WO2024046008A1 - 基于区块链的物流监管方法、装置、电子设备和存储介质 - Google Patents

基于区块链的物流监管方法、装置、电子设备和存储介质 Download PDF

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Publication number
WO2024046008A1
WO2024046008A1 PCT/CN2023/110546 CN2023110546W WO2024046008A1 WO 2024046008 A1 WO2024046008 A1 WO 2024046008A1 CN 2023110546 W CN2023110546 W CN 2023110546W WO 2024046008 A1 WO2024046008 A1 WO 2024046008A1
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Prior art keywords
data
target cargo
target
logistics
generate
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PCT/CN2023/110546
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English (en)
French (fr)
Inventor
陈志强
顾菁宇
吴相豪
戴俊娣
赵坤
Original Assignee
同方威视技术股份有限公司
清华大学
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Publication of WO2024046008A1 publication Critical patent/WO2024046008A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping
    • G06Q10/0833—Tracking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/602—Providing cryptographic facilities or services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components

Definitions

  • the present disclosure relates to the field of blockchain technology, and specifically relates to a blockchain-based logistics supervision method, device, electronic equipment and readable storage medium.
  • the present disclosure provides a blockchain-based logistics supervision method, device, electronic device and storage medium, which at least partially solves the problem of being unable to judge the status of goods in the logistics process and being unable to accurately obtain cargo logistics information. question.
  • a first aspect of the present disclosure provides a blockchain-based logistics supervision method, which includes: performing on-chain processing on the acquired initial characteristic data of target goods to generate first data, where the first data includes the The first hash value associated with the initial feature data, which is obtained based on the first image of the target cargo at the first position; real-time monitoring of the status information of the target cargo through electronic locking, Perform on-chain processing on the obtained abnormal status information to generate second data; perform on-chain processing on the obtained ending characteristic data of the target cargo to generate third data, where the third data includes the ending characteristic data associated with the ending characteristic data.
  • the second hash value, the end characteristic data is based on the target A second image of the cargo at a second position is acquired; and a supervision strategy for the target cargo is determined based on the obtained comparison result between the first data and the third data and/or the second data.
  • the method further includes: when the target cargo is located at the first location, perform uplink processing on the acquired initial business data of the target cargo, and generate a data of the target cargo. Logistics initial information; and when the target goods are located at the second location, perform on-chain processing on the obtained end business data of the target goods to generate logistics end information of the target goods, wherein the initial business data and The end service data is obtained from the Internet of Things data server.
  • the method further includes: before the initial characteristic data for the acquired target cargo is uploaded to generate the first data, the target at the first location is processed. The goods are photographed to obtain a first image of the target goods; feature extraction is performed on the first image of the target goods to generate initial feature data of the target goods.
  • performing on-chain processing on the acquired initial characteristic data of the target cargo and generating the first data includes: performing hash calculation on the initial characteristic data through a preset algorithm to generate the first Hash value; sign the first hash value to generate the first data.
  • the method further includes: before the end characteristic data of the acquired target cargo is uploaded to generate the third data, the target at the second location is processed.
  • the goods are photographed to obtain a second image of the target goods; feature extraction is performed on the second image of the target goods to generate end feature data of the target goods.
  • performing on-chain processing on the obtained end characteristic data of the target cargo and generating the third data includes: performing hash calculation on the end characteristic data through a preset algorithm to generate a second Hash value; sign the second hash value to generate third data.
  • the method further includes: based on the obtained comparison results of the first data and the third data and/or the second data, determining the The surveillance strategy for the target cargo previously included: decrypting the first data, Generate a first hash value; decrypt the third data to generate a second hash value; determine the comparison result according to the first hash value and the second hash value, wherein when the If the first hash value and the second hash value are the same, it is determined that the comparison result is that the logistics is normal; and when the first hash value and the second hash value are different, it is determined that the comparison result is normal.
  • the result is a logistics anomaly.
  • determining the regulatory policy for the target cargo based on the obtained comparison result of the first data and the third data and/or the second data includes: when When the comparison result is that the logistics is abnormal, or when the comparison result is that the logistics is normal and there is second data, it is determined that the supervision strategy of the target goods is to require unpacking and inspection.
  • the state information of the target cargo is monitored in real time through the electronic lock, and the obtained abnormal state information is processed on the chain.
  • Generating the second data includes: using the electronic lock.
  • the lock obtains the status information of the target cargo, and the status information includes at least one of sealing status information, geographical location information, and time information; determines whether the status information of the target cargo is abnormal through the Internet of Things data server; and converts the abnormal status
  • the information is processed on the chain to generate second data.
  • the method further includes: in response to a cross-chain synchronization instruction, synchronizing the first data, the second data and the third data from the source blockchain to at least one target through a synchronization component. in the blockchain.
  • the method further includes: responding to a query instruction, obtaining the logistics initial information and the logistics end information from the source blockchain and the at least one target blockchain. , at least one of the first data, the second data and the third data.
  • a second aspect of the embodiment of the present disclosure provides a blockchain-based logistics supervision device, including: a first generation module configured to perform on-chain processing on the acquired initial characteristic data of the target cargo and generate the 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;
  • a second generation module configured to The status information of the target cargo is monitored in real time through electronic locking, and the obtained abnormal status information is processed on the chain to generate the second data;
  • the third generation module is configured to target the obtained target
  • the end characteristic data of the goods is processed on the chain to generate third data.
  • the third data includes a second hash value associated with the end characteristic data.
  • the end characteristic data is based on the location of the target goods at the second location.
  • the second image is acquired;
  • the determination module is configured to determine the supervision strategy of the target cargo according to the obtained comparison result of the first data and the third data and/or the second data.
  • a third aspect of the embodiment of the present disclosure provides an electronic device, including: one or more processors; a storage device for storing executable instructions, which when executed by the processor, implement According to the method described above.
  • a fourth aspect of the embodiments of the present disclosure provides a computer-readable storage medium on which executable instructions are stored. When the instructions are executed by a processor, the method described above is implemented.
  • a fifth aspect of the embodiments of the present disclosure provides a computer program product, including a computer program that implements the method described above when executed by a processor.
  • the second data generated is used to determine the supervision strategy of the target goods, which can effectively improve the efficiency of logistics supervision.
  • uploading the obtained initial characteristic data, end characteristic data and abnormal status information to the chain it is convenient for logistics-related users to obtain detailed logistics information of the target goods from the blockchain, and because the information in the blockchain cannot be tampered with The logistics information obtained is more accurate.
  • Figure 1 schematically illustrates an exemplary system architecture in which a blockchain-based logistics supervision method can be applied according to an embodiment of the present disclosure
  • Figure 2 schematically shows a flow chart of a blockchain-based logistics supervision method according to an embodiment of the present disclosure
  • Figure 3 schematically illustrates blockchain-based logistics supervision according to an embodiment of the present disclosure.
  • Figure 4 schematically illustrates a flowchart of the operation S300 of the blockchain-based logistics supervision method before generating the first data according to an embodiment of the present disclosure
  • Figure 5 schematically shows a flow chart of the blockchain-based logistics supervision method in operation S210 according to an embodiment of the present disclosure
  • Figure 6 schematically shows a flow chart of the blockchain-based logistics supervision method in operation S220 according to an embodiment of the present disclosure
  • Figure 7 schematically shows a flow chart of the operation S400 of the blockchain-based logistics supervision method before generating the second data according to an embodiment of the present disclosure
  • Figure 8 schematically shows a flow chart of the blockchain-based logistics supervision method in operation S230 according to an embodiment of the present disclosure
  • Figure 9 schematically illustrates a flow chart of the operation S500 of the blockchain-based logistics supervision method before determining the supervision strategy of the target goods according to an embodiment of the present disclosure
  • Figure 10 schematically shows a specific flow chart of the blockchain-based logistics supervision method in operation S240 according to an embodiment of the present disclosure
  • Figure 11 schematically shows a flow chart of the blockchain-based logistics supervision method in operation S260 according to an embodiment of the present disclosure
  • Figure 12 schematically shows a flow chart of the blockchain-based logistics supervision method in operation S270 according to an embodiment of the present disclosure
  • Figure 13 schematically shows a block diagram of a blockchain-based logistics supervision device according to an embodiment of the present disclosure
  • Figure 14 schematically shows a block diagram of an electronic device used to implement a blockchain-based logistics supervision method according to an embodiment of the present disclosure.
  • the acquisition, storage and application of user personal information involved are in compliance with relevant laws and regulations, necessary confidentiality measures are taken, and do not violate public order and good customs.
  • the acquisition, storage and application of the user's personal information are all authorized by the user.
  • Embodiments of the present disclosure provide a blockchain-based logistics supervision method, device, electronic device, and readable storage medium.
  • the blockchain-based logistics supervision method includes: performing on-chain processing on the acquired initial characteristic data of the target goods, and generating first data.
  • the first data includes a first hash value associated with the initial characteristic data, and the initial characteristic data It is obtained based on the first image of the target cargo at the first position; the status information of the target cargo is monitored in real time through the electronic lock, and the obtained abnormal status information is processed on the chain to generate the second data; for the acquired target cargo
  • the end characteristic data is processed on the chain to generate the third data, the third data includes a second hash value associated with the end characteristic data, the end characteristic data is obtained according to the second image of the target cargo at the second position; according to the comparison of the obtained first data and the third data
  • the results and/or secondary data determine regulatory strategies for the target cargo.
  • the second data generated is used to determine the supervision strategy of the target goods, which can effectively improve the efficiency of logistics supervision.
  • uploading the obtained initial characteristic data, end characteristic data and abnormal status information to the chain it is convenient for logistics-related users to obtain detailed logistics information of the target goods from the blockchain, and because the information in the blockchain cannot be tampered with The logistics information obtained is more accurate.
  • FIG. 1 schematically illustrates an exemplary system architecture in which a blockchain-based logistics supervision method can be applied according to an embodiment of the present disclosure.
  • Figure 1 is only an example of a system architecture to which embodiments of the present disclosure can be applied, to help those skilled in the art understand the technical content of the present disclosure, but does not mean that the embodiments of the present disclosure cannot be used in other applications.
  • Device, system, environment or scenario It should be noted that the logistics supervision methods, devices, electronic devices and readable storage media provided by the embodiments of the present disclosure can be used in related aspects of the logistics field, and can also be used in various fields other than the logistics field.
  • the embodiments of the present disclosure provide The application fields of logistics supervision methods, devices, electronic equipment and readable storage media are not limited.
  • the system architecture that can be applied to the blockchain-based logistics supervision method according to the embodiment of the present disclosure includes a first image acquisition device 101, an electronic lock 102, a second image acquisition device 103, a user 104, and the Internet of Things.
  • Data server 105 Data server 105, blockchain 106 and network 107.
  • the first image acquisition device 101 and the second image acquisition device 102 are used to acquire images of target goods in different places or logistics at different locations.
  • they may be X-ray image acquisition devices, used to acquire X-ray images of target goods.
  • the electronic lock 102 can be a lock that detects the status information of the target cargo.
  • the electronic lock can be set to be legally opened by a specific key or instruction at a set position. When the opening conditions of the electronic lock do not meet the set conditions, When required, abnormal information about the illegal opening of the electronic lock can be recorded, and the abnormal information can be used to determine the location of the target goods during logistics transportation. in the state.
  • the user 104 can be, for example, a cargo carrier, consignee, cargo supplier, customs officer, etc., and can obtain data from the blockchain 106 through the network 107 and perform operations such as viewing or writing data to the blockchain, so as to target Check and judge the logistics information and logistics status of the goods.
  • the Internet of Things data server 105 may be, for example, a server that provides various logistics information services, such as a server that enters, analyzes or manages information on carriers, consignees, and cargo suppliers.
  • the blockchain 106 is, for example, a consortium chain for use by specific groups or organizations, such as blockchains for cargo carriers, consignees, cargo suppliers, customs personnel, etc., to facilitate relevant users to obtain data from the blockchain 106 Information etc.
  • the network 107 is used to provide a medium for communication links between the first image collection device 101, the electronic lock 102, the second image collection device 103, the user 104, the Internet of Things data server 105, and the blockchain 106.
  • Network 107 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
  • the blockchain-based logistics supervision method of the embodiment of the present disclosure can be implemented.
  • the image of the target cargo is collected through the first image acquisition device 101 at the initial location, and the status information of the target cargo during transportation is monitored in real time through the electronic lock 102, and after the target cargo arrives at the target location, the target cargo is monitored through the electronic lock 102.
  • the second image capturing device 103 captures images of the target goods again. After the collected images are processed, they are uploaded to the blockchain 106 to facilitate other users 104 or the Internet of Things 105 to view or call the information.
  • first image capture device electronic lock
  • second image capture device users
  • IoT data server blockchain and network
  • first image acquisition devices electronic locks
  • second image acquisition devices users
  • IoT data servers IoT data servers
  • Figure 2 schematically shows a flow chart of a blockchain-based logistics supervision method according to an embodiment of the present disclosure.
  • the process 200 of the disclosed blockchain-based logistics supervision method includes including operation S210 to operation S240.
  • the obtained initial characteristic data of the target cargo is uploaded to generate first data.
  • the first data includes a first hash value associated with the initial characteristic data.
  • the initial characteristic data is based on the target cargo in the first
  • the first image of a location is acquired.
  • the status information of the target cargo is monitored in real time through the electronic lock, and the obtained abnormal status information is uploaded to generate second data.
  • the obtained end characteristic data of the target cargo is uploaded to generate third data.
  • the third data includes a second hash value associated with the end characteristic data.
  • the end characteristic data is based on the target cargo in the third data.
  • the second image of the second position was acquired.
  • a supervision policy for the target cargo is determined based on the comparison result of the obtained first data and the third data and/or the second data.
  • the target goods may be, for example, goods that require logistics supervision
  • the first location may be, for example, the shipping location of the target goods, or the first location may be the initial location where the target goods require logistics supervision.
  • the second position may be the receiving position of the target goods, or the second position may be the end position of the target goods for logistics supervision.
  • the target goods may be opened or unpacked during the logistics process. From the first location to the second location, or if the relevant parties who need to inspect the goods do not inspect the goods, they cannot effectively determine whether the target goods have changed during the logistics process. , and the process of unpacking and inspecting the target goods requires time and energy, which cannot effectively improve the efficiency of the target goods in the logistics process. In addition, if the target goods have not changed during the logistics process, the process of unpacking and inspection will cause a lot of ineffective work.
  • the logistics supervision method of the present disclosure also includes operation S250.
  • FIG. 3 schematically shows a flowchart of the blockchain-based logistics supervision method in operation S250 according to an embodiment of the present disclosure.
  • operation S250 includes operations S251 to S252.
  • the initial business data may be the origin information, driver information, cargo information, carrier information, consignor information, manufacturer information, trunk transporter information, head-end receiver information, etc. of the target goods and the target goods.
  • Business data related to the logistics business of goods After obtaining the initial business data, one or more of the initial business data can be processed on the chain to generate initial logistics information of the target goods.
  • the on-chain data is verified, and after the verification passes, it is recorded in a block in the blockchain. Relevant users can obtain the initial logistics information of the target goods by consulting the information in this block.
  • the end business data may be, for example, destination information of the target cargo, driver information, cargo information, carrier information, consignor information, manufacturer information, trunk transporter information, terminal dispatcher information, etc., and the target cargo.
  • Business data related to logistics business Based on the same process of uploading the initial business data to the blockchain, the completed business data will be uploaded to the blockchain to facilitate users to check the logistics completion information of the target goods recorded in the blockchain.
  • the initial service data and the end service data are obtained from the Internet of Things data server.
  • the origin information, arrival information, driver information, cargo information, carrier information, consignor information, manufacturer information, etc. of the target goods are obtained.
  • Trunk transporter information, head-end receiver information, terminal delivery provider information, etc. are collected through various data collection devices and stored in the IoT data server.
  • the information that each party needs to upload to the blockchain is defined, and the initial business data and the end business data are uploaded to the blockchain according to the corresponding uploading rules to generate the information stored in the blockchain. Logistics initial information and logistics end information of the target cargo.
  • the operation S300 is included before performing uplink processing on the acquired initial characteristic data of the target cargo and generating the first data.
  • FIG. 4 schematically illustrates a flowchart of operation S300 of the blockchain-based logistics supervision method before generating the first data according to an embodiment of the present disclosure.
  • operation S300 includes operations S310 to S320.
  • the target cargo at the first position is photographed to obtain a first image of the target cargo.
  • the logistics program is entered and the target goods are photographed, for example, through an X-ray device to generate an X-ray image of the target goods.
  • an X-ray device to generate an X-ray image of the target goods.
  • other photographing methods may be used to obtain images of the target goods and other content.
  • the first image is an image obtained by a photographing device, which may be an X-ray image of the target cargo, or an appearance photo of the target cargo, etc.
  • feature extraction is performed on the first image of the target cargo to generate initial feature data of the target cargo.
  • feature extraction of the first image of the target cargo may be performed through a specific algorithm, such as extracting features of the first image through the HOG (Histogram of Oriented Gradient) algorithm to generate initial feature data of the target cargo.
  • HOG Heistogram of Oriented Gradient
  • FIG. 5 schematically shows a flow chart of the blockchain-based logistics supervision method in operation S210 according to an embodiment of the present disclosure.
  • operation S210 After obtaining the initial characteristic data of the target cargo, operation S210 is performed. As shown in FIG. 5 , operation S210 includes operations S211 to S212.
  • hash calculation is performed on the initial feature data through a preset algorithm to generate a first hash value.
  • the preset algorithm may be a specific hash function, through which the initial feature data is calculated to generate a hash value with a specific length.
  • the first hash value is signed to generate first data.
  • the first hash value is signed with a private key owned by the user to generate the first data.
  • the first data may be recorded in a blockchain, for example, to facilitate users to read the first data.
  • the target cargo is photographed at the first position, and after acquiring the initial characteristic data of the first image of the target cargo at the first position, the target cargo is sealed, that is, the target cargo is loaded into the container. Or after the vehicle is carrying out logistics, the door of the box is closed, and a specific person applies an electronic lock, so that the status of the target cargo can be monitored in real time.
  • FIG. 6 schematically shows a flowchart of the blockchain-based logistics supervision method in operation S220 according to an embodiment of the present disclosure.
  • operation S220 includes operations S221 to S223.
  • status information of the target cargo is obtained through electronic locking.
  • the status information includes at least one of sealing status information, geographical location information, and time information.
  • the electronic lock can obtain the status information of the target goods.
  • the status information can be sealing status information, geographical location information, or time information.
  • the geographical location information of the target cargo is obtained in real time.
  • the logistics trajectory of the target cargo can be determined and whether the target cargo deviates from the set trajectory.
  • the sealing status information it can be determined whether the target goods have been opened or changed during the logistics process.
  • the detention time of the target cargo in different locations can be determined. If the detention time exceeds the set time, it means there may be an abnormality.
  • the data obtained through the electronic lock is transmitted to the IoT data server.
  • the IoT data server compares the obtained target status information with the set status information to determine whether the status information of the target cargo is abnormal.
  • the logistics trajectory of the target cargo deviates from the set trajectory, or the residence time of the target cargo in a certain geographical location exceeds the set time, or the sealing status of the electronic lock shows that the sealing status is abnormal, etc., it can be determined.
  • the status information of the target cargo is abnormal.
  • the abnormal status information is uploaded to generate second data.
  • the obtained abnormal status information is uploaded to the chain, that is, the abnormal status information is recorded in the blocks of the blockchain network to generate second data. Relevant users can read the abnormal status information from the blockchain network.
  • operation S400 Before performing on-chain processing on the obtained end characteristic data of the target cargo and generating the third data, operation S400 is also included.
  • FIG. 7 schematically illustrates a flowchart of the operation S400 of the blockchain-based logistics supervision method before generating the second data according to an embodiment of the present disclosure.
  • operation S400 includes operations S410 to S420.
  • the target cargo at the second location is photographed to obtain a second image of the target cargo.
  • the second location is a receiving location of the target goods. Take a photo of the received target goods at the second location to obtain a second image.
  • the image acquisition equipment used at the first position and the second position is the same equipment, for example, both use X-ray devices to acquire X-ray images of the target cargo at the second position.
  • feature extraction of the second image of the target cargo may be performed through a specific algorithm, for example, the HOG (Histogram of Oriented Gradient) algorithm is used to extract features of the second image and generate end feature data of the target cargo.
  • HOG Heistogram of Oriented Gradient
  • operation S230 is performed.
  • FIG. 8 schematically shows a flowchart of the blockchain-based logistics supervision method in operation S230 according to an embodiment of the present disclosure.
  • operation S230 includes operations S231 to S232.
  • hash calculation is performed on the end feature data through a preset algorithm to generate a second hash value.
  • the preset algorithm in operation S231 and the preset algorithm in operation S211 may be the same, for example.
  • the end characteristic data is calculated using a hash function in a preset algorithm to generate a second hash value.
  • the second hash value is signed to generate third data.
  • the second hash value is signed with a private key owned by the user to generate third data.
  • the third data may be recorded in the blockchain, for example, so that the user can read the third data and compare it with the first data to obtain the comparison result.
  • Operation S500 is included before determining the regulatory policy for the target cargo based on the obtained comparison result of the first data and the third data and/or the second data.
  • FIG. 9 schematically illustrates a flowchart of operation S500 of the blockchain-based logistics supervision method before determining the supervision policy of the target goods according to an embodiment of the present disclosure.
  • operation S500 includes operations S510 to S530.
  • the first data is decrypted and a first hash value is generated.
  • the first data of a certain block on the blockchain is obtained.
  • the data is, for example, the data signed by using the private key to sign the first hash value.
  • the user obtains the first data from the blockchain, he uses the signer's public key to decrypt the first data and generates the first hash value.
  • the third data is decrypted to generate a first hash value.
  • the second data is decrypted using the signer's public key to generate a second hash value.
  • the comparison result is determined according to the first hash value and the second hash value, wherein when the first hash value and the second hash value are the same, it is determined that the comparison result is that the logistics is normal, and when the first hash value The hash value is different from the second hash value, and the comparison result is determined to be a logistics abnormality.
  • the first hash value and the second hash value are the same, it means that the characteristic data of the target cargo transported from the first location to the second location has not changed, that is, the target cargo has not changed.
  • the first hash value and the second hash value are not the same, it means that the characteristic data of the target goods transported from the first location to the second location has changed, and the target goods have changed, thereby determining that the comparison result is a logistics abnormality.
  • Figure 10 schematically shows a specific flow chart of the blockchain-based logistics supervision method in operation S240 according to an embodiment of the present disclosure.
  • operation S240 includes operation S241.
  • operation S241 when the comparison result is that the logistics is abnormal, or when the comparison result is that the logistics is normal and there is second data, it is determined The supervision policy of the target goods requires unpacking and inspection.
  • the comparison result is a logistics abnormality
  • the comparison result is that the logistics is normal and the second data exists, it means that the target goods have abnormal status information during the logistics transportation. At this time, there may also be problems with the target goods. It is determined that the supervision policy of the target goods requires unpacking. Inspection.
  • the blockchain-based logistics supervision method of the present disclosure can also realize the data synchronization requirements of different blockchains, and also includes operation S260.
  • FIG. 11 schematically shows a flowchart of the blockchain-based logistics supervision method in operation S260 according to an embodiment of the present disclosure.
  • 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.
  • the data recorded in the source blockchain network can be synchronized to the target blockchain to meet the requirements of different blockchain networks in different regions.
  • the data in the source blockchain is synchronized to at least one target blockchain through the synchronization component in response to the cross-chain synchronization instruction.
  • the data in the source blockchain is synchronized to at least one target blockchain through the synchronization component in response to the cross-chain synchronization instruction.
  • the blockchain may be a consortium chain, for example.
  • the blockchain-based logistics supervision method of the present disclosure can also respond to query instructions from different users and perform the query operation S270.
  • FIG. 12 schematically shows a flowchart of the blockchain-based logistics supervision method in operation S270 according to an embodiment of the present disclosure.
  • the logistics initial information, logistics end information, first data, second data and third data are obtained from the source blockchain and at least one target blockchain. At least one.
  • the second data generated is used to determine the supervision strategy of the target goods, which can effectively improve the efficiency of logistics supervision.
  • uploading the obtained initial characteristic data, end characteristic data and abnormal status information to the chain it is convenient for logistics-related users to obtain detailed logistics information of the target goods from the blockchain, and because the information in the blockchain cannot be tampered with The logistics information obtained is more accurate.
  • Figure 13 schematically shows a block diagram of a blockchain-based logistics supervision device according to an embodiment of the present disclosure.
  • the logistics supervision device 600 of the embodiment of the present disclosure includes a first generation module 610 , a second generation module 620 , a third generation module 630 and a determination module 640 .
  • the first generation module 610 is configured to perform uplink processing on the acquired initial characteristic data of the target cargo and generate first data.
  • the first data includes a first hash value associated with the initial characteristic data.
  • the initial characteristic data is based on the target cargo.
  • the first image at the first position is acquired.
  • the first generation module 610 may be used to perform the operation S210 described above, which will not be described again here.
  • the second generation module 620 is configured to monitor the status information of the target cargo in real time through electronic locking, perform uplink processing on the acquired abnormal status information, and generate second data.
  • the second generation module 620 may be used to perform the operation S220 described above, which will not be described again here.
  • the third generation module 630 is configured to perform on-chain processing on the acquired end characteristic data of the target cargo and generate third data.
  • the third data includes a second hash value associated with the end characteristic data.
  • the end characteristic data is based on the target cargo.
  • the second image is acquired at the second position.
  • the third generation module 630 may be used to perform the operation S230 described above, which will not be described again here.
  • the determination module 640 is configured to determine the supervision policy of the target cargo based on the obtained comparison result of the first data and the third data and/or the second data.
  • the determination module 640 may be used to perform the operation S240 described above, which will not be described again here.
  • the logistics supervision device further includes a logistics information generation module, and the logistics information generation module is configured to: when the target goods are located at the first location, perform uplink processing on the acquired initial business data of the target goods, Generate the initial logistics information of the target goods; and when the target goods are located at the second position, perform on-chain processing on the obtained end business data of the target goods to generate the logistics end information of the target goods, wherein the initial business data and the end business data are Obtained from IoT data server.
  • the logistics supervision device further includes an initial feature generation module.
  • the initial feature generation module is configured to: perform uplink processing on the acquired initial feature data of the target cargo and generate the first data before generating the first data. Take a photo of the target cargo at a location to obtain the first image of the target cargo; perform feature extraction on the first image of the target cargo to generate initial feature data of the target cargo.
  • the first generation module includes a first generation sub-module.
  • the first generation sub-module is configured to: perform hash calculation on the initial feature data through a preset algorithm to generate a first hash value; sign the first hash value to generate the first data.
  • the logistics supervision device further includes an end feature generation module, and the end feature generation module is configured to: before performing uplink processing on the acquired end feature data of the target cargo and generating the third data, The target goods at the second position are photographed to obtain a second image of the target goods; features are extracted from the second image of the target goods to generate end feature data of the target goods.
  • the third generation module includes a third generation sub-module.
  • the third generation sub-module is configured to: perform hash calculation on the end characteristic data through a preset algorithm to generate a second hash value; sign the second hash value to generate the third data.
  • the logistics supervision device further includes a comparison result determination module configured to: determine the target cargo according to the obtained comparison result of the first data and the third data and/or the second data.
  • the first data is decrypted to 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, where , when the first hash value and the second hash value are the same, it is determined that the comparison result is that the logistics is normal, and when the first hash value and the second hash value are different, it is determined that the comparison result is that the logistics is abnormal.
  • the determination module includes a determination sub-module, and the determination sub-module is configured to: when the comparison result is that the logistics is abnormal, or when the comparison result is that the logistics is normal and the second data exists, determine the supervision of the target goods
  • the strategy requires unpacking and inspection.
  • the second generation module includes a second generation sub-module.
  • the second generation sub-module is configured to: obtain the status information of the target cargo through the electronic lock, where the status information includes at least one of sealing status information, geographical location information, and time information; determine the status information of the target cargo through the Internet of Things data server Whether it is abnormal; the abnormal status information is processed on the chain and the second data is generated.
  • the logistics supervision device further includes a synchronization module configured to: respond to the cross-chain synchronization instruction and synchronize the first data, the second data and the third data from the source blockchain through the synchronization component. to at least one target blockchain.
  • the logistics supervision device further includes a query module, and the query module is configured to: respond to the query instruction, obtain logistics initial information, logistics end information, and third logistics information from the source blockchain and at least one target blockchain. At least one of first data, second data and third data.
  • any multiple modules among the first generation module 610, the second generation module 620, the third generation module 630 and the determination module 640 may be combined and implemented in one module, or any one of the modules may be Split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first generation module 610 , the second generation module 620 , the third generation module 630 and the determination module 640 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA).
  • FPGA field programmable gate array
  • At least one of the first generation module 610, the second generation module 620, the third generation module 630 and the determination module 640 may be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function.
  • FIG. 14 schematically shows a block diagram of an electronic device used to implement a blockchain-based logistics supervision method according to an embodiment of the present disclosure.
  • the electronic device shown in FIG. 14 is only an example and should not impose any limitations on the functions and scope of use of the embodiments of the present disclosure.
  • an electronic device 700 includes a processor 701 that can be loaded into a random access memory (RAM) 703 according to a program stored in a read-only memory (ROM) 702 or from a storage part 708 program to perform various appropriate actions and processes.
  • processor 701 may include, for example, a general-purpose microprocessor (eg, CPU), an instruction set processor and/or associated chipset, and/or a special-purpose microprocessor (eg, application specific integrated circuit (ASIC)), or the like.
  • 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 the embodiment of the present disclosure.
  • the processor 701, ROM 702 and RAM 703 are connected to each other through a bus 704.
  • the processor 701 performs various operations according to the method flow of the embodiment of the present disclosure by executing programs in the ROM 702 and/or RAM 703. It should be noted that the program may also be stored in one or more memories other than ROM 702 and RAM 703.
  • the processor 701 may also perform various operations according to the method flow of embodiments of the present disclosure by executing programs stored in the one or more memories.
  • the electronic device 700 may further include an input/output (I/O) interface 705 that is also connected to the bus 704 .
  • Electronic device 700 may also include one or more of the following components connected to I/O interface 705: an input portion 706 including a keyboard, mouse, etc.; including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and an output section 707 of speakers and the like; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN card, a modem and the like.
  • the communication section 709 performs communication processing via a network such as the Internet.
  • Driver 710 is also connected to I/O interface 705 as needed.
  • Removable media 711 such as magnetic disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on the drive 710 as needed, so that a computer program read therefrom is installed into the storage portion 708 as needed.
  • the present disclosure also provides a computer-readable storage medium, which The quality may be included in the equipment/device/system described in the above embodiments; it may also exist independently without being assembled into the equipment/device/system.
  • the above computer-readable storage medium carries one or more programs. When the above one or more programs are executed, the logistics supervision method according to the embodiment of the present disclosure is implemented.
  • the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, but is not limited to, portable computer disks, hard disks, random access memory (RAM), and read-only memory (ROM). , erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • a computer-readable storage medium may be any tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device.
  • the computer-readable storage medium may include one or more memories other than ROM 702 and/or RAM 703 and/or ROM 702 and RAM 703 described above.
  • Embodiments of the present disclosure also include a computer program product including a computer program containing program code for performing the method illustrated in the flowchart.
  • the program code is used to cause the computer system to implement the logistics supervision method provided by the embodiment of the present disclosure.
  • the computer program may rely on tangible storage media such as optical storage devices and magnetic storage devices.
  • the computer program can also be transmitted and distributed in the form of a signal on a network medium, and downloaded and installed through the communication part 709, and/or installed from the removable medium 711.
  • the program code contained in the computer program can be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.
  • the computer program may be downloaded and installed from the network via communication portion 709 and/or installed from removable media 711 .
  • the computer program is executed by the processor 701, the above-described functions defined in the system of the embodiment of the present disclosure are performed.
  • the systems, devices, devices, modules, units, etc. described above may be implemented by computer program modules.
  • the program code for executing the computer program provided by the embodiments of the present disclosure may be written in any combination of one or more programming languages. Specifically, high-level procedural and/or object-oriented programming may be utilized. programming language, and/or assembly/machine language to implement these computational procedures. Programming languages include, but are not limited to, programming languages such as Java, C++, python, "C" language or similar programming languages.
  • the program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server.
  • the remote computing device may be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device, such as provided by an Internet service. (business comes via Internet connection).
  • LAN local area network
  • WAN wide area network
  • Internet service business comes via Internet connection
  • each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more logic functions that implement the specified executable instructions.
  • the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown one after another may actually execute substantially in parallel, or they may sometimes execute in the reverse order, depending on the functionality involved.
  • each block in the block diagram or flowchart illustration, and combinations of blocks in the block diagram or flowchart illustration can be implemented by special purpose hardware-based systems that perform the specified functions or operations, or may be implemented by special purpose hardware-based systems that perform the specified functions or operations. Achieved by a combination of specialized hardware and computer instructions.

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Abstract

本公开提供了一种基于区块链的物流监管方法、装置、电子设备和存储介质，可用于区块链技术领域，该方法包括：针对获取的目标货物的初始特征数据进行上链处理，生成第一数据，第一数据包括与初始特征数据相关联的第一哈希值，初始特征数据是根据目标货物在第一位置的第一图像获取的；通过电子关锁对目标货物的状态信息进行实时监控，针对获取的异常状态信息进行上链处理，生成第二数据；针对获取的目标货物的结束特征数据进行上链处理，生成第三数据，第三数据包括与结束特征数据相关联的第二哈希值，结束特征数据是根据目标货物在第二位置的第二图像获取的；根据获取的第一数据与第三数据的比对结果和/或第二数据，确定目标货物的监管策略。

Description

基于区块链的物流监管方法、装置、电子设备和存储介质 技术领域
本公开涉及区块链技术领域，具体涉及一种基于区块链的物流监管方法、装置、电子设备和可读存储介质。
背景技术
随着经济全球化的发展，物流的数量和货物增长迅猛，物流在运送过程中可能出现各种各样的情况，导致物流运送的货物和数量发生变化，而在货物运送至目标位置后，无法判断货物在运送途中是否发生变化，需要对货物进行人工验货，效率低下，不利于货物的高效运输。此外，货物在运送过程中，由于不同的承运人、货物地点等不同，导致各货物承运人、收货人、货物供应商等无法及时获取货物的物流状态，现有技术中无法对货物在物流过程中的状态进行判断，以及物流相关方无法有效准确获取货物的物流信息等内容。
发明内容
有鉴于此，本公开提供一种基于区块链的物流监管方法、装置、电子设备和存储介质，至少部分地解决了无法对货物在物流过程中的状态进行判断以及无法准确获取货物物流信息的问题。
本公开的第一方面，提供了一种基于区块链的物流监管方法，包括：针对获取的目标货物的初始特征数据进行上链处理，生成第一数据，所述第一数据包括与所述初始特征数据相关联的第一哈希值，所述初始特征数据是根据所述目标货物在第一位置的第一图像获取的；通过电子关锁对所述目标货物的状态信息进行实时监控，针对获取的异常状态信息进行上链处理，生成第二数据；针对获取的目标货物的结束特征数据进行上链处理，生成第三数据，所述第三数据包括与所述结束特征数据相关联的第二哈希值，所述结束特征数据是根据目标 货物在第二位置的第二图像获取的；根据获取的所述第一数据与所述第三数据的比对结果和/或所述第二数据，确定所述目标货物的监管策略。
在本公开的示例性实施例中，所述的方法还包括：在所述目标货物位于所述第一位置时，针对获取的所述目标货物的初始业务数据进行上链处理，生成目标货物的物流初始信息；以及在所述目标货物位于所述第二位置时，针对获取的所述目标货物的结束业务数据进行上链处理，生成目标货物的物流结束信息，其中，所述初始业务数据和所述结束业务数据是从物联网数据服务器获取的。
在本公开的示例性实施例中，所述的方法还包括：在所述针对获取的目标货物的初始特征数据进行上链处理，生成第一数据之前，对所述第一位置的所述目标货物进行拍照，获取所述目标货物的第一图像；对所述目标货物的第一图像进行特征提取，生成所述目标货物的初始特征数据。
在本公开的示例性实施例中，所述针对获取的目标货物的初始特征数据进行上链处理，生成第一数据包括：通过预设算法对所述初始特征数据进行哈希计算，生成第一哈希值；对所述第一哈希值进行签名，生成所述第一数据。
在本公开的示例性实施例中，所述的方法还包括：在所述针对获取的目标货物的结束特征数据进行上链处理，生成第三数据之前，对所述第二位置的所述目标货物进行拍照，获取所述目标货物的第二图像；对所述目标货物的第二图像进行特征提取，生成所述目标货物的结束特征数据。
在本公开的示例性实施例中，所述针对获取的目标货物的结束特征数据进行上链处理，生成第三数据包括：通过预设算法对所述结束特征数据进行哈希计算，生成第二哈希值；将所述第二哈希值进行签名，生成第三数据。
在本公开的示例性实施例中，所述的方法还包括：在所述根据获取的所述第一数据与所述第三数据的比对结果和/或所述第二数据，确定所述目标货物的监管策略之前包括：对所述第一数据进行解密， 生成第一哈希值；对所述第三数据进行解密，生成第二哈希值；根据所述第一哈希值和所述第二哈希值确定所述比对结果，其中，当所述第一哈希值和所述第二哈希值相同，确定所述比对结果为物流正常，以及当所述第一哈希值和所述第二哈希值不同，确定所述比对结果为物流异常。
在本公开的示例性实施例中，所述根据获取的所述第一数据与所述第三数据的比对结果和/或所述第二数据，确定所述目标货物的监管策略包括：当所述比对结果为物流异常，或当所述比对结果为物流正常且存在第二数据，确定所述目标货物的监管策略为需要开箱验货。
在本公开的示例性实施例中，所述通过电子关锁对所述目标货物的状态信息进行实时监控，针对获取的异常状态信息进行上链处理，生成第二数据包括：通过所述电子关锁获取目标货物的状态信息，所述状态信息包括施封状态信息、地理位置信息、时间信息中的至少一者；通过物联网数据服务器判断所述目标货物的状态信息是否异常；将异常的状态信息进行上链处理，生成第二数据。
在本公开的示例性实施例中，所述的方法还包括：响应跨链同步指令，通过同步组件将所述第一数据、第二数据和第三数据从源区块链同步到至少一个目标区块链中。
在本公开的示例性实施例中，所述的方法还包括：响应查询指令，从所述源区块链和所述至少一个目标区块链中获取所述物流初始信息、所述物流结束信息、所述第一数据、所述第二数据和所述第三数据中的至少一者。
本公开实施例的第二方面，提供了一种基于区块链的物流监管装置，包括：第一生成模块，配置为针对获取的目标货物的初始特征数据进行上链处理，生成第一数据，所述第一数据包括与所述初始特征数据相关联的第一哈希值，所述初始特征数据是根据所述目标货物在第一位置的第一图像获取的；第二生成模块，配置为通过电子关锁对所述目标货物的状态信息进行实时监控，针对获取的异常状态信息进行上链处理，生成第二数据；第三生成模块，配置为针对获取的目标 货物的结束特征数据进行上链处理，生成第三数据，所述第三数据包括与所述结束特征数据相关联的第二哈希值，所述结束特征数据是根据目标货物在第二位置的第二图像获取的；确定模块，配置为根据获取的所述第一数据与所述第三数据的比对结果和/或所述第二数据，确定所述目标货物的监管策略。
本公开实施例的第三方面，提供了一种电子设备，包括：一个或多个处理器；存储装置，用于存储可执行指令，所述可执行指令在被所述处理器执行时，实现根据上文所述的方法。
本公开实施例的第四方面，提供了一种计算机可读存储介质，其上存储有可执行指令，该指令被处理器执行时，实现根据上文所述的方法。
本公开实施例的第五方面，提供了一种计算机程序产品，包括计算机程序，所述计算机程序被处理器执行时实现根据上文所述的方法。
根据本公开的实施例，通过基于在第一位置获取目标货物的初始特征数据和在第二位置获取目标货物的结束特征数据的比对结果，并基于目标货物在物流过程中的根据异常状态信息生成的第二数据来确定目标货物的监管策略，可以有效提高物流监管的效率。此外，通过将获取的初始特征数据、结束特征数据以及异常状态信息进行上链处理，便于物流的相关用户从区块链中获取目标货物的详细物流信息，并且由于区块链中的信息不可篡改性，获取的物流信息更加准确。
附图说明
通过以下参照附图对本公开实施例的描述，本公开的上述以及其他目的、特征和优点将更为清楚，在附图中：
图1示意性示出了根据本公开实施例的可以应用基于区块链的物流监管方法的示例性系统架构；
图2示意性示出了根据本公开实施例的基于区块链的物流监管方法的流程图；
图3示意性示出了根据本公开实施例的基于区块链的物流监管 方法在操作S250的流程图；
图4示意性示出了根据本公开实施例的基于区块链的物流监管方法在生成第一数据之前的操作S300的流程图；
图5示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S210的流程图；
图6示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S220的流程图；
图7示意性示出了根据本公开实施例的基于区块链的物流监管方法在生成第二数据之前的操作S400的流程图；
图8示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S230的流程图；
图9示意性示出了根据本公开实施例的基于区块链的物流监管方法在确定目标货物的监管策略之前的操作S500的流程图；
图10示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S240的具体流程图；
图11示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S260的流程图；
图12示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S270的流程图；
图13示意性示出了根据本公开实施例的基于区块链的物流监管装置的框图；
图14示意性示出了根据本公开实施例的用于实现的基于区块链的物流监管方法的电子设备的框图。
具体实施方式
以下，将参照附图来描述本公开的实施例。但是应该理解，这些描述只是示例性的，而并非要限制本公开的范围。在下面的详细描述中，为便于解释，阐述了许多具体的细节以提供对本公开实施例的全面理解。然而，明显地，一个或多个实施例在没有这些具体细节的情况下也可以被实施。此外，在以下说明中，省略了对公知结构和技术 的描述，以避免不必要地混淆本公开的概念。
在此使用的术语仅仅是为了描述具体实施例，而并非意在限制本公开。在此使用的术语“包括”、“包含”等表明了特征、步骤、操作和/或部件的存在，但是并不排除存在或添加一个或多个其他特征、步骤、操作或部件。
在此使用的所有术语(包括技术和科学术语)具有本领域技术人员通常所理解的含义，除非另外定义。应注意，这里使用的术语应解释为具有与本说明书的上下文相一致的含义，而不应以理想化或过于刻板的方式来解释。
在使用类似于“A、B或C等中至少一个”这样的表述的情况下，一般来说应该按照本领域技术人员通常理解该表述的含义来予以解释(例如，“具有A、B或C中至少一个的系统”应包括但不限于单独具有A、单独具有B、单独具有C、具有A和B、具有A和C、具有B和C、和/或具有A、B、C的系统等)。术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个特征。
在本公开的技术方案中，所涉及的用户个人信息的获取、存储和应用等，均符合相关法律法规的规定，采取了必要保密措施，且不违背公序良俗。在本公开的技术方案中，所涉及的用户个人信息的获取、存储和应用等操作，均获得了用户的授权。
为了解决相关技术中无法对货物在物流过程中的状态进行判断，以及物流相关方无法有效准确获取货物的物流信息等内容的问题。本公开的实施例提供了一种基于区块链的物流监管方法、装置、电子设备和可读存储介质。该基于区块链的物流监管方法包括：针对获取的目标货物的初始特征数据进行上链处理，生成第一数据，第一数据包括与初始特征数据相关联的第一哈希值，初始特征数据是根据目标货物在第一位置的第一图像获取的；通过电子关锁对目标货物的状态信息进行实时监控，针对获取的异常状态信息进行上链处理，生成第二数据；针对获取的目标货物的结束特征数据进行上链处理，生成第三 数据，第三数据包括与结束特征数据相关联的第二哈希值，结束特征数据是根据目标货物在第二位置的第二图像获取的；根据获取的第一数据与第三数据的比对结果和/或第二数据，确定目标货物的监管策略。
根据本公开的实施例，通过基于在第一位置获取目标货物的初始特征数据和在第二位置获取目标货物的结束特征数据的比对结果，并基于目标货物在物流过程中的根据异常状态信息生成的第二数据来确定目标货物的监管策略，可以有效提高物流监管的效率。此外，通过将获取的初始特征数据、结束特征数据以及异常状态信息进行上链处理，便于物流的相关用户从区块链中获取目标货物的详细物流信息，并且由于区块链中的信息不可篡改性，获取的物流信息更加准确。
图1示意性示出了根据本公开实施例的可以应用基于区块链的物流监管方法的示例性系统架构。需要注意的是，图1所示仅为可以应用本公开实施例的系统架构的示例，以帮助本领域技术人员理解本公开的技术内容，但并不意味着本公开实施例不可以用于其他设备、系统、环境或场景。需要说明的是，本公开实施例提供的物流监管方法、装置、电子设备和可读存储介质可用于物流领域的相关方面，也可用于除物流领域之外的多种领域，本公开实施例提供的物流监管方法、装置、电子设备和可读存储介质对应用领域不做限定。
如图1所示，本公开实施例的可以应用于基于区块链的物流监管方法的系统架构包括第一图像采集设备101、电子关锁102、第二图像采集设备103、用户104、物联网数据服务器105、区块链106以及网络107。
第一图像采集设备101和第二图像采集设备102用于对不同地点或者不同位置的物流的目标货物采集图像，例如可以是X射线图像采集设备，用于采集目标货物的X射线图像等。
电子关锁102例如可以是对目标货物的状态信息进行检测的一种锁，电子关锁可以设置为在设定位置通过特定的钥匙或者指令合法打开，当电子关锁的打开条件未满足设定要求时，可以记录电子关锁被非法打开的异常信息，通过异常信息来判断目标货物在物流运输途 中的状态。
用户104例如可以是货物承运人、收货人、货物供应商、海关人员等，可以通过网络107从区块链106中获取数据并进行查看或者向区块链中写入数据等操作，从而目标货物的物流信息以及物流状态进行查看和判断。
物联网数据服务器105例如可以是提供各种物流信息服务的服务器，例如对承运人、收货人、货物供应商的信息进行录入、分析或者进行管理的服务器。
区块链106例如是供特定的群体或组织使用的联盟链，例如向货物承运人、收货人、货物供应商、海关人员等的区块链，便于相关用户从区块链106中获取数据信息等。
网络107用以在第一图像采集设备101、电子关锁102、第二图像采集设备103、用户104、物联网数据服务器105、区块链106之间提供通信链路的介质。网络107可以包括各种连接类型，例如有线、无线通信链路或者光纤电缆等等。
通过图1中所示的系统架构，可以实现本公开实施例的基于区块链的物流监管方法。例如，目标货物在初始地点通过第一图像采集设备101进行图像采集，并通过电子关锁102，对目标货物的在运输过程中的状态信息进行实时监控，并在目标货物到达目标地点后，通过第二图像采集设备103对目标货物再次进行图像采集。采集的图像经过处理后，上链至区块链106中，便于其他用户104或者物联网105对该信息进行查看或调用。
应该理解，图1中的第一图像采集设备、电子关锁、第二图像采集设备、用户、物联网数据服务器、区块链以及网络的数目仅仅是示意性的。根据实现需要，可以具有任意数目的第一图像采集设备、电子关锁、第二图像采集设备、用户、物联网数据服务器、区块链以及网络。
图2示意性示出了根据本公开实施例的基于区块链的物流监管方法的流程图。
如图2所示，本公开的基于区块链的物流监管方法的流程200包 括操作S210至操作S240。
在操作S210中，针对获取的目标货物的初始特征数据进行上链处理，生成第一数据，第一数据包括与初始特征数据相关联的第一哈希值，初始特征数据是根据目标货物在第一位置的第一图像获取的。
在操作S220中，通过电子关锁对目标货物的状态信息进行实时监控，针对获取的异常状态信息进行上链处理，生成第二数据。
在操作S230中，针对获取的目标货物的结束特征数据进行上链处理，生成第三数据，第三数据包括与结束特征数据相关联的第二哈希值，结束特征数据是根据目标货物在第二位置的第二图像获取的。
在操作S240中，根据获取的第一数据与第三数据的比对结果和/或所述第二数据，确定目标货物的监管策略。
以下结合图2至图12对本公开实施例的基于区块链的物流监管方法进行详细说明。
在本公开的实施例中，目标货物例如可以是需要进行物流监管的货物，第一位置例如可以是目标货物的发货位置，或者第一位置也可以是目标货物需要进行物流监管的初始位置。第二位置例如可以是目标货物的收货位置，或者第二位置也可以是目标货物进行物流监管的结束位置。
目标货物在物流途中，可能被存在打开或者拆封等问题，从第一位置到达第二位置，或者需要对货物进行检查的相关方若不对货物进行查验，无法有效判断目标货物在物流途中是否改变，而对目标货物进行开箱验货的过程需要耗费时间和精力，无法有效提高目标货物在物流过程中的效率。此外，若目标货物在物流途中没有发生改变，开箱验货的过程造成大量的无效工作。
通过对第一位置和第二位置的目标货物的特征数据进行比对，来判断目标货物在物流途中是否发生改变，此外，本公开的物流监管方法还包括操作S250。
图3示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S250的流程图。
如图3所示，操作S250包括操作S251至操作S252。
在操作S251中，在目标货物位于第一位置时，针对获取的目标货物的初始业务数据进行上链处理，生成目标货物的物流初始信息。
示例性地，初始业务数据例如可以是目标货物的起运地信息、司机信息、货物信息、承运人信息、发货人信息、制造商信息、干线运输商信息、首端接收商信息等与该目标货物的物流业务相关联的业务数据。在获取了初始业务数据后，可以针对初始业务数据中的一者或者多者，进行上链处理，生成目标货物的物流初始信息。例如在对上链数据进行校验，并在校验通过后，记录在区块链中的一个区块中。相关用户可以通过查阅该区块中的信息来获取目标货物的物流初始信息。
在操作S252中，在目标货物位于所述第二位置时，针对获取的目标货物的结束业务数据进行上链处理，生成目标货物的物流结束信息。
示例性地，结束业务数据例如可以是目标货物的到达地信息、司机信息、货物信息、承运人信息、发货人信息、制造商信息、干线运输商信息、末端派送商信息等与该目标货物的物流业务相关联的业务数据。基于上述将初始业务数据进行上链的相同过程，将结束业务数据上链至区块链中，便于用户查阅区块链中记录的目标货物的物流结束信息。
在本公开的实施例中，初始业务数据和结束业务数据是从物联网数据服务器获取的。例如，在目标货物进入物流程序之前，物流途中以及物流结束之后，获取的目标货物的起始地信息、到达地信息、司机信息、货物信息、承运人信息、发货人信息、制造商信息、干线运输商信息、首端接收商信息、末端派送商信息等通过各个数据收集装置进行收集，并存储在物联网数据服务器中。在运用区块链的过程中，定义各方所需要上传至区块链的信息，并根据响应的上链规则，对初始业务数据和结束业务数据进行上链，生成存储在区块链中的目标货物的物流初始信息和物流结束信息。
在本公开的实施例中，在针对获取的目标货物的初始特征数据进行上链处理，生成第一数据之前包括操作S300。
图4示意性示出了根据本公开实施例的基于区块链的物流监管方法在生成第一数据之前的操作S300的流程图。
如图4所示，操作S300包括操作S310至操作S320。
在操作S310中，对第一位置的目标货物进行拍照，获取目标货物的第一图像。
在本公开的实施例中，在目标货物到达第一位置后，进入物流程序，对目标货物进行拍照，例如，通过X射线装置，生成目标货物的X射线图像。在其他的可选实施例中，可以是通过其他的拍照方式获取目标货物的图像等内容。第一图像即通过拍照设备获取的图像，例如可以是目标货物的X射线图像，或者目标货物的外观照片等。
在操作S320中，对目标货物的第一图像进行特征提取，生成目标货物的初始特征数据。
示例性地，对目标货物的第一图像进行特征提取，可以是通过特定的算法进行特征提取，例如通过HOG(Histogram of Oriented Gradient)算法来提取第一图像的特征，生成目标货物的初始特征数据。
图5示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S210的流程图。
在获取到目标货物的初始特征数据后，执行操作S210，如图5所示，操作S210包括操作S211至操作S212。
在操作S211中，通过预设算法对所述初始特征数据进行哈希计算，生成第一哈希值。
示例性地，该预设算法例如可以是特定的散列函数，通过散列函数对初始特征数据进行计算生成具有特定长度的哈希值。
在操作S212中，对第一哈希值进行签名，生成第一数据。
示例性地，通过用户所具有的私钥对第一哈希值进行签名，生成第一数据。
在本公开的实施例中，第一数据例如可以记录在区块链中，便于用户对该第一数据进行读取。
在本公开的实施例中，对目标货物在第一位置进行拍照，并获取了目标货物在第一位置的第一图像的初始特征数据后，对目标货物进行施封，即将目标货物装入集装箱或者进行物流的车辆后，关闭箱门，由特定人员施加电子关锁，从而可以实时监控目标货物的状态。
图6示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S220的流程图。
如图6所示，操作S220包括操作S221至操作S223。
在操作S221中，通过电子关锁获取目标货物的状态信息，状态信息包括施封状态信息、地理位置信息、时间信息中的至少一者。
在本公开的实施例中，在目标货物的物流途中，电子关锁可以获取目标货物的状态信息，状态信息可以是施封状态信息、地理位置信息、或者时间信息。
例如实时获取目标货物的地理位置信息，根据地理位置信息，可以确定目标货物的物流轨迹，判断目标货物是否偏移设定轨迹。根据施封状态信息，可以判断目标货物在物流途中是否被打开或者改变。根据时间信息和地理位置信息，可以判断目标货物在不同的位置的滞留时间，若滞留时间超设定时间则说明可能存在异常。
在操作S222中，通过物联网数据服务器判断目标货物的状态信息是否异常。
通过电子关锁获取的数据传输至物联网数据服务器，物联网数据服务器针对获取的目标状态信息与设定的状态信息进行比对，从而判断目标货物的状态信息是否异常。
示例性地，当目标货物的物流轨迹偏移设定轨迹，或者目标货物在某一地理位置的滞留时间超过设定时间，或者电子关锁的施封状态显示施封状态异常等，均可以判定为目标货物的状态信息异常。
在操作S223中，将异常的状态信息进行上链处理，生成第二数据。
将获取的异常的状态信息进行上链处理，即将异常的状态信息记录在区块链网络的区块中，生成第二数据。相关用户可以从区块链网络中读取该异常的状态信息。
在针对获取的目标货物的结束特征数据进行上链处理，生成第三数据之前，还包括操作S400。
图7示意性示出了根据本公开实施例的基于区块链的物流监管方法在生成第二数据之前的操作S400的流程图。
如图4所示，操作S400包括操作S410至操作S420。
在操作S410中，对第二位置的目标货物进行拍照，获取目标货物的第二图像。
示例性地，第二位置例如是目标货物的收货位置。在第二位置对收到的目标货物进行拍照，获取第二图像。在第一位置和第二位置采用的图像采集设备为相同的设备，例如都采用X射线装置获取目标货物在第二位置的X射线图像。
在操作S420中，对目标货物的第二图像进行特征提取，生成目标货物的结束特征数据。
示例性地，对目标货物的第二图像进行特征提取，可以是通过特定的算法进行特征提取，例如通过HOG(Histogram of Oriented Gradient)算法来提取第二图像的特征，生成目标货物的结束特征数据。
通过采用相同的图像采集设备以及采用相同的算法对图像的特征进行提取，从而可以保证在第一位置和第二位置的相同的目标货物具有相同的特征数据，从而可以实现准确的比对目标货物在不同的位置的状态。
在获取了目标货物的结束特征数据后，执行操作S230。
图8示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S230的流程图。
如图8所述，操作S230包括操作S231至操作S232。
在操作S231中，通过预设算法对结束特征数据进行哈希计算，生成第二哈希值。
示例性地，在操作S231中的预设算法与操作S211中的预设算法例如可以是相同的。通过预设算法中的散列函数对结束特征数据进行计算，生成第二哈希值。
在操作S232中，将第二哈希值进行签名，生成第三数据。
示例性地，通过用户所具有的私钥对第二哈希值进行签名，生成第三数据。
在本公开的实施例中，第三数据例如可以记录在区块链中，便于用户对该第三数据进行读取，用于与第一数据进行比较从而获取比较结果。
在根据获取的第一数据与第三数据的比对结果和/或第二数据，确定目标货物的监管策略之前包括操作S500。
图9示意性示出了根据本公开实施例的基于区块链的物流监管方法在确定目标货物的监管策略之前的操作S500的流程图。
如图9所示，操作S500包括操作S510至操作S530。
在操作S510中，对第一数据进行解密，生成第一哈希值。
示例性地，获取区块链上的某一区块的第一数据，该数据例如是利用私钥对第一哈希值进行签名后的数据。用户从区块链上获取了第一数据后，利用签名者的公钥对第一数据进行解密，生成第一哈希值。
在操作S520中，对第三数据进行解密，生成第一哈希值。
示例性地，通过操作S510中相同的操作，利用签名者的公钥对第二数据进行解密，生成第二哈希值。
在操作S530中，根据第一哈希值和第二哈希值确定比对结果，其中，当第一哈希值和第二哈希值相同，确定比对结果为物流正常，以及当第一哈希值和第二哈希值不同，确定比对结果为物流异常。
示例性地，当第一哈希值和第二哈希值相同，则说明目标货物从第一位置运送到第二位置的特征数据没有发生变化，即目标货物未发生变化。当第一哈希值和第二哈希值不相同，则说明目标货物从第一位置运送到第二位置的特征数据发生变化，目标货物发生改变，从而确定比对结果为物流异常。
图10示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S240的具体流程图。
如图10所示，操作S240包括操作S241。在操作S241中，当比对结果为物流异常，或当比对结果为物流正常且存在第二数据，确定 目标货物的监管策略为需要开箱验货。
示例性地，当比对结果为物流异常，则确定目标货物的监管策略为需要开箱验货。
示例性地，当比对结果为物流正常，并且存在第二数据时，说明目标货物在物流运送途中存在异常状态信息，此时目标货物也有可能出现问题，确定目标货物的监管策略为需要开箱验货。
在本公开的基于区块链的物流监管方法还可以实现不同的区块链的数据同步的要求，还包括操作S260。
图11示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S260的流程图。
如图11所示，在操作S260中，响应跨链同步指令，通过同步组件将第一数据、第二数据和第三数据从源区块链同步到至少一个目标区块链中。
为了满足不同的区块链网络的不同的数据类型的要求，可以将记载在源区块链网络中的数据同步至目标区块链中，从而满足不同地区的不同区块链网络的要求。
示例性地，在需要进行区块链中的数据进行同步时，响应跨链同步指令，通过同步组件将源区块链中的数据同步到至少一个目标区块链中。或者，将目标区块链中的部分数据同步至源区块链网络中，从而实现跨链数据同步的要求。
在本公开的实施例中，区块链例如可以是联盟链。
在本公开的基于区块链的物流监管方法还可以响应不同用户的查询指令，执行查询操作S270。
图12示意性示出了根据本公开实施例的基于区块链的物流监管方法在操作S270的流程图。
如图12所示，在操作S270中，响应查询指令，从源区块链和至少一个目标区块链中获取物流初始信息、物流结束信息、第一数据、第二数据和第三数据中的至少一者。
示例性地，根据相关用户获取的上述信息，可以准确查询到物流的各种信息，并且，由于这类信息记录在区块链的各个区块中，信息 完全透明可信，以及防篡改和可溯源的特性，便于用户对数据进行查询。
根据本公开的实施例，通过基于在第一位置获取目标货物的初始特征数据和在第二位置获取目标货物的结束特征数据的比对结果，并基于目标货物在物流过程中的根据异常状态信息生成的第二数据来确定目标货物的监管策略，可以有效提高物流监管的效率。此外，通过将获取的初始特征数据、结束特征数据以及异常状态信息进行上链处理，便于物流的相关用户从区块链中获取目标货物的详细物流信息，并且由于区块链中的信息不可篡改性，获取的物流信息更加准确。
图13示意性示出了根据本公开实施例的基于区块链的物流监管装置的框图。
如图13所示，本公开实施例的物流监管装置600包括第一生成模块610、第二生成模块620、第三生成模块630以及确定模块640。
第一生成模块610配置为针对获取的目标货物的初始特征数据进行上链处理，生成第一数据，第一数据包括与初始特征数据相关联的第一哈希值，初始特征数据是根据目标货物在第一位置的第一图像获取的。在一实施例中，第一生成模块610可以用于执行前文描述的操作S210，在此不再赘述。
第二生成模块620配置为通过电子关锁对目标货物的状态信息进行实时监控，针对获取的异常状态信息进行上链处理，生成第二数据。在一实施例中，第二生成模块620可以用于执行前文描述的操作S220，在此不再赘述。
第三生成模块630配置为针对获取的目标货物的结束特征数据进行上链处理，生成第三数据，第三数据包括与结束特征数据相关联的第二哈希值，结束特征数据是根据目标货物在第二位置的第二图像获取的。第三生成模块630可以用于执行前文描述的操作S230，在此不再赘述。
确定模块640配置为根据获取的第一数据与第三数据的比对结果和/或第二数据，确定目标货物的监管策略。确定模块640可以用于执行前文描述的操作S240，在此不再赘述。
在本公开的示例性实施例中，物流监管装置还包括物流信息生成模块，物流信息生成模块配置为：在目标货物位于第一位置时，针对获取的目标货物的初始业务数据进行上链处理，生成目标货物的物流初始信息；以及在目标货物位于第二位置时，针对获取的目标货物的结束业务数据进行上链处理，生成目标货物的物流结束信息，其中，初始业务数据和结束业务数据是从物联网数据服务器获取的。
在本公开的示例性实施例中，物流监管装置还包括初始特征生成模块，初始特征生成模块配置为：在针对获取的目标货物的初始特征数据进行上链处理，生成第一数据之前，对第一位置的目标货物进行拍照，获取目标货物的第一图像；对目标货物的第一图像进行特征提取，生成目标货物的初始特征数据。
在本公开的示例性实施例中，第一生成模块包括第一生成子模块。第一生成子模块配置为：通过预设算法对初始特征数据进行哈希计算，生成第一哈希值；对第一哈希值进行签名，生成第一数据。
在本公开的示例性实施例中，物流监管装置还包括结束特征生成模块，结束特征生成模块配置为：在针对获取的目标货物的结束特征数据进行上链处理，生成第三数据之前，对第二位置的目标货物进行拍照，获取目标货物的第二图像；对目标货物的第二图像进行特征提取，生成目标货物的结束特征数据。
在本公开的示例性实施例中，第三生成模块包括第三生成子模块。第三生成子模块配置为：通过预设算法对结束特征数据进行哈希计算，生成第二哈希值；将第二哈希值进行签名，生成第三数据。
在本公开的示例性实施例中，物流监管装置还包括比对结果确定模块，配置为：在根据获取的第一数据与第三数据的比对结果和/或第二数据，确定目标货物的监管策略之前，对第一数据进行解密，生成第一哈希值；对第三数据进行解密，生成第二哈希值；根据第一哈希值和第二哈希值确定比对结果，其中，当第一哈希值和第二哈希值相同，确定比对结果为物流正常，以及当第一哈希值和第二哈希值不同，确定比对结果为物流异常。
在本公开的示例性实施例中，确定模块包括确定子模块，确定子模块配置为：当比对结果为物流异常，或当比对结果为物流正常且存在第二数据，确定目标货物的监管策略为需要开箱验货。
在本公开的示例性实施例中，第二生成模块包括第二生成子模块。第二生成子模块配置为：通过电子关锁获取目标货物的状态信息，状态信息包括施封状态信息、地理位置信息、时间信息中的至少一者；通过物联网数据服务器判断目标货物的状态信息是否异常；将异常的状态信息进行上链处理，生成第二数据。
在本公开的示例性实施例中，物流监管装置还包括同步模块，同步模块配置为：响应跨链同步指令，通过同步组件将第一数据、第二数据和第三数据从源区块链同步到至少一个目标区块链中。
在本公开的示例性实施例中，物流监管装置还包括查询模块，查询模块配置为：响应查询指令，从源区块链和至少一个目标区块链中获取物流初始信息、物流结束信息、第一数据、第二数据和第三数据中的至少一者。
根据本公开的实施例，第一生成模块610、第二生成模块620、第三生成模块630以及确定模块640中的任意多个模块可以合并在一个模块中实现，或者其中的任意一个模块可以被拆分成多个模块。或者，这些模块中的一个或多个模块的至少部分功能可以与其他模块的至少部分功能相结合，并在一个模块中实现。根据本公开的实施例，第一生成模块610、第二生成模块620、第三生成模块630以及确定模块640中的至少一个可以至少被部分地实现为硬件电路，例如现场可编程门阵列(FPGA)、可编程逻辑阵列(PLA)、片上系统、基板上的系统、封装上的系统、专用集成电路(ASIC)，或可以通过对电路进行集成或封装的任何其他的合理方式等硬件或固件来实现，或以软件、硬件以及固件三种实现方式中任意一种或以其中任意几种的适当组合来实现。或者，第一生成模块610、第二生成模块620、第三生成模块630以及确定模块640中的至少一个可以至少被部分地实现为计算机程序模块，当该计算机程序模块被运行时，可以执行相应的功能。
图14示意性示出了根据本公开实施例的用于实现的基于区块链的物流监管方法的电子设备的框图。图14示出的电子设备仅仅是一个示例，不应对本公开实施例的功能和使用范围带来任何限制。
如图14所示，根据本公开实施例的电子设备700包括处理器701，其可以根据存储在只读存储器(ROM)702中的程序或者从存储部分708加载到随机访问存储器(RAM)703中的程序而执行各种适当的动作和处理。处理器701例如可以包括通用微处理器(例如CPU)、指令集处理器和/或相关芯片组和/或专用微处理器(例如，专用集成电路(ASIC))等等。处理器701还可以包括用于缓存用途的板载存储器。处理器701可以包括用于执行根据本公开实施例的方法流程的不同动作的单一处理单元或者是多个处理单元。
在RAM 703中，存储有电子设备700操作所需的各种程序和数据。处理器701、ROM 702以及RAM 703通过总线704彼此相连。处理器701通过执行ROM 702和/或RAM 703中的程序来执行根据本公开实施例的方法流程的各种操作。需要注意，所述程序也可以存储在除ROM 702和RAM 703以外的一个或多个存储器中。处理器701也可以通过执行存储在所述一个或多个存储器中的程序来执行根据本公开实施例的方法流程的各种操作。
根据本公开的实施例，电子设备700还可以包括输入/输出(I/O)接口705，输入/输出(I/O)接口705也连接至总线704。电子设备700还可以包括连接至I/O接口705的以下部件中的一项或多项：包括键盘、鼠标等的输入部分706；包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分707；包括硬盘等的存储部分708；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分709。通信部分709经由诸如因特网的网络执行通信处理。驱动器710也根据需要连接至I/O接口705。可拆卸介质711，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器710上，以便于从其上读出的计算机程序根据需要被安装入存储部分708。
本公开还提供了一种计算机可读存储介质，该计算机可读存储介 质可以是上述实施例中描述的设备/装置/系统中所包含的；也可以是单独存在，而未装配入该设备/装置/系统中。上述计算机可读存储介质承载有一个或者多个程序，当上述一个或者多个程序被执行时，实现根据本公开实施例的物流监管方法。
根据本公开的实施例，计算机可读存储介质可以是非易失性的计算机可读存储介质，例如可以包括但不限于：便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本公开中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。例如，根据本公开的实施例，计算机可读存储介质可以包括上文描述的ROM 702和/或RAM 703和/或ROM 702和RAM 703以外的一个或多个存储器。
本公开的实施例还包括一种计算机程序产品，其包括计算机程序，该计算机程序包含用于执行流程图所示的方法的程序代码。当计算机程序产品在计算机系统中运行时，该程序代码用于使计算机系统实现本公开实施例所提供的物流监管方法。
在该计算机程序被处理器701执行时执行本公开实施例的系统/装置中限定的上述功能。根据本公开的实施例，上文描述的系统、装置、模块、单元等可以通过计算机程序模块来实现。
在一种实施例中，该计算机程序可以依托于光存储器件、磁存储器件等有形存储介质。在另一种实施例中，该计算机程序也可以在网络介质上以信号的形式进行传输、分发，并通过通信部分709被下载和安装，和/或从可拆卸介质711被安装。该计算机程序包含的程序代码可以用任何适当的网络介质传输，包括但不限于：无线、有线等等，或者上述的任意合适的组合。
在这样的实施例中，该计算机程序可以通过通信部分709从网络上被下载和安装，和/或从可拆卸介质711被安装。在该计算机程序被处理器701执行时，执行本公开实施例的系统中限定的上述功能。 根据本公开的实施例，上文描述的系统、设备、装置、模块、单元等可以通过计算机程序模块来实现。
根据本公开的实施例，可以以一种或多种程序设计语言的任意组合来编写用于执行本公开实施例提供的计算机程序的程序代码，具体地，可以利用高级过程和/或面向对象的编程语言、和/或汇编/机器语言来实施这些计算程序。程序设计语言包括但不限于诸如Java，C++，python，“C”语言或类似的程序设计语言。程序代码可以完全地在用户计算设备上执行、部分地在用户设备上执行、部分在远程计算设备上执行、或者完全在远程计算设备或服务器上执行。在涉及远程计算设备的情形中，远程计算设备可以通过任意种类的网络，包括局域网(LAN)或广域网(WAN)，连接到用户计算设备，或者，可以连接到外部计算设备(例如利用因特网服务提供商来通过因特网连接)。
附图中的流程图和框图，图示了按照本公开各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分，上述模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图或流程图中的每个方框、以及框图或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
本领域技术人员可以理解，本公开的各个实施例和/或权利要求中记载的特征可以进行多种组合或/或结合，即使这样的组合或结合没有明确记载于本公开中。特别地，在不脱离本公开精神和教导的情况下，本公开的各个实施例和/或权利要求中记载的特征可以进行多种组合和/或结合。所有这些组合和/或结合均落入本公开的范围。
以上对本公开的实施例进行了描述。但是，这些实施例仅仅是为了说明的目的，而并非为了限制本公开的范围。尽管在以上分别描述 了各实施例，但是这并不意味着各个实施例中的措施不能有利地结合使用。本公开的范围由所附权利要求及其等同物限定。不脱离本公开的范围，本领域技术人员可以做出多种替代和修改，这些替代和修改都应落在本公开的范围之内。

Claims (15)

  1. 一种基于区块链的物流监管方法，包括：
    针对获取的目标货物的初始特征数据进行上链处理，生成第一数据，所述第一数据包括与所述初始特征数据相关联的第一哈希值，所述初始特征数据是根据所述目标货物在第一位置的第一图像获取的；
    通过电子关锁对所述目标货物的状态信息进行实时监控，针对获取的异常状态信息进行上链处理，生成第二数据；
    针对获取的目标货物的结束特征数据进行上链处理，生成第三数据，所述第三数据包括与所述结束特征数据相关联的第二哈希值，所述结束特征数据是根据目标货物在第二位置的第二图像获取的；
    根据获取的所述第一数据与所述第三数据的比对结果和/或所述第二数据，确定所述目标货物的监管策略。
  2. 根据权利要求1所述的方法，其中，还包括：
    在所述目标货物位于所述第一位置时，针对获取的所述目标货物的初始业务数据进行上链处理，生成目标货物的物流初始信息；以及
    在所述目标货物位于所述第二位置时，针对获取的所述目标货物的结束业务数据进行上链处理，生成目标货物的物流结束信息，
    其中，所述初始业务数据和所述结束业务数据是从物联网数据服务器获取的。
  3. 根据权利要求2所述的方法，其中，还包括：
    在所述针对获取的目标货物的初始特征数据进行上链处理，生成第一数据之前，
    对所述第一位置的所述目标货物进行拍照，获取所述目标货物的第一图像；
    对所述目标货物的第一图像进行特征提取，生成所述目标货物的初始特征数据。
  4. 根据权利要求3所述的方法，其中，
    所述针对获取的目标货物的初始特征数据进行上链处理，生成第一数据包括：
    通过预设算法对所述初始特征数据进行哈希计算，生成第一哈希值；
    对所述第一哈希值进行签名，生成所述第一数据。
  5. 根据权利要求4所述的方法，其中，还包括：
    在所述针对获取的目标货物的结束特征数据进行上链处理，生成第三数据之前，
    对所述第二位置的所述目标货物进行拍照，获取所述目标货物的第二图像；
    对所述目标货物的第二图像进行特征提取，生成所述目标货物的结束特征数据。
  6. 根据权利要求5所述的方法，其中，
    所述针对获取的目标货物的结束特征数据进行上链处理，生成第三数据包括：
    通过预设算法对所述结束特征数据进行哈希计算，生成第二哈希值；
    将所述第二哈希值进行签名，生成第三数据。
  7. 根据权利要求6所述的方法，其中，还包括：
    在所述根据获取的所述第一数据与所述第三数据的比对结果和/或所述第二数据，确定所述目标货物的监管策略之前包括：
    对所述第一数据进行解密，生成第一哈希值；
    对所述第三数据进行解密，生成第二哈希值；
    根据所述第一哈希值和所述第二哈希值确定所述比对结果，
    其中，当所述第一哈希值和所述第二哈希值相同，确定所述比对结果为物流正常，以及
    当所述第一哈希值和所述第二哈希值不同，确定所述比对结果为物流异常。
  8. 根据权利要求7所述的方法，其中，
    所述根据获取的所述第一数据与所述第三数据的比对结果和/或所述第二数据，确定所述目标货物的监管策略包括：
    当所述比对结果为物流异常，或
    当所述比对结果为物流正常且存在第二数据，
    确定所述目标货物的监管策略为需要开箱验货。
  9. 根据权利要求1所述的方法，其中，
    所述通过电子关锁对所述目标货物的状态信息进行实时监控，针对获取的异常状态信息进行上链处理，生成第二数据包括：
    通过所述电子关锁获取目标货物的状态信息，所述状态信息包括施封状态信息、地理位置信息、时间信息中的至少一者；
    通过物联网数据服务器判断所述目标货物的状态信息是否异常；
    将异常的状态信息进行上链处理，生成第二数据。
  10. 根据权利要求2所述的方法，其中，还包括：
    响应跨链同步指令，通过同步组件将所述第一数据、第二数据和第三数据从源区块链同步到至少一个目标区块链中。
  11. 根据权利要求10所述的方法，其中，还包括：
    响应查询指令，从所述源区块链和所述至少一个目标区块链中获取所述物流初始信息、所述物流结束信息、所述第一数据、所述第二数据和所述第三数据中的至少一者。
  12. 一种基于区块链的物流监管装置，包括：
    第一生成模块，配置为针对获取的目标货物的初始特征数据进行上链处理，生成第一数据，所述第一数据包括与所述初始特征数据相关联的第一哈希值，所述初始特征数据是根据所述目标货物在第一位置的第一图像获取的；
    第二生成模块，配置为通过电子关锁对所述目标货物的状态信息进行实时监控，针对获取的异常状态信息进行上链处理，生成第二数据；
    第三生成模块，配置为针对获取的目标货物的结束特征数据进行上链处理，生成第三数据，所述第三数据包括与所述结束特征数据相关联的第二哈希值，所述结束特征数据是根据目标货物在第二位置的第二图像获取的；
    确定模块，配置为根据获取的所述第一数据与所述第三数据的比对结果和/或所述第二数据，确定所述目标货物的监管策略。
  13. 一种电子设备，包括：
    一个或多个处理器；
    存储装置，用于存储可执行指令，所述可执行指令在被所述处理器执行时，实现根据权利要求1至11任一项所述的方法。
  14. 一种计算机可读存储介质，其上存储有可执行指令，该指令被处理器执行时，实现根据权利要求1至11任一项所述的方法。
  15. 一种计算机程序产品，包括计算机程序，所述计算机程序被处理器执行时实现根据权利要求1至11中任一项所述的方法。
PCT/CN2023/110546 2022-09-01 2023-08-01 基于区块链的物流监管方法、装置、电子设备和存储介质 WO2024046008A1 (zh)

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