Multi-node fusion supervision method based on block chain

Abstract

The invention discloses a block chain-based multi-node fusion supervision method, which comprises a node management module, a data recording module, a block chain data verification module and a supply chain supervision optimization module, and is characterized in that the node management module is used for managing supervision nodes in a supply chain; the data recording module is used for recording supervision data and supply chain historical processing data, the block chain data verification module is used for writing the supervision data into a block chain and then verifying and tracing the supervision data, and the supply chain supervision optimization module is used for analyzing and optimizing a supply chain. The node management module, the data recording module, the block chain data verification module and the supply chain supervision optimization module are in network connection with one another; according to the method, the operation of the supply chain is optimized, the risk and uncertainty in the supply chain are reduced, the overall efficiency and quality of the supply chain are improved, and the method has the characteristics of high supervision safety and capability of optimizing the supply chain.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain management, and in particular to a multi-node fusion supervision method based on blockchain. Background Art

[0002] There are many links in the food supply chain, including farms, processing plants, transportation, warehousing and retailers, etc. Traditional food safety supervision is often the responsibility of a single regulatory agency, but due to information asymmetry and difficulty in supervision, the supervision effect is limited.

[0003] With the rapid development of blockchain technology, its decentralized and tamper-proof features provide a new solution for food supply chain management. However, existing technical solutions still have deficiencies in data security and regulatory efficiency. Especially in terms of supply chain supervision optimization, when problems arise in the supply chain, it is impossible to provide users with visual data and supply chain cooperation decisions, making it difficult for users to accurately judge the necessity of upstream and downstream supply chain cooperation. Therefore, it is necessary to design a multi-node fusion supervision method based on blockchain that has high supervision security and can optimize the supply chain. Summary of the invention

[0004] The purpose of the present invention is to provide a multi-node fusion supervision method based on blockchain to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a multi-node fusion supervision system based on blockchain, comprising a node management module, a data recording module, a blockchain data verification module and a supply chain supervision optimization module, wherein the node management module is used to manage the supervision nodes in the supply chain, the data recording module is used to record the supervision data and the historical processing data of the supply chain, the blockchain data verification module is used to verify and trace the supervision data after writing it into the blockchain, the supply chain supervision optimization module is used to analyze and optimize the supply chain, and the node management module, the data recording module, the blockchain data verification module and the supply chain supervision optimization module are interconnected by network.

[0006] According to the above technical solution, the node management module includes a node registration submodule, an identity authentication submodule and a permission management submodule. The node registration submodule is used to register the node information of the regulatory participants, including identity information and submitted verification information. The identity authentication submodule is used to verify the authenticity and uniqueness of the node identity. The permission management submodule is used to record and access the data of the authorized nodes.

[0007] According to the above technical solution, the data recording module includes a supervision data acquisition submodule and a processing data recording submodule. The supervision data acquisition submodule is used to acquire monitoring data associated with the supervision node, and the processing data recording submodule is used to record historical data of product problem responsibility tracing processing under the supervision node.

[0008] According to the above technical solution, the blockchain data verification module includes a consensus mechanism submodule, a blockchain writing submodule, a data verification submodule and a traceability and accountability submodule. The consensus mechanism submodule is used to establish a consensus algorithm and implement a consensus mechanism for all nodes. The blockchain writing submodule is used to package the regulatory data in the form of blocks and write them into the blockchain. The data verification submodule is used to verify the authenticity and integrity of the blockchain data through a digital signature. The traceability and accountability submodule is used to track the data records of the blockchain to find the source of the problem in the supply chain when a responsibility issue occurs.

[0009] According to the above technical solution, the supply chain supervision optimization module includes a standard setting submodule, a visualization analysis submodule, a factor control submodule, a value matching submodule and an adjustment submodule. The standard setting submodule is used to formulate and analyze responsibility standardization criteria for supply chain source issues. The visualization analysis submodule is used to construct a visualization image based on the responsibility standardization criteria formulated by the standard setting submodule. The factor control submodule is used to obtain external factors that cause responsibility and make macro adjustments to the analysis results. The value matching submodule is used to analyze and match the value matching degree between the currently regulated supply chains. The adjustment submodule is used to adjust the upstream and downstream supply chains.

[0010] A multi-node fusion supervision method based on blockchain, the multi-node fusion supervision method comprising the following steps:

[0011] Step S1: Building a blockchain platform for supply chain management;

[0012] Step S2: On the blockchain platform, the regulatory participant registers the node and submits relevant identity information and public key;

[0013] Step S3: At each link of the supply chain, the supervision node records the relevant supervision data;

[0014] Step S4: After the regulatory data is recorded, the system establishes a consensus algorithm, and each node reaches a consensus through the consensus mechanism, and writes the regulatory data into the blockchain in the form of blocks;

[0015] Step S5: Verify blockchain data and trace the responsibility when product problems occur;

[0016] Step S6: After tracing and identifying the responsibility for product problems in the supply chain, start optimizing and adjusting the supply chain.

[0017] According to the above technical solution, step S3 also includes recording the historical processing data of each regulatory node in the supply chain. The specific recording method is: after the supply chain and its regulatory nodes are generated, a new sub-block is generated for each regulatory node respectively. The sub-block is used to store the recorded historical data of traceability processing when product problem responsibility occurs. Each regulatory node in each link of the supply chain corresponds to a sub-block.

[0018] According to the above technical solution, step S6 further includes the following steps:

[0019] Step S61: When the problem is traced back to the source of the supply chain, the responsibility of the supervisory node of the link that bears the responsibility for the current problem is determined;

[0020] Step S62: After the responsibility is determined, a visual data chart is created according to the established responsibility standards to visualize the responsibility of the problem links in the supply chain and quickly obtain the responsibility of the supply chain problems;

[0021] Step S63: further obtain external factors that may cause the problem, and then make a floating adjustment to the analyzed responsibility value up or down, wherein the first-level adjustment is 5% up or down based on the original analyzed value. The external factors include: the identification, prevention and response capabilities of malicious and intentional acts;

[0022] Step S64: Obtain the historical data stored in the sub-block corresponding to the supervision node of the supply chain link that bears the responsibility, and re-match the value of the supply chain link that bears the problem responsibility in combination with the historical responsibility data;

[0023] Step S65: When the value matching degree is lower than the lower limit of the termination of cooperation, the judgment criteria are output, and after the value is output, the value is used as proof of termination of cooperation, and then the cooperative supply chain is re-searched. When the new supply chain replacement link is confirmed, the new supply chain link is connected to the system through the adjustment sub-module.

[0024] According to the above technical solution, step S61 further includes:

[0025] Step S611: First, formulate problem responsibility severity analysis data, including three analysis dimensions: casualty data q, environmental damage level w, and economic loss amount e. The casualty data q is based on the hospital's light injury level as the benchmark standard, while when serious injuries and deaths occur, αq and βq are corresponding according to the preset weight standard;

[0026] Step S612: Then formulate a basic responsibility unit, the corresponding responsibility size of the basic responsibility unit is equal to the size of the problem responsibility required for the initial penalty and accountability, and the basic responsibility unit is converted with the three analysis dimensions of casualty data q, environmental damage level w, and economic loss amount e, respectively. The conversion formula is b=γq=δw=εe, where b is the formulated standard responsibility value; γ is the conversion coefficient between casualty data q and standard responsibility value b; δ is the conversion coefficient between environmental damage level w and standard responsibility value b; ε is the conversion coefficient between economic loss amount e and standard responsibility value b;

[0027] Step S613: Then obtain the responsibility data q, w, e corresponding to the current problem, and convert the responsibility data corresponding to the current problem into the current problem responsibility value

[0028] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention, through a multi-node fusion supervision method based on blockchain, can realize the decentralization and multi-party participation of supply chain management, reduce the risk of information asymmetry and single point failure, and improve the credibility and reliability of supply chain management. The method also has the advantages of information transparency, data security and efficiency improvement, which helps to promote innovation and improvement of supply chain management. In addition, by recording responsibility handling matters, formulating unified qualitative standards for responsibility and matching value requirements between supply chains, it further realizes the role of digital and visual verification of the necessity of supply chain cooperation when problems occur in the supply chain, and effectively helps users provide objective development decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0030] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] See also Figure 1The present invention provides a technical solution: a multi-node fusion supervision system based on blockchain, including a node management module, a data recording module, a blockchain data verification module and a supply chain supervision optimization module. The node management module is used to manage the supervision nodes in the supply chain, the data recording module is used to record the supervision data and the historical processing data of the supply chain, the blockchain data verification module is used to verify and trace the supervision data after writing it into the blockchain, the supply chain supervision optimization module is used to analyze and optimize the supply chain, and the node management module, the data recording module, the blockchain data verification module and the supply chain supervision optimization module are connected to each other through a network; by introducing blockchain technology, information sharing, data security and supervision efficiency of supply chain management can be achieved, which is helpful to optimize the operation of the supply chain, reduce the risks and uncertainties in the supply chain, and improve the overall efficiency and quality of the supply chain.

[0033] The node management module includes a node registration submodule, an identity authentication submodule and a permission management submodule. The node registration submodule is used to register the node information of the regulatory participants, including identity information and submitted verification information. The identity authentication submodule is used to verify the authenticity and uniqueness of the node identity. The permission management submodule is used to record and access the data of the authorized nodes.

[0034] The data recording module includes a supervision data acquisition submodule and a processing data recording submodule. The supervision data acquisition submodule is used to obtain monitoring data associated with the supervision node, and the processing data recording submodule is used to record historical data of product problem responsibility tracing processing under the supervision node.

[0035] The blockchain data verification module includes a consensus mechanism submodule, a blockchain writing submodule, a data verification submodule, and a traceability and accountability submodule. The consensus mechanism submodule is used to establish a consensus algorithm and implement a consensus mechanism for all nodes. The blockchain writing submodule is used to package regulatory data in the form of blocks and write them into the blockchain. The data verification submodule is used to verify the authenticity and integrity of blockchain data through digital signatures. The traceability and accountability submodule is used to track blockchain data records to find the source of problems in the supply chain when liability issues occur.

[0036] The supply chain supervision optimization module includes a standard-setting submodule, a visualization analysis submodule, a factor control submodule, a value matching submodule and an adjustment submodule. The standard-setting submodule is used to formulate and analyze responsibility standardization criteria for supply chain source issues. The visualization analysis submodule is used to construct a visualization image based on the responsibility standardization criteria formulated by the standard-setting submodule. The factor control submodule is used to obtain external factors that cause responsibility and make macro adjustments to the analysis results. The value matching submodule is used to analyze and match the value matching degree between the current regulated supply chains. The adjustment submodule is used to adjust the upstream and downstream supply chains.

[0037] A multi-node fusion supervision method based on blockchain, the multi-node fusion supervision method comprises the following steps:

[0038] Step S1: Build a blockchain platform for supply chain management; the platform has functions such as node registration, identity authentication, data recording and consensus achievement;

[0039] Step S2: On the blockchain platform, the regulatory participant registers the node and submits relevant identity information and public key; node registration requires identity verification to ensure the authenticity and uniqueness of the node; identity verification can be performed through digital certificates, encryption technology, and digital signatures;

[0040] Step S3: At each link of the supply chain, the supervision node records the relevant supervision data; the supervision data can be obtained through sensors, monitoring equipment and manual records to ensure the accuracy and completeness of the data.

[0041] Step S4: After the regulatory data is recorded, the system establishes a consensus algorithm, and each node reaches a consensus through the consensus mechanism, and writes the regulatory data into the blockchain in the form of blocks; once a consensus is reached, the regulatory data will be written into the blockchain to form a new block;

[0042] Step S5: Verify blockchain data and trace the responsibility when product problems occur; any node can achieve real-time monitoring and traceability through blockchain data, timely discover problems in the supply chain and take corresponding measures; at the same time, regulators can use the immutability of blockchain to protect the rights and interests of consumers and the security of the supply chain;

[0043] Step S6: After tracing and identifying the responsibility for product problems in the supply chain, start optimizing and adjusting the supply chain.

[0044] Step S3 also includes recording the historical processing data of each regulatory node in the supply chain. The specific recording method is: after the supply chain and its regulatory nodes are generated, a new sub-block is generated for each regulatory node. The sub-block is used to store the recorded historical data of traceability processing when product problem responsibilities occur. Each regulatory node in each link of the supply chain corresponds to a sub-block.

[0045] Step S6 further comprises the following steps:

[0046] Step S61: When the problem is traced back to the source of the supply chain, the responsibility of the supervisory node of the link that bears the responsibility for the current problem is determined;

[0047] Step S62: After the responsibility is determined, a visual data chart is created according to the established responsibility standards to visualize the responsibility of the problem links in the supply chain and quickly obtain the responsibility of the supply chain problems;

[0048] Step S63: further obtain external factors that may cause the problem, and then make a floating adjustment to the analyzed responsibility value up or down, wherein the first-level adjustment is 5% up or down based on the original analyzed value. The external factors include: the identification, prevention and response capabilities of malicious and intentional acts;

[0049] Step S64: Obtain the historical data stored in the corresponding sub-block of the supervision node of the supply chain link that bears the responsibility, and re-match the value of the supply chain link that bears the problem responsibility in combination with the historical responsibility data; the matching method is: when the supply chain cooperates, an initial matching value of 100 is assigned, and after the current problem responsibility and the historical problem responsibility are counted, the matching degree deduction value is obtained by weighting with the system fixed conversion system K, and the current value matching degree is obtained by subtracting the value from 100;

[0050] Step S65: When the value matching degree is lower than the lower limit of the termination of cooperation, the judgment standard is output, and after the value is output, the value is used as the proof of termination of cooperation, and then the cooperative supply chain is re-searched. When the new supply chain replacement link is confirmed, the new supply chain link is connected to the system by adjusting the sub-module; and then after quickly tracing the responsibility, by recording the responsibility handling matters, a unified qualitative standard of responsibility and the matching value requirements between the supply chains are formulated, which realizes the role of digital and visual verification of the necessity of supply chain cooperation when problems arise in the supply chain, and effectively helps users provide objective development decisions.

[0051] Step S61 further includes:

[0052] Step S611: First, formulate problem responsibility severity analysis data, including three analysis dimensions: casualty data q, environmental damage level w, and economic loss amount e. The casualty data q is based on the hospital's light injury level as the benchmark standard, while when serious injuries and deaths occur, αq and βq are corresponding according to the preset weight standard;

[0053] Step S612: Then formulate a basic responsibility unit, the corresponding responsibility size of the basic responsibility unit is equal to the size of the problem responsibility required for the initial penalty and accountability, and the basic responsibility unit is converted with the three analysis dimensions of casualty data q, environmental damage level w, and economic loss amount e, respectively. The conversion formula is b=γq=δw=εe, where b is the formulated standard responsibility value; γ is the conversion coefficient between casualty data q and standard responsibility value b; δ is the conversion coefficient between environmental damage level w and standard responsibility value b; ε is the conversion coefficient between economic loss amount e and standard responsibility value b;

[0054] Step S613: Then obtain the responsibility data q, w, e corresponding to the current problem, and convert the responsibility data corresponding to the current problem into the current problem responsibility value

[0055] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0056] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A multi-node fusion supervision system based on blockchain, characterized by: The multi-node fusion supervision system includes a node management module, a data recording module, a blockchain data verification module and a supply chain supervision optimization module. The node management module is used to manage the supervision nodes in the supply chain, the data recording module is used to record the supervision data and the historical processing data of the supply chain, the blockchain data verification module is used to verify and trace the supervision data after writing it into the blockchain, and the supply chain supervision optimization module is used to analyze and optimize the supply chain. The node management module, data recording module, blockchain data verification module and supply chain supervision optimization module are interconnected through a network.

2. According to claim 1, a multi-node fusion supervision system based on blockchain is characterized in that: The node management module includes a node registration submodule, an identity authentication submodule and a permission management submodule. The node registration submodule is used to register the node information of the regulatory participants, including identity information and submitted verification information. The identity authentication submodule is used to verify the authenticity and uniqueness of the node identity. The permission management submodule is used to record and access the data of the authorized nodes.

3. According to claim 2, a multi-node fusion supervision system based on blockchain is characterized in that: The data recording module includes a supervision data acquisition submodule and a processing data recording submodule. The supervision data acquisition submodule is used to acquire monitoring data associated with the supervision node, and the processing data recording submodule is used to record historical data of product problem responsibility tracing processing under the supervision node.

4. According to claim 3, a multi-node fusion supervision system based on blockchain is characterized in that: The blockchain data verification module includes a consensus mechanism submodule, a blockchain writing submodule, a data verification submodule and a traceability and accountability submodule. The consensus mechanism submodule is used to establish a consensus algorithm and implement a consensus mechanism for all nodes. The blockchain writing submodule is used to package the regulatory data in the form of blocks and write them into the blockchain. The data verification submodule is used to verify the authenticity and integrity of the blockchain data through a digital signature. The traceability and accountability submodule is used to track the data records of the blockchain to find the source of the problem in the supply chain when a responsibility issue occurs.

5. According to claim 4, a multi-node fusion supervision system based on blockchain is characterized in that: The supply chain supervision optimization module includes a standard-setting submodule, a visualization analysis submodule, a factor control submodule, a value matching submodule and an adjustment submodule. The standard-setting submodule is used to formulate and analyze responsibility standardization criteria for supply chain source issues. The visualization analysis submodule is used to construct a visualization image based on the responsibility standardization criteria formulated by the standard-setting submodule. The factor control submodule is used to obtain external factors that cause responsibility and make macro adjustments to the analysis results. The value matching submodule is used to analyze and match the value matching degree between the currently regulated supply chains. The adjustment submodule is used to adjust the upstream and downstream supply chains.

6. A multi-node fusion supervision method based on blockchain, characterized by: The multi-node fusion supervision method comprises the following steps: Step S1: Building a blockchain platform for supply chain management; Step S2: On the blockchain platform, the regulatory participant registers the node and submits relevant identity information and public key; Step S3: At each link of the supply chain, the supervision node records the relevant supervision data; Step S4: After the regulatory data is recorded, the system establishes a consensus algorithm, and each node reaches a consensus through the consensus mechanism, and writes the regulatory data into the blockchain in the form of blocks; Step S5: Verify blockchain data and trace the responsibility when product problems occur; Step S6: After tracing and identifying the responsibility for product problems in the supply chain, start optimizing and adjusting the supply chain.

7. A multi-node fusion supervision method based on blockchain according to claim 6, characterized in that: The step S3 also includes recording the historical processing data of each regulatory node in the supply chain. The specific recording method is: after the supply chain and its regulatory nodes are generated, a new sub-block is generated for each regulatory node. The sub-block is used to store the recorded historical data of traceability processing when product problem responsibility occurs. Each regulatory node in each link of the supply chain corresponds to a sub-block.

8. According to claim 7, a multi-node fusion supervision method based on blockchain is characterized in that: The step S6 further comprises the following steps: Step S61: When the problem is traced back to the source of the supply chain, the responsibility of the supervisory node of the link that bears the responsibility for the current problem is determined; Step S62: After the responsibility is determined, a visual data chart is created according to the established responsibility standards to visualize the responsibility of the problem links in the supply chain and quickly obtain the responsibility of the supply chain problems; Step S63: further obtain external factors that may cause the problem, and then make a floating adjustment to the analyzed responsibility value up or down, wherein the first-level adjustment is 5% up or down based on the original analyzed value. The external factors include: the identification, prevention and response capabilities of malicious and intentional acts; Step S64: Obtain the historical data stored in the sub-block corresponding to the supervision node of the supply chain link that bears the responsibility, and re-match the value of the supply chain link that bears the problem responsibility in combination with the historical responsibility data; Step S65: When the value matching degree is lower than the lower limit of the termination of cooperation, the judgment criteria are output, and after the value is output, the value is used as proof of termination of cooperation, and then the cooperative supply chain is re-searched. When the new supply chain replacement link is confirmed, the new supply chain link is connected to the system through the adjustment sub-module.

9. A multi-node fusion supervision method based on blockchain according to claim 8, characterized in that: The step S61 further comprises: Step S611: First, formulate problem responsibility severity analysis data, including three analysis dimensions: casualty data q, environmental damage level w, and economic loss amount e. The casualty data q is based on the hospital's light injury level as the benchmark standard, while when serious injuries and deaths occur, aq and βq are corresponding according to the preset weight standard; Step S612: Then formulate a basic responsibility unit, the corresponding responsibility size of the basic responsibility unit is equal to the size of the problem responsibility required for the initial penalty and accountability, and the basic responsibility unit is converted with the three analysis dimensions of casualty data q, environmental damage level w, and economic loss amount e, respectively. The conversion formula is b=γq=δw=εe, where b is the formulated standard responsibility value; γ is the conversion coefficient between casualty data q and standard responsibility value b; δ is the conversion coefficient between environmental damage level w and standard responsibility value b; ε is the conversion coefficient between economic loss amount e and standard responsibility value b; Step S613: Then obtain the responsibility data q, w, e corresponding to the current problem, and convert the responsibility data corresponding to the current problem into the current problem responsibility value

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