has been opened or altered during transit. Based on time and geographical location information, the dwell time of the target cargo at different locations can be determined; if the dwell time exceeds a set time, it indicates a potential anomaly.

[0089] In operation S222, the IoT data server is used to determine whether the status information of the target goods is abnormal.

[0090] The data obtained through the electronic lock is transmitted to the IoT data server. The IoT data server compares the acquired target status information with the set status information to determine whether the status information of the target goods is abnormal.

[0091] For example, when the logistics trajectory of the target goods deviates from the set trajectory, or when the target goods stay in a certain geographical location for a longer period of time than the set time, or when the sealing status of the electronic lock shows an abnormal sealing status, the status information of the target goods can be determined to be abnormal.

[0092] In operation S223, the abnormal status information is processed on the blockchain to generate the second data.

[0093] The acquired abnormal status information is processed on the blockchain, meaning it is recorded in a block of the blockchain network, generating secondary data. Relevant users can then read this abnormal status information from the blockchain network.

[0094] Before the acquisition of the target cargo's end feature data is processed on the blockchain to generate the third data, operation S400 is also included.

[0095] Figure 7 The flowchart illustrating operation S400 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure before the generation of second data is shown.

[0096] like Figure 4 As shown, operation S400 includes operations S410 to S420.

[0097] In operation S410, a photograph is taken of the target cargo at the second location to obtain a second image of the target cargo.

[0098] For example, the second location is, for instance, the receiving location of the target goods. A photograph is taken of the received target goods at the second location to obtain a second image. The image acquisition device used at both the first and second locations is the same device, for example, an X-ray device is used to obtain an X-ray image of the target goods at the second location.

[0099] In operation S420, feature extraction is performed on the second image of the target cargo to generate the end feature data of the target cargo.

[0100] For example, feature extraction of the second image of the target cargo can be performed using a specific algorithm, such as the HOG (Histogram of Oriented Gradient) algorithm, to extract features from the second image and generate end feature data of the target cargo.

[0101] By using the same image acquisition equipment and the same algorithm to extract image features, it can be ensured that the same target cargo at the first and second positions has the same feature data, thereby enabling accurate comparison of the state of the target cargo at different positions.

[0102] After obtaining the end characteristic data of the target cargo, operation S230 is executed.

[0103] Figure 8 The flowchart illustrating the operation S230 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown.

[0104] like Figure 8 The operation S230 includes operations S231 to S232.

[0105] In operation S231, the end feature data is hashed using a preset algorithm to generate a second hash value.

[0106] For example, the preset algorithm in operation S231 may be the same as the preset algorithm in operation S211. The hash function in the preset algorithm is used to calculate the end feature data to generate a second hash value.

[0107] In operation S232, the second hash value is signed to generate the third data.

[0108] For example, the second hash value is signed using the user's private key to generate the third data.

[0109] In embodiments of this disclosure, the third data may be recorded in a blockchain, making it easy for users to read the third data and compare it with the first data to obtain a comparison result.

[0110] Operation S500 is included before determining the regulatory strategy for the target cargo based on the comparison results of the first and third data and / or the second data.

[0111] Figure 9 The flowchart illustrating operation S500 of a blockchain-based logistics supervision method according to an embodiment of the present disclosure prior to determining the supervision strategy for target goods is shown.

[0112] like Figure 9 As shown, operation S500 includes operations S510 to S530.

[0113] In operation S510, the first data is decrypted to generate the first hash value.

[0114] For example, the user obtains the first data from a block on the blockchain, which may be data signed using a private key with a first hash value. After obtaining the first data from the blockchain, the user decrypts the first data using the signer's public key to generate the first hash value.

[0115] In the operation of S520, the third data is decrypted to generate the first hash value.

[0116] For example, by performing the same operation in S510, the second data is decrypted using the signer's public key to generate a second hash value.

[0117] In operation S530, the comparison result is determined based on the first hash value and the second hash value. When the first hash value and the second hash value are the same, the comparison result is determined to be normal logistics, and when the first hash value and the second hash value are different, the comparison result is determined to be abnormal logistics.

[0118] For example, if the first hash value and the second hash value are the same, it means that the characteristic data of the target goods from the first location to the second location has not changed, that is, the target goods have not changed. If the first hash value and the second hash value are different, it means that the characteristic data of the target goods from the first location to the second location has changed, the target goods have changed, and thus the comparison result is determined to be a logistics anomaly.

[0119] Figure 10 The schematic diagram illustrates a specific flowchart of the blockchain-based logistics supervision method according to an embodiment of the present disclosure in operation S240.

[0120] like Figure 10 As shown, operation S240 includes operation S241. In operation S241, when the comparison result is a logistics anomaly, or when the comparison result is a normal logistics situation and second data exists, the regulatory strategy for the target goods is determined to require opening the box for inspection.

[0121] For example, if the comparison result indicates a logistics anomaly, the regulatory strategy for the target goods is determined to require unpacking and inspection.

[0122] For example, when the comparison result shows that the logistics are normal and there is second data, it indicates that the target goods have abnormal status information during logistics transportation. At this time, the target goods may also have problems, and the supervision strategy for the target goods is to open the box for inspection.

[0123] The blockchain-based logistics supervision method disclosed herein can also meet the data synchronization requirements of different blockchains, and also includes operation S260.

[0124] Figure 11 The flowchart illustrating the operation S260 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown.

[0125] like Figure 11 As shown, in operation S260, in response to the cross-chain synchronization instruction, the first data, the second data, and the third data are synchronized from the source blockchain to at least one target blockchain through the synchronization component.

[0126] To meet the different data type requirements of different blockchain networks, data recorded in the source blockchain network can be synchronized to the target blockchain, thereby meeting the requirements of different blockchain networks in different regions.

[0127] For example, when data synchronization across blockchains is required, a cross-chain synchronization command is invoked, and a synchronization component synchronizes the data from the source blockchain to at least one target blockchain. Alternatively, a portion of the data from the target blockchain is synchronized to the source blockchain network, thereby fulfilling the requirement for cross-chain data synchronization.

[0128] In embodiments of this disclosure, the blockchain may be, for example, a consortium blockchain.

[0129] The blockchain-based logistics supervision method disclosed herein can also respond to query commands from different users and execute query operations S270.

[0130] Figure 12 The flowchart illustrating the operation S270 of the blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown.

[0131] like Figure 12 As shown, in operation S270, in response to a query command, at least one of the following is obtained from the source blockchain and at least one target blockchain: initial logistics information, end logistics information, first data, second data, and third data.

[0132] For example, based on the information obtained by the relevant user, various logistics information can be accurately queried. Furthermore, since this information is recorded in various blocks of the blockchain, the information is completely transparent and trustworthy, and has the characteristics of being tamper-proof and traceable, making it convenient for users to query the data.

[0133] According to embodiments of this disclosure, by comparing the initial characteristic data of the target cargo obtained at a first location and the final characteristic data of the target cargo obtained at a second location, and by determining the regulatory strategy for the target cargo based on second data generated from abnormal status information during the logistics process, the efficiency of logistics supervision can be effectively improved. Furthermore, by uploading the acquired initial characteristic data, final characteristic data, and abnormal status information to the blockchain, relevant logistics users can easily obtain detailed logistics information of the target cargo from the blockchain, and due to the immutability of information in the blockchain, the obtained logistics information is more accurate.

[0134] Figure 13 A block diagram of a blockchain-based logistics monitoring device according to an embodiment of the present disclosure is shown schematically.

[0135] like Figure 13 As shown, the logistics monitoring device 600 of this embodiment includes a first generation module 610, a second generation module 620, a third generation module 630, and a determination module 640.

[0136] The first generation module 610 is configured to perform on-chain processing on the acquired initial feature data of the target goods to generate first data. The first data includes a first hash value associated with the initial feature data, which is obtained based on a first image of the target goods at a first location. In one embodiment, the first generation module 610 can be used to perform the operation S210 described above, which will not be repeated here.

[0137] The second generation module 620 is configured to monitor the status information of the target goods in real time through electronic locks, process the acquired abnormal status information on the blockchain, and generate second data. In one embodiment, the second generation module 620 can be used to perform the operation S220 described above, which will not be repeated here.

[0138] The third generation module 630 is configured to perform on-chain processing on the acquired end feature data of the target cargo to generate third data. The third data includes a second hash value associated with the end feature data, which is obtained from a second image of the target cargo at a second location. The third generation module 630 can be used to perform the operation S230 described above, which will not be repeated here.

[0139] The determination module 640 is configured to determine the regulatory strategy for the target cargo based on the comparison result of the acquired first data and third data and / or second data. The determination module 640 can be used to perform the operation S240 described above, which will not be repeated here.

[0140] In an exemplary embodiment of this disclosure, the logistics monitoring device further includes a logistics information generation module, which is configured to: when the target goods are located at a first location, perform on-chain processing on the acquired initial business data of the target goods to generate initial logistics information of the target goods; and when the target goods are located at a second location, perform on-chain processing on the acquired final business data of the target goods to generate final logistics information of the target goods, wherein the initial business data and the final business data are acquired from an Internet of Things data server.

[0141] In an exemplary embodiment of this disclosure, the logistics monitoring device further includes an initial feature generation module, which is configured to: take a picture of the target goods at a first location to obtain a first image of the target goods before processing the initial feature data of the acquired target goods on the blockchain to generate the first data; and extract features from the first image of the target goods to generate the initial feature data of the target goods.

[0142] In an exemplary embodiment of this disclosure, the first generation module includes a first generation submodule. The first generation submodule is configured to: perform hash calculation on initial feature data using a preset algorithm to generate a first hash value; and sign the first hash value to generate first data.

[0143] In an exemplary embodiment of this disclosure, the logistics monitoring device further includes an end feature generation module, which is configured to: take a picture of the target goods at a second location to obtain a second image of the target goods before processing the acquired end feature data of the target goods on the blockchain to generate third data; and extract features from the second image of the target goods to generate end feature data of the target goods.

[0144] In an exemplary embodiment of this disclosure, the third generation module includes a third generation submodule. The third generation submodule is configured to: perform hash calculation on the end feature data using a preset algorithm to generate a second hash value; and sign the second hash value to generate third data.

[0145] In an exemplary embodiment of this disclosure, the logistics monitoring device further includes a comparison result determination module, configured to: before determining the monitoring strategy for the target goods based on the comparison result of the acquired first data and third data and / or second data, decrypt the first data to generate a first hash value; decrypt the third data to generate a second hash value; and determine the comparison result based on the first hash value and the second hash value, wherein when the first hash value and the second hash value are the same, the comparison result is determined to be normal logistics, and when the first hash value and the second hash value are different, the comparison result is determined to be abnormal logistics.

[0146] In an exemplary embodiment of this disclosure, the determining module includes a determining submodule, which is configured to: when the comparison result is abnormal logistics, or when the comparison result is normal logistics and second data exists, determine that the regulatory strategy for the target goods is to require opening and inspecting the goods.

[0147] In an exemplary embodiment of this disclosure, the second generation module includes a second generation submodule. The second generation submodule is configured to: acquire the status information of the target goods through an electronic lock, the status information including at least one of sealing status information, geographical location information, and time information; determine whether the status information of the target goods is abnormal through an IoT data server; and process the abnormal status information on the blockchain to generate second data.

[0148] In an exemplary embodiment of this disclosure, the logistics monitoring device further includes a synchronization module configured to: in response to a cross-chain synchronization instruction, synchronize first data, second data, and third data from a source blockchain to at least one target blockchain via a synchronization component.

[0149] In an exemplary embodiment of this disclosure, the logistics monitoring device further includes a query module configured to: in response to a query command, obtain at least one of the following from a source blockchain and at least one target blockchain: initial logistics information, end logistics information, first data, second data, and third data.

[0150] According to embodiments of this disclosure, any plurality of modules among the first generation module 610, the second generation module 620, the third generation module 630, and the determining module 640 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least a portion of the functionality of one or more of these modules may be combined with at least a portion of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the first generation module 610, the second generation module 620, the third generation module 630, and the determining module 640 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in a suitable combination of any of these. Alternatively, at least one of the first generation module 610, the second generation module 620, the third generation module 630, and the determining module 640 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0151] Figure 14 A block diagram of an electronic device for implementing a blockchain-based logistics supervision method according to an embodiment of the present disclosure is shown schematically. Figure 14 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0152] like Figure 14 As shown, an electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage portion 708 into a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0153] RAM 703 stores various programs and data required for the operation of electronic device 700. Processor 701, ROM 702, and RAM 703 are interconnected via bus 704. Processor 701 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 702 and / or RAM 703. It should be noted that the programs may also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0154] According to embodiments of this disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to a bus 704. The electronic device 700 may also include one or more of the following components connected to the I / O interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the storage section 708 as needed.

[0155] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the logistics monitoring method according to the embodiments of this disclosure.

[0156] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 702 and / or RAM 703 and / or one or more memories other than ROM 702 and RAM 703 described above.

[0157] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code enables the computer system to implement the logistics monitoring method provided in the embodiments of this disclosure.

[0158] When the computer program is executed by the processor 701, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0159] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 709, and / or installed from a removable medium 711. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0160] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0161] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0162] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0163] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0164] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A blockchain-based logistics supervision method, comprising: The initial feature data of the acquired target goods is processed on the blockchain to generate first data, which includes a first hash value associated with the initial feature data. The initial feature data is obtained based on a first image of the target goods at a first location. The status information of the target goods is monitored in real time through electronic locks, and abnormal status information is processed on the blockchain to generate second data. The acquired end feature data of the target goods is processed on the blockchain to generate third data, which includes a second hash value associated with the end feature data. The end feature data is obtained based on a second image of the target goods at a second location. The first data is decrypted to generate the first hash value; The third data is decrypted to generate a second hash value; The comparison result is determined based on the first hash value and the second hash value. Wherein, when the first hash value and the second hash value are the same, the comparison result is determined to be that the logistics are normal; When the first hash value and the second hash value are different, the comparison result is determined to be a logistics anomaly; Based on the comparison results of the first data and the third data and / or the second data, a regulatory strategy for the target cargo is determined.

2. The method according to claim 1, wherein, Also includes: When the target goods are located at the first location, the initial business data of the target goods are processed on the blockchain to generate initial logistics information of the target goods. as well as When the target goods are located at the second location, the acquired end-of-business data of the target goods is processed on the blockchain to generate logistics end-of-business information for the target goods. The initial business data and the ending business data are obtained from the Internet of Things data server.

3. The method according to claim 2, wherein, Also includes: Before the initial feature data of the acquired target goods is processed on the blockchain to generate the first data, Take a picture of the target goods at the first location to obtain a first image of the target goods; Feature extraction is performed on the first image of the target cargo to generate initial feature data of the target cargo.

4. The method according to claim 3, wherein, The process of uploading the initial feature data of the acquired target goods to the blockchain to generate the first data includes: The initial feature data is hashed using a preset algorithm to generate a first hash value; The first hash value is signed to generate the first data.

5. The method according to claim 4, wherein, Also includes: Before the acquisition of the end feature data of the target goods is processed on the blockchain to generate the third data, Take a picture of the target goods at the second location to obtain a second image of the target goods; Feature extraction is performed on the second image of the target cargo to generate the end feature data of the target cargo.

6. The method according to claim 5, wherein, The process of uploading the acquired end-of-life characteristic data of the target goods to the blockchain to generate third data includes: A second hash value is generated by performing a hash calculation on the end feature data using a preset algorithm. The second hash value is signed to generate the third data.

7. The method according to claim 1, wherein, The step of determining the regulatory strategy for the target goods based on the comparison result of the first data and the third data and / or the second data includes: When the comparison result indicates a logistics anomaly, or When the comparison result indicates that the logistics are normal and second data exists. The regulatory strategy for the target goods is determined to require opening and inspection.

8. The method according to claim 1, wherein, The real-time monitoring of the target cargo's status information via electronic locks, and the on-chain processing of any abnormal status information to generate second data, include: The electronic lock is used to obtain the status information of the target goods, and the status information includes at least one of sealing status information, geographical location information, and time information. The IoT data server is used to determine whether the status information of the target goods is abnormal. The abnormal status information is processed on the blockchain to generate the second data.

9. The method according to claim 2, wherein, Also includes: In response to a cross-chain synchronization command, the first data, the second data, and the third data are synchronized from the source blockchain to at least one target blockchain via a synchronization component.

10. The method according to claim 9, wherein, Also includes: In response to a query command, at least one of the following is obtained from the source blockchain and the at least one target blockchain: the initial logistics information, the end logistics information, the first data, the second data, and the third data.

11. A blockchain-based logistics monitoring device, comprising: The first generation module is configured to perform on-chain processing on the initial feature data of the acquired target goods to generate first data. The first data includes a first hash value associated with the initial feature data, which is obtained based on a first image of the target goods at a first location. The second generation module is configured to monitor the status information of the target goods in real time through electronic locks, process the abnormal status information obtained by uploading it to the blockchain, and generate second data. The third generation module is configured to perform on-chain processing on the acquired end feature data of the target goods to generate third data. The third data includes a second hash value associated with the end feature data, which is obtained based on a second image of the target goods at a second location. The comparison result determination module is configured to decrypt the first data and generate a first hash value; The third data is decrypted to generate a second hash value; The comparison result is determined based on the first hash value and the second hash value. When the first hash value and the second hash value are the same, the comparison result is determined to be normal logistics; when the first hash value and the second hash value are different, the comparison result is determined to be abnormal logistics. The determination module is configured to determine the regulatory strategy for the target goods based on the comparison result of the first data and the third data and / or the second data.

12. An electronic device, comprising: One or more processors; A storage device for storing executable instructions, which, when executed by the processor, implement the method according to any one of claims 1 to 10.

13. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, implement the method according to any one of claims 1 to 10.

14. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 10.

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