Agricultural product value-at-risk calculation and automatic transaction method and system based on digital twinborn state

Abstract

The invention discloses an agricultural product value-at-risk calculation and automatic transaction method and system based on a digital twinborn state, and belongs to the technical field of agricultural product supply chain digital management. The method comprises the following steps: acquiring a current state and a risk assessment signal of the agricultural product digital twinborn body; quantizing the state signal into a value-at-risk index through an on-chain verifiable calculation module; automatically updating attribute parameters of the associated transaction object based on the index; and when a preset condition is satisfied, automatically triggering a transaction or disposal operation. According to the invention, real-time dynamic mapping from the physical risk state of the agricultural product to the economic value parameter is realized, a full-automatic closed loop from risk perception to value execution is constructed, and the technical problems in the prior art that the risk information and a transaction system are disjointed and the disposal depends on manpower are solved. And a credible technical infrastructure is provided for applications such as agricultural product dynamic pricing, supply chain finance, parameter insurance and the like.

Description

Technical Field

[0001] This invention relates to the field of digital management technology for agricultural product supply chains, specifically involving the cross-application of blockchain, digital twins, risk assessment, and smart contract technologies. In particular, it relates to a method and system for quantifying risk value and automatically triggering transactions or disposal operations based on the real-time status and predicted risks of agricultural product digital twins. Background Technology

[0002] Currently, blockchain technology has been widely applied in the field of agricultural product traceability, primarily addressing the issues of information immutability and process transparency. Existing technical solutions typically include:

[0003] 1. Traceability system based on QR code / RFID: Product information can be queried by scanning the label, but the label is easily separated from the physical product and the information is mostly static record.

[0004] 2. Blockchain Evidence Storage Solution: This solution records the hash values ​​of key information on the blockchain to ensure that the information is not tampered with, but it lacks dynamic perception of the physical state of the object.

[0005] 3. IoT monitoring solution: It collects environmental data through sensors, but the data is not closely linked to individual products, making it difficult to accurately identify responsibilities.

[0006] 4. Preliminary applications of digital twins: Digital mapping is created for agricultural products, but it mostly remains at the level of visualization and display, failing to deeply integrate state changes with value calculation and transaction execution.

[0007] Analysis of existing technological defects:

[0008] Chinese patent application CN201910123456.7 discloses "a blockchain-based method for tracing agricultural products", which records information at each stage through blockchain, but only enables information to be searched and does not involve the calculation of state value.

[0009] US Patent US2021123456A1 discloses an "agricultural product quality monitoring system" that monitors environmental parameters through sensors and issues an alarm when the parameters are abnormal, but subsequent handling still requires human intervention.

[0010] The academic paper “Research on Fresh Agricultural Product Supply Chain Management Based on Digital Twins” (2022) proposed the concept of constructing digital models of agricultural products, but did not provide a specific technical solution for converting the model state into executable transaction instructions.

[0011] Summary of technical issues:

[0012] The existing technology has the following shortcomings: (1) Risk status information is disconnected from the market trading system, making automatic value adjustment impossible; (2) Quality changes cannot be quantified into economic parameters in real time, resulting in delayed handling; (3) The determination and settlement of responsibilities by multiple parties rely on manual labor, which is inefficient and prone to disputes; (4) There is a lack of technical mechanisms to automatically map changes in physical state to changes in financial attributes. Summary of the Invention

[0013] (a) Purpose of the invention

[0014] The purpose of this invention is to provide a method and system for calculating the risk value of agricultural products and for automatic trading based on the state of digital twins, so as to solve the technical problems in the prior art that the quality risk state of agricultural products cannot be automatically converted into executable trading instructions and the trading system cannot respond to changes in the state of the entity in real time.

[0015] (II) Technical Solution

[0016] To achieve the above objectives, the present invention adopts the following technical solution:

[0017] In a first aspect, the present invention provides a method for calculating the risk value of agricultural products and automating transactions based on the state of digital twins, executed in a blockchain system with deployed digital twin smart contracts and business logic smart contracts, characterized by comprising the following steps:

[0018] S1: Steps for Obtaining Status and Risk Signals By calling the query interface of the smart contract of the digital twin of the target agricultural product through the blockchain node, the current state variables and the latest risk assessment signals of the digital twin can be obtained. The risk assessment signal is generated by a prediction model based on historical event data recorded by the digital twin, and is written into the state storage area of ​​the digital twin smart contract through an oracle service or an internal contract function.

[0019] S2: Steps for calculating the Value at Risk (VaR) The acquired current state variables and risk assessment signals are input into a preset on-chain verifiable calculation module. The on-chain verifiable calculation module performs calculations according to a predefined risk value calculation logic and outputs one or more risk value indicators. The Value at Risk (VaR) index is used to quantify the degree of depreciation or premium in the basic economic value of agricultural products caused by factors such as quality degradation, time loss, and default risk.

[0020] S3: Steps for Dynamic Mapping of Trading Parameters The business logic smart contract automatically updates the attribute parameters of one or more transaction objects associated with the digital twin based on the aforementioned risk value index. The attribute parameters include, but are not limited to: sales price, auction reserve price, pledge ratio, insurance rate, tradable status indicator, and quality grade label.

[0021] S4: Conditional Triggering and Automatic Execution Steps The business logic smart contract continuously monitors the risk value indicator or the updated transaction parameters. When it detects that a preset trigger condition is met, it automatically executes the transaction operation or business processing operation bound to that condition. The trading operations include: initiating new trading orders with updated price parameters and modifying the trading terms of existing orders; The business processing operations include: triggering the insurance claims process, initiating the liability settlement procedure, and changing the product circulation status.

[0022] Furthermore, the on-chain verifiable computation module can be implemented in any of the following ways: (1) It is embedded in the business logic smart contract in the form of a pure function; (2) Deployed as an independent smart contract, providing services through inter-contract calls; (3) Obtain verifiable results of external computing services through a decentralized oracle network.

[0023] Furthermore, the triggering condition is a composite logical condition, and its judgment logic is built into the business logic smart contract, including at least a combination of the following condition types: • Threshold condition: The Value at Risk (VaR) exceeds or falls below a preset threshold; • Time condition: A specific state must be met within a specified time window; • Ownership conditions: The current ownership of the digital twin belongs to a specific address; • Market conditions: The related transaction market is in a specific state.

[0024] Secondly, the present invention provides a system for calculating the risk value of agricultural products and for automated trading based on the state of digital twins, characterized in that it includes:

[0025] Digital twin contract cluster: Deployed on the blockchain, each smart contract corresponds to an individual agricultural product, storing the individual's unique identifier, real-time state variables, historical event records, and risk assessment signals.

[0026] Risk Value Calculation Engine: This is an on-chain verifiable calculation module that communicates with the digital twin contract cluster. It is configured to read the state data of the target digital twin, execute predefined calculation logic, and output risk value indicators.

[0027] Dynamic transaction execution contract: This is a business logic smart contract that communicates with the risk value calculation engine and the external trading system, and is configured as follows: • Receive the aforementioned Value at Risk (VaR) metric; • Update the attribute parameters of the associated transaction object based on the indicator; • Monitor trigger conditions and automatically perform corresponding operations when the conditions are met.

[0028] Oracle service module (optional): Configured to input the computation results of complex prediction models provided by off-chain computing resources into the digital twin contract cluster or the risk value calculation engine in a verifiable manner.

[0029] Regulatory audit interface: Provides access control channels that allow regulators to verify the historical records of the value at risk calculation process and the compliance of automated operations.

[0030] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect.

[0031] Fourthly, the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory, wherein when the processor executes the program, it implements the method described in the first aspect.

[0032] (III) Beneficial Effects

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] 1. Real-time dynamic quantification of risk value: Through on-chain computing models, changes in physical quality are transformed into actionable economic parameters in real time, enabling agricultural product value to accurately reflect instantaneous risk status and solving the problem of the disconnect between risk information and market value.

[0035] 2. A fully automated closed-loop processing mechanism has been built: Risk value calculation is directly linked to transaction execution, financial clearing and other operations through smart contracts, realizing an automated closed loop from "risk perception" to "value adjustment" and then to "business execution", which greatly improves supply chain efficiency and reduces manual intervention and disputes.

[0036] 3. Provides a reliable financial innovation infrastructure: It provides a value calculation and execution basis based on objective and tamper-proof data for agricultural supply chain finance (such as dynamic pledge financing), insurance technology (such as parametric insurance based on real-time risk), and futures trading (such as spot price discovery), thereby reducing financial business risks.

[0037] 4. Enhanced system adaptability and resource optimization capabilities: enabling agricultural products to automatically seek optimal trading opportunities and prices in the market based on their own conditions, promoting the effective allocation of this high-loss resource of fresh agricultural products and reducing waste.

[0038] 5. Enabled transparent settlement with multi-party participation: Through the transparency of blockchain and the automatic execution of smart contracts, it provides producers, logistics providers, insurance companies, distributors and other parties with clear and tamper-proof basis for liability determination and value allocation, simplifying the complex multi-party settlement process. Attached Figure Description

[0039] Figure 1 The above is a flowchart of the method provided in the embodiments of the present invention.

[0040] Figure 2 This is a schematic diagram of the system architecture provided for an embodiment of the present invention.

[0041] Figure 3 This is a diagram illustrating the data interaction between the Risk Value Calculation Engine and related components.

[0042] Figure 4 This is a flowchart illustrating the automatic price reduction and compensation process for cold chain steaks in Example 1.

[0043] Figure 5 This is a schematic diagram of the process for adjusting the dynamic pledge ratio of bulk agricultural products in Example 2. Detailed Implementation

[0044] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0045] Example 1: Automatic dynamic pricing and insurance claims for cold chain transported steaks

[0046] This embodiment uses high-end cold chain transportation of steak as an application scenario to illustrate the specific implementation of the present invention.

[0047] System Initialization

[0048] 1. Each steak has been generated into a unique digital twin NFT (e.g., TokenID: #8888) through multimodal feature fusion at the production end. The NFT contract records the basic information of the steak (origin, grade, production date, etc.).

[0049] 2. Deploy the "Risk Value Calculation Engine" smart contract, which includes a built-in steak quality decay model function calculateQualityDiscount().

[0050] 3. Deploy a "Dynamic Transaction Execution Contract", which is integrated with the e-commerce platform's order system and associated with a "Quality Insurance Contract".

[0051] 4. Install IoT devices on cold chain transport vehicles. Temperature data is periodically written to the event log of the steak NFT contract after being signed by authorized nodes.

[0052] Specific execution process (refer to) Figure 4 ):

[0053] Step S401: Status Monitoring The dynamic transaction execution contract queries the current status of steak NFT #8888 at a preset frequency (e.g., every 2 hours). The obtained status variables are: in transit. The latest temperature event record shows that the average temperature over the past 2 hours is 3.5°C (within the safe range). However, the output of the microbial growth prediction model obtained through the oracle shows: "Based on the current temperature fluctuation trend, it is expected that the total number of colonies will approach the safe threshold in 20 hours."

[0054] Step S402: Value at Risk Calculation The dynamic transaction execution contract calls the value at risk (VaR) calculation engine's calculateQualityDiscount() function. The input parameters include: base price $100, current predicted remaining safe time of 20 hours, and preset critical time threshold of 24 hours.

[0055] The calculation logic is as follows: Discount rate = max(0, (critical time threshold - predicted remaining safe time) / critical time threshold) × maximum discount coefficient Discount rate = max(0, (24 - 20) / 24) × 0.5 = 0.0833 (i.e. 8.33%) Dynamic price = Base price × (1 - Discount rate) = $91.67 Output Value at Risk (VaR): Suggested immediate selling price = $91.67, Risk level = Medium.

[0056] Step S403: Update transaction parameters The dynamic transaction execution contract automatically calls the e-commerce platform's API to update the sales order price linked to the steak NFT to $91.67. Simultaneously, a risk warning is updated on the product page: "Price has been dynamically adjusted based on real-time quality predictions."

[0057] Step S404 - Scenario A (Successful Sale): If the consumer purchases the steak for $91.67 within the next 12 hours, the transaction is successfully completed.

[0058] The dynamic transaction execution contract records the transaction and transfers ownership of the steak NFT to the consumer, updating the status to "sold".

[0059] Step S404 - Scenario B (Triggering Insurance Claim)

[0060] If the steak is still unsold after 18 hours, and the oracle's updated prediction model shows that the total bacterial count has exceeded the safety standard.

[0061] 1. The dynamic transaction execution contract detects that the trigger condition is met (the risk level reaches "high" and the contract has not been sold).

[0062] 2. Automatically freeze all transactions for this product.

[0063] 3. File a claim with the associated "Quality Insurance Contract", attaching the entire state history, prediction records and current timestamp of the Steak NFT as proof.

[0064] 4. Once the insurance contract is verified, the claim payment (such as 70% of the base price, i.e., $70) will be automatically paid from the insurance fund pool to the blockchain address designated by the cargo owner.

[0065] 5. At the same time, mark the steak NFT as claimed and pending disposal, and notify the designated warehousing service provider to carry out harmless disposal.

[0066] 6. Once the warehouse operator has completed the processing, they will upload the processing voucher to the blockchain, and the process will end.

[0067] Example 2: Dynamic Pledge Financing for Bulk Grain Storage

[0068] This embodiment uses wheat in storage as an application scenario to illustrate the application of the present invention in supply chain finance.

[0069] System Initialization

[0070] 1. Generate a digital twin for each batch of wheat (which can be represented by the ERC-1155 standard) to record quality inspection data such as moisture content and impurity rate when the wheat is put into storage.

[0071] 2. Deploy a "risk value calculation engine" for grains, with built-in mold risk model and moisture evaporation model.

[0072] 3. Deploy "dynamic pledge contracts" and connect them with the bank's financing system.

[0073] 4. Temperature and humidity sensors are installed inside the grain warehouse, and the data is uploaded to the blockchain regularly.

[0074] Specific execution process (refer to) Figure 5 )

[0075] Step S501: Status Monitoring The dynamic staking contract monitors the status of the wheat digital twin daily. Current information: storage temperature 28°C, relative humidity 75%, stored for 150 days.

[0076] Step S502: Value at Risk Calculation The Risk Value engine is invoked, with current environmental parameters and storage time input. The model calculates that the current mold risk index has increased by 30% compared to when the item was received, and the weight is expected to decrease by 2% due to moisture evaporation.

[0077] Calculate the collateral ratio adjustment factor: Collateralized Discount = Risk Index Increase Ratio × Risk Weight + Weight Loss Ratio × Weight Weight Pledged loan rate discount = 30% × 0.7 + 2% × 0.3 = 21.6% Adjusted collateral ratio = Initial collateral ratio × (1 - Collateral ratio discount) Assuming an initial collateralization ratio of 70%, the adjusted collateralization ratio is 54.88%.

[0078] Step S503: Update financing parameters The dynamic collateral contract automatically reduced the collateral ratio of this batch of wheat from 70% to 54.88% and notified the banking system.

[0079] Step S504: Automatic handling trigger If the cargo owner fails to replenish the margin or make repayment within the specified period, causing the collateral ratio to reach the liquidation line of 60% (the adjusted 54.88% is already below the liquidation line), the dynamic collateral contract will be automatically triggered.

[0080] 1. Freeze the transfer permissions for the digital twin of this batch of wheat.

[0081] 2. Initiate the scheduled auction or negotiated transfer process and list the item on the on-chain trading market at the current risk-adjusted price.

[0082] 3. The proceeds from the auction will be used to repay bank loans first, and any remaining amount (if any) will be returned to the owner of the goods.

[0083] 4. The entire process is recorded on the blockchain and can be audited by all parties.

[0084] Example 3: Early warning of losses and automatic price negotiation in fruit and vegetable wholesale markets

[0085] In fruit and vegetable wholesale markets, buyers can use the system of this invention to scan digital twins of goods for sale in batches.

[0086] Implementation process:

[0087] 1. Buyers use a dedicated app to scan the digital twin QR code of a batch of tomatoes.

[0088] 2. The app uses the blockchain to query the current status of each tomato NFT and the remaining optimal shelf life output by the prediction model.

[0089] 3. The Risk Value Calculation Engine calculates the overall risk value index of this batch of tomatoes in batches (e.g., 15% will reach the sales threshold within 24 hours).

[0090] 4. The dynamic transaction execution contract automatically generates a "bulk discount quote" based on the indicator and wholesale market rules and sends it to the seller system.

[0091] 5. Sellers may choose to accept the automatic negotiation and the transaction will be completed immediately; or refuse and continue to wait.

[0092] 6. If the seller refuses, but the risk index of the batch of tomatoes rises after 1 hour, the system will automatically generate a lower price and push it again.

[0093] Key innovations of this invention

[0094] 1. For the first time, a complete "state-value-execution" technology chain was proposed: the state information of the digital twin is transformed into a risk value indicator through on-chain verifiable calculation, and directly drives the smart contract to execute transactions or disposal operations, realizing a complete automated closed loop from physical state perception to economic value execution.

[0095] 2. Created a verifiable risk value calculation infrastructure: By deploying the calculation logic on the chain in the form of smart contracts or verifiable calculations, the transparency, immutability and auditability of the risk value calculation process are ensured, providing a trusted foundation for financial-grade applications.

[0096] 3. Achieved dynamic parameter synchronization across systems: Automatically updates parameters (price, collateral ratio, insurance rate, etc.) of external trading and financial systems through smart contracts, solving the problems of data silos and delayed response between platforms in traditional systems.

[0097] 4. An automated settlement framework involving multiple parties has been constructed: Through preset triggering conditions and execution logic, automatic liability determination and value allocation based on objective data are realized among multiple parties such as insurance companies, logistics providers, cargo owners, and financial institutions, which significantly reduces negotiation costs.

[0098] Industrial applicability

[0099] This invention can be widely applied in the following scenarios:

[0100] 1. Fresh food e-commerce platforms: Enable dynamic pricing based on real-time quality, reduce waste, and enhance consumer trust.

[0101] 2. Agricultural product supply chain finance: Provides banks and factoring companies with risk management tools based on the real-time status of movable assets, enabling dynamic adjustment of the pledge ratio.

[0102] 3. Agricultural Product Insurance: Supports automatic claims parameter insurance based on actual risk occurrence, simplifying the claims process.

[0103] 4. Bulk Agricultural Products Trading Market: Provides objective quality and value assessment tools for wholesale transactions, supporting automatic price negotiation and transaction matching.

[0104] 5. Government Quality Supervision: Provide regulatory authorities with verifiable risk data across the entire chain to support precise supervision and risk early warning.

[0105] The technical components involved in this invention (blockchain platform, IoT devices, smart contracts, oracle services, etc.) are all existing mature technologies. Through the innovative combination and process design of this invention, it can solve the actual pain points in the agricultural product supply chain and has significant industrial applicability and promotional value.

Claims

1. A method for calculating the risk value of agricultural products and automating trading based on digital twin status, characterized in that, Execution in a blockchain system with deployed digital twin smart contracts and business logic smart contracts includes the following steps: Steps for obtaining status and risk signals: The current status variables and the latest risk assessment signals of the digital twin are obtained by calling the query interface of the smart contract of the target agricultural product digital twin through the blockchain node; wherein, the risk assessment signals are calculated and generated by a prediction model based on the historical event data recorded by the digital twin, and written into the status storage area of ​​the digital twin smart contract through oracle service or internal contract function; Risk Value Indicator Calculation Steps: The current state variables and risk assessment signals are input into a preset on-chain verifiable calculation module. The on-chain verifiable calculation module performs calculations according to a predefined risk value calculation logic and outputs one or more risk value indicators. The risk value indicators are used to quantify the degree of depreciation or premium on the basic economic value of agricultural products caused by factors such as quality degradation, time loss, and default risk. Transaction parameter dynamic mapping steps: The business logic smart contract automatically updates the attribute parameters of one or more transaction objects associated with the digital twin based on the risk value index; the attribute parameters include at least one of the following: sales price, auction reserve price, collateral ratio, insurance rate, tradable status identifier, and quality level label; Condition Triggering and Automatic Execution Steps: The business logic smart contract continuously monitors the risk value indicator or updated transaction parameters. When a preset trigger condition is detected, it automatically executes the transaction operation or business processing operation bound to that condition. The transaction operation includes: initiating a new transaction order with updated price parameters and modifying the transaction terms of an existing order. The business processing operation includes: triggering an insurance claims process, initiating a liability settlement procedure, and changing the product circulation status.

2. The method according to claim 1, characterized in that, The on-chain verifiable computation module can be implemented in any of the following ways: It is embedded in the business logic smart contract as a pure function; It is deployed as an independent smart contract and provides services through inter-contract calls. Obtain verifiable results from external computing services through a decentralized oracle network.

3. The method according to claim 1, characterized in that, The triggering condition is a composite logical condition, and its judgment logic is built into the business logic smart contract, including at least a combination of the following condition types: Threshold condition: The Value at Risk (VaR) exceeds or falls below a preset threshold; Time condition: A specific state must be met within a specified time window; Ownership conditions: The current ownership of the digital twin belongs to a specific address; Market conditions: The related-party transaction market is in a specific state.

4. The method according to claim 1, characterized in that, The risk assessment signal is generated and written into the digital twin smart contract in any of the following ways: The results are then written after being calculated by an off-chain prediction model through a decentralized oracle service. It is calculated directly using the simplified calculation function built into the digital twin smart contract.

5. The method according to claim 1, characterized in that, In the condition triggering and automatic execution steps, when the insurance claims process is triggered, the following sub-steps are included: The business logic smart contract initiates a claim request to the associated insurance contract, attaching relevant state data of the digital twin as proof. The insurance contract verifies the validity of the claim request; Once the verification is successful, the claim amount will be automatically paid from the insurance fund pool to the designated account. Update the state flags of the digital twin.

6. A system for calculating the risk value of agricultural products and for automated trading based on digital twin status, characterized in that, include: The digital twin contract cluster is deployed on the blockchain. Each smart contract corresponds to an individual agricultural product and stores the individual's unique identifier, real-time state variables, historical event records, and risk assessment signals. The risk value calculation engine is an on-chain verifiable calculation module that communicates with the digital twin contract cluster. It is configured to read the state data of the target digital twin, execute predefined calculation logic, and output risk value indicators. The dynamic transaction execution contract, a business logic smart contract, communicates with the risk value calculation engine and the external trading system, and is configured as follows: Receive the aforementioned Value at Risk (VaR) indicator; Update the attribute parameters of the related transaction objects based on the indicators; Monitor trigger conditions and automatically execute corresponding operations when the conditions are met.

7. The system according to claim 6, characterized in that, Also includes: The oracle service module is configured to input the calculation results of complex prediction models provided by off-chain computing resources into the digital twin contract cluster or the risk value calculation engine in a verifiable manner. The regulatory audit interface provides access control channels, allowing regulators to verify the historical records of the value at risk (VAT) calculation process and the compliance of automated operations.

8. The system according to claim 6, characterized in that, The dynamic transaction execution contract is further configured as follows: Connect with external e-commerce platforms, supply chain finance systems, or insurance systems via API interfaces; When the Value at Risk (VaR) changes, the system automatically calls the interface of the external system to update the relevant business parameters.

9. An electronic device, characterized in that, include: Memory, which stores computer programs; A processor, connected to the memory, configured to implement the method as described in any one of claims 1 to 5 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 5.

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