Transparent logistics supply chain tracing management system fused with block chain technology

Abstract

The invention discloses a transparent logistics supply chain tracing management system fused with a block chain technology. The transparent logistics supply chain tracing management system comprises a data acquisition module, a block chain storage module, an intelligent contract module, a user interface module and a data analysis module, the data acquisition module is responsible for collecting real-time data of each link of a supply chain and transmitting the data to the block chain storage module; the block chain storage module uses SHA-256 and ECDSA algorithms to ensure the security and authenticity of the data; according to the method, the blockchain technology is utilized, data of all links of the supply chain is subjected to chaining storage, the data are open, transparent and non-tampering, and the credibility of the data is enhanced; through an SHA-256 Hash algorithm and an ECDSA signature algorithm, the security and integrity of the data in the transmission and storage process are ensured, and the data are prevented from being tampered or forged; and transactions and operations in the supply chain are automatically executed through the intelligent contract module according to a preset rule, so that human intervention is reduced, and the automation level and the operation efficiency of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics supply chain management, and specifically to a transparent logistics supply chain traceability management system integrating blockchain technology. Background Art

[0002] Logistics supply chain management is a complex and critical field, which involves the coordination and optimization of all links from raw material procurement to the delivery of final products to consumers. With the rapid development of global trade and logistics industry, supply chain management has become more and more complex, requiring more efficient and flexible management methods to cope with the ever-changing market environment and customer needs. Logistics supply chain management refers to the management method of product manufacturing, transportation, distribution and sales that effectively organizes suppliers, manufacturers, warehouses, distribution centers and channel merchants to minimize the cost of the entire supply chain system under the condition of meeting a certain level of customer service. Its core goal is to reduce costs and improve customer satisfaction by optimizing logistics processes and improving the efficiency and response speed of the supply chain. Logistics supply chain management includes planning The five basic contents of supply chain are planning, purchasing, manufacturing, distribution and return. These links are interrelated and together constitute a complete supply chain system. Among them, logistics activities involve the flow of goods and the transmission of information, and are the key link connecting all links in the supply chain. Information flow is an indispensable part of the logistics process. It involves the collection, processing and transmission of all data and information related to product flow, such as order processing, inventory management, and transportation arrangements. The biggest feature of the supply chain is coordination and cooperation. For example, in terms of inventory point setting, transportation batch, transportation links, supply and demand relationships, etc., intensive and collaborative considerations must be taken into account. In addition, the supply chain itself has the characteristics of information sharing. Supply chain companies usually establish computer information networks to transmit information to each other and realize the sharing of sales information, inventory information, etc.

[0003] Traditional supply chain management systems usually rely on centralized databases and manual records. This approach has problems such as data opacity, easy tampering, and difficult traceability. In addition, each link in the supply chain (such as production, transportation, warehousing, etc.) often involves multiple independent stakeholders, and information sharing and coordination are inefficient, which affects the overall efficiency and reliability of the supply chain. In order to solve these problems, blockchain technology has been introduced into supply chain management. Blockchain is a distributed ledger technology with the characteristics of decentralization, immutability, transparency and traceability, which can effectively improve the credibility and security of data.

[0004] However, the existing technology of using only blockchain technology cannot completely solve the problems in supply chain management. There are still problems such as insufficient data security, insufficient automation level and insufficient operating efficiency. Therefore, it is necessary to combine other advanced technical means to make the system achieve more reliable supply chain traceability and management. To this end, a transparent logistics supply chain traceability management system integrating blockchain technology is proposed to solve the shortcomings of the existing technology. Summary of the invention

[0005] The purpose of the present invention is to provide a transparent logistics supply chain traceability management system integrating blockchain technology to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a transparent logistics supply chain traceability management system integrating blockchain technology, comprising a data acquisition module, a blockchain storage module, a smart contract module, a user interface module and a data analysis module; The data collection module is responsible for collecting real-time data from all links of the supply chain and transmitting the data to the blockchain storage module; The blockchain storage module uses SHA-256 and ECDSA algorithms to ensure the security and authenticity of data; The smart contract module monitors data changes according to preset rules and automatically executes operations when conditions are triggered; The data analysis module conducts in-depth analysis of the collected data, identifies potential problems and provides decision support; The data acquisition module, blockchain storage module, smart contract module and data analysis module all interact with the user through the user interface module, and provide a friendly operation interface through the user interface module.

[0007] As a further solution of the present invention: the data acquisition module monitors and collects data of various links of the supply chain in real time, including raw material procurement, production progress, inventory level and transportation status; the data acquisition module includes the following working steps: Step 1: First, deploy IoT sensors and scanning devices to monitor the status of each link in the supply chain in real time; Step 2: Collect key data, including temperature, humidity, location and timestamp; Step 3: Perform preliminary processing on the collected data to filter out redundant and irrelevant information; Step 4: Finally, pass the processed data to the blockchain storage module.

[0008] As a further solution of the present invention: the blockchain storage module uses blockchain technology to ensure the immutability and authenticity of data and provide a secure and transparent data storage environment.

[0009] As a further solution of the present invention: the blockchain storage module includes the following working steps: Step 1: First, encrypt the data and use The algorithm generates a unique hash value; its calculation formula is: ,in, is the original data, is the hash value; Step 2: Sign the data by using the elliptic curve digital signature algorithm Sign the hash value; the calculation formula is: ;in is the private key, and is the signature result; Step 3: Upload the data to the blockchain and upload the signed hash value to the blockchain network; Step 4: Data verification: The blockchain network nodes verify the validity of the signature through a consensus mechanism. The calculation formula is: ,in is the public key; Step 5: Finally, record the data. Once verified, the data will be permanently recorded on the blockchain.

[0010] As a further solution of the present invention: the smart contract module automatically executes transactions and operations in the supply chain according to preset business rules, thereby improving the automation level and efficiency of the system; the smart contract module includes the following working steps: Step 1: First, set the rules and set supply chain management rules, including inventory thresholds and order processing time; Step 2: Monitor indicators. The smart contract module monitors key indicators in real time, including inventory and order status; Step 3: Condition judgment and execution. When the indicator triggers the preset condition, the smart contract automatically executes the corresponding operation. When the inventory level is lower than the preset threshold, the smart contract automatically triggers the replenishment process. Step 4: Finally, the operation feedback is performed and the operation results are fed back to the user interface module for user query and confirmation.

[0011] As a further solution of the present invention: the user interface module is used to provide users with a friendly operation interface, so that users can easily query, monitor and manage data and operations in various links of the supply chain.

[0012] As a further solution of the present invention: the user interface module includes the following working steps: Step 1: Display data, transfer and display the data on the blockchain to users, including real-time data and historical records; Step 2: Provide an operation interface, providing an intuitive user interface that enables users to easily perform various operations, including querying inventory, checking order status, and setting alerts; Step 3: Feedback mechanism, receiving user input and instructions, and passing them to the corresponding module for processing.

[0013] As a further solution of the present invention: the data analysis module uses machine learning algorithms to conduct in-depth analysis of supply chain data, discover abnormal situations and make trend forecasts, and assist in decision support.

[0014] As a further solution of the present invention: the data analysis module includes the following working steps: Step 1: First, data collation is carried out to collect and organize historical data of the supply chain to ensure the integrity and accuracy of the data; Step 2: Train the model using support vector machine The algorithm trains the model to identify abnormal patterns in the data; its calculation formula is: ;in is the Lagrange multiplier, For labels, is the kernel function; Step 3: Trend prediction: Apply the random forest algorithm for trend prediction and risk assessment; the evaluation formula is: ,in For the The prediction results of the tree, is the number of trees; Step 4: Display the analysis results to users through the user interface module to assist in decision making.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention uses blockchain technology to store data from all links of the supply chain on the chain, making the data open, transparent and tamper-proof, and enhancing the credibility of the data; through the SHA-256 hash algorithm and ECDSA signature algorithm, the security and integrity of the data during transmission and storage are ensured to prevent the data from being tampered with or forged; and through the smart contract module, transactions and operations in the supply chain are automatically executed according to preset rules, reducing human intervention and improving the automation level and operating efficiency of the system.

[0016] 2. The present invention can monitor the key indicators of each link of the supply chain in real time, and automatically perform corresponding operations when conditions are triggered, thereby improving the response speed and flexibility of the supply chain; through the support vector machine (SVM) and random forest algorithm, anomaly detection and trend prediction of supply chain data are performed to help users discover potential problems and risks and provide decision support; the automation and intelligent characteristics of the system reduce the need for manual operation and reduce labor costs. At the same time, by optimizing the supply chain process, inventory backlogs and logistics delays are reduced, further reducing operating costs.

[0017] 3. The transparent management and traceability of the system in the present invention enhance customers' trust in the supply chain, and help improve brand image and market competitiveness; the system adopts a modular design, and each module can be independently developed and maintained, which is convenient for functional expansion and upgrading according to actual needs to meet the needs of enterprises of different sizes; the system provides a comprehensive supervision mechanism, including data collection, encryption, verification, storage, analysis and feedback, to ensure the comprehensiveness and effectiveness of supply chain management. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a schematic diagram of the overall structure of a transparent logistics supply chain traceability management system that integrates blockchain technology.

[0019] Figure 2 This is a workflow diagram of a transparent logistics supply chain traceability management system that integrates blockchain technology. DETAILED DESCRIPTION

[0020] 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.

[0021] Reference Figure 1-2In an embodiment of the present invention, a transparent logistics supply chain traceability management system integrating blockchain technology includes a data acquisition module, a blockchain storage module, a smart contract module, a user interface module and a data analysis module; the data acquisition module is responsible for collecting real-time data of each link of the supply chain and transmitting the data to the blockchain storage module; the blockchain storage module uses SHA-256 and ECDSA algorithms to ensure the security and authenticity of the data; the smart contract module monitors data changes according to preset rules and automatically executes operations when conditions are triggered; the data analysis module conducts in-depth analysis of the collected data, discovers potential problems and provides decision support; the data acquisition module, the blockchain storage module, the smart contract module and the data analysis module all interact with users through the user interface module, and provide a friendly operation interface through the user interface module.

[0022] The data collection module monitors and collects data from all links of the supply chain in real time, including raw material procurement, production progress, inventory levels and transportation status; the data collection module includes the following work steps: Step 1: First, deploy IoT sensors and scanning devices to monitor the status of each link in the supply chain in real time; Step 2: Collect key data, including temperature, humidity, location and timestamp; Step 3: Perform preliminary processing on the collected data to filter out redundant and irrelevant information; Step 4: Finally, pass the processed data to the blockchain storage module.

[0023] The blockchain storage module uses blockchain technology to ensure the immutability and authenticity of data and provides a secure and transparent data storage environment; the blockchain storage module includes the following working steps: Step 1: First, encrypt the data and use The algorithm generates a unique hash value; its calculation formula is: ,in, is the original data, is the hash value; Step 2: Sign the data by using the elliptic curve digital signature algorithm Sign the hash value; the calculation formula is: ;in is the private key, and is the signature result; Step 3: Upload the data to the blockchain and upload the signed hash value to the blockchain network; Step 4: Data verification: The blockchain network nodes verify the validity of the signature through a consensus mechanism. The calculation formula is: ,in is the public key; Step 5: Finally, record the data. Once verified, the data will be permanently recorded on the blockchain.

[0024] The smart contract module automatically executes transactions and operations in the supply chain according to preset business rules, improving the automation level and efficiency of the system; the smart contract module includes the following working steps: Step 1: First, set the rules and set supply chain management rules, including inventory thresholds and order processing time; Step 2: Monitor indicators. The smart contract module monitors key indicators in real time, including inventory and order status; Step 3: Condition judgment and execution. When the indicator triggers the preset condition, the smart contract automatically executes the corresponding operation. When the inventory level is lower than the preset threshold, the smart contract automatically triggers the replenishment process. Step 4: Finally, the operation feedback is performed and the operation results are fed back to the user interface module for user query and confirmation.

[0025] The user interface module is used to provide users with a friendly operation interface, enabling users to easily query, monitor and manage data and operations in all links of the supply chain; the user interface module includes the following work steps: Step 1: Display data, transfer and display the data on the blockchain to users, including real-time data and historical records; Step 2: Provide an operation interface, providing an intuitive user interface that enables users to easily perform various operations, including querying inventory, checking order status, and setting alerts; Step 3: Feedback mechanism, receiving user input and instructions, and passing them to the corresponding module for processing.

[0026] The data analysis module uses machine learning algorithms to conduct in-depth analysis of supply chain data, discover abnormal situations and make trend forecasts to assist in decision support; the data analysis module includes the following work steps: Step 1: First, data collation is carried out to collect and organize historical data of the supply chain to ensure the integrity and accuracy of the data; Step 2: Train the model using support vector machine The algorithm trains the model to identify abnormal patterns in the data; its calculation formula is: ;in is the Lagrange multiplier, For labels, is the kernel function; Step 3: Trend prediction: Apply the random forest algorithm for trend prediction and risk assessment; the evaluation formula is: ,in For the The prediction results of the tree, is the number of trees; Step 4: Display the analysis results to users through the user interface module to assist in decision making.

[0027] Reference Figure 1-2 The working method and steps of the transparent logistics supply chain traceability management system integrating blockchain technology in the present invention are as follows: S1: First, the data acquisition module monitors the supply chain status in real time and collects key data; ① Deploy IoT sensors and scanning devices in various links of the supply chain (such as warehouses, transport vehicles, production lines, etc.) to monitor key data such as temperature, humidity, location, inventory, etc. in real time; ② Sensors and devices send the collected data to the local gateway or central server for preliminary processing; ③ The data after preliminary processing is transmitted to the data acquisition module through the network to ensure the real-time and accuracy of the data; S2: Perform SHA-256 hashing and ECDSA signature on the collected data. The algorithm generates a unique hash value to ensure the integrity and non-tamperability of the data. The calculation formula is: ,in, is the original data, is the hash value; ② Use the elliptic curve digital signature algorithm () to sign the hash value to verify the authenticity of the data. The calculation formula is ,in, is the private key, and is the signature result; S3: The signed data is uploaded to the blockchain storage module and verified through the consensus mechanism. After verification, the data is recorded on the blockchain to achieve tamper-proof storage: ① Upload the signed hash value to the blockchain network node; ② The blockchain network node verifies the validity of the signature through the consensus mechanism (such as PoW, PoS, etc.) to ensure the authenticity and integrity of the data. The calculation formula is: ,in It is the public key. ③After verification, the data is permanently recorded on the blockchain to achieve tamper-proof storage; S4: The smart contract module monitors data changes according to preset rules and automatically executes operations when conditions are triggered: ① Business rules and management strategies are preset in the smart contract module, such as inventory thresholds, order processing time, etc.; ② The smart contract module monitors key indicators in real time, such as inventory volume, order status, etc.; ③ When the indicators trigger the preset conditions, the smart contract automatically executes the corresponding operations. For example, when the inventory level is lower than the preset threshold, the smart contract automatically triggers the replenishment process; ④ The operation results are displayed to the user through the user interface module for the user to query and confirm; S5: Analyze historical data through the data analysis module, use SVM and random forest algorithms for anomaly detection and trend prediction, ① collect and organize historical data of the supply chain to ensure the integrity and accuracy of the data; ② collect and organize historical data of the supply chain to ensure the integrity and accuracy of the data; ③ use support vector machine The algorithm trains the model to identify abnormal patterns in the data, and the calculation formula is: ,in is the Lagrange multiplier, For labels, is the kernel function; ④ Apply the random forest algorithm for trend prediction and risk assessment, and the calculation formula is: ,in For the The prediction results of the tree, is the number of trees; ⑤ The analysis results are displayed to the user through the user interface module to assist in decision making; S6: The operation results are displayed to the user through the user interface module for the user to query and confirm. ① The user can query the real-time data and historical records on the blockchain through the user interface module, including logistics status, inventory level, order details, etc.; ② Provide an intuitive user interface so that users can easily perform various operations, such as setting early warnings, viewing analysis reports, adjusting smart contract rules, etc.; ③ Receive user input and instructions and pass them to the corresponding module for processing. For example, users can manually trigger certain operations or adjust preset rules and thresholds.

[0028] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A transparent logistics supply chain traceability management system integrating blockchain technology, characterized by: It includes data collection module, blockchain storage module, smart contract module, user interface module and data analysis module; The data collection module is responsible for collecting real-time data from all links of the supply chain and transmitting the data to the blockchain storage module; The blockchain storage module uses SHA-256 and ECDSA algorithms to ensure the security and authenticity of data; The smart contract module monitors data changes according to preset rules and automatically executes operations when conditions are triggered; The data analysis module conducts in-depth analysis of the collected data, identifies potential problems and provides decision support; The data acquisition module, blockchain storage module, smart contract module and data analysis module all interact with the user through the user interface module, and provide a friendly operation interface through the user interface module.

2. The transparent logistics supply chain traceability management system integrating blockchain technology according to claim 1 is characterized by: The data collection module monitors and collects data from all links of the supply chain in real time, including raw material procurement, production progress, inventory levels and transportation status; the data collection module includes the following working steps: Step 1: First, deploy IoT sensors and scanning devices to monitor the status of each link in the supply chain in real time; Step 2: Collect key data, including temperature, humidity, location and timestamp; Step 3: Perform preliminary processing on the collected data to filter out redundant and irrelevant information; Step 4: Finally, pass the processed data to the blockchain storage module.

3. The transparent logistics supply chain traceability management system integrating blockchain technology according to claim 1 is characterized by: The blockchain storage module uses blockchain technology to ensure the immutability and authenticity of data and provide a secure and transparent data storage environment.

4. The transparent logistics supply chain traceability management system integrating blockchain technology according to claim 1 is characterized by: The blockchain storage module includes the following working steps: Step 1: First, encrypt the data and use The algorithm generates a unique hash value; The calculation formula is: ,in, is the original data, is the hash value; Step 2: Sign the data by using the elliptic curve digital signature algorithm Sign the hash value; the calculation formula is: ;in is the private key, and is the signature result; Step 3: Upload the data to the blockchain and upload the signed hash value to the blockchain network; Step 4: Data verification: The blockchain network nodes verify the validity of the signature through a consensus mechanism. The calculation formula is: ,in is the public key; Step 5: Finally, record the data. Once verified, the data will be permanently recorded on the blockchain.

5. The transparent logistics supply chain traceability management system integrating blockchain technology according to claim 1 is characterized by: The smart contract module automatically executes transactions and operations in the supply chain according to preset business rules, improving the automation level and efficiency of the system; the smart contract module includes the following working steps: Step 1: First, set the rules and set supply chain management rules, including inventory thresholds and order processing time; Step 2: Monitor indicators. The smart contract module monitors key indicators in real time, including inventory and order status; Step 3: Condition judgment and execution. When the indicator triggers the preset condition, the smart contract automatically executes the corresponding operation. When the inventory level is lower than the preset threshold, the smart contract automatically triggers the replenishment process. Step 4: Finally, the operation feedback is performed and the operation results are fed back to the user interface module for user query and confirmation.

6. The transparent logistics supply chain traceability management system integrating blockchain technology according to claim 1 is characterized by: The user interface module is used to provide users with a friendly operation interface, allowing users to easily query, monitor and manage data and operations in various links of the supply chain.

7. The transparent logistics supply chain traceability management system integrating blockchain technology according to claim 1 is characterized by: The user interface module includes the following working steps: Step 1: Display data, transfer and display the data on the blockchain to users, including real-time data and historical records; Step 2: Provide an operation interface, providing an intuitive user interface that enables users to easily perform various operations, including querying inventory, checking order status, and setting alerts; Step 3: Feedback mechanism, receiving user input and instructions and passing them to the corresponding module for processing.

8. The transparent logistics supply chain traceability management system integrating blockchain technology according to claim 1 is characterized by: The data analysis module uses machine learning algorithms to conduct in-depth analysis of supply chain data, discover abnormal situations and make trend forecasts to assist in decision support.

9. The transparent logistics supply chain traceability management system integrating blockchain technology according to claim 1 is characterized by: The data analysis module includes the following working steps: Step 1: First, collect and organize the historical data of the supply chain to ensure the integrity and accuracy of the data; Step 2: Train the model using support vector machine The algorithm trains the model to identify unusual patterns in the data; its calculation formula is: ;in is the Lagrange multiplier, For labels, is the kernel function; Step 3: Trend prediction: Apply the random forest algorithm for trend prediction and risk assessment; the evaluation formula is: ,in For the The prediction results of the tree, is the number of trees; Step 4: Display the analysis results to users through the user interface module to assist in decision making.

Images