Blockchain-based vaccine management method, system, device and medium

Abstract

The present application relates to the technical field of vaccine management, in particular to a vaccine management method, system, device and medium based on a blockchain, the method comprising: acquiring and preprocessing vaccine-related data; constructing a multi-role alliance chain network based on the preprocessed vaccine-related data, and storing the vaccine-related data in layers; constructing a vaccine dynamic allocation decision model based on the trusted data in the multi-role alliance chain network, optimizing and solving according to a preset constraint condition with the goal of minimizing the vaccine management cost, and generating a decision result; verifying the decision result on the chain based on the smart contract in the multi-role alliance chain network, and generating a multi-role collaborative decision instruction; and responding to changes in real-time environmental state data and dynamically optimizing and deciding the vaccine dynamic allocation decision model. The purpose is to realize multi-party collaborative decision based on a blockchain, reduce the cost of collaborative decision, and improve the decision credibility and dynamic response capability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vaccine management, in particular to a vaccine management method, system, device and medium based on a blockchain. BACKGROUND

[0002] As a core link of public health safety, vaccine management involves multiple subjects such as production, cold chain transportation, storage, inoculation and supervision. Traditional vaccine supply management generally adopts a centralized information management system, which coordinates the supply and demand matching process of the supply side and the inoculation side by the regulatory agency. Specifically, the supply side reports inventory and logistics status through an independent database, the inoculation side submits regional demand through a local system, and the regulatory agency makes resource allocation decisions based on manually aggregated data. Such a system relies on a centralized data platform to realize information interaction, for example, recording vaccine batch information in a traditional database, transferring demand plans through a spreadsheet, and completing allocation according to pre-set static rules. However, the data silos between multiple subjects under the centralized architecture lead to lag in information interaction and low efficiency in supply and demand matching. At the same time, the manual decision-making process lacks transparency and traceability, making it difficult to ensure potency compliance verification in the vaccine supply chain. SUMMARY

[0003] In order to realize multi-party collaborative decision-making based on a blockchain, reduce the cost of collaborative decision-making, and improve the credibility and dynamic response capability of decision-making, the present application provides a vaccine management method, system, device and medium based on a blockchain, and the technical solutions adopted are as follows:

[0004] The technical solution of the first aspect of the present application provides a vaccine management method based on a blockchain, which comprises:

[0005] acquiring vaccine-related data and preprocessing it;

[0006] constructing a multi-role alliance chain network based on the preprocessed vaccine-related data, and storing the vaccine-related data in layers;

[0007] constructing a vaccine dynamic allocation decision-making model based on the trusted data in the multi-role alliance chain network, optimizing and solving it according to pre-set constraints with the goal of minimizing vaccine management cost, and generating a decision-making result;

[0008] verifying the decision-making result on the chain based on the smart contract in the multi-role alliance chain network, and generating a multi-role collaborative decision-making instruction;

[0009] responding to changes in real-time environmental state data and dynamically optimizing the decision-making of the vaccine dynamic allocation decision-making model.

[0010] Further, acquiring vaccine-related data and preprocessing it comprises:

[0011] Collecting vaccine batch core metadata including batch number, production date, expiration date and initial potency by supplier node;

[0012] Collecting regional vaccine consumption and the number of people to be vaccinated by inoculation node to generate dynamic demand gap;

[0013] Configuring vaccine potency decay rules and cold chain resource constraints by regulatory node;

[0014] Collecting real-time temperature and humidity data of vaccine transportation environment and marking abnormal state by Internet of Things sensor.

[0015] Further, based on the pre-processed vaccine related data, a multi-role alliance chain network is constructed, and the vaccine related data is stored in layers, including:

[0016] The vaccine batch core metadata, dynamic demand gap and potency decay rules are generated into on-chain hash values;

[0017] The original business data, decision algorithm and sensor data stream are encrypted and stored in a distributed storage system to generate off-chain index identifiers;

[0018] The on-chain hash values and off-chain index identifiers are associated through on-chain smart contracts to build multi-role data channels.

[0019] Further, based on the trusted data in the multi-role alliance chain network, a vaccine dynamic allocation decision model is constructed, including:

[0020] Based on the on-chain hash values and off-chain index identifiers, the trusted data is located;

[0021] Define the decision variables of vaccine batch and regional allocation;

[0022] Quantify the vaccine loss cost based on the vaccine potency decay rules and real-time environmental data;

[0023] According to the deviation between dynamic demand gap and actual supply, the supply and demand imbalance cost is quantified;

[0024] The weighted sum of the loss cost and the supply and demand imbalance cost is minimized as the objective function.

[0025] Further, according to the preset constraint conditions, the vaccine management cost is minimized as the target for optimization and solution, and the decision result is generated, including:

[0026] In response to vaccine batch update, demand change or regulatory rule adjustment events, call off-chain solver;

[0027] Inject the cold chain resource constraints and transportation environment limits;

[0028] An allocation scheme satisfying all constraints is output, and a decision proof file based on zero-knowledge proof is generated.

[0029] Further, the decision result is verified on-chain based on a smart contract in the multi-role alliance chain network, and a multi-role collaborative decision instruction is generated, including:

[0030] The zero-knowledge proof of the decision proof file is verified by the smart contract;

[0031] After verification, a logistics instruction containing the vaccine batch identifier, target area and off-chain index identifier is issued to the supplier node;

[0032] The cold storage resource pre-occupancy and the receiving voucher are sent to the inoculation node.

[0033] Further, in response to changes in real-time environmental state data, dynamic optimization decisions of the vaccine dynamic allocation decision model are made, including:

[0034] When the abnormal state marked by the temperature and humidity data lasts for more than a preset time length, the corresponding vaccine batch is frozen and the decision model is re-solved;

[0035] When the dynamic demand gap change exceeds a preset threshold, the constraint condition is updated and the allocation scheme is regenerated;

[0036] Based on the off-chain index identifier, the original business data is traced back to verify the consistency of vaccine potency loss and allocation.

[0037] The second aspect of the technical solution of the present application provides a vaccine management system based on a block chain, which adopts the vaccine management method based on a block chain of the first aspect of the technical solution of the present application, and the system comprises:

[0038] A data acquisition module configured to acquire and preprocess vaccine-related data;

[0039] An alliance chain construction module configured to construct a multi-role alliance chain network based on the preprocessed vaccine-related data, and store the vaccine-related data in layers;

[0040] A decision module configured to construct a vaccine dynamic allocation decision model based on trusted data in the multi-role alliance chain network, optimize and solve according to a preset constraint condition with the goal of minimizing vaccine management cost, and generate a decision result;

[0041] An instruction generation module configured to verify the decision result on-chain based on a smart contract in the multi-role alliance chain network, and generate a multi-role collaborative decision instruction;

[0042] A dynamic optimization module configured to respond to changes in real-time environmental state data, and make dynamic optimization decisions of the vaccine dynamic allocation decision model.

[0043] The technical solution of the third aspect of the present application provides an electronic device, comprising a processor and a memory connected in communication with 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 of the first aspect of the present application.

[0044] The technical solution of the fourth aspect of the present application provides a computer-readable storage medium having a program for implementing a blockchain-based vaccine management method stored thereon, and the program for implementing the blockchain-based vaccine management method is executed by a processor to implement the steps of the blockchain-based vaccine management method of the first aspect of the present application.

[0045] The present application has the following beneficial effects:

[0046] The blockchain-based vaccine management method provided by the present application realizes distributed and trusted recordation and real-time sharing of vaccine data among multiple subjects through the construction of a multi-role alliance chain network, and solves the problem of data silos among multiple subjects on the premise of protecting data privacy based on a hierarchical storage mechanism. Then, a dynamic decision-making model integrating vaccine management characteristics is constructed using the trusted data on the chain, and an optimal allocation scheme considering timeliness constraints and supply-demand balance is generated by optimization. The decision-making result is automatically verified on the chain by means of a smart contract, and a collaborative instruction is generated, eliminating the efficiency bottleneck and trust risk caused by manual intervention. Finally, the decision-making model is dynamically re-optimized relying on real-time environmental data, realizing rapid response to transportation abnormalities and demand mutations. The present application can improve the collaborative decision-making efficiency of, for example, regulatory parties, supply parties and vaccination parties, reduce the collaborative cost caused by asynchronous information and manual verification, enhance the auditability of the vaccine distribution process and the credibility of potency guarantee, and thus improve the agility of resource allocation in public health events. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the drawings needed in the description of the embodiments or the prior art will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0048] Figure 1 The method flowchart of the blockchain-based vaccine management method provided by an embodiment of the present application;

[0049] Figure 2 The structural schematic diagram of the blockchain-based vaccine management system provided by an embodiment of the present application. Detailed Implementation

[0050] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation methods, structures, features, and effects of a blockchain-based vaccine management method, system, device, and medium proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0051] Unless otherwise defined, 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 pertains.

[0052] The following description, in conjunction with the accompanying drawings, details a specific solution for a blockchain-based vaccine management method, system, device, and medium provided by this invention.

[0053] Please see Figure 1 The diagram illustrates a flowchart of a blockchain-based vaccine management method according to an embodiment of the present invention, the method comprising:

[0054] Step S100: Obtain vaccine-related data and perform preprocessing;

[0055] Step S100 specifically includes:

[0056] Step S110: Collect core metadata of vaccine batches through the supplier node, including batch number, production date, expiration date, and initial potency. Specifically, bind an UHF RFID tag to each batch of vaccines. The tag has a unique batch identifier built in, which can be configured as "enterprise code-production date-batch serial number", such as "P001-20240801-001". Then, the following static attributes can be entered through the Manufacturing Execution System (MES): batch number, production date, timestamp format, batch expiration date in days, and initial potency of the batch. After collection, a metadata fingerprint is generated by a hash algorithm. The metadata fingerprint is the preprocessed data of the subsequent on-chain hash and is temporarily stored in the local database along with the original data.

[0057] Step S120: Collect regional vaccine consumption and the number of people waiting to be vaccinated through vaccination nodes 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:

[0058]

[0059] In the formula, For the region Dynamic demand gap; For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region

[0060] Step S130: Configure vaccine potency decay rules and cold chain resource constraints through regulatory node; The vaccine potency decay model can be expressed as:

[0061]

[0062] In the formula, For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region For the number of people to be vaccinated in the region

[0063] Cold chain resource constraints include: cold storage capacity constraint : Maximum storage capacity in the region Transportation time limit constraint: maximum transportation time Potency threshold constraint: minimum inoculable potency retention rate .

[0064] Step S140: Collect real-time temperature and humidity data of vaccine transportation environment using Internet of Things sensors and mark abnormal state; Collect transportation temperature through temperature and humidity sensors on cold chain vehicles, and trigger real-time uploading when continuous abnormal duration exceeds the preset threshold.

[0065] 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 regulatory node, supply node and inoculation node, this embodiment adopts a hierarchical storage architecture, on-chain storage hash ensures non-tamperability, off-chain uses InterPlanetary File System (IPFS) to store big data, and realizes verifiable reference through content identifier (CID).

[0066] Step S200 specifically includes:

[0067] Step S210: generating a chain hash value for the vaccine batch core metadata, dynamic demand gap and potency decay rule; the key data pre-processed in step S100 is converted into a fixed-length hash value through a hash algorithm, and is stored in a blockchain to ensure data non-tamperability and avoid on-chain storage of redundant information.

[0068] In some embodiments, a hash value is generated for each of the three types of core data:

[0069] Vaccine batch core metadata hash: generated based on vaccine unique batch identifier, batch number, expiration date, initial potency, etc., consistent with the "metadata fingerprint" in step S110, used to uniquely identify the core attributes of the batch;

[0070] Dynamic demand gap hash: generated by combining inoculation area identifier, current demand gap value and calculation timestamp, ensuring the timeliness of demand data, and the corresponding hash value is updated synchronously each time the demand gap is updated;

[0071] Potency decay rule hash: generated based on temperature sensitivity coefficient , minimum potency threshold , etc. regulatory rule parameters, combined with regulatory digital signature to ensure the non-tamperability of the rule.

[0072] In some embodiments, the generated hash value is written to the blockchain by calling the hash storage function of the smart contract, and the data type, generation timestamp and operation node address are recorded synchronously when chaining to form a non-tamperable on-chain record; wherein the data type includes batch data and demand data;

[0073] Step S220: encrypting and storing the original business data, decision algorithm and sensor data stream to a distributed storage system to generate an off-chain index identifier; storing the original business data and real-time sensor data stream in IPFS and encrypting, while generating a unique CID to realize efficient positioning.

[0074] In some embodiments, the original business data stores the capacity plan of the supply party, the patient privacy information of the vaccination party, and other confidential data, which are encrypted by the AES-256 encryption algorithm, and then uploaded to the InterPlanetary File System (IPFS) to generate a unique content identifier , as the only index of the encrypted data off-chain;

[0075] In some embodiments, the decision optimization algorithm code that passes the review of the regulatory party is directly uploaded to the IPFS to generate a corresponding , to ensure the consistency of the algorithm version, and the algorithm code corresponding to the CID is called when solving the subsequent decision;

[0076] In some embodiments, the sensor data stream, such as real-time temperature, humidity, and other time series data during vaccine transportation, is uploaded to the IPFS after being encrypted by time slicing, and each piece of data generates a unique , supporting quick query of corresponding historical data by time range.

[0077] Step S230: associate the on-chain hash value with the off-chain index identifier through the on-chain smart contract to build a multi-role data channel. Specifically, the corresponding relationship between the on-chain hash value and the off-chain index identifier CID is established through the smart contract to realize on-chain verifiability and off-chain traceability.

[0078] In some embodiments, the associated smart contract is configured to store the corresponding relationship between the on-chain hash and the off-chain CID through a mapping structure.

[0079] In some embodiments, the hash of the core metadata of a batch of vaccines corresponds to the of the off-chain original data of the batch of vaccines, and the hash of the demand gap of a certain region corresponds to the of the demand detail data of the region, to ensure that the off-chain data can be quickly located through the on-chain hash;

[0080] In some embodiments, the multi-role permission control is configured as an access control list built into the smart contract, and different permissions are assigned based on the node identity (regulatory party, supply party, vaccination party). The regulatory party can query the association relationship of all data, the supply party can only query the batch data association related to itself, and the vaccination party can only query the demand data association of the region, and needs to decrypt the off-chain encrypted data through its own private key to access the data;

[0081] In some embodiments, any node can verify the integrity of the 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 hash value of the decrypted 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.

[0082] Step S200 uses the tamper-proof nature of the blockchain to ensure the credibility of the core data of the vaccine through a layered architecture of on-chain hash attestation, off-chain encrypted storage, and smart contract association, and solves the technical problems of data storage and privacy protection through a distributed file system and encryption technology; wherein, multi-role permission control ensures that data can be visible on demand, avoiding information leakage; the association mechanism of on-chain hash and off-chain index realizes the verifiable traceability of data, providing a credible, secure, and efficient data foundation for subsequent multi-agent collaborative decision-making, thereby avoiding data silos and trust barriers in traditional vaccine management systems.

[0083] Step S300: Based on the trusted data in the multi-role alliance chain network, a dynamic allocation decision model of the vaccine is constructed, and the decision result is generated by optimizing and solving according to the preset constraint condition with the goal of minimizing the vaccine management cost;

[0084] Step S300 specifically includes:

[0085] Step S310: Based on the on-chain hash value and the off-chain index identifier, the trusted data is located;

[0086] 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 according to its own permissions:

[0087] The regulatory party, the supplier, and the vaccination party node obtain the unique index identifier of the corresponding off-chain data by inputting the on-chain hash value through the associated smart contract of step S230;

[0088] In some embodiments, the node decrypts the off-chain encrypted data through its own private key and extracts three types of core information:

[0089] Vaccine batch attributes: including the number of vaccines in each batch , production time , remaining validity period, value per dose , volume ;

[0090] Regional attributes: including the dynamic demand gap of each vaccination region , cold storage capacity , transportation distance from the production site of each batch to the region ;

[0091] Environmental data: including the real-time temperature time series of each batch during transportation .

[0092] Step S311: Define the decision variable of the allocation of vaccine batches and regions, which can be represented as is a binary variable, used to represent the allocation relationship between the vaccine batch and the inoculation area, when the variable takes the value of 1, it means that the vaccine of the corresponding batch is allocated to the corresponding area; when the variable takes the value of 0, it means that the allocation of the batch and the area is not performed; wherein is the total number of vaccine batches, is the total number of inoculation areas

[0093] Step S312: Quantify the vaccine loss cost based on the vaccine titer decay rule and real-time environmental data;

[0094] In some embodiments, based on the titer decay rule of step S130, combined with the transportation temperature data, the vaccine value loss caused by temperature exceeding the standard is quantified: the time range from the production time of a batch of vaccines to the expected arrival time of the target area is extracted , and the real-time temperature sequence in this period is obtained ; for the temperature at each time point, the temperature deviation is calculated, and the deviation value is recorded only when the temperature exceeds 8℃; combined with the temperature sensitivity coefficient , the titer retention rate of the batch when arriving at the target area is calculated by integration, the initial value is 1, the longer and larger the temperature exceeds the standard, the lower the retention rate, and its expression is:

[0095]

[0096] In the formula, is the titer retention rate of the batch when arriving at the area ;

[0097] In some embodiments, the loss cost is the product of the total value of the batch of vaccines and the titer loss ratio, that is:

[0098]

[0099] In the formula, is the loss cost of the batch allocated to the area ; is the number of vaccines of the batch ; is the value of each dose of vaccine; is the titer loss ratio; if the batch is not allocated to the area, the loss cost is 0.

[0100] Step S313: Quantify the supply-demand imbalance cost according to the deviation between the dynamic demand gap and the actual supply amount; in some embodiments, the management cost brought by shortage or surplus is reflected by punishing the deviation between the vaccine supply and demand in the inoculation area: the actual supply amount of a certain area is the sum of the batch quantities of all vaccines allocated to the area, and the supply-demand deviation is the absolute value of the actual supply amount and the dynamic demand gap of the area In this embodiment, the area priority coefficient is introduced, which is configured by the supervisor, and the priority coefficient of the core area is higher. The supply-demand deviation is multiplied by the priority coefficient to obtain the supply-demand imbalance cost of the area. The higher the priority of the area, the greater the cost penalty corresponding to the same deviation. It can be expressed as:

[0101]

[0102] In the formula, is the supply-demand imbalance cost of the area ; is the priority coefficient of the area ; is the dynamic demand gap of the area ; and is the total number of vaccine batches Step S314: Take the weighted sum of the loss cost and the supply-demand imbalance cost as the objective function, and the weight coefficient can be configured by the supervisor through the rules in step S130; Step S320: In response to vaccine batch update, demand change or regulatory rule adjustment events, call the off-chain solver;

[0103] In some embodiments, the smart contract listens to three types of events in real time, and automatically triggers the re-optimization of the decision model when the events occur:

[0104] Vaccine batch update event: a new vaccine batch is hashed and chained in step S210;

[0105] Demand change event: the variation range of the area demand gap calculated in step S120 exceeds 10%;

[0106] Regulatory rule adjustment event: the weight coefficient or the area priority coefficient in step S130 is updated.

[0107] After the event is triggered, the smart contract connects the off-chain solver through the Oracle mechanism, and transmits the key data required for decision-making, including the batch and area quantities involved in the decision, the parameters of the objective function, and the parameters of the constraint conditions.

[0108] Step S321: Inject the cold chain resource constraint condition and the transportation environment limit value

[0109]

[0110] Step S321: Inject the cold chain resource constraint condition and the transportation environment limit value ​​

[0111] In some embodiments, the solver parses and injects four types of constraints to ensure that the generated allocation scheme is executable in a real-world scenario:

[0112] Single-batch single-region constraint: Each vaccine batch is allocated to at most one region to avoid the same batch being allocated to multiple regions;

[0113] Cold storage capacity constraint: 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 ;

[0114] Expiration date constraint: The time from production to arrival at the target region of a vaccine batch must not exceed its remaining shelf life ;

[0115] Transportation distance constraint: The transportation distance from the production site of a vaccine batch to the target region must not exceed the maximum transportation distance set by the regulatory authority .

[0116] Step S322: Output the allocation scheme 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 predetermined time, output the optimal allocation scheme .

[0117] In some embodiments, the zk-SNARKs algorithm is used to compile the objective function and the constraints into a Rank-1 Constraint System (R1CS) circuit. The optimal allocation scheme and data such as the number of vaccines , demand gap are input to generate a proof that ensures that if the scheme satisfies all constraints, it can be verified ; at the same time does not reveal any private data; compresses to a few hundred bytes for easy on-chain storage.

[0118] In some embodiments, the smart contract calls the verification function to verify and , and if the verification is successful, the scheme is stored on-chain as evidence; if the verification fails, an exception audit is triggered.

[0119] Step S300 is based on the trusted data provided by the alliance chain, constructs a multi-objective optimization model integrating vaccine potency decay, regional supply and demand dynamics, and operation cost, breaks through the performance bottleneck of the blockchain through an off-chain solver, outputs an optimal allocation scheme under the multi-dimensional constraints of single batch uniqueness, cold storage capacity, expiration date, and transportation distance, and realizes privacy protection and on-chain verifiability of the decision-making process with the help of zero-knowledge proof; wherein, the mechanism dynamically responds to vaccine batch updates, demand mutations, and regulatory rule adjustments, ensuring that the decision always fits the actual scenario, effectively reducing vaccine loss rate and improving supply and demand matching efficiency.

[0120] Step S400: verifying the decision result on the chain based on the smart contract in the multi-role alliance chain network, and generating a multi-role collaborative decision instruction;

[0121] Step S400 specifically includes:

[0122] Step S410: verifying the zero-knowledge proof of the decision proof file through the smart contract; with the cryptographic properties of zero-knowledge proof, the smart contract verifies whether the allocation scheme meets all the constraint conditions without accessing the original data.

[0123] In some embodiments, a decision verification smart contract is configured, and the core verification function of the smart contract receives two parts of input: one is the zero-knowledge proof generated in step S322 , and the other is the optimal allocation scheme , i.e. the specific decision result of which vaccine batches are allocated to which vaccination regions; the smart contract calls the R1CS circuit compiled by step S322 to automatically check whether the scheme meets the four core constraints: each vaccine batch is allocated to at most one region; the total volume of all vaccines allocated to a region does not exceed the cold storage capacity of the region ; the time for the vaccine to be transported from the production to the target region does not exceed its remaining validity period; the transportation distance does not exceed the upper limit set by the regulator . After verification, the contract writes the allocation scheme , the verification timestamp, and the hash value of the proof into the blockchain for permanent record; if the verification fails, an abnormal event is triggered to notify the regulator to check the solving process.

[0124] Step S420: after verification, logistics instructions containing vaccine batch identification, target region, and off-chain index identification are issued to the supplier node; based on the on-chain verified allocation scheme, the smart contract generates transportation instructions associated with off-chain data to guide the supplier to accurately perform distribution;

[0125] In some embodiments, all combinations of "a certain batch allocated to a certain region" are extracted from the verified allocation schemes, and the associated smart contract in step S230 is invoked to obtain two types of off-chain data indices corresponding to that batch: one is the index of the IoT sensor data stream in step S140. Secondly, the index of the original business data in step S220. The generated logistics instructions contain the following core information: a unique identifier for 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.

[0126] In some embodiments, the supplier node monitors logistics events on the chain in real time and initiates two operations upon receiving instructions: one is through... Real-time collection of transport temperature If the temperature exceeds the safe range of 2-8℃ and persists for 10 minutes, the re-optimization process in step S300 will be automatically triggered; secondly, the process will be called... The route information is used to arrange cold chain transportation and ensure delivery within the time limit.

[0127] Step S430: Send the pre-occupancy amount of cold storage resources and the receipt certificate to the inoculation node. Calculate the cold storage resource demand for the target area according to the allocation plan, generate verifiable receipt certificates, and realize advance planning and dynamic management of storage capacity.

[0128] In some embodiments, for each vaccination area, the total volume of all vaccine batches allocated to that area is counted to obtain the pre-occupancy quantity of cold storage for that area. The generated receipt includes a unique identifier for the vaccine batch. The target inoculation area, the pre-occupancy amount of cold storage in that area, and the batch metadata hash stored in step S210.

[0129] In some embodiments, the operations performed by the inoculation node after receiving the certificate include:

[0130] Verify the consistency between the batch metadata hash and the on-chain evidence to confirm the batch's legitimacy and validity;

[0131] Verification Does it exceed the current remaining storage capacity? If it does, a storage capacity conflict event is triggered, driving step S300 to re-optimize the allocation scheme.

[0132] Once the vaccines arrive, upload confirmation information such as the actual receipt time and temperature, and update the inventory status record on the blockchain.

[0133] In summary, step S400 realizes the connection of decision results from on-chain credibility to off-chain executable through the verification, instructions, and feedback loop of the smart contract: the on-chain verification of zero-knowledge proof can ensure compliance while protecting data privacy, the association of logistics instructions and off-chain data enables the supply side to accurately execute and dynamically respond to temperature abnormalities, and the push of pre-occupied capacity and receiving credentials of the cold storage helps the inoculation side to plan resources in advance; this embodiment can compress the collaborative response time of multiple subjects from hours to minutes, and ultimately build a vaccine management system with verifiable decisions, traceable executions, and rapid responses to abnormalities, thereby improving the efficiency of collaborative management of vaccines among multiple subjects.

[0134] Step S500: respond to changes in real-time environmental state data and make dynamic optimization decisions for the vaccine dynamic allocation decision model;

[0135] Step S500 specifically includes:

[0136] Step S510: when the abnormal state of the temperature and humidity data marker lasts for more than a preset time length, freeze the corresponding vaccine batch and trigger the decision model to be resolved again; through real-time monitoring of the Internet of Things and automatic response of the smart contract, rapid control and alternative scheme generation of abnormal vaccine batches are realized, and excessive loss of potency is avoided.

[0137] In some embodiments, the Internet of Things sensor can be configured to collect the transportation temperature of the vaccine batch at a minute level , and the data is stored in a distributed file system after encryption, and the on-chain smart contract listens to temperature events in real time; when the detected temperature exceeds the 2-8℃ safe range of the vaccine cold chain, and the duration reaches 10 minutes, it is determined to be abnormal. Then the smart contract calls the freeze function to mark the vaccine batch as “frozen” state, prohibit it from continuing to distribute or allocate, record the abnormal start and end time, the highest and lowest temperature, and associate the index of the temperature sensor data as evidence.

[0138] In some embodiments, the freezing event automatically triggers the optimization model of step S300, adds a new constraint that this batch cannot be allocated to any area; the off-chain solver loads the updated constraints and recalculates the optimal allocation scheme to generate an alternative scheme , for other alternative areas; and verify compliance through a new zero-knowledge proof . After verification, the smart contract issues new logistics instructions to the supply side to replace the distribution plan of the original batch.

[0139] Step S520: When the dynamic demand gap changes exceed the preset threshold, update the constraint condition and regenerate the allocation scheme; based on the change of the urgent demand of the inoculation party, dynamically adjust the constraints of the optimization model to ensure that the allocation scheme matches the actual demand in real time, avoiding imbalance between supply and demand.

[0140] In some embodiments, the inoculation party can submit an urgent demand update for the region through a preset function, with a digital signature to verify identity; after the supervisory party's audit, the smart contract calculates the demand change, i.e., the difference between the new demand and the original demand, and when the change exceeds 10% of the original demand, the constraint update process is started;

[0141] In some embodiments, the smart contract updates the demand parameter of the region from the original demand to the new demand, while verifying the reasonableness of the new demand; the off-chain solver loads the updated demand constraints and re-solves the objective function to generate a new allocation scheme, ensuring that the total supply matches the new demand;

[0142] In some embodiments, the new scheme is verified by zero-knowledge proof and then uploaded to the chain, and the smart contract pushes the updated cold storage pre-occupancy to the inoculation party, i.e., the total volume of vaccines allocated to the region, and notifies the supplier to adjust the distribution plan.

[0143] Step S530: Based on the off-chain index, the original business data is traced back to verify the consistency of vaccine potency loss and allocation; this step realizes the penetration verification of vaccine potency loss calculation and allocation scheme through on-chain and off-chain data association, ensuring that the decision-making process is fully auditable and responsibility is traceable.

[0144] In some embodiments, any node, such as the supervisory party node, can call the associated smart contract to obtain three types of off-chain data indexes by the on-chain hash of the vaccine batch: batch original metadata index, transportation temperature curve index , potency decay calculation algorithm index ; based on the temperature curve, the potency retention rate of the batch is recalculated , and then compared with the on-chain recorded potency retention rate, with a deviation within a preset accuracy threshold of 5%. If the potency is below the minimum inoculable threshold of 80%, it needs to be verified whether it has been marked as "scrap", and the responsibility is traced according to the temperature anomaly record;

[0145] In some embodiments, the consistency of the on-chain allocation scheme and the actual execution record is verified: the actual distribution area of the vaccine is confirmed to be consistent with the target area in the scheme through the logistics receipt; the actual occupancy of the inoculation party's cold storage is checked against the pre-occupancy, with a deviation of no more than 5% of the total capacity of the cold storage, ensuring accurate resource planning.

[0146] Step S500 is based on the vaccine management dynamic mechanism constructed based on abnormal real-time response, demand dynamic adaptation and data verification, and the batch freezing and re-solution triggered by abnormal temperature and humidity can control the potency loss rate within 5%; the method realizes the auditability of potency calculation and distribution execution based on the full-link backtracking verification of off-chain index, and further provides an unalterable evidence chain for responsibility tracing. The three synergies based on the method can ensure that the vaccine management system can still operate efficiently and comply with regulations under environmental fluctuations, demand changes and other disturbances, and improve the public health emergency response capability and management transparency.

[0147] In summary, the vaccine management method based on the blockchain provided by the application realizes distributed and credible record of vaccine data and real-time sharing across subjects by constructing a multi-role alliance chain network, solves the problem of data silos among multiple parties in traditional centralized systems by storing key data hash values on the chain based on a hierarchical storage architecture and encrypting and associating original data indexes off the chain, the scheme constructs an optimized decision model that integrates a vaccine potency dynamic decay model and regional supply and demand characteristics based on the trusted data on the chain, generates a distribution scheme that takes into account timeliness and economy under cold chain resource constraints by quantifying the vaccine loss cost caused by temperature exceeding the standard and the supply and demand imbalance cost, at the same time, the zero-knowledge proof technology is used to realize the on-chain verifiability of off-chain solving results, to ensure that the decision-making process does not leak data and meets the regulatory compliance requirements, finally, the logistics instructions and resource pre-occupancy mechanism are automatically triggered based on the smart contract, to realize the collaborative response of accurate distribution of suppliers and dynamic management of inoculation site capacity; through real-time monitoring of transportation environment anomalies and demand mutation event-driven model dynamic re-optimization, a closed-loop management mechanism of data credible record, scientific decision verification, accurate execution linkage and rapid anomaly correction is formed.

[0148] Please refer to Figure 2 which shows a structure schematic diagram of the vaccine management system based on the blockchain provided by an embodiment of the application, the system comprises:

[0149] The data acquisition module is configured to acquire vaccine-related data and perform preprocessing;

[0150] The alliance chain construction module is configured to construct a multi-role alliance chain network based on the preprocessed vaccine-related data, and store the vaccine-related data in layers;

[0151] The decision module is configured to construct a vaccine dynamic allocation decision model based on the trusted data in the multi-role alliance chain network, optimize and solve according to the preset constraint condition with the goal of minimizing the vaccine management cost, and generate a decision result;

[0152] The 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;

[0153] The dynamic optimization module is configured to respond to changes in real-time environmental state data and make dynamic optimization decisions for the vaccine dynamic allocation decision model.

[0154] The technical solution of the third aspect of the present application provides an electronic device, which comprises a processor and a memory connected with the processor in communication; 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 of the technical solution of the first aspect of the present application.

[0155] The technical solution of the fourth aspect of the present application provides a computer readable storage medium, which stores a program for implementing a blockchain-based vaccine management method, and the program for implementing the blockchain-based vaccine management method is executed by a processor to implement the steps of the blockchain-based vaccine management method of the technical solution of the first aspect of the present application.

[0156] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or may be advantageous.

[0157] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other, and each embodiment mainly describes the difference from other embodiments.

Claims

1. A blockchain-based vaccine management method, characterized in that, The method includes: Acquire vaccine-related data and preprocess it; A multi-role consortium blockchain network is constructed based on preprocessed vaccine-related data, and the vaccine-related data is stored in layers, including: Generate on-chain hash values ​​from the core metadata of vaccine batches, dynamic demand gaps, and potency decay rules; The original business data, decision-making algorithms, and sensor data streams are encrypted and stored in a distributed storage system, generating off-chain index identifiers. By associating the on-chain hash value with the off-chain index identifier through on-chain smart contracts, a multi-role data channel is constructed; the multi-role consortium blockchain network includes regulatory nodes, supply nodes, and inoculation nodes. A dynamic vaccine allocation decision model is constructed based on trusted data in a multi-role consortium blockchain network. The model is optimized to minimize vaccine management costs according to preset constraints, generating decision results, including: Trusted data is located 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 attrition costs by combining vaccine potency decay rules with real-time environmental data; Quantify the cost of supply-demand imbalance based on the deviation between dynamic demand gap and actual supply. The objective function is to minimize the weighted sum of the aforementioned loss costs and supply-demand imbalance costs. The decision results are verified on-chain based on smart contracts in a multi-role consortium blockchain network, generating multi-role collaborative decision-making instructions. Responding to changes in real-time environmental status data and dynamically optimizing the vaccine allocation decision-making model, including: When the abnormal state marked by temperature and humidity data continues for more than the preset time, the corresponding vaccine batch is frozen and the decision model is re-solved. When the change in dynamic demand gap exceeds a preset threshold, the constraints are updated and the allocation scheme is regenerated. Based on the off-chain index identifier, the original business data is traced back to verify the consistency between vaccine potency loss and allocation.

2. The blockchain-based vaccine management method as described in claim 1, characterized in that, Acquire and preprocess vaccine-related data, including: Collect core metadata of vaccine batches through supplier nodes, including batch number, production date, expiration date and initial potency; By collecting data on regional vaccine consumption and the number of people waiting to be vaccinated at vaccination sites, a dynamic demand gap is generated. Configure vaccine potency decay rules and cold chain resource constraints through regulatory nodes; The system uses IoT sensors to collect real-time temperature and humidity data of the vaccine transportation environment and marks abnormal conditions.

3. The blockchain-based vaccine management method as described in claim 1, characterized in that, The optimization solution is performed based on preset constraints with the objective of minimizing vaccine management costs, generating decision results, including: In response to events such as vaccine batch updates, demand changes, or regulatory rule adjustments, the off-chain solver is invoked. Inject cold chain resource constraints and transportation environment limits; Output an allocation scheme that satisfies all constraints and generate a decision proof file based on zero-knowledge proof.

4. The blockchain-based vaccine management method as described in claim 3, characterized in that, The decision results are verified on-chain based on smart contracts in a multi-role consortium blockchain network, generating multi-role collaborative decision-making instructions, including: The zero-knowledge proof of the decision proof document is verified through a smart contract; Once the verification is successful, a logistics instruction containing the vaccine batch identifier, target region, and off-chain index identifier is issued to the supplier node; Send the pre-occupancy amount of cold storage resources and receipt certificate to the inoculation node.

5. A blockchain-based vaccine management system, characterized in that, The system employs the blockchain-based vaccine management method according to any one of claims 1 to 4, wherein the system comprises: The data acquisition module is configured to acquire vaccine-related data and perform preprocessing. The consortium blockchain construction module is configured to build a multi-role consortium blockchain network based on preprocessed vaccine-related data and store the vaccine-related data in layers; The decision-making module is configured to build a dynamic vaccine allocation decision model based on trusted data in a multi-role consortium blockchain network, optimize the solution according to preset constraints with the goal of minimizing vaccine management costs, and generate decision results. The instruction generation module is configured to perform on-chain verification of the decision results based on smart contracts in a multi-role consortium blockchain network, and generate multi-role collaborative decision-making instructions. 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.

6. 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, the instructions being executed by the processor to enable the processor to perform the steps of the blockchain-based vaccine management method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program for implementing a blockchain-based vaccine management method, which is executed by a processor to implement the steps of the blockchain-based vaccine management method according to any one of claims 1 to 4.

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