Data processing method, processor and program product

Abstract

The invention discloses a data processing method, a processor and a program product. The method comprises the steps that product attribute information of a target biological object is collected, and the product attribute information is used for representing a biological product category; based on the product attribute information, initial identification information of the target organism is generated, and the initial identification information is used for identifying the target organism; performing encryption processing on the initial identification information to obtain target identification information; and uploading the target identification information to the block chain. The technical problem that the full-link credible traceability ecology in the block chain cannot be constructed is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of information security, in particular to a data processing method, a processor and a program product. BACKGROUND

[0002] At present, with the development of blockchain and Internet of Things technology in the field of food traceability, product traceability technology based on blockchain has emerged. This technology, with the characteristics of distributed storage and non-tamperability, provides a new way to solve the problem of food supply chain data credible evidence, and further leads to the current traditional traceability system and single blockchain traceability method.

[0003] However, the current traditional traceability system and single blockchain traceability method have the key problem of trust rupture caused by data silos. The traditional traceability system adopts centralized storage, and the data of each link such as planting, processing and logistics cannot be interconnected, which causes the technical problem that a full-link trusted traceability ecology in the blockchain cannot be constructed.

[0004] At present, there is no effective solution to the above problems. SUMMARY

[0005] The embodiments of the present application provide a data processing method, a processor and a program product to at least solve the technical problem that a full-link trusted traceability ecology in the blockchain cannot be constructed.

[0006] According to an aspect of an embodiment of the present application, a data processing method is provided, which can include: collecting product attribute information of a target biological object, wherein the product attribute information is used to represent the product category of the biological object; generating initial identification information of the target biological object based on the product attribute information, wherein the initial identification information is used to identify the target biological object; encrypting the initial identification information to obtain target identification information; and uploading the target identification information to the blockchain.

[0007] Optionally, generating the initial identification information of the target biological object based on the product attribute information includes: converting the product attribute information to obtain a first identification code corresponding to the target biological object, wherein the first identification code is used to determine the growth data of the target biological object; determining a first object used to produce the target biological object from the product attribute information; obtaining first identity information of the first object, and converting the first identity information to obtain a second identification code corresponding to the target biological object, wherein the second identification code is used to determine the production qualification required for the first object to produce the target biological object; determining second identity information of a second object supervising the first object, and converting the second identity information to obtain a third identification code corresponding to the target biological object, wherein the third identification code is used to determine the calling data authority of the second object; and combining the first identification code, the second identification code and the third identification code to obtain the initial identification information.

[0008] Optionally, the method can further include: in response to a third object of the transaction target biological object existing in the blockchain, obtaining third identity information of the third object, and converting the third identity information to obtain a fourth identification code corresponding to the target biological object, wherein the fourth identification code is used to represent the transaction behavior of the third object; and associating the target identification information and the fourth identification code.

[0009] Optionally, the method can further include: obtaining virtual identification information corresponding to the target biological object in the blockchain, wherein the virtual identification information is used to represent a virtual object corresponding to the target biological object in the blockchain; and using a target program in the blockchain to construct a mapping relationship between the virtual identification information and the target identification information.

[0010] Optionally, the method can further include: in response to a change in an environment in which the target biological object is located, collecting environment change data; using the target program to adjust the virtual object according to the environment change data, and determining a terminal device associated with the target identification information; and displaying the adjusted virtual object in the terminal device.

[0011] Optionally, the method can further include: in response to an abnormal change in a growth state of the target biological object, prohibiting the first identification code in the target identification information from being changed, and using the target program to adjust a display result of the virtual object according to a change result of the target biological object.

[0012] Optionally, the method can further include: in response to the credit degree of the first object being less than or equal to a target value, stopping generating identification information of a biological object produced by the first object.

[0013] Optionally, the method can further include: obtaining evaluation information of the target biological object by the third object; extracting at least one keyword in the evaluation information, and determining weight data corresponding to the keyword, wherein the weight data is used to represent an importance degree of the keyword in evaluating a use condition of the target biological object by the third object; and determining an adjustment parameter of the target biological object based on the weight data and the keyword, wherein the adjustment parameter is used to adjust a production environment of the target biological object.

[0014] According to another aspect of the embodiments of the present application, a data processing apparatus is also provided, which can include: an acquisition unit configured to acquire product attribute information of a target biological object, wherein the product attribute information is used to represent a product category of the biological object; a generation unit configured to generate initial identification information of the target biological object based on the product attribute information, wherein the initial identification information is used to identify the target biological object; a processing unit configured to perform encryption processing on the initial identification information to obtain target identification information; and an uploading unit configured to upload the target identification information to a blockchain.

[0015] According to another aspect of the embodiments of the present application, a computer readable storage medium is also provided, including a stored program, wherein the computer readable storage medium controls a device where the computer readable storage medium is located to execute the data processing method of the embodiments of the present application when the program is run.

[0016] According to another aspect of the embodiments of the present application, a processor is also provided, which is used to run a program, wherein the processor executes the data processing method of the embodiments of the present application when the program is run.

[0017] According to another aspect of the embodiments of the present application, a computer program product is also provided, which includes computer instructions, wherein the computer instructions implement the data processing method of the embodiments of the present application when executed by a processor.

[0018] In the embodiments of the present application, product attribute information of a target biological object is collected, wherein the product attribute information is used to represent a product category of the biological object; initial identification information of the target biological object is generated based on the product attribute information, wherein the initial identification information is used to identify the target biological object; the initial identification information is encrypted to obtain target identification information; and the target identification information is uploaded to a blockchain. That is, in the embodiments of the present application, product attribute information of a target biological object is collected, and initial identification information is constructed based on the product attribute information. The initial identification information can be used to implement a data value chain construction of “production-circulation-supervision-consumption”, and the state between the target biological object and a virtual object in the blockchain is bound, so as to achieve the purpose of constructing a self-evolving trusted traceability ecological system, solve the technical problem that a full-link trusted traceability ecology in the blockchain cannot be constructed, and achieve the technical effect that a full-link trusted traceability ecology in the blockchain can be constructed. BRIEF DESCRIPTION OF DRAWINGS

[0019] The accompanying drawings, which are included to provide a further understanding of the present application, form a part of the present application and illustrate the illustrative embodiments of the present application and the explanation of the present application, and do not constitute improper limitations on the present application. In the drawings:

[0020] Figure 1 is a flowchart of a data processing method according to an embodiment of the present application;

[0021] Figure 2 is a flowchart of a one-key code generation method according to an embodiment of the present application;

[0022] Figure 3 is a flowchart of a virtual-real synchronization triggered by a supervision code according to an embodiment of the present application;

[0023] Figure 4 is a flowchart of a data screening strategy according to an embodiment of the present application;

[0024] Figure 5 is a four-code linkage process system diagram according to an embodiment of the application;

[0025] Figure 6 is a flowchart of an NLP and NFT decision linkage process according to an embodiment of the application;

[0026] Figure 7 is a flowchart of a double-NFT hash mapping process according to an embodiment of the application;

[0027] Figure 8 is a schematic diagram of a food full-link trusted traceability ecological chain according to an embodiment of the application;

[0028] Figure 9 is a schematic diagram of a data processing device according to an embodiment of the application;

[0029] Figure 10 is a structural block diagram of a computer terminal according to an embodiment of the application;

[0030] Figure 11 is a block diagram of an electronic device of a data processing method according to an embodiment of the application. DETAILED DESCRIPTION

[0031] In order to enable persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative labor should be within the scope of protection of the present application.

[0032] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, such as a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0033] First, some of the nouns or terms appearing in the description of the embodiments of the present application are applicable to the following explanations:

[0034] Blockchain, using a consortium chain (such as FISCOBCOS consortium chain) architecture, supporting a national secret algorithm (such as SM2 / SM3 algorithm), having a distributed storage, a data non-tamperable feature, a distributed ledger system;

[0035] Edge computing, deploying related hardware at network edge nodes of farms, processing plants and the like, can be used to realize real-time data collection and preprocessing;

[0036] Smart contract, an automatic program deployed on a blockchain, automatically performing data verification, permission adjustment, instruction triggering and the like according to preset rules, supporting four-code state synchronization and virtual-real data linkage;

[0037] Natural language processing (NLP), through an algorithm to analyze user evaluation text, using a standardized data exchange (JSON) format to transmit optimized recommendations through MQTT, for example, a parameter conversion formula is that for every 1% adjustment in nitrogen fertilizer ratio, the fertilizer amount is +5 kg / acre, and the analysis result can affect enterprise code credit score and product code permission.

[0038] According to the embodiments of the present application, an embodiment of a data processing method is provided, the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that here.

[0039] At present, with the development of blockchain and Internet of Things technology in the field of food traceability, product traceability technology based on blockchain has emerged. This technology, with the characteristics of distributed storage and non-tamperability, provides a new way to solve the problem of food supply chain data credible evidence, and further leads to the current traditional traceability system and single blockchain traceability method.

[0040] However, the current traditional traceability system and single-blockchain traceability method have the key problem of trust rupture caused by data island. The traditional traceability system adopts centralized storage, and the data of each link such as planting, processing and logistics is fragmented and cannot be interchanged, and the data is easy to be tampered with. Although the single-blockchain traceability method realizes data storage, users can only passively query traceability information, and although the single-blockchain traceability emphasizes "tamper-proof", users are difficult to understand the technical principles such as hash value comparison and consensus mechanism, and the perception of data credibility only stays at the level of textual description. For example, users see the record of "pesticide residue qualified" on the chain, but cannot verify whether the data is true through operation, resulting in that the trust in technology is transformed into the trust in data, which is inefficient. Passive query cannot collect user feedback on data (such as questioning the data of a certain link), and the production end or the supervision end cannot adjust the strategy according to the user behavior. This trust rupture not only affects the consumer's purchase decision, but also makes it difficult for enterprises to obtain market recognition through credible data, small and medium-sized enterprises are difficult to participate due to high technical threshold, and the supervision department also leads to event response lag due to insufficient data credibility, and the average checking time of food safety incidents is more than 72 hours, which seriously restricts the healthy development of food traceability ecology.

[0041] To solve the above problems, in this embodiment, a data processing method is proposed, which can collect product attribute information of a target biological object, based on the product attribute information, initial identification information of the target biological object is constructed, and the data value chain construction of "production-circulation-supervision-consumption" can be realized by using the initial identification information, and the state between the target biological object and the virtual object in the blockchain is bound, so as to achieve the purpose of constructing a self-evolving credible traceability ecological system, solve the technical problem that the full-link credible traceability ecological system in the blockchain cannot be constructed, and realize the technical effect that the full-link credible traceability ecological system in the blockchain can be constructed.

[0042] Figure 1 is a flowchart of a data processing method according to an embodiment of the present application. As shown in Figure 1 , the method can include the following steps:

[0043] Step S101, collecting product attribute information of a target biological object, wherein the product attribute information is used to represent the product category of the biological object;

[0044] Step S102, generating initial identification information of the target biological object based on the product attribute information, wherein the initial identification information is used to identify the target biological object;

[0045] Step S103, encrypting the initial identification information to obtain target identification information;

[0046] Step S104, uploading the target identification information to the blockchain.

[0047] In this embodiment, the target biological object can be a farmed plant, animal, aquatic organism, or other living object. The product attribute information can be used to represent at least the product category of the biological object, and can include but is not limited to: product category, product producing enterprise, enterprise type, enterprise production qualification, target production object processing data, growth data, and the like. The initial identification information can be a two-dimensional code, which can be structured information integrating product, enterprise, and processing data, and can be used to determine the type, production wage, and growth environment of the target biological object. The initial identification information can include but is not limited to: a first identification code (i.e., product code), a second identification code (i.e., enterprise code), and a third identification code (i.e., regulatory code). It should be noted that the above is only an example, and the type of target biological object, the content of product attribute information, and the type of initial identification information are not specifically limited. The target identification information can be a two-dimensional code containing a hash value, which can include: a first identification code containing a hash value, a second identification code containing a hash value, and a third identification code containing a hash value.

[0048] Optionally, the product attribute information of the target biological object is collected, and based on the product attribute information, the initial identification information of the target biological object can be constructed. The initial identification information can be encrypted to obtain the target identification information. The target identification information can be uploaded to the blockchain, and after constructing a transaction and a digital signature, it can be submitted to the alliance chain to return the chaining result.

[0049] In this embodiment, the "one-click code generation" is realized by using a Software as a Service (SaaS) platform. Starting from an Application Programming Interface (API) gateway, the product data, which can be product attribute information, is collected by a data collection module. The product attribute information is converted by a code generation engine to obtain a two-dimensional code / NFT, and then the two-dimensional code / NFT is processed by a blockchain interaction module in combination with an encryption signature module to generate an encrypted hash (i.e., target identification information) and is chained. Finally, the chaining result can be fed back to a user interface to realize the process of product data collection, processing, and chaining display.

[0050] Optionally, a non-homogeneous token (NFT) can be a unique digital asset identifier based on a blockchain, which can be used to bind virtual items (such as virtual farm fruits) and entity rights (such as offline coupons, offline fruits), product code NFT can be used to store real growth data hash value, virtual fruit NFT records user interaction behavior hash, through smart contract to realize double NFT state synchronization, synchronization delay is less than 2 seconds, virtual maturity = (virtual growth days / real period) x 100%. Wherein, the target identification information can include (product code NFT), and the virtual fruit NFT can be virtual identification information.

[0051] Optionally, the product attribute information of the target biological object is collected, which can include but is not limited to product, enterprise, processing data and the like, and the product attribute information can be aggregated to generate structured information, that is, initial identification information. Further, the product code hash is generated by SHA-256, the NFT metadata is created and uploaded to the interplanetary file system (IPFS), the two-dimensional code containing the hash value is generated, that is, the target identification information. Finally, the blockchain interaction can construct a transaction, and after digital signature, it is submitted to the alliance chain and returns the on-chain result.

[0052] In this embodiment, after obtaining the product attribute information, the product attribute information can be subjected to outlier detection or trend analysis, such as temperature anomaly detection, which can adopt 3σ criterion, combined with sliding window (window size = 5 minutes) real-time monitoring, after marking the abnormal data, through the edge node local alarm (such as sound and light prompt), and at the same time, it is uploaded to the blockchain for storage. Or 5-point moving average formula, when the change rate of 3 consecutive time windows > 0.5℃ / 10min, trigger early warning, new user verification abnormal rate trend analysis (continuous 3 times > 30% trigger marking).

[0053] Figure 2 It is a flow chart of a one-key code generation method according to an embodiment of the present application, as shown in Figure 2 The generation process of the target identification information can include the following steps:

[0054] Step S201, obtaining product data.

[0055] In this embodiment, starting from the API gateway, the product data can be collected by the data collection module first, and the product data can be product attribute information.

[0056] Step S202, processing the product data to obtain initial identification information.

[0057] In this embodiment, the product data is generated into a two-dimensional code / NFT by the code generation engine, that is, the initial identification information.

[0058] In step S203, the initial identification information is encrypted to obtain target identification information.

[0059] In this embodiment, the blockchain interaction module is used to process and generate a cryptographic hash (that is, target identification information) after combining the encryption signature module, and then chain it. The chain result can be fed back to the user interface to realize the process of product data from collection, processing to chain display.

[0060] In this embodiment, a four-code linkage food full-link traceability system based on blockchain is provided. The system adopts a four-layer architecture of "edge collection-blockchain evidence-intelligent decision-user interaction", takes the four-code linkage mechanism as the core, and constructs a self-evolutionary trusted traceability ecology through the bidirectional mapping of product code NFT and virtual fruit NFT. The system can include: an edge computing and data collection module, a blockchain multi-code generation and management module, a supervision collaboration and smart contract module, and an NLP driven user interaction module.

[0061] Optionally, the edge computing and data collection module deploys edge computing nodes and intelligent terminal devices in farms and processing plants, collects and preprocesses data in real time, and realizes low-delay transmission to the cloud through 5G technology, ensuring the timeliness and accuracy of data collection and reducing cloud traffic costs. The edge node can adopt a primary and backup dual-machine hot standby architecture. When the primary node fails, the standby node automatically takes over within three seconds, triggers local audible and visual alarms, and records fault information on the chain, ensuring data collection continuity. The target biological object product attribute information can be collected by using the edge node.

[0062] Optionally, the blockchain multi-code generation and management module adopts a consortium chain architecture, jointly maintains the ledger with multiple nodes, generates product codes and enterprise codes through hash operation, realizes data tamper-proofing and multi-party sharing, and applies a decentralized design according to the different needs of consumers, merchants and regulatory authorities to open corresponding permissions, ensuring data security and effective use.

[0063] Through the above steps S101 to S104, the product attribute information of the target biological object is collected, wherein the product attribute information is used to represent the product category of the biological object; based on the product attribute information, initial identification information of the target biological object is generated, wherein the initial identification information is used to identify the target biological object; the initial identification information is encrypted to obtain target identification information; and the target identification information is uploaded to the blockchain. That is, in the embodiment of the present application, the product attribute information of the target biological object is collected, and based on the product attribute information, the initial identification information is constructed. The initial identification information can be used to realize the construction of the data value chain of "production-circulation-supervision-consumption", and the state between the target biological object and the virtual object in the blockchain is bound, so as to achieve the purpose of constructing a self-evolving trusted traceability ecological system. The technical problem of being unable to construct a full-link trusted traceability ecological system in the blockchain is solved, and the technical effect of being able to construct a full-link trusted traceability ecological system in the blockchain is realized.

[0064] The above method of the embodiment will be further introduced below.

[0065] As an optional implementation, in step S104, based on the product attribute information, the initial identification information of the target biological object is generated, including: converting the product attribute information to obtain a first identification code corresponding to the target biological object, wherein the first identification code is used to determine the growth data of the target biological object; determining a first object used to produce the target biological object from the product attribute information; obtaining first identity information of the first object, and converting the first identity information to obtain a second identification code corresponding to the target biological object, wherein the second identification code is used to determine the production qualification required for the first object to produce the target biological object; determining second identity information of a second object supervising the first object, and converting the second identity information to obtain a third identification code corresponding to the target biological object, wherein the third identification code is used to determine the calling data authority of the second object; and combining the first identification code, the second identification code and the third identification code to obtain the initial identification information.

[0066] In this embodiment, the first identification code described above can be a product code, which can be used to determine at least the growth data of the target biological object. For example, it can be a "blockchain+NFT" dual code generated for each batch of agricultural products, which can be used to store real growth data hash values such as planting environment, processing parameters, logistics track, etc. The first object described above can be an object that produces the target biological object, such as an enterprise or a processing plant that produces the target biological object. The first identity information described above can be used to determine the identity of the first object, and can be used to record the name, enterprise qualification, quality inspection report, and supply chain cooperation relationship of the first object. The second identification code described above can be an enterprise code, which can be used to record the production enterprise qualification, quality inspection report, and supply chain cooperation relationship, and can be associated with the product code to form an enterprise traceability file, and the credit score is dynamically adjusted by user evaluation and supervision data. The second object described above can be an object that supervises the first object, which can be a regulatory department. The second identity information described above can be a special code corresponding to the second object, which can be used to determine the identity of the second object, and can include but not limited to: unit code, unit number, etc. The third identification code described above can be a supervision code, through which the second object can real-time access the full-chain data, trigger the smart contract to automatically issue early warning (such as freezing sales within 10 minutes when pesticide residues exceed the standard), and synchronize the virtual fruit state. It should be noted that the above is only an example, and the representation of the first identification code, the type of the first object, the type of the second object, the content of the first identity information, the content of the second identity information, the representation of the second identification code, and the representation of the third identification code are not specifically limited.

[0067] Optionally, after obtaining the product attribute information, the product-related information such as product category and product growth condition in the product attribute information can be converted to obtain the first identification code, and the first object for producing the target biological object can be determined from the product attribute information. Based on the first identity information of the first object, the second identification code can be obtained. The second object that supervises the first object can be determined, and the second identity information of the second object can be obtained. The third identification code can be obtained by converting the second identity information. The initial identification information described above can include the first identification code, the second identification code, and the third identification code.

[0068] As an optional implementation, the method can further include: in response to the existence of a third object that trades the target biological object in the blockchain, obtaining third identity information of the third object, and converting the third identity information to obtain a fourth identification code corresponding to the target biological object, wherein the fourth identification code is used to represent the trading behavior of the third object; and associating the identification information with the fourth identification code.

[0069] In this embodiment, after the initial identification information is constructed, the initial identification information can be associated with a third object. In the blockchain, when the third object purchases the target biological object, third identity information of the third object can be obtained. The third identity information is converted to obtain a fourth identification code corresponding to the target biological object. The third object can be a consumer object, and can be a consumer who purchases the target biological object. The fourth identification code can be used to represent the identity of the third object, and can be used to represent the transaction behavior of the third object, that is, the fourth identification code can be used to process the transaction behavior of the third object to obtain an identification code, which can be a user code. The third identity information can include an identity code of the third object, a consumption single code, and the like, and can be used to determine the object that purchases the target biological object. It should be noted that this is only an example, and the content contained in the third identity information is not specifically limited.

[0070] Optionally, when the third object purchases the target biological object, a fourth identification code can be generated based on third identity information of the third object. The fourth identification code can be used to represent the transaction behavior of the third object in purchasing the target biological object, and can be used to determine the purchase quantity, the purchase time, and the like, and can be a user code. The user code can be associated with the initial identification information to achieve the purpose of four-code linkage.

[0071] In this embodiment, the product code, the enterprise code, the supervision code, and the user code realize the collaborative mechanism of data intercommunication and state synchronization through the smart contract, and contain a bidirectional hash mapping relationship of the product code NFT and the virtual fruit NFT.

[0072] Optionally, after the consumer scans the code, a unique user code (that is, a fourth identification code) is generated, the interaction behavior (such as virtual farm planting data and evaluation) is recorded, and the authenticity of the product code NFT is verified when the offline coupon is exchanged. The SHA-256 (device identification + random number) algorithm can be used to desensitize the original user information (such as a mobile phone number and an identity card number) when the user code is generated, only the hash value after desensitization is stored on the chain, and the original information is locally encrypted and stored.

[0073] Optionally, the four codes realize the whole process of cross-node communication and virtual-real data synchronization through the smart contract. Taking the scenario of excessive pesticide residues as an example, the linkage of the product code NFT freezing and the virtual fruit NFT withering state is highlighted, and the dynamic association of data triggering, contract execution, state change, and permission adjustment is realized.

[0074] In this embodiment, code generation is the premise of the linkage mechanism. The product code and the enterprise code are quickly generated through the SaaS platform to ensure that the coding rules are unified. The product code, the enterprise code, the supervision code, and the user code obtained through one-key code generation do not exist in isolation, but realize bidirectional mapping of physical data and virtual interaction through the following smart contract driven linkage mechanism.

[0075] Table 1 is a function table of four codes. As shown in Table 1, the product code can be used to store the real growth data hash. The technical implementation can be: blockchain+NFT double code, associated alliance chain sub-chain. The enterprise code can be used to determine the dynamic credit score of the first object. The dynamic credit score can be affected by evaluation. When the credit score is less than or equal to the target value (for example, 70), the application of related projects of the first object can be limited. The regulatory code can be used to real-time call regulatory data and trigger early warning. The real-time call of data can be completed by calling a function (for example, the checkPesticideLevel() function). The user code can be used to record interactive behavior and verify product authenticity. The consumer (i.e., the third object) can be bound to a virtual fruit NFT, and the rights and interests can be exchanged on the chain.

[0076] Table 1 Function table of four codes

[0077]

[0078] As an optional implementation, the method can further include: obtaining virtual identification information corresponding to the target biological object in the blockchain, wherein the virtual identification information is used to represent a virtual object corresponding to the target biological object in the blockchain; and constructing a mapping relationship between the virtual identification information and the target identification information by using a target program in the blockchain.

[0079] In this embodiment, the virtual identification information of the target biological object in the blockchain can also be obtained. The virtual identification information can be a virtual fruit NFT, and can be used to represent a virtual object corresponding to the target biological object in the blockchain. By using a target program in the blockchain, a mapping relationship between the virtual identification information and the target identification information can be constructed. The target program can be a smart contract.

[0080] Optionally, when there is a virtual object corresponding to the target biological object in the blockchain, a virtual identification information corresponding to the virtual object can be constructed. The virtual identification information is associated with the product code in the target identification information, so as to achieve the purpose of constructing a mapping relationship between the virtual identification information and the target identification information. That is, the product code and the virtual fruit NFT can be bound by the smart contract, so that the virtual fruit state changes when the real product data is updated.

[0081] Optionally, the four codes realize collaborative interaction through virtual-real synchronization, dynamic adjustment of authority, and user feedback closed loop. The virtual-real synchronization refers to binding physical world data and virtual world performance, allowing users to perceive data authenticity through visual interaction, providing a reliable data foundation for authority adjustment and user feedback. Dynamic adjustment of authority is based on dynamic adjustment of enterprise code credit score to adjust production authority, ensuring that untrustworthy data producers are constrained and the data quality of virtual-real synchronization is reversed. The user feedback closed loop refers to the evaluation feedback of users through virtual interaction, which is analyzed by NLP to drive production data optimization. The optimization results update the virtual state through virtual-real synchronization, and at the same time affect the enterprise code credit score, triggering authority adjustment (such as credit score recovery if optimization meets the standard).

[0082] Optionally, the above-mentioned supervision collaboration and smart contract module formulates smart contract rules to realize automatic processing of pesticide residue early warning, logistics temperature control traceability, etc. It provides real-time data dashboard for regulatory departments, shortens food safety incident investigation time, and improves regulatory efficiency.

[0083] Figure 3 According to an embodiment of the present application, a flowchart of a supervision code triggering virtual-real synchronization is shown in Figure 3 The supervision code triggering virtual-real synchronization flowchart can include the following steps:

[0084] Step S301, upload target identification information to the smart contract.

[0085] In this embodiment, the target identification information can be a two-dimensional code containing a hash value. It can include product code NFT, which can be used to represent environmental data, timestamp, device identity information, etc. The target identification information can be uploaded to the smart contract, which can be an automated program.

[0086] Optionally, upload hash H1 = SHA-256 (environmental data + timestamp + device ID).

[0087] Step S302, upload virtual identification information to the smart contract.

[0088] In this embodiment, a virtual fruit NFT can be uploaded to the smart contract. The virtual fruit NFT can be virtual identification information corresponding to a virtual object, which can be used to represent user behavior, evaluation object, random number, etc.

[0089] Optionally, upload hash H2 = SHA-256 (user behavior + evaluation ID + random number).

[0090] Step S303, calculate the cosine similarity.

[0091] In this embodiment, a random number salt is introduced to prevent collision, and a verifyHashMapping() function is used to calculate the cosine similarity between the product code NFT in the target identification information and the virtual identification information (i.e., the virtual fruit NFT).

[0092] In step S304, if the similarity is greater than or equal to a preset value, it is determined that the verification is passed.

[0093] In this embodiment, if the similarity is greater than or equal to a preset value (for example, 90%), it can be determined that the verification is passed, and "verification passed" can be displayed on the user end.

[0094] In step S305, if the similarity is less than the preset value, a warning can be sent.

[0095] In this embodiment, if the similarity is less than the preset value, a warning message can be sent to the supervision end, i.e., the customer terminal of the second object, and the warning message can include the comparison result between the target identification information and the virtual identification information.

[0096] As an optional implementation, the method can further include: in response to a change in the environment in which the target biological object is located, collecting environmental change data; using the target program, adjusting the virtual object according to the environmental change data, and determining the terminal device associated with the target identification information; and displaying the adjusted virtual object in the terminal device.

[0097] In this embodiment, if the living environment of the target biological object changes (i.e., the environment in which it is located changes), environmental change data can be collected. Using the target program, the virtual object displayed in the blockchain can be adjusted according to the environmental change data, and the terminal device associated with the target identification information can be determined. The terminal device can be a computer, a mobile terminal, etc. It should be noted that this is only an example and the type of mobile terminal is not limited. Further, the adjusted virtual object can be displayed in the terminal device. The living environment can include, but is not limited to, soil humidity, environmental humidity, etc. It should be noted that this is only an example and the type of living environment is not limited.

[0098] Optionally, a mapping between the product code NFT and the virtual fruit NFT is constructed. When a watering event occurs in the real farm, the edge node collects relevant data (which can be environmental change data), the product code NFT updates the growth hash value, then the smart contract triggers the virtual fruit NFT to increase the moisture value by 10%, and then the user code receives an interaction notification, thereby forming a "real operation-virtual feedback" closed loop.

[0099] As an optional implementation, the method can further include: in response to an abnormal change in the growth state of the target biological object, prohibiting the first identification code in the target identification information from being changed, and adjusting the display result of the virtual object according to the change result of the target biological object by using the target program.

[0100] In this embodiment, the supervision code triggers virtual-real synchronization. If the growth state of the target biological object changes abnormally, the first identification code in the target identification information can be prohibited from being changed, and the display result of the virtual object can be adjusted according to the change result of the target biological object by using the target program. That is, the display in the virtual object can be adjusted according to the real-time change of the target biological object.

[0101] For example, when the detection data exceeds the standard (such as 0.5 mg / kg), the supervision code can freeze the product code, the smart contract calls the virtual farm contract, and the virtual fruit NFT presents a "withering" state. The user can scan the code to synchronously view the real detection report and the virtual warning icon, and the perception of risk is strengthened.

[0102] Figure 4 is a flowchart of a data screening strategy according to an embodiment of the present application, as shown in Figure 4 The data screening strategy can include the following steps:

[0103] Step S401, the original sensor collects environment change data or growth state data of a target growth object.

[0104] In this embodiment, the original sensor collects environment change data or growth state data of a target growth object to obtain an original sensor data stream. The growth state data can be used to determine the growth state of the target biological object and the change in the growth state.

[0105] Step S402, judging the data type of the original sensor data stream.

[0106] In this embodiment, the data type of the original sensor data stream is judged. If the environment change data is an environment parameter, step S403 is executed, and if the environment change data is a process parameter (such as a growth process parameter), step S404 is executed.

[0107] Step S403, threshold comparison of the environment change data.

[0108] In this embodiment, if the environment change data exceeds the change threshold, the data is uploaded in real time, and if the change threshold is not exceeded, the environment change data is locally cached.

[0109] Step S404, threshold comparison of the change rate.

[0110] In this embodiment, growth data during the growth process can be acquired, and the growth data can be processed to obtain a change rate. The change rate can be used to determine the growth of the target biological object, and it can be determined whether the change rate exceeds a change threshold. If it exceeds, it can be uploaded in real time, and if it does not exceed, it can be summarized and uploaded in real time.

[0111] As an optional implementation, the method can further include: in response to the credit score of the first object being less than or equal to a target value, stopping generating identification information of the biological object produced by the first object.

[0112] In this embodiment, if the credit score (i.e., credit score) of the first object is less than or equal to a target value, the identification information of the biological object produced by the first object can be prohibited. The target value can be a pre-set value, such as 70. It should be noted that this is only an example and the size of the target value is not limited.

[0113] Optionally, the dynamic adaptation of the right is realized through the cooperative interaction of the product code, the enterprise code, the supervision code, and the user code. Here, the enterprise code credit is taken as the benchmark, the supervision code intervention is taken as the constraint, the product code generation is taken as the target, and the user code perception is taken as the feedback to build a linkage logic. The following table is an embodiment of the present application:

[0114] Table 2 Linkage logic table

[0115]

[0116] As shown in Table 2, the on-chain storage location is the storage location of the enterprise credit score. When the credit score corresponding to the enterprise code is less than or equal to 70 points, there is no product code generation right, the supervision node intervenes, and the on-chain storage location is the right adjustment block. When the credit score corresponding to the enterprise code is between 70 and 79, the enterprise has the right to generate the product code, which needs to be manually audited, and the on-chain storage location is the right adjustment block. When the credit score corresponding to the enterprise code is greater than or equal to 80 points, the product code can be automatically generated without corresponding right requirements.

[0117] In this embodiment, when the enterprise code credit score is less than or equal to 70 points, the PermissionCheck contract is triggered. Subsequently, the blockchain system can send a request to the regulator node containing the enterprise's identifier (ID) and product batch regulator signature. After receiving the request, the regulator node signs using the regulator public key (RegulatorPubKey), and the signature information is written into the "permission adjustment block", which also contains the signature time and node ID. After completing the above process, the product code is generated and takes effect; if the signature is not obtained, the related transaction will fail.

[0118] Optionally, when the credit score is less than or equal to 70 points, the product code generation transaction triggers the credit check (creditCheck()) contract, which forces the regulator node to sign; the signature record is stored in the "permission adjustment block", and the credit score is restored to 80 points after the permission restoration function (restorePermission()) is automatically executed. When the enterprise code credit score is greater than or equal to 80 points but the regulator code is still in the frozen state, the smart contract automatically calls the smart contract function (arbitratePermission(enterpriseCode, productCode) function), which automatically detects the permission conflict every 30 minutes. If the credit score update time is later than the freeze instruction time and there is no manual locking instruction from the regulator node, the freeze is automatically lifted (the priority of the regulator instruction is higher than that of the credit score rule), the virtual fruit NFT state is updated to "normal", and the arbitration result is pushed to the regulator node. If the arbitration fails for 3 consecutive times (e.g., the regulator node does not respond), the manual intervention process is triggered, the arbitration failure log is recorded on the chain, and a "manual appeal required" notification is pushed to the enterprise end.

[0119] Figure 5 According to an embodiment of the present application, a four-code linkage process system diagram is shown in FIG. 4, which can include the following steps: Figure 5

[0120] Step S501: Upload the over-standard data and call the function.

[0121] In this embodiment, the regulator code node can upload the over-standard data to the smart contract and call the checkPesticideLevel() function.

[0122] Step S502: Perform the freezing operation.

[0123] In this embodiment, the smart contract can perform the product code NFT freezing operation (updataStatus(”FROZEN”).

[0124] ​Step S503, deduct the credit score.

[0125] In this embodiment, the smart contract deducts the credit score and transmits the deducted credit score to the enterprise code for storage.

[0126] Step S504, synchronize the state.

[0127] In this embodiment, the smart contract can synchronize the state value in the virtual fruit NFT.

[0128] Step S505, display the withering icon and the over-standard display.

[0129] In this embodiment, the virtual fruit NFT can display the withering icon and the over-standard display on the user end.

[0130] Step S506, return the current credit score.

[0131] In this embodiment, after the enterprise code obtains the deducted credit score, it can determine the current credit score after the credit score is deducted, and can return the current credit score to the smart contract.

[0132] Step S507, return the execution result.

[0133] In this embodiment, the smart contract can return the execution result to the regulatory code node, and the execution result can be freeze success, delay 1.2 seconds.

[0134] As an optional implementation, the method can further include: obtaining evaluation information of a third object on the target biological object; extracting a keyword in the evaluation information and determining weight data corresponding to the keyword, wherein the weight data is used to represent the importance of the keyword in the third object's evaluation of the use of the target biological object; and determining an adjustment parameter of the target biological object based on the weight data and the keyword, wherein the adjustment parameter is used to adjust the production environment of the target biological object.

[0135] In this embodiment, the evaluation information can be the evaluation of the third object on the target biological object, such as evaluation information such as too small, too dry, etc. The keyword can be extracted from the evaluation information and can be used to represent the emotional color of the third object. The weight data can be used to represent the importance of the keyword in the third object's evaluation of the target biological object, such as the weight data corresponding to the keyword "very dry" being 0.8, because this word can represent the third object's evaluation of the target biological object. The adjustment parameter can be used to adjust the production environment of the target biological object, such as being used to adjust the precipitation, temperature, etc. of the target biological environment. It should be noted that this is only an example and the content of the evaluation information, the content of the keyword, the size of the weight data, and the content of the adjustment parameter are not limited.

[0136] Optionally, the NLP-driven user interaction module: develops a virtual farm game, synchronizes virtual crop growth data with real farms, and improves user engagement and dwell time; analyzes user comments using NLP algorithms, generates indices and feeds back to businesses and planting bases, and realizes user evaluation-driven supply chain optimization.

[0137] Optionally, after the target identification information is generated, four-code cooperation is realized through virtual-real synchronization and permission adjustment, and user interaction data is analyzed by NLP to benefit production. In the NLP-driven user interaction module, NFT as a trust bridge: product code NFT stores real growth data hash values (such as soil moisture, test reports), virtual fruit NFT records user interaction behavior (such as watering operations, evaluation data), and through smart contract realizes double-NFT state synchronization (delay < 2 seconds). Gamification as an interactive carrier: users plant crops through virtual farms, and their watering, fertilizing, and other operation data are real-time chained to form user behavior hash values stored in virtual fruit NFT; NLP as an optimization engine: analyzing user evaluation text, which can be evaluation information, such as the evaluation text can be sour taste, based on the evaluation information, the corresponding adjustment parameters can be generated, such as the adjustment parameter can be the fertilizer ratio adjustment suggestion, such as the nitrogen fertilizer ratio from 20% to 15%. After obtaining the adjustment parameters, they can be pushed to the production end device through the smart contract, and at the same time affect the enterprise code credit score.

[0138] Optionally, real data drives virtual interaction, after the edge node collects the watering event of the real farm, the product code NFT updates the growth hash, which will trigger the smart contract to increase the moisture value of the virtual fruit NFT by 10%, and finally the user applet will display the growth state of the crop, that is, when the edge node collects the real event of the target biological object, it can update the growth hash of the target biological object based on the event. In response to the growth hash of the target biological object being updated, triggering the smart contract to adjust the growth parameters of the virtual object.

[0139] Optionally, virtual behavior verifies real data, when the user's virtual watering frequency exceeds 5 times a week, the smart contract will retrieve the data of the real soil moisture sensor, and the delay of this process does not exceed 1.2 seconds. If the detected humidity is less than 30%, the irrigation system will be triggered to supplement water, and the user will be rewarded with NFT points, which can be used to exchange offline coupons.

[0140] Optionally, product code NFT hash generation: SHA-256 (soil humidity + temperature + fertilization amount + salt), where salt is a 32-bit random number randomly generated by the alliance chain, updated every 24 hours; virtual fruit NFT hash generation: SHA-256 (watering frequency + evaluation ID + salt), verified by the verifyHashMapping() contract with the product code NFT, and a matching degree of ≥ 90% is considered valid. Consistency verification: when the user scans the code, the mapping relationship of the two NFT hash values is compared, and a matching degree of < 90% is an abnormality. Anti-collision mechanism, on-chain daily checkHashCollision contract, collision detection on all hash values, trigger regulatory warning when abnormal.

[0141] In this embodiment, NLP and NFT decision linkage are performed, the user evaluation text is collected first to obtain evaluation information. Then the uploading operation is completed through the Hypertext Transfer Protocol Secure (HTTPS) interface, and then the Term Frequency-Inverse Document Frequency (TF-IDF) and pre-training language model (BERT) technology are used for analysis, and the targeted suggestion (SCAN) is generated based on the analysis result, which can be an adjustment parameter. Further, the smart contract can be triggered to execute the adjustment action of the production equipment according to the contract, and finally the operation record is stored on the chain.

[0142] Optionally, Figure 6 is a flowchart of an NLP and NFT decision linkage process according to an embodiment of the present application, as Figure 6 shown, the NLP and NFT decision linkage process can include the following steps:

[0143] Step S601, user game interaction.

[0144] In this embodiment, the user (i.e., the third object) can adjust the growth environment of the virtual object to achieve the purpose of game interaction.

[0145] Step S602, virtual fruit NFT update.

[0146] In this embodiment, based on the user's operation, the change of the virtual object can be determined, and based on the change of the virtual object, the virtual identification information can be adjusted.

[0147] Step S603, smart contract comparison of double NFT data.

[0148] In this embodiment, the smart contract compares the double NFT data, i.e., the product code in the target identification information and the virtual identification information are compared by using the smart contract.

[0149] Step S604, obtaining NLP analysis evaluation.

[0150] In this embodiment, the text evaluation (such as "fruit sweetness is insufficient" "acidity is too high" and the like) submitted by the consumer in the virtual farm game or evaluation interface is transmitted to the NLP analysis engine after being encrypted through the HTTPS protocol to ensure the security of the evaluation data in the transmission process.

[0151] Optionally, the NLP engine can extract keywords in the evaluation information by using the TF-IDF algorithm, such as "sweetness" "acidity" and the like, and calculate the weight data corresponding to the keywords. In combination with the pre-training model (such as BERT), the sentiment tendency is determined, and finally the quantitative production optimization suggestions (such as "increase the amount of potassium fertilizer application" "reduce the proportion of nitrogen fertilizer" and the like) and NFT parameter adjustment values are generated to obtain the adjustment parameters, which can include the production optimization suggestions and the NFT parameter adjustment values.

[0152] Optionally, the model is trained based on a plurality of labeled corpora (covering 120+ industry terms such as "pesticide residues" "taste is too hard" and the like), and when the number of newly added evaluations reaches 20,000 or the model accuracy is <92%, incremental training is triggered, and after training, the model can be verified through 3 supervision nodes before being deployed. The analysis logic is optimized for different food categories: fruit class strengthens the identification of keywords such as "sweetness" "acidity" "fruit aroma" and the like; vegetables focus on "freshness" "crispness" "pesticide residues"; meat highlights "tenderness" "fishy smell" "shelf life", and respectively establishes a category-specific corpus. It should be noted that the size of the above-mentioned numbers is only for illustration, and is not specifically limited here.

[0153] Optionally, after obtaining the evaluation information, the keywords in the evaluation information and the weight corresponding to the keywords can be extracted by using the TF-IDF algorithm. In combination with the pre-training model, the weight data and the keywords are identified to obtain the adjustment parameters of the current target biological object.

[0154] In this embodiment, if optimization of the target biological object is required, the NLP engine can push the generated optimization suggestions in a structured format (such as JSON) to the blockchain smart contract. The analysis results need to be verified by 3 regulatory nodes through the verifyNLPResult(resultHash) function signature verification. After verification, the NLP (Result) results are written to the on-chain contract, triggering the updateProductionParam function and the updateNFTByNLP function. The smart contract updateNFTByNLP executes an atomic transaction. If the NFT state update fails (such as chain congestion causing timeout), a revert operation is automatically triggered to roll back the previous state, and the retryNFTUpdate(nftId, result) function is used to retry (up to 3 times). If the retry fails, an early warning message is sent to the regulatory nodes, and the production end needs to adjust the parameters.

[0155] Optionally, in the "smart contract call", the optimization suggestions generated by the NLP engine (such as "reduce the proportion of nitrogen fertilizer") are first converted into specific numerical parameters (such as a 5% reduction in the proportion of nitrogen fertilizer). The smart contract receives and parses it into production equipment recognizable instructions (including device ID and adjustment value), pushes it to the edge node through the MQTT protocol, and then converts it into a hardware control signal to trigger automatic adjustment of the equipment. After the equipment executes, the results (such as the actual adjustment proportion) are fed back to the edge node and uploaded to the smart contract after encryption. After the contract verifies that the deviation is within a reasonable range, the results are written to the product code NFT and the virtual fruit NFT state is updated, allowing users to view the optimization effect in real time and achieve a closed loop from user evaluation to production adjustment. Chain execution example: user evaluation "obvious lack of sweetness" is analyzed by NLP to get the keyword "lack of sweetness" (weight 0.8), sentiment value -0.3. After the smart contract calls updateNFTByNLP, the "sugar content" of the corresponding virtual fruit NFT is reduced from 80 to 75, and the chain event NFTUpdated records the adjustment results (including block height, before and after adjustment values).

[0156] Optionally, the complete on-chain process of NLP and NFT linkage can include: user evaluation uploaded to the NLP engine through HTTPS, generating a JSON result containing keywords, weights, and sentiment values (such as {"keyword": "insufficient sweetness", "weight": 0.8, "sentiment": -0.3}). The result is signed by three regulatory nodes and stored in the transaction format {"from": NLP node, "to": nlpResult contract, "data": result hash} on-chain. The smart contract updateNFTByNLP monitors the state change of the nlpResult contract, automatically executes parameter adjustment (such as sugar content = 80 + (-0.3 x (-16.7)) = 75), and triggers the NFTUpdated event. The analysis result needs to be verified by the three regulatory nodes through the verifyNLPResult(resultHash) function signature, and after verification, it is written to the nlpResult on-chain contract, triggering the updateProductionParam function and the updateNFTByNLP function.

[0157] Step S605, determine whether optimization is needed.

[0158] In this embodiment, the adjustment parameters are confirmed to determine whether optimization is needed for the target biological object. If not, step S606 can be performed. If yes, step S607 can be performed.

[0159] Step S606, user continuous interaction.

[0160] In this embodiment, if the target biological object does not need to be optimized, the user's operation data on the virtual object can be continuously obtained.

[0161] Step S607, production end optimization.

[0162] In this embodiment, the smart contract instruction is synchronized to the production end device (such as a smart irrigation system, a fertilizer application machine), and the device automatically adjusts the operation parameters (such as increasing the potassium fertilizer application amount from 30 kg / acre to 35 kg / acre) according to the instruction. The production record (productionRecord) field of the production record is in a standardized data exchange format.

[0163] Optionally, the adjustment operation and result of the production end device (such as the actual fertilizer application amount, the execution time) are recorded in real time and a hash value is generated, which is written into the `productionRecord` field of the product code NFT, ensuring that the production adjustment process is traceable.

[0164] Step S608, product code NFT records optimization data.

[0165] In this embodiment, the NFT state synchronization, the product code NFT synchronizes the production adjustment record to the virtual fruit NFT, and the virtual fruit NFT state is updated to "optimizing" (a progress bar can be displayed, and the progress is bound to the production end operation completion rate), so that the user can intuitively perceive the production optimization progress.

[0166] Optionally, the whole process forms a closed loop of "user evaluation, data analysis, production adjustment, and state feedback", realizes the direct driving of user feedback to actual production, and enhances the sense of participation and trust of users in the optimization process through the state synchronization of NFT.

[0167] In this embodiment, the NLP model training can be training a BERT model based on 100,000+ labeled corpus (including "pesticide residues" and "taste" terms), incremental training with new evaluations every month, and when the accuracy is ≥92%, automatically deploy to the chain.

[0168] Optionally, after the NFT state is updated, the smart contract can call the pushNFTUpdate(userCode, nftId, oldValue, newValue) function to push the NFT update (user code, NFT identification, old value, new value) through the device bound by the user code (based on the WebSocket protocol to realize real-time pop-up window, content example: "The sugar content of the strawberry virtual fruit you follow has been adjusted from 80 to 75, click to view details").

[0169] For example, a batch of strawberries is triggered for optimization due to user evaluation "high acidity", NLP extracts the keyword "acidity" (weight 0.8), and generates the suggestion "nitrogen fertilizer ratio from 20% to 15%". The smart contract pushes the instruction to the irrigation system, the fertilizer amount is adjusted to 25 kg / acre, and the record is recorded on the chain to the product code NFT. The virtual fruit NFT synchronously displays "optimization completed", the original evaluation user scans the code to view the adjustment record, and obtains 10 points of NFT growth value.

[0170] Optionally, Table 3 is a table of NLP analysis results and virtual fruit NFT parameter mapping rules, as shown in Table 3. It should be noted that the content in Table 3 is only an example, and the mapping rules can be adjusted according to the actual situation.

[0171] Table 3 NLP analysis results and virtual fruit NFT parameter mapping rule table

[0172]

[0173] Step S609, the user scans the code to verify the optimization effect.

[0174] In this embodiment, the trusted association between physical data and virtual interaction is established through double NFT hash mapping, and the automatic conversion of user feedback to production optimization is realized through the linkage of NLP and NFT decision-making. After the production end completes the optimization, the evaluation user can trace the optimization whole process through the hash matching mechanism, and more users can perceive the ecological value through information pushing and benefit incentive. Finally, the technical achievements of production optimization are converted into commercial value trusted by users. Specifically, consumers (users), production enterprises and regulatory departments realize data interconnection, value exchange and responsibility sharing through user verification process and benefit exchange verification, forming a commercial ecological closed loop with user participation incentive, enterprise operation trust and regulatory governance basis.

[0175] Optionally, if the feedback evaluation user and the code scanning verification user are the same subject (through user code matching), the blockchain system (hereinafter referred to as the system) generates a verification hash through SHA-256 (product code + user code + timestamp + salt), and compares it with the user evaluation hash stored on the chain (the generation logic of the user evaluation hash: when the user submits the evaluation content (such as "fruit sweetness is insufficient" "acidity is too high" etc.), the system will extract the evaluation text, user code (unique identifier of the user), evaluation submission timestamp and random number, and perform encryption operation on these information through SHA-256 hash algorithm, finally generate a unique hash value, which is the user evaluation hash. This hash value can be used as the digital fingerprint of the evaluation content, which can be used for subsequent association verification with product code NFT and virtual fruit NFT, to ensure the integrity and non-tamperability of the evaluation data. If the matching degree is ≥95%, the verification is passed.

[0176] Optionally, after the verification is passed, the user code, product code (getRelatedData) interface is automatically called to retrieve the associated on-chain data of the original evaluation record and the production end optimization data, and the product code (productCode) field is associated with the optimization history (optimizeHistory) on-chain table. This table can store optimization record ID (optimizeID), product code before optimization (oldProductCode), adjustment parameter (adjustParams) and optimization timestamp (timestamp).

[0177] Optionally, the association of the original product code with the optimization data is valid for 12 months, and after expiration, the data is automatically archived to the history archive record (historyArchive) chain table associated with the enterprise code. Users can call the product code through the "history traceability" portal and query the enterprise code (queryArchivedData) interface. The interface permission rule is that consumers can only query the product data associated with their own user code, enterprises can query all archived data of the enterprise, and regulatory departments can query all archived data of all enterprises (need to carry regulatory digital signature). When a user queries the optimization record through the original product code, the system automatically calls the product code (getHistory) interface and returns the optimizeHistory table. The interface realizes query through the on-chain association path of product code, enterprise code, and optimizeHistory. The response delay is <1 second. The traceability association of the original product code and the optimization data is visually displayed on the "optimization record" page, and real-time detection data is provided for comparison. If the hash matching degree is <95%, the system automatically triggers the abnormal verification (abnormalVerify()) function, sends an early warning message (including product code, user code, and timestamp) to the regulatory node, and at the same time, the user end displays a "data verification exception" prompt, with the contact information of the regulatory node and the on-chain data snapshot comparison portal (supports viewing the last 3 times of on-chain record).

[0178] If they are different subjects, the system pushes optimization notifications (including product code blockchain address and DApp link) to the device bound to the user code (such as mobile phone APP, applet) based on MQTT protocol. After the user clicks the link, the DApp automatically connects the alliance chain node to verify the validity of the product code. The DAPP displays information in three levels (optimization summary, on-chain hash, regulatory signature), and at the same time, rewards 10 points of virtual fruit growth value to encourage attention.

[0179] Step S610, determine whether the verification is passed.

[0180] In this embodiment, it is determined whether the verification is passed, if not, step S611 can be performed, and if yes, step S601 can be performed.

[0181] Step S611, feedback to the production end for secondary optimization.

[0182] In this embodiment, the user can also redeem the rights and verify the redemption. When the user redeems, the verifyRedeem smart contract checks that the matching degree of the two NFT hashes is greater than or equal to 95%, and generates a redemption voucher containing a timestamp. The user can complete the redemption by scanning through a mobile terminal, and the record is written into the redemptionRecord table on the chain. The virtual fruit NFT right type and redemption rules are as follows: 100 points of growth value can redeem a 5-yuan offline coupon, 500 points can redeem a 9-yuan product coupon, and 1000 points can unlock the "priority purchase of new products" right (valid for 30 days). After the rights are redeemed, the growth value is automatically deducted and recorded on the chain.

[0183] The four-code linkage mechanism of the present application is combined with the NFT virtual fruit game to achieve multi-dimensional trust enhancement. At the data level, the product code and the virtual fruit NFT are bound through the smart contract, and when the real product data is updated, the virtual fruit state changes accordingly, and vice versa. The user can scan the code to verify the consistency of the real data and confirm that the real data has not been tampered with. At the user participation level, the virtual fruit can be exchanged for entity rights, and the user's operation when redeeming the rights is automatically recorded on the chain as a supplementary proof of the product code. The evaluation can also affect the relevant indices of the product code, enhancing the user's attention to data and participation, and further deepening the credibility of the traceability chain. The product code NFT is a digital mirror of the physical product (storing real data hashes), and the virtual fruit NFT is a digital mapping of user participation (recording interaction behavior data). The two form a "physical state-user behavior" twin relationship through the smart contract, breaking through the limitations of existing technologies "data storage ≠ user participation". Through blockchain and four-code linkage technology, the data is traced, which can significantly shorten the average verification time of food safety incidents. The use of NFT combined with virtual games improves the user's trust in data, and the use of natural language analysis to obtain user feedback from virtual games makes the system adaptable to dynamic changes.

[0184] Figure 7 is a flowchart of a double NFT hash mapping process according to an embodiment of the present application, as shown in Figure 7 The double NFT hash mapping can include the following steps:

[0185] Step S701, product code NFT hash generation.

[0186] In this embodiment, the product code NFT containing the hash can be uploaded to the smart contract. The hash data can include soil moisture, temperature, timestamp, etc.

[0187] Optionally, upload the hash (SHA-256 (soil moisture + temperature + timestamp)).

[0188] Step S702, virtual fruit NFT hash generation.

[0189] In this embodiment, the virtual fruit NFT can be uploaded to the smart contract.

[0190] Optionally, the hash (SHA-256 (user code + interaction behavior)) is uploaded.

[0191] Step S703, verify the matching degree.

[0192] In this embodiment, the virtual fruit NFT hash is generated: SHA-256 (user code + interaction behavior), and the product code NFT is verified by the verifyHashMapping() contract. A matching degree of ≥ 90% is considered valid.

[0193] Step S704, if the matching degree is ≥ 90%, it is displayed that the verification is passed, otherwise an alarm is given.

[0194] In this embodiment, the smart contract is used to compare the mapping relationship of the two NFT hash values. If the matching degree is ≥ 90%, it is displayed that the verification is passed, and if the matching degree is < 90%, an exception is prompted. The prompt information can be output to the user end.

[0195] In this embodiment, the dynamic permission chain is executed on the chain, the credit score is strongly bound with the product code permission, the supervision signature is stored in the "permission adjustment block", and the traceability is ensured. The NLP parameterization is driven, the evaluation keyword weight is directly converted into the production parameter, and the "evaluation-production" automatic closed loop is formed.

[0196] In this embodiment, a food full-link trusted traceability ecology is constructed to solve the trust fracture problem caused by the data island of the traditional traceability system. Through the four-code linkage mechanism of product code, enterprise code, supervision code and user code, combined with blockchain and NFT technology, the data value chain construction of "production-distribution-supervision-consumption" is realized. The smart contract is used to bind the virtual fruit and the real product state, so that the user can verify the data authenticity through interaction, and form an "evaluation-production" optimization closed loop. At the same time, with the help of edge computing and lightweight SaaS, the technical threshold is reduced, and finally the consumer trust degree is improved, the supervision efficiency is strengthened, the industry efficiency is driven, and a self-evolving trusted traceability ecological system is constructed.

[0197] Figure 8 According to an embodiment of the present application, a food full-link trusted traceability ecological chain is shown in the schematic diagram of Figure 8 As shown, the supervision code node can upload the exceeding standard data, and the smart contract can execute the product code freezing, deduct the enterprise credit score, and control the process of withering of the virtual fruit (i.e. virtual object). The product code freezing can be to adjust the permission of the product code to only query.

[0198] Optionally, the enterprise credit score is deducted to achieve the purpose of limiting the enterprise to apply for related projects.

[0199] Optionally, a complaint entry can also be added for the user code.

[0200] Optionally, the data can be synchronized to a full node.

[0201] In the embodiment of the present application, the product attribute information of the target biological object is collected, and the initial identification information is constructed based on the product attribute information. The initial identification information can be used to construct a data value chain of "production-circulation-supervision-consumption", and bind the state between the target biological object and the virtual object in the blockchain, so as to achieve the purpose of constructing a self-evolving trusted traceability ecological system, solve the technical problem that the full-link trusted traceability ecology in the blockchain cannot be constructed, and achieve the technical effect that the full-link trusted traceability ecology in the blockchain can be constructed.

[0202] According to the embodiment of the present application, a data processing device is also provided. It should be noted that the data processing device of this embodiment can be used to execute the data processing method of the above-mentioned embodiments of the present application.

[0203] Figure 9 is a schematic diagram of a data processing device according to an embodiment of the present application. As shown in Figure 9 the data processing device 90 can include an acquisition unit 902, a generation unit 904, a processing unit 906 and an uploading unit 908.

[0204] The acquisition unit 902 is configured to acquire product attribute information of a target biological object, wherein the product attribute information is used to represent the product category of the biological object.

[0205] The generation unit 904 is configured to generate initial identification information of the target biological object based on the product attribute information, wherein the initial identification information is used to identify the target biological object.

[0206] The processing unit 906 is configured to encrypt the initial identification information to obtain target identification information.

[0207] The uploading unit 908 is configured to upload the target identification information to the blockchain.

[0208] The data processing device of this embodiment acquires the product attribute information of the target biological object through the acquisition unit, wherein the product attribute information is used to represent the product category of the biological object; generates the initial identification information of the target biological object based on the product attribute information through the generation unit, wherein the initial identification information is used to identify the target biological object; encrypts the initial identification information through the processing unit to obtain the target identification information; and uploads the target identification information to the blockchain through the uploading unit, thereby solving the technical problem that the full-link trusted traceability ecology in the blockchain cannot be constructed, and achieving the technical effect that the full-link trusted traceability ecology in the blockchain can be constructed.

[0209] The embodiment of the present application can provide a computer terminal, which can be any one of computer terminal devices in a computer terminal group. Alternatively, in the embodiment, the computer terminal can be replaced by a mobile terminal or other terminal device.

[0210] Alternatively, in the embodiment, the computer terminal can be located in at least one of a plurality of network devices in a computer network.

[0211] In the embodiment, the computer terminal can execute program codes of the following steps in the data processing method: collecting product attribute information of a target biological object, wherein the product attribute information is used to represent a product category of the biological object; generating initial identification information of the target biological object based on the product attribute information, wherein the initial identification information is used to identify the target biological object; performing encryption processing on the initial identification information to obtain target identification information; and uploading the target identification information to a block chain.

[0212] Alternatively, Figure 10 is a structural block diagram of a computer terminal according to an embodiment of the present application, as Figure 10 shown, the computer terminal 1008 can include one or more (only one is shown in the figure) processors 1002, a memory 1004, and a transmission device 1006.

[0213] The memory can be used to store software programs and modules, such as program instructions / modules corresponding to the data processing method and device in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, implements the above-mentioned data processing method. The memory can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory can further include a memory remotely arranged with respect to the processor, which can be connected to the computer terminal 1008 through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0214] Those of ordinary skill in the art can understand that Figure 10 the structure shown is only a schematic, and the computer terminal 1008 can also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a palm computer, a mobile Internet device (Mobile Internet Device, abbreviated as MID), a PAD, and other terminal devices. Figure 10 It does not limit the structure of the above-mentioned computer terminal 1008. For example, the computer terminal 1008 can also include more Figure 10more or less components than those shown, such as no network interface, display, or either or both of the interfaces 210 and 212, or a different configuration of components and their interconnection. All or part of the components can be implemented as one or more circuits, such as and including one or more processors, such as a microprocessor(s) and / or one or more ASICs and / or one or more FPGAs, and / or one or more controllers. Figure 10

[0215] Those skilled in the art can understand that all or part of the steps in the above-mentioned embodiments can be completed by instructing the terminal device related hardware through a program, and the program can be stored in a computer readable storage medium, which can include a flash disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0216] According to the embodiments of the present application, a computer readable storage medium is also provided, which includes a stored program, wherein the program performs the data processing method in the above-mentioned embodiments.

[0217] Optionally, in the present embodiment, the above-mentioned computer readable storage medium can be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the mobile terminals in the mobile terminal group.

[0218] Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the following steps: converting the product attribute information to obtain a first identification code corresponding to the target biological object, wherein the first identification code is used to determine the growth data of the target biological object; determining a first object used to produce the target biological object from the product attribute information; obtaining first identity information of the first object, and converting the first identity information to obtain a second identification code corresponding to the target biological object, wherein the second identification code is used to determine the production qualification required by the first object to produce the target biological object; determining second identity information of a second object supervising the first object, and converting the second identity information to obtain a third identification code corresponding to the target biological object, wherein the third identification code is used to determine the calling data authority of the second object; and combining the first identification code, the second identification code and the third identification code to obtain identification information.

[0219] Optionally, the above-mentioned computer readable storage medium can also execute program code for performing the following steps: in response to the existence of a third object trading the target biological object in the blockchain, obtaining third identity information of the third object, and converting the third identity information to obtain a fourth identification code corresponding to the target biological object, wherein the fourth identification code is used to represent the trading behavior of the third object; and associating the identification information and the fourth identification code.

[0220] ​Optionally, the computer readable storage medium can further execute program codes of the following steps: obtaining virtual identification information corresponding to the target biological object in the blockchain, wherein the virtual identification information is used to represent a virtual object corresponding to the target biological object in the blockchain; and constructing a mapping relationship between the virtual identification information and the first identification information in the identification information by using a target program in the blockchain.

[0221] Optionally, the computer readable storage medium can further execute program codes of the following steps: collecting environmental change data in response to a change in the environment in which the target biological object is located; adjusting the virtual object according to the environmental change data by using the target program, and determining a fourth identification code associated with the identification information; and displaying the adjusted virtual object in a terminal device associated with the fourth identification code.

[0222] Optionally, the computer readable storage medium can further execute program codes of the following steps: in response to an abnormal change in the growth state of the target biological object, prohibiting the first identification code in the identification information from being changed, and adjusting the display result of the virtual object according to the change result of the target biological object by using the target program.

[0223] Optionally, the computer readable storage medium can further execute program codes of the following steps: in response to the credit of the first object being less than or equal to a target value, stopping generating identification information of biological objects produced by the first object.

[0224] In this embodiment, the product attribute information of the target biological object is collected, and the initial identification information is constructed based on the product attribute information. The initial identification information can be used to implement the construction of a data value chain of “production-circulation-supervision-consumption”, and bind the state between the target biological object and the virtual object in the blockchain, so as to achieve the purpose of constructing a self-evolutionary trusted traceability ecological system. The technical problem of being unable to construct a full-link trusted traceability ecological system in the blockchain is solved, and the technical effect of being able to construct a full-link trusted traceability ecological system in the blockchain is achieved.

[0225] According to the embodiments of the present application, a processor is also provided, which is used to run a program, wherein the data processing method in the above embodiments is executed when the program is run by the processor.

[0226] Optionally, in this embodiment, the computer terminal can be located in at least one network device of a plurality of network devices of a computer network.

[0227] In this embodiment, the computer terminal can execute program codes of the above steps in the data processing method.

[0228] The memory can be used to store software programs and modules, such as program instructions / modules corresponding to the data processing method and device in the embodiments of the present application, and the processor executes various functions and data processing by running the software programs and modules stored in the memory, that is, implements the data processing method described above. The memory can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory can further include a memory remotely arranged with respect to the processor, which can be connected to the computer terminal through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0229] By adopting the embodiments of the present application, the product attribute information of the target biological object is collected, the initial identification information is constructed based on the product attribute information, the data value chain construction of "production-circulation-supervision-consumption" can be realized by using the initial identification information, and the state between the target biological object and the virtual object in the blockchain is bound, so as to achieve the purpose of constructing a self-evolutionary trusted traceability ecological system, and solve the technical problem that the full-link trusted traceability ecology in the blockchain cannot be constructed, and realize the technical effect that the full-link trusted traceability ecology in the blockchain can be constructed.

[0230] According to the embodiments of the present application, a computer program product is also provided, which includes computer instructions, wherein the computer instructions are executed by the processor to implement the data processing method in the above embodiments.

[0231] Embodiments of the present application can provide an electronic device, which can include a memory and a processor.

[0232] Figure 11 is a block diagram of an electronic device according to a data processing method of an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0233] As Figure 11As shown, the device 1100 includes a computing unit 1101 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 1102 or a computer program loaded from a storage unit 1108 into a random access memory (RAM) 1103. Various programs and data required for the operation of the device 1100 can also be stored in the RAM 1103. The computing unit 1101, the ROM 1102, and the RAM 1103 are connected to each other through a bus 1104. An input / output (I / O) interface 1105 is also connected to the bus 1104.

[0234] Various components in the device 1100 are connected to the I / O interface 1105, including an input unit 1106 such as a keyboard, a mouse, etc., an output unit 1107 such as various types of displays, speakers, etc., a storage unit 1108 such as a magnetic disk, an optical disk, etc., and a communication unit 1109 such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 1109 allows the device 1100 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0235] The computing unit 1101 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 1101 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 1101 performs various methods and processes described above, such as the data verification method. For example, in some embodiments, the data verification method can be implemented as a computer software program that is tangibly embodied in a machine-readable medium, such as the storage unit 1108. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 1100 via the ROM 1102 and / or the communication unit 1109. When the computer program is loaded into the RAM 1103 and executed by the computing unit 1101, one or more steps of the data verification method described above can be performed. Alternatively, in other embodiments, the computing unit 1101 can be configured to perform the data verification method by any other appropriate means, such as by means of firmware.

[0236] According to an embodiment of the present application, a method for processing data is provided. It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0237] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a System on a Chip (SOC), a Complex Programmable Logic Device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0238] Program code for carrying out methods of the present application can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces a means for implementing the functions / acts specified in the flowcharts and / or block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0239] In the context of this application, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium would include a linearly ordered electrical connection, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0240] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0241] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0242] The computer system can include clients and servers. This description and the following description use the terms "client" and "server" generically, referring to both actual computing devices and virtual computing devices, and virtual machines, and virtual instances of servers. The clients and the servers are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The servers can be cloud servers, servers of a distributed system, or servers incorporating blockchain.

[0243] The above-mentioned sequence numbers of the embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0244] In the above-mentioned embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0245] In the several embodiments provided by the present application, it should be understood that the disclosed technology can be implemented in other ways. Of course, the unit embodiment described above is only schematic. For example, the division of the units can be a logical function division, and there can be another division manner in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, and can be electrical or other forms.

[0246] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they can be located in one place, or they can be distributed on multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the present embodiment.

[0247] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0248] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0249] The above is only the preferred embodiment of the present application, and it should be pointed out that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which should be considered as the protection scope of the present application.

Claims

1. A data processing method, characterized in that, include: Collect product attribute information of the target biological object, wherein the product attribute information is used to characterize the product category of the biological object; Based on the product attribute information, initial identification information for the target biological object is generated, wherein the initial identification information is used to identify the target biological object; The initial identification information is encrypted to obtain the target identification information; The target identification information is uploaded to the blockchain.

2. The method according to claim 1, characterized in that, The step of generating initial identification information for the target biological object based on the product attribute information includes: The product attribute information is converted to obtain a first identification code corresponding to the target biological object, wherein the first identification code is used to determine the growth data of the target biological object; From the product attribute information, a first object for producing the target biological object is determined; The first identity information of the first object is obtained and the first identity information is converted to obtain the second identification code corresponding to the target biological object, wherein the second identification code is used to determine the production qualification required by the first object to produce the target biological object; The second identity information of the second object that supervises the first object is determined, and the second identity information is converted to obtain the third identification code corresponding to the target biological object, wherein the third identification code is used to determine the data access permissions of the second object; The first identifier, the second identifier, and the third identifier are combined to obtain the initial identifier information.

3. The method according to claim 2, characterized in that, The method further includes: In response to the existence of a third object in the blockchain that transacts with the target biological object, the third identity information of the third object is obtained, and the third identity information is converted to obtain a fourth identification code corresponding to the target biological object, wherein the fourth identification code is used to characterize the transaction behavior of the third object; Associate the target identification information with the fourth identification code.

4. The method according to claim 3, characterized in that, The method further includes: Obtain the virtual identifier information corresponding to the target biological object in the blockchain, wherein the virtual identifier information is used to characterize the virtual object corresponding to the target biological object in the blockchain; Using the target program in the blockchain, a mapping relationship is constructed between the virtual identifier information and the target identifier information.

5. The method according to claim 4, characterized in that, The method further includes: In response to changes in the environment in which the target biological object is located, environmental change data is collected; Using the target program, the virtual object is adjusted according to the environmental change data, and the terminal device associated with the target identification information is determined; The adjusted virtual object is displayed on the terminal device.

6. The method according to claim 4, characterized in that, The method further includes: In response to an abnormal change in the growth state of the target biological object, the first identifier code in the target identifier information is prohibited from being changed, and the display result of the virtual object is adjusted according to the change result of the target biological object using the target program.

7. The method according to claim 3, characterized in that, The method further includes: In response to the first object's credit score being less than or equal to the target value, the generation of identification information for the biological objects produced by the first object is stopped.

8. The method according to any one of claims 3 to 7, characterized in that, The method further includes: Obtain the evaluation information of the target biological object by the third object; Extract at least one keyword from the evaluation information and determine the weight data corresponding to the keyword, wherein the weight data is used to characterize the importance of the keyword to the third object's evaluation of the target biological object's use; Based on the weight data and the keywords, adjustment parameters for the target biological object are determined, wherein the adjustment parameters are used to adjust the production environment of the target biological object.

9. A processor, characterized in that, The processor is used to run a program, wherein the program is executed by the processor to perform the method according to any one of claims 1 to 8.

10. A computer program product, characterized in that, Includes computer instructions that, when executed by a processor, implement the method described in any one of claims 1 to 8.

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