Vaccine management method, system and equipment based on block chain and medium

Abstract

The invention relates to the technical field of vaccine management, in particular to a vaccine management method, system and device based on a block chain and a medium, and the method comprises the steps: obtaining and preprocessing vaccine-related data; constructing a multi-role alliance chain network based on the pre-processed vaccine-related data, and storing the vaccine-related data in a layered manner; a vaccine dynamic allocation decision model is constructed based on the credible data in the multi-role alliance chain network, optimization solution is carried out by taking minimization of vaccine management cost as a target according to a preset constraint condition, and a decision result is generated; on-chain verification is carried out on the decision result based on an intelligent contract in a multi-role alliance chain network, and a multi-role collaborative decision instruction is generated; and responding to the change of the real-time environment state data, and performing dynamic optimization decision of the vaccine dynamic distribution decision model. The objective of the invention is to realize multi-party collaborative decision-making based on the block chain, reduce collaborative decision-making cost, and improve decision-making credibility and dynamic response capability.

Description

Technical Field

[0001] The present invention relates to the field of vaccine management technology, and specifically to a blockchain-based vaccine management method, system, equipment, and medium. Background Art

[0002] Vaccine management, a core component of public health and safety, involves the collaborative operations of multiple entities, including production, cold chain transportation, warehousing, vaccination, and supervision. Traditional vaccine supply management generally utilizes a centralized information management system, with regulatory agencies coordinating the supply and demand matching process between suppliers and vaccinators. Specifically, suppliers report inventory and logistics status through independent databases, vaccinators submit regional requirements through local systems, and regulatory agencies make resource allocation decisions based on manually aggregated data. Such systems rely on centralized data centers for information exchange, such as recording vaccine batch information in traditional databases, communicating demand plans through spreadsheets, and completing allocations based on pre-set static rules. However, data silos between multiple entities within a centralized architecture lead to delayed information exchange and inefficient supply and demand matching. Furthermore, the manual decision-making process lacks transparency and traceability, making it difficult to ensure potency compliance verification during vaccine circulation. Summary of the Invention

[0003] In order to achieve multi-party collaborative decision-making based on blockchain, reduce the cost of collaborative decision-making, and improve the credibility and dynamic response capabilities of decision-making, the present invention provides a vaccine management method, system, device and medium based on blockchain. The technical solutions adopted are as follows: The technical solution of the first aspect of the present invention provides a vaccine management method based on blockchain, the method comprising: Obtain vaccine-related data and perform pre-processing; Build a multi-role alliance chain network based on pre-processed vaccine-related data, and store vaccine-related data in layers; A dynamic vaccine allocation decision model is built based on trusted data in a multi-role alliance chain network. Optimization is performed based on preset constraints to minimize vaccine management costs and generate decision results. The decision results are verified on-chain based on the smart contract in the multi-role alliance chain network to generate multi-role collaborative decision instructions; Respond to changes in real-time environmental status data and make dynamic optimization decisions for the vaccine dynamic allocation decision model.

[0004] Furthermore, vaccine-related data is obtained and pre-processed, including: Collect core metadata of vaccine batches through supplier nodes, including batch number, production date, expiration date and initial potency; The vaccination node collects regional vaccine consumption and the number of people to be vaccinated to generate a dynamic demand gap; Configure vaccine potency attenuation rules and cold chain resource constraints through the supervisory node; Use IoT sensors to collect real-time temperature and humidity data of the vaccine transportation environment and mark abnormal conditions.

[0005] Furthermore, a multi-role alliance chain network is constructed based on the pre-processed vaccine-related data, and vaccine-related data is stored in layers, including: Generate an on-chain hash value for the vaccine batch core metadata, dynamic demand gap, and potency decay rules; Encrypt and store the original business data, decision algorithms, and sensor data streams in a distributed storage system to generate off-chain index identifiers; The on-chain hash value and the off-chain index identifier are associated through the on-chain smart contract to build a multi-role data channel.

[0006] Furthermore, a dynamic vaccine allocation decision model is constructed based on the trusted data in the multi-role alliance chain network, including: Locating trusted data based on the on-chain hash value and the off-chain index identifier; Define the decision variables for vaccine batch and regional allocation; Quantify vaccine loss costs by combining vaccine potency decay rules and real-time environmental data; Quantify the cost of supply-demand imbalance based on the deviation between the dynamic demand gap and the actual supply; The objective function is to minimize the weighted sum of the loss cost and the supply-demand imbalance cost.

[0007] Furthermore, an optimization solution is performed based on preset constraints with the goal of minimizing vaccine management costs, generating decision results, including: In response to vaccine batch updates, demand changes, or regulatory rule adjustments, call the off-chain solver; Inject the cold chain resource constraints and transportation environment limits; Output an allocation plan that satisfies all constraints and generates a decision proof document based on zero-knowledge proof.

[0008] Furthermore, the decision result is verified on-chain based on the smart contract in the multi-role alliance chain network, and a multi-role collaborative decision instruction is generated, including: Verify the zero-knowledge proof of the decision-making document through a smart contract; After verification, a logistics instruction containing the vaccine batch identification, target area and off-chain index identification is sent to the supplier node; Send the cold storage resource pre-occupancy amount and receipt certificate to the vaccination node.

[0009] Furthermore, in response to changes in real-time environmental status data, dynamic optimization decisions are made in the vaccine dynamic allocation decision model, including: When the abnormal state marked by temperature and humidity data lasts for more than the preset time, the corresponding vaccine batch is frozen and the decision model is triggered to be re-solved; When the change in the dynamic demand gap exceeds the preset threshold, the constraints are updated and the allocation plan is regenerated; Based on the off-chain index identifier, the original business data is traced back to verify the vaccine potency loss and distribution consistency.

[0010] The technical solution of the second aspect of the present invention provides a blockchain-based vaccine management system, which adopts the blockchain-based vaccine management method described in the technical solution of the first aspect of the present invention, and the system includes: a data acquisition module configured to acquire vaccine-related data and perform preprocessing; A consortium chain construction module is configured to build a multi-role consortium chain network based on pre-processed vaccine-related data and store vaccine-related data in layers; The decision-making module is configured to build a dynamic vaccine allocation decision model based on trusted data in the multi-role alliance chain network, optimize and solve the problem with the goal of minimizing vaccine management costs according to preset constraints, and generate decision results; An instruction generation module is configured to verify the decision result on the chain based on the smart contract in the multi-role alliance chain network and generate a multi-role collaborative decision instruction; The dynamic optimization module is configured to respond to changes in real-time environmental status data and make dynamic optimization decisions for the vaccine dynamic allocation decision model.

[0011] The technical solution of the third aspect of the present invention provides an electronic device, comprising: a processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor so that the processor can execute the steps of the blockchain-based vaccine management method described in the technical solution of the first aspect of the present invention.

[0012] The technical solution of the fourth aspect of the present invention provides a computer-readable storage medium, on which is stored a program for implementing a blockchain-based vaccine management method. The program for implementing a blockchain-based vaccine management method is executed by a processor to implement the steps of the blockchain-based vaccine management method described in the technical solution of the first aspect of the present invention.

[0013] The present invention has the following beneficial effects: The blockchain-based vaccine management method provided by the present invention realizes distributed trusted evidence storage and cross-subject real-time sharing of vaccine data by constructing a multi-role alliance chain network. Based on the hierarchical storage mechanism, it can solve the problem of data islands between multiple subjects while ensuring data privacy; then use the trusted data on the chain to build a dynamic decision-making model that integrates the characteristics of vaccine management, and generate the optimal allocation plan that takes into account timeliness constraints and supply and demand balance through optimization and solution; with the help of smart contracts, the decision results are automatically verified on the chain and collaborative instructions are generated to eliminate efficiency bottlenecks and trust risks caused by manual intervention; finally, relying on real-time environmental data to trigger dynamic re-optimization of the decision model, rapid response to transportation anomalies and sudden changes in demand. The present invention can achieve, for example, improved efficiency in collaborative decision-making among regulators, suppliers and vaccinators, and reduce collaborative costs caused by information asynchrony and manual verification; enhance the auditability of the vaccine distribution process and the credibility of potency assurance, thereby improving the agility of resource allocation in public health events. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0015] Figure 1 A flowchart of a blockchain-based vaccine management method according to one embodiment of the present invention; Figure 2 A schematic diagram of the structure of a blockchain-based vaccine management system provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0016] To further illustrate the technical means and effectiveness of the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a blockchain-based vaccine management method, system, device, and medium proposed by the present invention. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0017] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0018] The following describes in detail the specific scheme of a blockchain-based vaccine management method, system, equipment and medium provided by the present invention in conjunction with the accompanying drawings.

[0019] See also Figure 1 , which shows a flowchart of a vaccine management method based on blockchain provided by one embodiment of the present invention, the method comprising: Step S100: Acquire vaccine-related data and perform preprocessing; Step S100 specifically includes: Step S110: Vaccine batch core metadata, including batch number, production date, expiration date, and initial potency, is collected through the supplier node. Specifically, each batch of vaccine is bound to an ultra-high frequency RFID tag with a built-in unique batch identifier, which can be configured as "enterprise code-production date-batch serial number", such as "P001-20240801-001". The following static attributes can then be entered through the production execution system (MES): batch number, production date, timestamp format, batch expiration date in days, and the initial potency of the batch. After collection, a metadata fingerprint is generated through a hash algorithm. The metadata fingerprint is the pre-processed data of the subsequent on-chain hash and is temporarily stored in the local database with the original data. Step S120: Vaccine nodes collect regional vaccine consumption and the number of people to be vaccinated to generate a dynamic demand gap. Vaccination nodes, such as community health service centers and hospital vaccination sites, collect and calculate demand data in real time through the vaccination management system. The dynamic demand gap can be expressed as:

[0020] Where, For the region Dynamic demand gap; For the region Number of people waiting to be vaccinated; For the region In the Vaccine consumption in a statistical period, represents the initial moment, Indicates the current time in days; To take the maximum value function, ensure that the demand gap is non-negative; the dynamic demand gap can be configured to automatically perform calculations at 3 am every day. If the change exceeds 10% compared to the previous day, a real-time update will be triggered and pushed to the alliance chain; Step S130: Configure the vaccine potency decay rules and cold chain resource constraints through the supervisory node; the vaccine potency decay model can be expressed as:

[0021] Where, For batch In time The potency retention rate, dimensionless, initial value Corresponding to 100% titer; is the instantaneous decay rate of potency retention; represents differential; is the temperature sensitivity coefficient, with a value of 0.005 / ℃·day. When the temperature exceeds 8℃, the daily potency retention rate decreases by an additional 0.5% for every 1℃ increase in temperature; For batch In time The real-time transportation temperature is the same as the transportation temperature collected by the IoT sensor in step S140; Indicates that the attenuation is calculated only when the temperature exceeds 8°C, and the attenuation rate is 0 when the temperature is lower than or equal to 8°C; Cold chain resource constraints include: cold storage capacity constraints :area Maximum storage capacity; transportation time constraint: maximum transportation time ; Titer threshold constraint: minimum inoculatable titer retention rate .

[0022] Step S140: Use IoT sensors to collect real-time temperature and humidity data of the vaccine transportation environment and mark abnormal conditions; collect transportation temperature through the temperature and humidity sensors installed on the cold chain vehicle, and trigger the chain in real time when the continuous abnormal duration exceeds the preset threshold.

[0023] Step S200: Construct a multi-role alliance chain network based on the pre-processed vaccine-related data, and store the vaccine-related data in layers; specifically, the multi-role alliance chain network includes regulator nodes, supplier nodes and vaccination nodes. This embodiment adopts a layered evidence storage architecture, and the hash stored on the chain ensures that it cannot be tampered with. The InterPlanetary File System (IPFS) is used off-chain to store big data, and verifiable references are achieved through content identifiers (CIDs).

[0024] Step S200 specifically includes: Step S210: Generate an on-chain hash value for the core metadata of the vaccine batch, dynamic demand gap and potency decay rules; convert the key data pre-processed in step S100 into a hash value of fixed length through a hash algorithm, and store it in the blockchain to ensure that the data cannot be tampered with, while avoiding the storage of redundant information on the chain.

[0025] In some embodiments, hash values ​​are generated for three types of core data: Vaccine batch core metadata hash: generated based on the vaccine's unique batch identifier, batch number, expiration date, initial potency, and other information, consistent with the "metadata fingerprint" in step S110, used to uniquely identify the core attributes of the batch; Dynamic demand gap hash: generated by combining the vaccination area identifier, current demand gap value and calculation timestamp to ensure the timeliness of demand data. Each time the demand gap is updated, the corresponding hash value is updated synchronously; Potency decay rule hashing: based on temperature sensitivity coefficient , minimum potency threshold Regulatory rule parameters such as the PIN are generated in combination with the regulator’s digital signature to ensure that the rules cannot be tampered with.

[0026] In some embodiments, the generated hash value is written to the blockchain by calling the hash storage function of the smart contract. When the hash value is written to the blockchain, the data type, generation timestamp, and operation node address are recorded synchronously to form an unalterable on-chain record; the data type includes batch data and demand data. Step S220: Encrypt and store the original business data, decision algorithm and sensor data stream in a distributed storage system to generate an off-chain index identifier; store the original business data and sensor real-time data stream in IPFS and encrypt them, and generate a unique CID to achieve efficient positioning.

[0027] In some embodiments, the original business data stores confidential data such as the supplier's capacity plan and the vaccine party's patient privacy information, which is encrypted using the AES-256 encryption algorithm and then uploaded to the InterPlanetary File System (IPFS) to generate a unique content identifier. , as the unique index of the encrypted data off-chain; In some embodiments, the decision optimization algorithm code approved by the regulator is directly uploaded to IPFS to generate the corresponding , ensure the consistency of the algorithm version, and call the algorithm code corresponding to the CID in subsequent decision-making and solving; In some embodiments, sensor data streams, such as real-time temperature, humidity and other time series data during vaccine transportation, are encrypted and uploaded to IPFS according to time slices, and each piece of data generates a unique , supports quick query of corresponding historical data by time range.

[0028] Step S230: The on-chain hash value is associated with the off-chain index identifier through the on-chain smart contract to build a multi-role data channel. Specifically, the smart contract establishes a corresponding relationship between the on-chain hash value and the off-chain index identifier CID, achieving on-chain verifiability and off-chain traceability.

[0029] In some embodiments, the configured associated smart contract stores the correspondence between the on-chain hash and the off-chain CID through a mapping structure.

[0030] In some embodiments, the core metadata hash of a vaccine batch corresponds to its off-chain raw data The demand gap hash of a region corresponds to its demand detail data , to ensure that off-chain data can be quickly located through on-chain hashing; In some embodiments, multi-role permission control is configured as a role access control list built into the smart contract, which assigns different permissions based on the node identity (regulator, supplier, vaccinator). The regulator can query the association relationship of all data, the supplier can only query the association of batch data related to itself, and the vaccinator can only query the association of demand data in this area. In addition, the encrypted data off-chain can only be accessed by decrypting with its own private key; In some embodiments, any node can verify the integrity of off-chain data through the verification function of the smart contract. By inputting the CID corresponding to the off-chain data, the smart contract calculates the decrypted hash value of the data and compares it with the hash value stored on the chain. If they are consistent, it means that the data has not been tampered with.

[0031] Step S200 uses a layered architecture of on-chain hash evidence, off-chain encrypted storage, and smart contract association to ensure the credibility of the core vaccine data by utilizing the immutability of the blockchain, and solves the technical problems of data storage and privacy protection through distributed file systems and encryption technology; among them, multi-role permission control ensures that data can be visible on demand to avoid information leakage; the association mechanism of on-chain hash and off-chain index realizes the verifiable traceability of data, providing a reliable, secure and efficient data foundation for subsequent multi-subject collaborative decision-making, thereby avoiding data silos and trust barriers in traditional vaccine management systems.

[0032] Step S300: Construct a dynamic vaccine allocation decision model based on trusted data in the multi-role alliance chain network, perform optimization and solution based on preset constraints with the goal of minimizing vaccine management costs, and generate a decision result; Step S300 specifically includes: Step S310: Locate trusted data based on the on-chain hash value and the off-chain index identifier; In some embodiments, according to the on-chain and off-chain association system constructed in step S200, each role node obtains the trusted data required for decision-making based on its own authority: The supervisor, supplier, and vaccination nodes call the associated smart contract of step S230 and input the on-chain hash value to obtain the unique index identifier of the corresponding off-chain data; In some embodiments, a node uses its own private key to decrypt off-chain encrypted data and extract three types of core information: Vaccine batch attributes: including the quantity of vaccine in each batch , production time , remaining validity period, value per dose ,volume ; Regional attributes: including dynamic demand gaps in each vaccination area , cold storage capacity , transportation distance from the origin of each batch to the region ; Environmental data: including real-time temperature time series of each batch during transportation .

[0033] Step S311: Define the decision variables for vaccine batch and regional allocation, which can be expressed as , is a binary variable used to represent the allocation relationship between vaccine batches and vaccination areas. When the variable value is 1, it means that the corresponding batch of vaccines will be allocated to the corresponding area; when the variable value is 0, it means that the batch and the area will not be allocated. is the total number of vaccine batches, The total number of vaccination areas Step S312: quantifying vaccine loss costs by combining vaccine potency decay rules and real-time environmental data; In some embodiments, based on the potency decay rule of step S130, combined with the transportation temperature data, the loss of vaccine value caused by excessive temperature is quantified: extract the value of a batch of vaccine from the production time To the expected destination area Time Range , get the real-time temperature series within the period ; For the temperature at each time point, calculate the temperature deviation , only record the deviation value when the temperature exceeds 8℃; combined with the temperature sensitivity coefficient , the potency retention rate of the batch when it reaches the target area is calculated by integration. The initial value is 1. The longer the temperature exceeds the standard and the greater the amplitude, the lower the retention rate. The expression is:

[0034] Where, For batch Arrival Area The potency retention rate at 37°C; In some embodiments, the loss cost is the product of the total value of the vaccine batch and the potency loss ratio, that is:

[0035] Where, For batch Assign to area loss costs; For batch the number of vaccines; is the value of each vaccine dose; is the potency loss ratio; if the batch is not allocated to this area, the loss cost is 0.

[0036] Step S313: Quantify the supply-demand imbalance cost based on the deviation between the dynamic demand gap and the actual supply; in some embodiments, the management cost of shortage or surplus is reflected by penalizing the deviation between the vaccine supply and demand in the vaccination area: the actual supply in a certain area is the sum of the number of vaccine batches allocated to the area, and the supply-demand deviation is the difference between the actual supply and the dynamic demand gap in the area. The absolute value of the regional priority coefficient is introduced in this embodiment. , configured by the regulator, the core area has a higher priority coefficient. Multiplying the supply and demand deviation by the priority coefficient gives the supply and demand imbalance cost of the area. The higher the priority area, the greater the cost penalty for the same deviation, which can be expressed as:

[0037] Where, For the region the cost of supply and demand imbalance; For the region The priority coefficient of For the region Dynamic demand gap; is the total number of vaccine batches; Step S314: minimizing the weighted sum of the loss cost and the supply-demand imbalance cost is used as the objective function. The weight coefficient can be configured by the regulator according to the rules of step S130; Step S320: In response to vaccine batch updates, demand changes, or regulatory rule adjustments, call the off-chain solver; In some embodiments, smart contracts monitor three types of events in real time and automatically trigger re-optimization of the decision model when an event occurs: Vaccine batch update event: a new vaccine batch hash is uploaded to the chain in step S210; Demand change event: the regional demand gap calculated in step S120 changes by more than 10%; Regulatory rule adjustment event: the weight coefficient or regional priority coefficient in step S130 is updated.

[0038] After the event is triggered, the smart contract connects to the off-chain solver through the oracle mechanism to transmit the key data required for decision-making, including the number of batches and regions involved in the decision, the various parameters of the objective function, and the parameters of the constraint conditions.

[0039] Step S321: injecting the cold chain resource constraints and transportation environment limits; In some embodiments, the solver parses and injects four types of constraints to ensure that the generated allocation solution is executable in real-world scenarios: Single batch single region constraint: , each vaccine batch is allocated to at most one region to avoid the same batch being repeatedly allocated to multiple regions; Cold storage capacity constraints: The total volume of all vaccine batches allocated to a region must not exceed the upper limit of the cold storage capacity of that region. ; Validity period constraints: The time from the production of a vaccine batch to its arrival in the target area shall not exceed its remaining validity period. ; Transport distance constraints: The transportation distance from the vaccine batch production site to the target area shall not exceed the maximum transportation distance set by the regulator. .

[0040] Step S322: Output the allocation plan that satisfies all constraints and generate a decision proof file based on zero-knowledge proof; a mixed integer linear programming solver can be used to calculate the minimum value of the objective function within a preset time and output the optimal allocation plan .

[0041] In some embodiments, the zk-SNARKs algorithm is used to compile the objective function and constraints into a Rank-1 Constraint System (R1CS) circuit; the optimal allocation solution is input. and data, such as the number of vaccines , demand gap , generate proof , the proof ensures that: if the solution satisfies all constraints, then Can be verified; Do not disclose any private data; Compressed to a few hundred bytes for easy on-chain storage.

[0042] In some embodiments, the smart contract calls the verification function and Verification is performed, and if the verification passes, the plan will be uploaded to the chain for evidence; if the verification fails, an abnormal audit will be triggered.

[0043] Step S300 is based on the trusted data provided by the alliance chain to construct a multi-objective optimization model that integrates vaccine potency attenuation, regional supply and demand dynamics, and operating costs. It breaks through the blockchain performance bottleneck through the off-chain solver and outputs the optimal allocation plan under multi-dimensional constraints such as single batch uniqueness, cold storage capacity, validity period, and transportation distance. At the same time, it uses zero-knowledge proof to achieve privacy protection and on-chain verifiability of the decision-making process; among them, the mechanism of dynamically responding to vaccine batch updates, sudden changes in demand, and adjustments to regulatory rules can ensure that decisions are always in line with actual scenarios, effectively reducing vaccine loss rates and improving supply and demand matching efficiency.

[0044] Step S400: Verify the decision result on the chain based on the smart contract in the multi-role alliance chain network and generate a multi-role collaborative decision instruction; Step S400 specifically includes: Step S410: Verify the zero-knowledge proof of the decision-making document through a smart contract; with the help of the cryptographic properties of zero-knowledge proof, the smart contract verifies whether the allocation plan meets all constraints without accessing the original data.

[0045] In some embodiments, a decision verification smart contract is configured, and its core verification function receives two parts of input: one is the zero-knowledge proof generated in step S322 , and the second is the optimal allocation plan , that is, the specific decision results of which vaccine batches are allocated to which vaccination areas; the smart contract calls the R1CS circuit compiled by step S322 to automatically verify whether the plan meets the four core constraints: each vaccine batch is allocated to at most one area; the total volume of all vaccines allocated to a certain area does not exceed the cold storage capacity of the area. The time from vaccine production to delivery to the target area does not exceed its remaining shelf life; the transportation distance does not exceed the upper limit set by the regulator. After verification, the contract will allocate the plan , verify timestamp and proof The hash value is written into the blockchain for permanent storage; if the verification fails, an abnormal event is triggered and the regulator is notified to verify the solution process.

[0046] Step S420: After verification, a logistics instruction containing the vaccine batch identifier, target area, and off-chain index identifier is issued to the supplier node; based on the verified on-chain allocation plan, the smart contract generates a transportation instruction associated with the off-chain data to guide the supplier to accurately execute the distribution; In some embodiments, all combinations of "a certain batch allocated to a certain area" are extracted from the verified allocation plan, and the associated smart contract of step S230 is called to obtain two types of off-chain data indexes corresponding to the batch: one is the index of the IoT sensor data stream of step S140 , and the second is the index of the original business data in step S220 ; The generated logistics instructions contain the following core information: unique identification of the vaccine batch , target vaccination area j, index of temperature monitoring data , index of transportation planning data and the transportation time limit calculated based on the validity period constraints.

[0047] In some embodiments, the supplier node monitors the logistics events on the chain in real time and initiates two operations after receiving the instructions: Real-time collection of transportation temperature If the temperature exceeds the safety range of 2-8℃ and lasts for 10 minutes, the re-optimization process of step S300 is automatically triggered; the second is to call We will use the route information in the package to arrange cold chain transportation and ensure delivery within the time limit.

[0048] Step S430: Send the cold storage resource pre-occupancy amount and receipt to the vaccination node. Calculate the cold storage resource demand in the target area based on the allocation plan and generate a verifiable receipt to achieve advance planning and dynamic management of storage capacity.

[0049] In some embodiments, for each vaccination area, the total volume of all vaccine batches allocated to the area is counted to obtain the cold storage pre-occupancy volume of the area. ; The generated receipt includes the unique identifier of the vaccine batch , the target vaccination area, the pre-occupancy amount of cold storage in the area, and the batch metadata hash stored in step S210.

[0050] In some embodiments, the operations performed by the vaccination node after receiving the credential include: Verify the consistency of the batch metadata hash with the on-chain evidence to confirm that the batch is legal and valid; Verification Whether it exceeds the current remaining storage capacity. If so, a storage capacity conflict event is triggered, driving step S300 to re-optimize the allocation plan; After the vaccine arrives, upload confirmation information such as the actual receipt time and temperature, and update the inventory status record on the chain.

[0051] In summary, step S400 realizes the connection between the decision-making results from on-chain trust to off-chain execution through the verification, instruction, and feedback loop of the smart contract: the on-chain verification of zero-knowledge proof can ensure the compliance of the plan while protecting data privacy, and the association of logistics instructions with off-chain data enables suppliers to accurately execute and dynamically respond to temperature anomalies. The push of cold storage pre-occupancy and receipt certificates helps the vaccinator to plan resources in advance; this embodiment can compress the collaborative response time of multiple subjects from hours to minutes, and finally build a vaccine management system with verifiable decisions, traceable execution, and rapid response to anomalies, thereby improving the efficiency of collaborative vaccine management among multiple subjects.

[0052] Step S500: responding to changes in real-time environmental status data and making dynamic optimization decisions for the vaccine dynamic allocation decision model; Step S500 specifically includes: Step S510: When the abnormal state marked by the temperature and humidity data continues for more than a preset time, the corresponding vaccine batch is frozen and the decision model is triggered to be re-solved; through real-time monitoring of the Internet of Things and automatic response of smart contracts, rapid management and control of abnormal vaccine batches and generation of alternative solutions are achieved to avoid excessive loss of potency.

[0053] In some embodiments, IoT sensors can be configured to collect the transport temperature of vaccine batches on a minute-by-minute basis. The data is encrypted and stored in a distributed file system. The on-chain smart contract monitors temperature events in real time. When the temperature exceeds the vaccine cold chain safety range of 2-8°C and lasts for 10 minutes, it is considered abnormal. The smart contract then calls the freeze function, marking the vaccine batch as "frozen", prohibiting it from further distribution or allocation. At the same time, it records the start and end time of the abnormality, the highest and lowest temperatures, and associates the index of the temperature sensor data. As evidence.

[0054] In some embodiments, the freeze event automatically triggers the optimization model of step S300, adding a new constraint condition The batch cannot be allocated to any area; the off-chain solver loads the updated constraints, recalculates the optimal allocation plan, and generates an alternative plan , For other optional areas; and through new zero-knowledge proof Verify compliance. Once verification is passed, the smart contract issues new logistics instructions to the supplier, replacing the original batch's delivery plan.

[0055] Step S520: When the change in the dynamic demand gap exceeds the preset threshold, the constraints are updated and the allocation plan is regenerated; based on the changes in the urgent needs of the vaccination party, the optimization model constraints are dynamically adjusted to ensure that the allocation plan matches the actual demand in real time to avoid imbalance between supply and demand.

[0056] In some embodiments, the vaccinator can submit an emergency demand update for the region through a preset function, which must be accompanied by a digital signature to verify the identity; after the supervisor approves the application, the smart contract calculates the change in demand, that is, the difference between the new demand and the original demand. When the change exceeds 10% of the original demand, the constraint update process is initiated; In some embodiments, the smart contract updates the region's demand parameters from the original demand to the new demand, while verifying the rationality of the new demand. The off-chain solver loads the updated demand constraints, re-solves the objective function, and generates a new allocation plan to ensure that the total supply matches the new demand. In some embodiments, the new plan is uploaded to the chain after being verified by zero-knowledge proof, and the smart contract pushes the updated cold storage pre-occupancy capacity to the vaccination party, that is, the total volume of all vaccines allocated to the area, and notifies the supplier to adjust the distribution plan.

[0057] Step S530: Based on the off-chain index identifier, trace back to the original business data to verify the consistency of vaccine potency loss and distribution; this step realizes the penetrating verification of vaccine potency loss calculation and distribution plan through the association of on-chain and off-chain data, ensuring that the decision-making process is auditable and responsibility is traceable.

[0058] In some embodiments, any node, such as the supervisory node, uses the on-chain hash of the vaccine batch to call the associated smart contract to obtain three types of off-chain data indexes: batch original metadata index, transportation temperature curve index, and so on. , Valence decay calculation algorithm index ; Recalculate the potency retention rate of this batch based on the temperature curve , and then compare it with the potency retention rate recorded on the chain. The deviation must be controlled within the preset accuracy threshold of 5%. If the potency is lower than the minimum vaccination threshold of 80%, it is necessary to verify whether it has been marked as "scrapped" and trace the responsibility based on the temperature abnormality record; In some embodiments, the consistency between the on-chain allocation plan and the actual execution records is verified: the actual vaccine distribution area is confirmed to be consistent with the target area in the plan through the logistics receipt; the actual occupancy and pre-occupancy of the vaccination party's cold storage are checked, and the deviation must not exceed 5% of the total capacity of the cold storage to ensure accurate resource planning.

[0059] Step S500 builds a dynamic vaccine management mechanism based on real-time response to anomalies, dynamic demand adaptation, and data verification. By utilizing batch freezing and re-calculation triggered by temperature and humidity anomalies, the potency loss rate can be controlled to less than 5%. This method, based on full-link backtracking verification of off-chain indexes, achieves auditability of potency calculation and distribution execution, thereby providing an unalterable chain of evidence for accountability. The synergy of these three elements based on this method ensures that the vaccine management system can operate efficiently and compliantly despite disturbances such as environmental fluctuations and changes in demand, thereby enhancing public health emergency response capabilities and management transparency.

[0060] In summary, the blockchain-based vaccine management method provided by the present invention realizes distributed trusted evidence storage and real-time sharing of vaccine data across subjects by constructing a multi-role alliance chain network, and stores key data hash values ​​on the chain and encrypted associated original data indexes off-chain based on a layered storage architecture, thereby solving the problem of data silos between multiple parties in traditional centralized systems; the scheme constructs an optimization decision-making model that integrates the dynamic attenuation model of vaccine potency and regional supply and demand characteristics based on the trusted data on the chain, and generates an allocation plan that takes into account timeliness and economy under the constraints of cold chain resources by quantifying the vaccine loss cost and supply and demand imbalance cost caused by temperature exceeding the standard; at the same time, the zero-knowledge proof technology is used to realize the on-chain verifiability of the off-chain solution results, ensuring that the decision-making process does not leak data and meets regulatory compliance requirements; finally, based on the smart contract, the logistics instructions and resource pre-occupation mechanism are automatically triggered to realize the coordinated response of the supplier's precise distribution and the dynamic management of the vaccination party's storage capacity; by real-time monitoring of transportation environment anomalies and demand mutation events to drive dynamic re-optimization of the model, a closed-loop management mechanism is formed with trusted data evidence, scientific verification of decision-making, precise execution linkage, and rapid correction of anomalies.

[0061] See also Figure 2 , which shows a schematic diagram of the structure of a vaccine management system based on blockchain provided by one embodiment of the present invention, the system includes: a data acquisition module configured to acquire vaccine-related data and perform preprocessing; A consortium chain construction module is configured to build a multi-role consortium chain network based on pre-processed vaccine-related data and store vaccine-related data in layers; The decision-making module is configured to build a dynamic vaccine allocation decision model based on trusted data in the multi-role alliance chain network, optimize and solve the problem with the goal of minimizing vaccine management costs according to preset constraints, and generate decision results; An instruction generation module is configured to verify the decision result on the chain based on the smart contract in the multi-role alliance chain network and generate a multi-role collaborative decision instruction; The dynamic optimization module is configured to respond to changes in real-time environmental status data and make dynamic optimization decisions for the vaccine dynamic allocation decision model.

[0062] The technical solution of the third aspect of the present invention provides an electronic device, comprising: a processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor so that the processor can execute the steps of the blockchain-based vaccine management method described in the technical solution of the first aspect of the present invention.

[0063] The technical solution of the fourth aspect of the present invention provides a computer-readable storage medium, on which is stored a program for implementing a blockchain-based vaccine management method. The program for implementing a blockchain-based vaccine management method is executed by a processor to implement the steps of the blockchain-based vaccine management method described in the technical solution of the first aspect of the present invention.

[0064] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0065] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A vaccine management method based on blockchain, characterized in that: The method comprises: Obtain vaccine-related data and perform pre-processing; Build a multi-role alliance chain network based on pre-processed vaccine-related data, and store vaccine-related data in layers; Based on the trusted data in the multi-role alliance chain network, a dynamic vaccine allocation decision model is built, and the optimization solution is performed according to the preset constraints with the goal of minimizing the vaccine management cost to generate the decision result; The decision results are verified on-chain based on the smart contract in the multi-role alliance chain network to generate multi-role collaborative decision instructions; Respond to changes in real-time environmental status data and make dynamic optimization decisions for the vaccine dynamic allocation decision model.

2. The blockchain-based vaccine management method according to claim 1, characterized in that: Acquire vaccine-related data and perform pre-processing, including: Collect core metadata of vaccine batches through supplier nodes, including batch number, production date, expiration date and initial potency; The vaccination node collects regional vaccine consumption and the number of people to be vaccinated to generate a dynamic demand gap; Configure vaccine potency attenuation rules and cold chain resource constraints through the supervisory node; Use IoT sensors to collect real-time temperature and humidity data of the vaccine transportation environment and mark abnormal conditions.

3. The blockchain-based vaccine management method according to claim 2, characterized in that: A multi-role alliance chain network is built based on the pre-processed vaccine-related data, and vaccine-related data is stored in layers, including: Generate an on-chain hash value for the vaccine batch core metadata, dynamic demand gap, and potency decay rules; Encrypt and store the original business data, decision algorithms, and sensor data streams in a distributed storage system to generate off-chain index identifiers; The on-chain hash value and the off-chain index identifier are associated through the on-chain smart contract to build a multi-role data channel.

4. The blockchain-based vaccine management method according to claim 3, characterized in that: A dynamic vaccine allocation decision model is built based on trusted data in a multi-role alliance chain network, including: Locating trusted data based on the on-chain hash value and the off-chain index identifier; Define the decision variables for vaccine batch and regional allocation; Quantify vaccine loss costs by combining vaccine potency decay rules and real-time environmental data; Quantify the cost of supply-demand imbalance based on the deviation between the dynamic demand gap and the actual supply; The objective function is to minimize the weighted sum of the loss cost and the supply-demand imbalance cost.

5. The blockchain-based vaccine management method according to claim 4, characterized in that: Based on the preset constraints, the optimization solution is performed with the goal of minimizing the vaccine management cost, and the decision results are generated, including: In response to vaccine batch updates, demand changes, or regulatory rule adjustments, call the off-chain solver; Inject the cold chain resource constraints and transportation environment limits; Output an allocation plan that satisfies all constraints and generates a decision proof document based on zero-knowledge proof.

6. The blockchain-based vaccine management method according to claim 5, characterized in that: The decision results are verified on-chain based on the smart contract in the multi-role alliance chain network, and multi-role collaborative decision instructions are generated, including: Verify the zero-knowledge proof of the decision-making document through a smart contract; After verification, a logistics instruction containing the vaccine batch identification, target area and off-chain index identification is sent to the supplier node; Send the cold storage resource pre-occupancy amount and receipt certificate to the vaccination node.

7. The blockchain-based vaccine management method according to claim 6, characterized in that: Respond to changes in real-time environmental status data and make dynamic optimization decisions for the vaccine dynamic allocation decision model, including: When the abnormal state marked by temperature and humidity data lasts for more than the preset time, the corresponding vaccine batch is frozen and the decision model is triggered to be re-solved; When the change in the dynamic demand gap exceeds the preset threshold, the constraints are updated and the allocation plan is regenerated; Based on the off-chain index identifier, the original business data is traced back to verify the vaccine potency loss and distribution consistency.

8. The vaccine management system based on blockchain is characterized by: The blockchain-based vaccine management method according to any one of claims 1 to 7 is adopted, wherein the system comprises: a data acquisition module configured to acquire vaccine-related data and perform preprocessing; A consortium chain construction module is configured to build a multi-role consortium chain network based on pre-processed vaccine-related data and store vaccine-related data in layers; The decision-making module is configured to build a dynamic vaccine allocation decision model based on trusted data in the multi-role alliance chain network, optimize and solve the problem with the goal of minimizing vaccine management costs according to preset constraints, and generate decision results; An instruction generation module is configured to verify the decision result on the chain based on the smart contract in the multi-role alliance chain network and generate a multi-role collaborative decision instruction; The dynamic optimization module is configured to respond to changes in real-time environmental status data and make dynamic optimization decisions for the vaccine dynamic allocation decision model.

9. An electronic device, characterized in that: The electronic device includes: a processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor to enable the processor to perform the steps of the blockchain-based vaccine management method described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a program for implementing a blockchain-based vaccine management method, and the program for implementing a blockchain-based vaccine management method is executed by a processor to implement the steps of the blockchain-based vaccine management method described in any one of claims 1 to 7.

Images