Coffee product information management method based on NFC traceability verification

Abstract

The invention discloses a coffee product information management method based on NFC traceability verification, and relates to the technical field of coffee product information management, and the method comprises the following steps: obtaining the serial number SN of an NFC chip embedded in a coffee package, and sending the SN to a background server; the server verifies authenticity based on the SN and queries a batch information database, if verification is passed, a metadata record is generated, a block chain smart contract is called, a unique static NFT identity card is cast according to the metadata record, and an NFT address is returned to the client; nFT and batch COA information are displayed at a client, and a user is allowed to upload physiological data through an optional brainwave device to update NFT metadata. By integrating NFC traceability, the block chain and brain wave updating, the problems of isolation and static performance in the prior art are solved, dynamic and personalized management of coffee products is realized, and the anti-counterfeiting performance of the products and the user experience are enhanced.

Description

Technical Field

[0001] This invention relates to the field of coffee product information management technology, and specifically to a coffee product information management method based on NFC traceability verification. Background Technology

[0002] In existing technologies, coffee product traceability primarily relies on traditional methods, such as QR codes or RFID tags, to verify product authenticity and query batch information (e.g., production date, origin, and quality inspection report). Meanwhile, with the development of the digital economy, non-fungible token (NFT) technology is being applied to product identity management, for example, minting static NFTs on the blockchain as digital ownership certificates. These technologies operate independently: NFC or QR codes are used for physical product traceability, obtaining batch data stored on servers by scanning tags; NFTs are used for virtual asset representation, but are mostly statically designed and cannot be dynamically linked to user-personalized data (e.g., physiological state). Existing solutions also include web-based database query systems where users scan tags via mobile applications, and the system returns coffee information in text or image format (e.g., COA report).

[0003] However, NFC traceability methods are isolated, relying on simple database matching for authenticity verification, lacking anti-tampering mechanisms, and vulnerable to forgery attacks (such as serial number duplication), leading to unreliable traceability. Secondly, NFT applications are mostly static (such as digital collectibles), unable to incorporate personalized user data (such as brainwave states) for dynamic evolution. Users cannot update NFT attributes through behavior (such as meditation training), weakening the interactivity and incentive of identity management. Furthermore, coffee product management lacks personalized integration; existing systems cannot bind physical product traceability (such as batch flavor) to user digital identities (such as personality tags), limiting commercial value (e.g., inability to recommend customized coffee flavors). Finally, in terms of deployment, existing solutions often rely on public blockchains and cryptocurrency mechanisms, restricting compliant applications. Therefore, we propose a coffee product information management method based on NFC traceability verification. Summary of the Invention

[0004] The purpose of this invention is to address the following issues: First, NFC traceability methods are often isolated, relying on simple database matching for authenticity verification, lacking anti-tampering mechanisms, and vulnerable to forgery attacks (such as serial number duplication), leading to unreliable traceability. Second, NFT applications are mostly static (such as digital collectibles), unable to incorporate personalized user data (such as brainwave states) for dynamic evolution. Users cannot update NFT attributes through behavior (such as meditation training), weakening the interactivity and incentive of identity management. Furthermore, coffee product management lacks personalized integration; existing systems cannot bind physical product traceability (such as batch flavor) to user digital identities (such as personality tags), limiting commercial value (e.g., inability to recommend customized coffee flavors). Finally, in terms of deployment, existing solutions often rely on public blockchains and cryptocurrency mechanisms, limiting compliant applications. This invention provides a coffee product information management method based on NFC traceability verification.

[0005] To achieve the above objectives, the present invention specifically adopts the following technical solution:

[0006] A method for managing coffee product information based on NFC traceability verification includes the following steps:

[0007] S1. Obtain the NFC chip serial number (SN) embedded in the coffee packaging and send the SN to the backend server;

[0008] S2. The server verifies the authenticity of the SN and queries the batch information database. If the verification is successful, a metadata record is generated, which includes batch information and flavor personality tags.

[0009] S3. Call the blockchain smart contract to create a unique static NFT ID based on the metadata record, and return the NFT address to the client;

[0010] S4. Display NFT and batch COA information on the client and allow users to upload physiological data via optional EEG devices to update NFT metadata.

[0011] Furthermore, the NFC chip is an ISO 14443-A standard tag, embedded in the bottom or lid of the coffee packaging can.

[0012] Furthermore, the authenticity verification adopts the SHA-256 hash algorithm, which specifically includes calculating the hash value of the input SN: Hashoutput = SHA-256(SNinput); comparing Hash_output with the pre-stored hash library, if they match, it is true, otherwise it is false.

[0013] Furthermore, the batch information database is a key-value pair structure, where the key is the SN and the value includes the batch ID, production date, place of origin, COA report URL, and flavor description.

[0014] Furthermore, the blockchain is a consortium blockchain or a permissioned blockchain, and the smart contracts are based on the ERC-721 standard and deployed using the OpenZeppel in library.

[0015] Furthermore, the metadata record includes a batch hash value, flavor personality tag, and initial attributes, wherein the batch hash value is calculated using MetaHash = SHA-256 (batch information JSON).

[0016] Furthermore, the brainwave data update is an optional step, which includes using the NeuroSky EEG device to collect brainwave signals, analyzing the frequency band ratio through the FFT algorithm, and triggering NFT metadata update and points rewards if the ratio exceeds a threshold.

[0017] Furthermore, the FFT algorithm takes brainwave time series data as input and outputs the proportions of Alpha, Theta, and Gamma frequency bands. The formula for calculating the proportion of frequency bands is: proportion = frequency band energy / total energy × 100%. If any proportion is greater than 50%, the state type is determined.

[0018] Furthermore, the flavor personality tags are based on NFT type mapping of coffee flavors, including: type 1 corresponding to blueberry flavor, type 2 corresponding to grape flavor, and type 3 corresponding to almond flavor.

[0019] A coffee product information management system based on NFC traceability and verification, characterized in that it includes:

[0020] An NFC reader module is used to scan the chip and obtain the serial number (SN).

[0021] The authenticity verification and batch query module executes the SHA-256 algorithm and performs database queries.

[0022] The blockchain interaction module deploys smart contracts and mints NFTs;

[0023] The front-end display module renders the NFT image and COA information;

[0024] An optional brainwave data acquisition module is available to collect and analyze brainwave signals to update metadata.

[0025] The beneficial effects of this invention are as follows:

[0026] This invention integrates NFC traceability, blockchain, and brainwave updates, overcoming the isolation and static nature of existing technologies to achieve dynamic and personalized management of coffee products, enhancing anti-counterfeiting capabilities and user experience. By scanning the NFC chip, consumers can quickly verify the authenticity of coffee products and obtain detailed batch information and flavor descriptions, thereby increasing trust in the products. Simultaneously, the NFT identity tokens forged using blockchain technology provide a unique digital identity for each batch of coffee products, ensuring transparency and immutability of product information. Furthermore, the introduction of a brainwave data update mechanism not only increases user interactivity and engagement but also provides a novel, physiologically data-based verification method for coffee product traceability, further enhancing product security and credibility. This innovative information management method not only satisfies consumers' pursuit of coffee product quality but also provides coffee producers with effective brand protection and marketing tools, helping to enhance product market competitiveness and brand influence. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below.

[0028] This invention provides a method for managing coffee product information based on NFC traceability verification, comprising the following steps:

[0029] S1. Obtain the NFC chip serial number (SN) embedded in the coffee packaging and send the SN to the backend server;

[0030] S2. The server verifies the authenticity of the SN and queries the batch information database. If the verification is successful, a metadata record is generated, which includes batch information and flavor personality tags.

[0031] S3. Call the blockchain smart contract to create a unique static NFT ID based on the metadata record, and return the NFT address to the client;

[0032] S4. Display NFT and batch COA information on the client and allow users to upload physiological data via optional EEG devices to update NFT metadata.

[0033] NFC data collection and authenticity verification specifically include:

[0034] Users scan the NFC chip (ISO 14443-A standard tag) on ​​the coffee packaging with their mobile devices to obtain the serial number (SN). The SN is then sent to the backend server.

[0035] Input value: SN (string, such as "SN-123456").

[0036] Output values: Verification result (Boolean: true or false), batch information (JSON format, including production date, place of origin, and COA report).

[0037] The authenticity verification algorithm uses the SHA-256 hash algorithm. The server pre-stores a hash library of valid serial numbers (SNs). The hash value of the input SN is calculated: Hashoutput = SHA-256(SNinput). Hashoutput is compared with the hash library: if they match, it is true; otherwise, it is false.

[0038] To ensure that the serial number (SN) cannot be forged (one-way hashing prevents tampering), the SHA-256 algorithm is chosen because of its low collision rate (1 in 2^128), which enhances the reliability of traceability.

[0039] The batch query method is as follows: If the verification is true, query the batch database (structure is key-value pairs, key=SN, value={batch ID, production date, place of origin, COA_URL, flavor description}). Return the batch information.

[0040] If verification fails, an alarm forgery is triggered; if successful, a metadata record (including serial number, batch information, and flavor profile tag) is generated. The flavor profile tag is based on a predefined mapping (e.g., NFT type 1 corresponds to "blueberry flavor") and is used for subsequent personalized recommendations.

[0041] This process ensures that every bag of coffee is traceable to its source, providing consumers with transparent product information. NFC data collection is not only fast and convenient but also significantly reduces the possibility of counterfeit products. Consumers can obtain detailed batch information and authenticity verification results with a simple scan, increasing their trust in the product. Simultaneously, the introduction of flavor personality tags allows consumers to gain a deeper understanding of the coffee's characteristics, meeting their personalized needs. The application of this method not only enhances the market competitiveness of coffee products but also provides a new solution for food safety traceability.

[0042] The specific methods for minting blockchain NFTs include:

[0043] The server invokes a smart contract (based on Solidity) to mint ERC-721 standard NFTs on the Polygon consortium blockchain.

[0044] Input value: Metadata record (JSON, including batch hash, flavor personality tag, initial attribute such as "Focus +10").

[0045] Output value: NFT address (string, such as "0x123...abc").

[0046] Metadata processing: Calculate the hash value of the batch information and write it to the NFT metadata field.

[0047] MetaHash = SHA-256 (Batch Information JSON)

[0048] Metadata field: {"type":"NFT type","batch_hash":MetaHash,"attr":"Initial attributes"}.

[0049] Smart contract call: Deploy the contract using the OpenZeppelin library, with the function mintNFT(userAddress, MetaHash). Output the NFT address.

[0050] Choosing Polygon ensures data immutability (hash-based anti-tampering); the ERC-721 standard supports unique identity binding.

[0051] NFTs serve as digital identity cards, viewable on client-side applications. Metadata hashing supports backend verification of authenticity, ensuring that each batch of coffee products can be accurately tracked and verified through the uniqueness of the NFT. This guarantees the transparency and authenticity of coffee product information. Consumers can scan or query the NFT address to obtain detailed information about the coffee product, including batch hashes, flavor profile tags, and initial attributes. This not only enhances consumer trust but also provides coffee producers with an effective anti-counterfeiting measure. Furthermore, leveraging the immutability of data on the Polygon blockchain ensures the security and reliability of coffee product information during transmission and storage, effectively preventing information tampering and forgery.

[0052] The specific method for displaying client information is as follows:

[0053] The mobile application receives the NFT address and displays the NFT image (including a static coffee ID) and batch COA information.

[0054] Input values: NFT address, batch information.

[0055] Output values: UI interface (images and text).

[0056] Calculation method: The front-end (React Native) parses the NFT metadata and renders the image (e.g., NFT type 1 displays a "blueberry flavor" pattern). COA information is loaded directly from the batch database.

[0057] Offering an intuitive user experience and enhanced brand interaction, the app facilitates user understanding of coffee details, NFT identity, and future updates. It also features interactive functions, allowing users to explore further details about the coffee product's story, origin, cultivation process, and production workflow through clicks or scans. This information is presented in various formats, including text, images, videos, and AR (Augmented Reality), greatly enriching the user's reading experience and making them feel as if they are at the coffee production site, personally experiencing the charm of coffee and the stories behind it.

[0058] In addition, the app offers personalized recommendations, intelligently suggesting coffee products that match the user's tastes based on their preferences and purchase history. This intelligent recommendation method not only enhances the user's shopping experience but also provides coffee producers with more sales opportunities.

[0059] By combining NFT and blockchain technologies, coffee product information has become more transparent, authentic, and interactive, providing consumers with a more convenient, secure, and engaging shopping experience, while also bringing greater commercial value and brand influence to coffee producers.

[0060] The specific methods for updating brainwave data are as follows:

[0061] Users perform tasks (such as 5-minute meditation) through brainwave devices (such as NeuroSky EEG). The devices collect brainwave data (Alpha, Theta, and Gamma bands), and the system analyzes and updates NFT metadata.

[0062] Input value: Raw brainwave signal (time series data).

[0063] Output value: Updated metadata points reward.

[0064] Brainwave analysis algorithms use Fast Fourier Transform (FFT) to extract frequency band energy. The input is the original signal, and the FFT formula is:

[0065]

[0066] Where x_n represents the sampling points, k represents the frequency points, and N represents the number of samples. Calculate the proportion of each frequency band:

[0067]

[0068] If the proportion of any frequency band is >50%, the state type is determined. Alpha >50% indicates high focus.

[0069] Brainwave data score = (Alpha ratio × weight A) + (Theta ratio × weight B) + (Gamma ratio × weight C), where weight A = 0.4, B = 0.3, and C = 0.3.

[0070] If the brainwave score reaches the threshold and the Alpha ratio is >75% for 10 minutes, the smart contract triggers the updateMetadata function, and the brainwave score is mapped to points: if the score is >2.5, 5 points are awarded.

[0071] The FFT algorithm is highly efficient (O(N log N) complexity) and analyzes brainwaves in real time; weights are based on frequency band importance (e.g., Gamma related to logical thinking). A consortium blockchain is chosen for updates to ensure security and compliance; encrypted transmission is used when updating metadata to protect user data privacy. This update method not only increases the interactivity and fun of NFTs but also adds a unique user experience to the traceability and verification process of coffee products through brainwave data analysis. Users can earn points by improving their meditation concentration, a mechanism that encourages deeper user participation in the coffee product experience, enhancing user stickiness, and also providing an innovative way to manage coffee product information.

[0072] This invention integrates NFC traceability, blockchain, and brainwave updates, overcoming the isolation and static nature of existing technologies to achieve dynamic and personalized management of coffee products, enhancing anti-counterfeiting capabilities and user experience. By scanning the NFC chip, consumers can quickly verify the authenticity of coffee products and obtain detailed batch information and flavor descriptions, thereby increasing trust in the products. Simultaneously, the NFT identity tokens forged using blockchain technology provide a unique digital identity for each batch of coffee products, ensuring transparency and immutability of product information. Furthermore, the introduction of a brainwave data update mechanism not only increases user interactivity and engagement but also provides a novel, physiologically data-based verification method for coffee product traceability, further enhancing product security and credibility. This innovative information management method not only satisfies consumers' pursuit of coffee product quality but also provides coffee producers with effective brand protection and marketing tools, helping to enhance product market competitiveness and brand influence.

[0073] In this embodiment, preferably, the NFC chip is an ISO 14443-A standard tag, embedded in the bottom or lid of the coffee packaging can, ensuring that the NFC chip can be easily scanned and read throughout the entire lifecycle of the coffee product. This chip has a high data storage capacity, capable of storing multiple key data points including coffee origin, production date, batch number, flavor characteristics, and manufacturer information. Furthermore, the choice of the ISO 14443-A standard ensures broad compatibility between the NFC chip and various NFC reading devices, allowing consumers to easily obtain detailed information about the coffee product using only ordinary NFC devices such as smartphones, greatly improving the convenience and efficiency of the user experience.

[0074] In this embodiment, preferably, the authenticity verification uses the SHA-256 hash algorithm, specifically including calculating the hash value of the input SN: Hashoutput = SHA-256(SNinput); comparing Hash_output with a pre-stored hash library; if they match, it's genuine; otherwise, it's fake. This hash algorithm ensures that each coffee product has a unique identifier. During the production process, the NFC chip on each coffee package is assigned a specific serial number SNinput, and a corresponding hash value Hash_output is generated using the SHA-256 algorithm. This hash value is then stored in a secure hash library, corresponding one-to-one with the serial number. When consumers or relevant institutions need to verify the authenticity of a coffee product, they simply use an NFC reader to scan the NFC chip on the package, read the serial number, calculate the hash value using the same SHA-256 algorithm, and compare it with the pre-stored value in the hash library. If they match, the coffee product is genuine; if they do not match, it may be a counterfeit product. This method not only improves the accuracy and efficiency of product authenticity verification, but also effectively prevents the circulation of counterfeit and substandard products, further protecting consumers' rights and the brand image of coffee producers.

[0075] In this embodiment, preferably, the batch information database is a key-value pair structure, where the key is SN, and the value includes batch ID, production date, origin, COA report URL, and flavor description. It stores traceability information and supports flavor recommendations. The batch ID uniquely identifies a specific batch of coffee products, the production date records the specific time the batch was produced, the origin indicates the location where the coffee was grown or processed, and the COA (Certificate of Analysis) report URL provides an online access address for the batch's quality inspection report. Consumers or relevant institutions can view detailed test data by clicking the link. The flavor description is a textual description of the taste, aroma, and other characteristics of the batch of coffee, helping consumers choose according to their personal preferences. This key-value pair structure design makes information retrieval fast and efficient, providing strong support for coffee product traceability verification and flavor recommendations.

[0076] In this embodiment, preferably, the blockchain is a consortium blockchain or a permissioned blockchain, and the smart contracts are based on the ERC-721 standard and deployed using the OpenZeppelin library. The design of consortium blockchains or permissioned blockchains ensures the trustworthiness of participating nodes and the protection of data privacy. Compared to public blockchains, they are more suitable for traceability verification scenarios requiring certain access controls and data security. The smart contracts are based on the ERC-721 standard, meaning that each batch of coffee products can be uniquely identified as a non-fungible token (NFT). This design not only increases the product's uniqueness and collectible value but also provides an immutable record for coffee product traceability. Deploying smart contracts using the OpenZeppelin library further enhances the security and reliability of the contracts. As a widely audited and community-verified smart contract development framework, OpenZeppelin provides rich security modules and best practices, effectively reducing security risks during smart contract development. This technology selection not only improves the transparency of coffee product information but also provides consumers with a more convenient and secure means of traceability verification.

[0077] In this embodiment, preferably, the metadata record includes a batch hash value, flavor personality tags, and initial attributes. The batch hash value is calculated using MetaHash = SHA-256 (batch information JSON). The flavor personality tags and initial attributes reflect the characteristics and added value of the coffee, respectively. This information in the metadata record not only provides consumers with detailed coffee product information but also offers coffee producers an effective product management method. During the production process, each batch of coffee is assigned a unique batch hash value, which is obtained by performing a SHA-256 hash calculation on the batch information (including batch ID, production date, origin, COA report URL, and flavor description, etc.). This design ensures that the information for each batch of coffee is unique and cannot be tampered with. The flavor personality tags are based on a predefined mapping relationship, corresponding the characteristics of the coffee to specific tags, such as "blueberry flavor" or "nut flavor," which helps consumers choose according to their personal preferences. The initial attributes may include some additional information related to coffee, such as "focus +10," which increases the fun and interactivity of the coffee product.

[0078] In this embodiment, preferably, the brainwave data update is an optional step, including collecting brainwave signals using the NeuroSky EEG device, analyzing the frequency band ratios using an FFT algorithm, and triggering NFT metadata updates and point rewards if the ratio exceeds a threshold. This mechanism aims to add more dynamic and personalized elements to the coffee product experience through user physiological feedback. When users use the NeuroSky EEG device for tasks such as meditation, the device collects the user's brainwave data in real time, including signals in the Alpha, Theta, and Gamma frequency bands. The system then uses an FFT algorithm to analyze these signals and calculate the energy ratio of each frequency band. If the energy ratio of a certain frequency band exceeds a preset threshold, such as the Alpha frequency band ratio consistently exceeding 75%, the user is determined to be in a highly focused state. Based on this determination, the system triggers an NFT metadata update operation and gives the user corresponding point rewards. This reward mechanism not only encourages users to actively participate in the coffee product experience but also provides a new physiological data-based verification method for the traceability and verification of coffee products through brainwave data analysis, further enhancing the product's safety and credibility. At the same time, the points reward system increases user stickiness and engagement, providing coffee producers with more opportunities to interact with users, which helps to enhance brand loyalty and market competitiveness.

[0079] In this embodiment, preferably, the FFT algorithm takes brainwave time-series data as input and outputs the proportions of Alpha, Theta, and Gamma frequency bands. The formula for calculating the frequency band proportion is: Proportion = Frequency Band Energy / Total Energy × 100%. If any proportion > 50%, the state type is determined. The frequency band energy is calculated based on the results of the FFT algorithm by accumulating the energy of each frequency point. The total energy is the sum of the energies of all frequency bands. The state type is determined by the proportion of the frequency bands. If the proportion of a certain frequency band exceeds 50%, it is considered that this frequency band dominates the current brainwave signal, and the user's physiological state, such as high concentration or relaxation, can be inferred from this. This method of analyzing frequency band proportions provides an important basis for the subsequent processing and application of brainwave data, and also makes the NFT metadata update mechanism based on brainwave data more scientific and reliable. By continuously optimizing the algorithm and parameter settings, the accuracy and practicality of brainwave data analysis can be further improved, providing users with a more personalized and interesting coffee product experience.

[0080] In this embodiment, preferably, the flavor personality label is based on NFT type mapping of coffee flavor, including: Type 1 corresponding to blueberry flavor, Type 2 corresponding to grape flavor, and Type 3 corresponding to almond flavor. This mapping relationship not only gives each batch of coffee products a unique flavor label, but also provides consumers with a more intuitive and easy-to-understand basis for flavor selection. For example, when consumers see that the NFT type of a certain batch of coffee is Type 1, they can immediately associate it with the fresh fruity aroma and sweet and sour taste of blueberries, and thus make a choice according to their own taste preferences. In addition, this flavor personality label design based on NFT type mapping also provides coffee producers with an effective product differentiation strategy, helping them stand out in fierce market competition.

[0081] A coffee product information management system based on NFC traceability and verification, characterized in that it includes:

[0082] An NFC reader module is used to scan the chip and obtain the serial number (SN).

[0083] The authenticity verification and batch query module executes the SHA-256 algorithm and performs database queries.

[0084] The blockchain interaction module deploys smart contracts and mints NFTs;

[0085] The front-end display module renders the NFT image and COA information;

[0086] An optional brainwave data acquisition module is available to collect and analyze brainwave signals to update metadata.

[0087] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for managing coffee product information based on NFC traceability verification, characterized in that, Includes the following steps S1. Obtain the NFC chip serial number (SN) embedded in the coffee packaging and send the SN to the backend server; S2. The server verifies the authenticity of the SN and queries the batch information database. If the verification is successful, a metadata record is generated, which includes batch information and flavor personality tags. S3. Call the blockchain smart contract to create a unique static NFT ID based on the metadata record, and return the NFT address to the client; S4. Display NFT and batch COA information on the client and allow users to upload physiological data via optional EEG devices to update NFT metadata.

2. The coffee product information management method based on NFC traceability verification according to claim 1, characterized in that: The NFC chip is an ISO 14443-A standard tag that is embedded in the bottom or lid of the coffee packaging can.

3. The coffee product information management method based on NFC traceability verification according to claim 1, characterized in that: The authenticity verification uses the SHA-256 hash algorithm, which specifically includes calculating the hash value of the input SN: Hashoutput = SHA-256(SNinput); comparing Hash_output with the pre-stored hash library, if they match, it is true, otherwise it is false.

4. The coffee product information management method based on NFC traceability verification according to claim 1, characterized in that: The batch information database is a key-value pair structure, where the key is the SN and the value includes the batch ID, production date, place of origin, COA report URL, and flavor description.

5. The coffee product information management method based on NFC traceability verification according to claim 1, characterized in that: The blockchain is either a consortium blockchain or a permissioned blockchain, and the smart contracts are based on the ERC-721 standard. OpenZeppel deployment in the library.

6. The coffee product information management method based on NFC traceability verification according to claim 1, characterized in that: The metadata record includes a batch hash value, flavor personality tag, and initial attributes, wherein the batch hash value is calculated using MetaHash = SHA-256 (batch information JSON).

7. The coffee product information management method based on NFC traceability verification according to claim 1, characterized in that: The brainwave data update is an optional step, which includes using the NeuroSky EEG device to collect brainwave signals, analyzing the frequency band ratio through the FFT algorithm, and triggering NFT metadata update and points reward if the ratio exceeds a threshold.

8. The coffee product information management method based on NFC traceability verification according to claim 7, characterized in that: The FFT algorithm takes brainwave time series data as input and outputs the proportions of Alpha, Theta, and Gamma frequency bands. The formula for calculating the proportion of frequency bands is: proportion = frequency band energy / total energy × 100%. If any proportion is greater than 50%, the state type is determined.

9. A coffee product information management method based on NFC traceability verification according to claim 1, characterized in that: The flavor personality tags are based on NFT type mapping of coffee flavors, including: type 1 corresponding to blueberry flavor, type 2 corresponding to grape flavor, and type 3 corresponding to almond flavor.

10. A coffee product information management system based on NFC traceability verification, characterized in that, include: An NFC reader module is used to scan the chip and obtain the serial number (SN). The authenticity verification and batch query module executes the SHA-256 algorithm and performs database queries. The blockchain interaction module deploys smart contracts and mints NFTs; The front-end display module renders the NFT image and COA information; An optional brainwave data acquisition module is available to collect and analyze brainwave signals to update metadata.

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