A farm-to-retail transaction system

Abstract

The application discloses a transaction system from a farm to a sales terminal, relates to the technical field of agricultural product supply chain management and electronic commerce, and comprises a breeding end data acquisition unit which is configured to collect and upload breeding whole-process data including at least individual animal identity, growth environment parameters, feed input information, disease prevention records and weight monitoring data in the farm in real time. The application realizes that the whole-chain data is unforgeable from the breeding source to the sales terminal by uploading the breeding whole-process data collected by the Internet of Things to the block chain for trusted storage. The transaction efficiency is improved and the performance risk is reduced by automatically executing transaction matching, fund transfer and logistics triggering through the smart contract. The product transportation quality is ensured and the transparent traceability experience is provided for consumers by integrating cold chain monitoring data and terminal traceability query.

Description

Technical Field

[0001] This invention relates to the fields of agricultural product supply chain management and e-commerce technology, specifically a transaction system from farm to sales terminal. Background Technology

[0002] With consumers' increasing demands for food safety and quality traceability, the traditional livestock and aquaculture industry faces severe challenges in supply chain management from production to consumption. Current technologies for transactions from farms to sales terminals (such as supermarkets, restaurants, and fresh food e-commerce platforms) typically suffer from the following technical deficiencies: Information asymmetry is a prominent issue. Key data such as the actual growth environment, feed usage, and disease prevention at the farming end are difficult to transmit completely and accurately to sales terminals and consumers. This makes it difficult for high-quality products to command premium prices, while inferior products may enter the market through false advertising. Farms often only provide handwritten farming records or simple certificates of conformity, making it difficult to verify the authenticity of the data.

[0003] The traceability mechanism is unreliable. Existing traceability systems mostly use centralized databases for storage, making the data susceptible to tampering or falsification. Once a food safety issue occurs, it is difficult to accurately pinpoint the source of the problem, and tracing responsibility becomes challenging. The information consumers see after scanning QR codes often only provides superficial information about "where it came from," lacking a true reconstruction of the entire farming process.

[0004] Traditional agricultural and livestock product transactions suffer from low efficiency, relying on in-person inspections, paper contracts, and manual reconciliation. This results in long transaction cycles, slow capital turnover, and risks associated with contract performance. Farms often wait for sales terminals to complete the sale of their livestock before receiving payment, leading to significant financial pressure.

[0005] The lack of cold chain logistics monitoring means that key environmental parameters such as temperature and humidity are not monitored and recorded in real time during transportation, making it impossible to ensure product quality and safety. Although some transport vehicles are equipped with temperature recorders, the data may be tampered with and cannot be automatically linked to transaction orders.

[0006] The problem of data silos is severe, with data from various stages such as farming, logistics, transactions, finance, and regulation being isolated from each other, hindering effective data collaboration and restricting the development of value-added services such as supply chain finance and precision regulation. Financial institutions, unable to obtain accurate and reliable operational data, find it difficult to provide financing services to small and medium-sized farms.

[0007] Therefore, there is an urgent need to provide a transaction system that can reliably collect data from the entire breeding process, automate the execution of the transaction process, transparently monitor the logistics links, and ensure authentic and reliable traceability from the farm to the sales terminal, in order to solve the above-mentioned technical problems. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention provides a transaction system from farms to sales terminals, resolving the aforementioned problems in the prior art.

[0009] To achieve the above objectives, the present invention provides the following technical solution: a transaction system from a farm to a sales terminal, comprising: The data collection unit at the breeding end is configured to collect and upload data in real time, including at least the identification of individual animals in the breeding farm, growth environment parameters, feed input information, disease prevention and control records, and weight monitoring data for the entire breeding process. The supply chain management unit is connected to the data acquisition unit at the breeding end and is configured to generate electronic goods orders corresponding to the animals to be sold based on the data of the entire breeding process, and to establish logistics route planning information and cold chain environment monitoring data from the breeding farm to the sales terminal based on the electronic goods orders. The trusted evidence storage unit is constructed using blockchain technology and configured to perform distributed storage of the entire breeding process data, electronic waybills, logistics route planning information, and cold chain environment monitoring data, generating tamper-proof traceability evidence records. The intelligent transaction matching unit is communicatively connected to the trusted evidence storage unit and is configured to receive purchase requests from the sales terminal, match the purchase requests with the full-process breeding data and electronic bills of lading in the traceability and evidence storage records, and generate a smart contract containing the identities of the two parties, the subject of the transaction, the transaction price, and the delivery conditions. The transaction execution unit, communicatively connected to the intelligent transaction matching unit and the supply chain management unit, is configured to automatically freeze and transfer transaction funds in response to the generation of the smart contract, and trigger the supply chain management unit to initiate logistics delivery according to the logistics route planning information; and The terminal traceability query unit is configured to provide sales terminals and / or consumers with a unique traceability code based on the individual animal identification or electronic invoice, so as to query the entire breeding process data, logistics route planning information and cold chain environment monitoring data related to the transaction target in the traceability record.

[0010] In some embodiments, the aquaculture end data acquisition unit includes: Electronic ear tags or implanted sensors worn on individual animals are used to collect the individual animal's identification, body temperature information, and activity data; An array of environmental sensors installed within the aquaculture environment is used to collect parameters of the growth environment, including temperature, humidity, ammonia concentration, and light intensity; and The video monitoring module is used to collect video image data from the farm. The video image data is associated with the individual animal identification and uploaded to the trusted evidence storage unit.

[0011] In some embodiments, the supply chain management unit includes: The slaughter inspection subunit is configured to determine whether an individual animal meets the slaughter standards based on the weight monitoring data and disease prevention records, and generate the electronic order form only for individual animals that meet the slaughter standards. The logistics scheduling subunit is configured to dynamically plan the logistics route planning information based on the geographical location of the sales terminal, traffic conditions, and the real-time status of cold chain transport vehicles; and The cold chain monitoring subunit is configured to collect real-time transportation environment temperature, transportation time and vehicle location information during the logistics transportation process, and synchronize the collected information to the trusted evidence storage unit.

[0012] In some embodiments, the intelligent transaction matching unit is further configured to: Obtain credit rating information and historical transaction records of sales terminals; Based on the credit rating information and historical transaction records, and combined with the product grade indicators in the entire breeding process data, the transaction price is calculated using a preset pricing model; and In response to the digital signature confirmation of the smart contract by both parties to the transaction, the smart contract is deployed to the trusted evidence storage unit.

[0013] In some embodiments, the transaction execution unit includes: The fund custody sub-unit is connected to a third-party payment platform or financial institution and is used to freeze the funds in the buyer's account corresponding to the transaction price after the smart contract is generated. The delivery confirmation subunit is configured to receive receipt confirmation information from the sales terminal or logistics receipt information from the supply chain management unit, and trigger the funds escrow subunit to transfer frozen funds to the seller's account based on the receipt confirmation information or logistics receipt information; and The anomaly handling subunit is configured to interrupt the fund transfer and send an anomaly alarm message to both parties to the transaction when the logistics delivery exceeds a preset time or the cold chain environment monitoring data exceeds a preset threshold.

[0014] In some embodiments, it also includes: The financial service interface unit is communicatively connected to the trusted evidence storage unit and the intelligent transaction matching unit. It is configured to provide supply chain finance assessment reports to farms and / or sales terminals based on the full-process data of breeding and the execution status of smart contracts in the traceability evidence storage records, and to complete the disbursement and recovery of financing funds in response to the credit instructions of financial institutions.

[0015] In some embodiments, the terminal tracing and querying unit is further configured as follows: Generate a graphic code containing a query entry point, wherein the graphic code uniquely corresponds to the electronic bill of lading or individual animal identification; In response to the scanning operation of the graphic code, the system displays in a visual manner real-life image of the farm environment, animal growth curves, feed formula information, quarantine certificates, and playback animation of logistics and transportation trajectories.

[0016] In some embodiments, it also includes: The government regulatory interface unit is configured to grant data access permissions to the government regulatory platform. These data access permissions enable the government regulatory platform to obtain real-time data on the entire breeding process, electronic waybills, logistics route planning information, and the execution status of smart contracts, and support the regulatory platform in issuing quarantine or recall orders.

[0017] In some embodiments, the trusted evidence storage unit is configured with a data privacy protection module, which is used for: The data uploaded to the trusted evidence storage unit is encrypted in a hierarchical manner, wherein the information of the farm operator, the transaction price, and the identity information of the two parties to the transaction are set to be visible only to the transaction participants; The individual animal identification, growth environment parameters, and disease prevention records in the entire breeding process data are set to be visible to sales terminals and consumers; and By employing zero-knowledge proof technology, when providing data verification to third-party institutions, only the verification results are disclosed, not the original data.

[0018] In some embodiments, the intelligent transaction matching unit further includes: The demand forecasting subunit is configured to use a machine learning model to predict regional market demand within a preset time period based on historical procurement demand data, seasonal factors, and market conditions. The production suggestion subunit is configured to generate production plan adjustment suggestions for farms based on the regional market demand and the full-process data of breeding collected by the breeding end data collection unit. The production plan adjustment suggestions include at least breeding scale adjustment suggestions, feed ratio optimization suggestions, or slaughter time planning suggestions.

[0019] Beneficial Effects: This invention provides a transaction system from farm to sales terminal. By uploading data collected through the Internet of Things (IoT) throughout the entire breeding process to the blockchain for trusted storage, this invention achieves tamper-proof data across the entire chain from breeding source to sales terminal. Through smart contracts, it automatically executes transaction matching, fund transfers, and logistics triggering, significantly improving transaction efficiency and reducing performance risks. By integrating cold chain monitoring data and terminal traceability queries, it ensures product transportation quality and provides consumers with a transparent traceability experience. Furthermore, by setting up financial service interfaces and government regulatory interfaces, it achieves in-depth data value mining and cross-departmental collaboration. Compared with existing technologies, this invention has the technical advantages of high data credibility, strong transaction automation, comprehensive and authentic traceability information, and good system scalability. Attached Figure Description

[0020] Figure 1 This is a flowchart of a transaction system from a farm to a sales terminal as described in this invention.

[0021] Figure 2 This is a structural block diagram of a transaction system from a farm to a sales terminal as described in this invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0023] It should be noted that the terms "first," "second," etc., used in the specification and claims of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the term "comprising" and any variations thereof are intended to cover non-exclusive inclusion.

[0024] Combination Figure 1-2 It can be known that: Example 1

[0025] This embodiment provides a transaction system from farm to sales terminal, such as... Figure 1As shown, the overall workflow of the system includes the following main steps: the data acquisition unit at the breeding end collects and uploads data from the entire breeding process in real time; the trusted evidence storage unit stores the collected data on the blockchain; the intelligent transaction matching unit matches the procurement needs of the sales terminal with the stored data and generates a smart contract; the transaction execution unit executes fund custody and transfer, and triggers the supply chain management unit to start logistics and distribution; the terminal traceability query unit provides consumers with a full-process information query service based on the traceability code. The specific implementation methods of each component are described in detail below.

[0026] Specific implementation methods of the aquaculture end data acquisition unit The data acquisition unit at the farming site is deployed on the farm. Its core function is to collect various types of data throughout the entire farming process in real time and automatically, and then upload them to the trusted data storage unit. This unit further includes: Individual animal monitoring module: This module combines RFID electronic ear tags with implanted body temperature sensors. The electronic ear tags record a unique identifier for each animal, while the implanted body temperature sensor collects the animal's temperature every 30 minutes and transmits it to the facility gateway via a low-power wide area network. Simultaneously, an accelerometer worn on the animal's leg collects activity data to help determine the animal's health status and estrus cycle.

[0027] Environmental sensor array: Multi-parameter environmental sensors, including temperature and humidity sensors, ammonia sensors, carbon dioxide sensors, and light sensors, are evenly distributed throughout the pig farm. Each sensor collects data every 10 minutes, and the data is aggregated to a data acquisition terminal via an RS-485 bus. For example, in a large-scale pig farm, one collection point is set up for every 200 square meters to ensure the spatial representativeness of the environmental data.

[0028] Feed input monitoring module: Flow meters and weight sensors are installed at the feed tower outlet and drinking water pipe inlet to record the type, weight, and time of each feed input in real time, and associate them with the feed batch number. Simultaneously, image recognition technology is used to monitor the license plate recognition and unloading of feed trucks, ensuring traceability of feed sources.

[0029] Weight monitoring module: A dynamic weighing channel is set up at the exit of the breeding shed. When animals pass through, their weight data is automatically acquired and linked to electronic ear tags to form an individual weight growth curve. For aquaculture, a combination of underwater sonar weighing and sampling is used.

[0030] Disease prevention and control record module: Immunization records, veterinary drug use records, and harmless disposal records of dead animals can be entered via mobile terminal or PC. All records must be uploaded after being electronically signed by a veterinarian.

[0031] Video surveillance module: High-definition network cameras are deployed in key locations such as breeding sheds, feed warehouses, and exit gates. The video stream is processed by edge computing nodes to extract key frames (such as animal feeding and activity scenes), and is spatiotemporally associated with individual animal identification. The video is stored in a distributed file system (IPFS), and its hash value is uploaded to a trusted evidence storage unit.

[0032] Table 1: Data types and collection frequency collected by the aquaculture data collection unit Specific implementation methods of supply chain management units The supply chain management unit is responsible for determining when animals will be slaughtered, logistics planning, and transportation monitoring. This unit includes: The slaughter inspection subunit sets up a slaughter standard database, storing thresholds for slaughter weight ranges, backfat thickness, and number of days of rearing required for different breeds and sales terminals. When an individual animal's weight monitoring data and number of days of rearing reach the preset thresholds, and disease prevention records show no risk of residual medication use, the system automatically marks the animal as "ready for slaughter" and generates an electronic manifest. The electronic manifest includes a list of animal identification tags, estimated total weight, slaughter time, and quarantine certificate number.

[0033] The logistics scheduling subunit integrates map service APIs (such as Amap and Baidu Maps) to obtain the precise geographical location of sales terminals. Based on the real-time location, remaining load capacity, and temperature control equipment status of cold chain transport vehicles (owned or third-party), combined with real-time road conditions, an improved ant colony algorithm is used to dynamically plan the optimal transportation route. For example, for deliveries to multiple sales destinations, the system automatically calculates the shortest path and ensures that the transportation time does not exceed the preset shelf life of fresh products (e.g., no more than 48 hours for pork).

[0034] Cold chain monitoring subunit: Multi-temperature zone sensors are installed inside the transport compartment to collect temperature, humidity, and vibration data every 5 minutes. Simultaneously, real-time location information is obtained via onboard GPS. When the temperature exceeds a preset threshold (e.g., the temperature in a refrigerated truck exceeds 4°C), the system immediately sends an audible and visual alarm to the driver and management personnel and records the abnormal event on the blockchain.

[0035] Table 2: Cold Chain Logistics Monitoring Parameters and Alarm Threshold Settings Specific implementation methods of trusted evidence storage unit The trusted evidence storage unit is built on a consortium blockchain, with participating nodes including farms, core sales companies, third-party testing institutions, and regulatory agencies. This unit performs hash calculations on all the aforementioned data before storing it on the blockchain, ensuring the immutability of the data and the authority of the timestamps.

[0036] Data upload process: Before uploading, edge computing nodes calculate the hash value of various data types, attaching a timestamp and the uploader's digital signature. After verifying the data format, the blockchain smart contract packages the hash value and metadata (data type, associated animal ID, time) into a transaction, which is then confirmed by a consensus mechanism (such as PBFT) and written to the blockchain ledger. On-chain confirmation typically takes 2-5 seconds, meeting real-time requirements.

[0037] Data privacy protection module: Employs a tiered encryption strategy. Level 1: Sensitive data (such as farm legal entity information, transaction prices, and buyer's bank account) is encrypted using the public key of the transaction participants, and only the two parties involved can decrypt and view it. Level 2: Publicly available traceability data (such as animal ear tags, growth environment parameters, and quarantine results) is encrypted using the system's global public key, and can be viewed by authorized sales terminals and consumers. Level 3: For scenarios requiring proof of transaction authenticity to financial institutions, zero-knowledge proof technology is used. The system can provide banks with proof that "the farm's transaction volume in the past 6 months exceeds 5 million yuan," without disclosing the specific buyer information or price of each transaction.

[0038] Table 3: Data Hierarchical Encryption Strategy for Trusted Evidence Storage Units Detailed Implementation of the Intelligent Transaction Matching Unit The intelligent trading matching unit is the core of automated trading. This unit includes the following sub-functions: Procurement Request Posting: Sales terminals can enter procurement requests via mobile or web terminals, including product category (e.g., broiler chickens), specifications (weight per chicken 1.8-2.2kg), quantity (5000 chickens), expected price range (15-18 RMB / kg), delivery location, and expected delivery time. After the procurement request is posted, the system automatically broadcasts it to the matching engine.

[0039] Matching Algorithm: The system iterates through the 300 trusted evidence storage units to identify electronic invoices that have been generated but not yet traded, filtering out farms that match the product category, specifications, and quantity. The matching process considers the following factors: the farm's historical performance rating (based on past transaction execution, including on-time delivery rate, product qualification rate, etc.), product grade (automatically assessed based on data such as body weight uniformity, lean meat percentage, and feed conversion ratio), and geographical distance (affecting logistics costs). The matching algorithm employs a multi-objective optimization model, prioritizing the top three farms with the highest overall scores for sales terminals to choose from.

[0040] Pricing Model: A dynamic pricing model is adopted. The base price is the recent average market price of the same product category (obtained from a third-party price data source). Based on this, farms with the following characteristics receive a price premium: organic certification (+5%), antibiotic-free farming throughout the entire process (+8%), complete blockchain traceability (+3%), and green food certification (+4%). Simultaneously, based on the sales terminal's credit rating (based on historical on-time payment rates), certain credit period discounts may be granted. The pricing model can be expressed by the formula: in, The benchmark price (yuan / kg) The weight of the i-th quality characteristic, The quality characteristic score (between 0 and 1) This represents the credit discount rate (between 0 and 0.1). For example, a farm has organic certification (w=0.05, f=1) and antibiotic-free farming (w=0.08, f=1), with a base price of 16 yuan / kg and a retail credit discount rate of 5%. Therefore, the final price P = 16 × (1 + 0.05 + 0.08) × (1 - 0.05) = 16 × 1.13 × 0.95 = 17.18 yuan / kg.

[0041] Smart Contract Generation: Upon successful matching, the system generates a smart contract, which includes: seller (farm) identification, buyer (sales terminal) identification, transaction object (electronic waybill number), total transaction price, delivery time, delivery location, acceptance standards (e.g., a minimum pass rate of ≥98% upon arrival inspection), and fund transfer conditions (automatic transfer within 24 hours of receipt confirmation). After both parties digitally sign the contract using their private keys, the smart contract is deployed to the blockchain. The smart contract's code is publicly verifiable, ensuring transparent execution logic.

[0042] Table 4: Examples of Core Parameters and Execution Conditions for Smart Contracts Detailed Implementation Method of Transaction Execution Unit The transaction execution unit is responsible for the automatic execution of smart contracts, including: Funds Custody Sub-unit: Connects with commercial banks or licensed third-party payment institutions via API. After the smart contract takes effect, the funds custody sub-unit automatically initiates a pre-authorization freeze request to the buyer's account, freezing the corresponding transaction amount. Upon successful freezing, a "shipment ready" instruction is sent to the supply chain management unit. During the fund freeze period, the buyer cannot access the funds, and the seller need not worry about not receiving payment after shipment.

[0043] Delivery Confirmation Subunit: After logistics and delivery are completed, the sales terminal signs for receipt by scanning the QR code on the accompanying packing slip via the APP, or the logistics personnel upload an electronic receipt. The system verifies the receipt information (such as geographical location comparison and receipt time verification). After confirming that everything is correct, it sends a transfer instruction to the fund custody subunit. For batch transactions, batch confirmation and batch transfer are supported.

[0044] The anomaly handling subunit has a pre-set anomaly rule library, including: logistics delays exceeding timeout limits (e.g., exceeding the estimated arrival time by 12 hours), cold chain temperature exceeding the threshold (cumulatively exceeding the threshold by 30 minutes), and a failure rate of over 5% in incoming goods inspections. When any anomaly rule is triggered, the system automatically suspends fund transfers, sends an anomaly alert to both parties to the transaction, and initiates a dispute resolution process. During dispute resolution, funds remain frozen until both parties reach an agreement or the platform intervenes to adjudicate. The dispute resolution result (e.g., partial refund, return of goods, etc.) is also automatically executed through a smart contract.

[0045] Table 5: Rules and Handling Mechanisms for Transaction Execution Anomalies Detailed Implementation of Terminal Tracing and Query Unit The terminal traceability query unit provides consumers and sales terminals with visualized traceability services. The specific implementation method is as follows: Traceability code generation: A unique QR code is generated for each batch of animals sold or each individual package. The QR code information includes the electronic waybill number, the animal's individual identification range, and the on-chain transaction hash value. The QR code uses anti-counterfeiting technology to prevent copying and forgery.

[0046] Inquiry portal: Consumers can scan the QR code via WeChat mini-program, Alipay mini-program, or a dedicated app, or manually enter the traceability code. The system supports multilingual display to meet the needs of consumers in different regions.

[0047] Information Display: The breeding process includes: displaying the animals' birth dates, feed types and batches, immunization records (showing only vaccine names and dates, without involving commercially sensitive information), weight gain curves (displayed as line graphs), and real-life photos of the breeding farm environment (updated weekly).

[0048] Quarantine process: Displays an electronic version of the official animal quarantine certificate issued by a veterinarian, along with a digital signature verification button from the quarantine agency, allowing consumers to verify the authenticity of the quarantine certificate with a single click.

[0049] In the logistics process: the vehicle's trajectory is replayed in the form of a map animation, and the temperature change curve during transportation is displayed in real time, with different colors used to distinguish temperature ranges (green for acceptable, red for exceeding the standard).

[0050] Transaction process: Display the slaughter date, cutting and packaging date, and the name and address of the sales terminal.

[0051] Interactive features: Consumers can rate products and provide feedback, with the feedback information also stored on the blockchain as evidence, serving as a reference for the farm's credit rating. Simultaneously, the system supports one-click complaints to the regulatory platform, with complaint information automatically linked to the product traceability record.

[0052] Table 6: Terminal Traceability Information Display Content and Data Sources Specific implementation methods of the expansion unit Financial Services Interface Unit: This unit periodically retrieves data on the farm's breeding scale, historical sales data, smart contract execution status, and fund recovery records from the trusted evidence storage unit, generating a multi-dimensional supply chain finance assessment report. The assessment report includes: basic farm information, sales volume and trends over the past 12 months, fulfillment rate (on-time delivery rate, product qualification rate), accounts receivable balance, credit score, etc. Banks or factoring companies can view the report through authorized portals and issue "farming loans" or "accounts receivable factoring" financing online. Financing funds are directly deposited into the farm's account, and repayment is automatically deducted from sales proceeds via smart contracts. The system also supports an "order financing" model, where farms can apply for financing using generated electronic invoices.

[0053] Government Regulatory Interface Unit: Provides regulatory data dashboards to agricultural and rural affairs departments and market supervision departments. Regulatory personnel can view in real-time the use of veterinary drugs, the harmless disposal of dead animals, the declaration of slaughter and quarantine, and the sampling results of market-circulated products in farms within their jurisdiction. The system supports setting a regulatory rule engine, automatically pushing early warning information to the regulatory platform when farms exhibit abnormal veterinary drug usage (e.g., exceeding the standard dosage by 200%) or abnormally high mortality rates. In the event of regional disease outbreaks or food safety incidents, the regulatory platform can issue suspension of transactions or product recall orders through the system. The system automatically executes relevant operations, including freezing the transaction permissions of relevant farms, notifying all sales terminals that have purchased the batch of products, and sending recall notices to consumers.

[0054] Table 7: Data Integration Contents Between Financial Service Interface and Government Regulatory Interface Example of the overall system workflow (taking a batch of live pig transactions as an example) To more clearly illustrate the overall workflow of the system of the present invention, the following description is provided in conjunction with specific examples and references. Figure 1 The flowchart shown is a workflow diagram.

[0055] Step 1: Aquaculture Data Collection and Uploading to the Blockchain A pig farm (Farm A) has 1,000 pigs, each wearing an RFID electronic ear tag (numbered P0001-P1000). During the rearing process, environmental sensors upload data on the pigpen temperature (18-22℃) and ammonia concentration (<10ppm) every 10 minutes. A feed input monitoring module records the daily feed intake (total 2500kg). A weight monitoring channel collects weight data weekly and records individual growth curves. All data is uploaded in real time to a trusted evidence storage unit 300 for blockchain-based evidence storage, generating tamper-proof records.

[0056] Step 2: Slaughter Determination and Electronic Waybill Generation When pigs reach a weight of 110kg, have been fed for 180 days, and the last medication was administered more than the withdrawal period (28 days), the slaughter inspection subunit marks this batch of pigs as "ready for slaughter." The system generates an electronic manifest (number: EBILL-20250315-001), containing 500 pigs (P0001-P0500), with an estimated total weight of 55 tons, and is accompanied by a quarantine certificate (number: JY20250315001).

[0057] Step 3: Procurement Request Posting and Intelligent Matching Sales terminal B (a chain supermarket) published a purchase request through the system: the product category is live pigs, the size is 110-120kg / head, the quantity is 500 heads, the expected price range is 16-18 yuan / kg, and the delivery location is Pudong New Area, Shanghai. The intelligent transaction matching unit 400 retrieved the electronic order from farm A. Based on farm A's historical performance score (98 points), product grade (Grade A, good weight uniformity, high lean meat percentage), and geographical distance (300 kilometers), farm A ranked first in overall matching degree. The system pushed the matching result to sales terminal B, and after sales terminal B confirmed it, the pricing stage began.

[0058] Step 4: Smart Contract Generation and Confirmation The system calculates the transaction price based on a dynamic pricing model. The base price is 17 yuan / kg. Farm A has green food certification (+4%), antibiotic-free farming (+8%), and a total markup of 12%, resulting in a final price of 19.04 yuan / kg. The total transaction amount is 19.04 yuan / kg × 55,000 kg = 1,047,200 yuan. The system generates a smart contract, which is then confirmed by both parties through digital signatures and deployed to the blockchain.

[0059] Step 5: Funds Freeze and Logistics Trigger The fund custody subunit of transaction execution unit 500 initiates a pre-authorization freeze of RMB 1,047,200 in the bank account of sales terminal B. Upon successful freezing, supply chain management unit 200 is triggered to arrange for a cold chain transport vehicle (license plate number: Shanghai A·XXXXX) to load and ship the goods. The logistics scheduling subunit plans the optimal route: Farm A → G15 Expressway → Shanghai Ring Expressway → Sales Terminal B, with an estimated transportation time of 8 hours.

[0060] Step 6: Logistics monitoring and receipt confirmation During transportation, the cold chain monitoring subunit uploads the temperature data of the vehicle compartment every 5 minutes, maintaining it between 2-4℃ throughout the journey, which meets the requirements. Upon arrival, sales terminal B signs for receipt by scanning the QR code on the accompanying manifest via the APP, confirming a quantity of 500 heads and a weight of 55.2 tons (within the allowable error range). The delivery confirmation subunit records the signing time, location, and signatory information.

[0061] Step 7: Funds transfer and transaction completion Within 24 hours of delivery confirmation, the escrow unit will transfer RMB 1,047,200 to Farm A's bank account. The transaction is complete, and all relevant data (including logistics tracking, temperature curves, and delivery records) will be stored on the blockchain.

[0062] Step 8: Terminal traceability query When consumers purchase pork at the supermarket, they can scan the QR code on the packaging to access the terminal traceability query unit 600. The page displays: real-time photos of the farm environment, pig weight growth curves, feed formula information (65% corn, 20% soybean meal, 5% premix), an electronic version of the quarantine certificate, an animation of the transportation trajectory, and a temperature curve throughout the process (green indicates compliance). Consumers can rate the product, and the rating information is stored on the blockchain as evidence.

[0063] Summary of technical effects Compared with existing technologies, the transaction system from farm to sales terminal provided by this invention has the following beneficial technical effects: First, data credibility is significantly improved. By directly storing IoT data from the entire breeding process on the blockchain, and leveraging the immutability of blockchain, the authenticity and reliability of data at every stage from the breeding source to the sales terminal are ensured, effectively solving the problem of data falsification in traditional traceability systems.

[0064] Second, the transaction is highly automated. By automatically executing operations such as procurement matching, fund freezing, logistics triggering, and fund transfer through smart contracts, the transaction cycle is significantly shortened, and errors and risks caused by human intervention are reduced. Transaction efficiency is improved by more than 60% compared to the traditional model.

[0065] Third, the traceability information is comprehensive and transparent. Consumers can access information across the entire chain, from breeding and quarantine to logistics and sales. This includes not only written records but also visualized data such as real-time environmental scenes, growth curves, and temperature trajectories, enhancing consumer trust.

[0066] Fourth, the system has strong scalability. Through financial service interfaces and government regulatory interfaces, it enables in-depth mining of data value, providing a data foundation for value-added services such as supply chain finance, precision regulation, and market monitoring, and forming a multi-party collaborative industrial ecosystem.

[0067] It should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

Claims

1. A transaction system from farm to sales terminal, characterized in that, include: The data collection unit at the breeding end is configured to collect and upload data in real time, including at least the identification of individual animals in the breeding farm, growth environment parameters, feed input information, disease prevention and control records, and weight monitoring data for the entire breeding process. The supply chain management unit is connected to the data acquisition unit at the breeding end and is configured to generate electronic goods orders corresponding to the animals to be sold based on the data of the entire breeding process, and to establish logistics route planning information and cold chain environment monitoring data from the breeding farm to the sales terminal based on the electronic goods orders. The trusted evidence storage unit is constructed using blockchain technology and configured to perform distributed storage of the entire breeding process data, electronic waybills, logistics route planning information, and cold chain environment monitoring data, generating tamper-proof traceability evidence records. The intelligent transaction matching unit is communicatively connected to the trusted evidence storage unit and is configured to receive purchase requests from the sales terminal, match the purchase requests with the full-process breeding data in the traceability evidence storage record and the electronic order, and generate a smart contract containing the identities of the two parties, the subject of the transaction, the transaction price and the delivery conditions. The transaction execution unit is communicatively connected to the smart transaction matching unit and the supply chain management unit, and is configured to automatically freeze and transfer transaction funds in response to the generation of the smart contract, and trigger the supply chain management unit to start logistics delivery according to the logistics route planning information; as well as The terminal traceability query unit is configured to provide sales terminals and / or consumers with a unique traceability code based on the individual animal identification or the electronic order, so as to query the entire breeding process data, logistics route planning information and cold chain environment monitoring data related to the transaction target in the traceability record.

2. The transaction system from farm to sales terminal according to claim 1, characterized in that, The aquaculture end data acquisition unit includes: Electronic ear tags or implanted sensors worn on individual animals are used to collect the individual animal's identification, body temperature information, and activity data; An array of environmental sensors installed within the aquaculture environment is used to collect parameters of the growth environment, including temperature, humidity, ammonia concentration, and light intensity; and The video monitoring module is used to collect video image data from the farm. The video image data is associated with the individual animal identification and uploaded to the trusted evidence storage unit.

3. The transaction system from farm to sales terminal according to claim 1, characterized in that, The supply chain management unit includes: The slaughter inspection subunit is configured to determine whether an individual animal meets the slaughter standards based on the weight monitoring data and disease prevention records, and generate the electronic order form only for individual animals that meet the slaughter standards. The logistics scheduling subunit is configured to dynamically plan the logistics route planning information based on the geographical location of the sales terminal, traffic conditions, and the real-time status of cold chain transport vehicles; and The cold chain monitoring subunit is configured to collect real-time transportation environment temperature, transportation time and vehicle location information during the logistics transportation process, and synchronize the collected information to the trusted evidence storage unit.

4. The transaction system from farm to sales terminal according to claim 1, characterized in that, The intelligent transaction matching unit is further configured as follows: Obtain credit rating information and historical transaction records of sales terminals; Based on the credit rating information and historical transaction records, and combined with the product grade indicators in the entire breeding process data, the transaction price is calculated using a preset pricing model. as well as In response to the digital signature confirmation of the smart contract by both parties to the transaction, the smart contract is deployed to the trusted evidence storage unit.

5. The transaction system from farm to sales terminal according to claim 1, characterized in that, The transaction execution unit includes: The fund custody sub-unit is connected to a third-party payment platform or financial institution and is used to freeze the funds in the buyer's account corresponding to the transaction price after the smart contract is generated. The delivery confirmation subunit is configured to receive receipt confirmation information from the sales terminal or logistics receipt information from the supply chain management unit, and trigger the funds escrow subunit to transfer frozen funds to the seller's account based on the receipt confirmation information or logistics receipt information; and The anomaly handling subunit is configured to interrupt the fund transfer and send an anomaly alarm message to both parties to the transaction when the logistics delivery exceeds a preset time or the cold chain environment monitoring data exceeds a preset threshold.

6. The transaction system from farm to sales terminal according to claim 1, characterized in that, Also includes: The financial service interface unit is communicatively connected to the trusted evidence storage unit and the intelligent transaction matching unit. It is configured to provide supply chain finance assessment reports to farms and / or sales terminals based on the full-process data of breeding and the execution status of smart contracts in the traceability evidence storage records, and to complete the disbursement and recovery of financing funds in response to the credit instructions of financial institutions.

7. The transaction system from farm to sales terminal according to claim 1, characterized in that, The terminal tracing and query unit is further configured as follows: Generate a graphic code containing a query entry point, wherein the graphic code uniquely corresponds to the electronic bill of lading or individual animal identification; In response to the scanning operation of the graphic code, the system displays in a visual manner real-life image of the farm environment, animal growth curves, feed formula information, quarantine certificates, and playback animation of logistics and transportation trajectories.

8. The transaction system from farm to sales terminal according to claim 1, characterized in that, Also includes: The government regulatory interface unit is configured to grant data access permissions to the government regulatory platform. These data access permissions enable the government regulatory platform to obtain real-time data on the entire breeding process, electronic waybills, logistics route planning information, and the execution status of smart contracts, and support the regulatory platform in issuing quarantine or recall orders.

9. A transaction system from farm to sales terminal according to claim 1, characterized in that, The trusted evidence storage unit is equipped with a data privacy protection module, which is used for: The data uploaded to the trusted evidence storage unit is encrypted in a hierarchical manner, wherein the information of the farm operator, the transaction price, and the identity information of the two parties to the transaction are set to be visible only to the transaction participants; The individual animal identification, growth environment parameters, and disease prevention records in the entire breeding process data are set to be visible to sales terminals and consumers; and By employing zero-knowledge proof technology, when providing data verification to third-party institutions, only the verification results are disclosed, not the original data.

10. A transaction system from farm to sales terminal according to claim 1, characterized in that, The intelligent transaction matching unit also includes: The demand forecasting subunit is configured to use a machine learning model to predict regional market demand within a preset time period based on historical procurement demand data, seasonal factors, and market conditions. The production suggestion subunit is configured to generate production plan adjustment suggestions for farms based on the regional market demand and the full-process data of breeding collected by the breeding end data collection unit. The production plan adjustment suggestions include at least breeding scale adjustment suggestions, feed ratio optimization suggestions, or slaughter time planning suggestions.

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