A water dispenser filter anti-counterfeiting and traceability method and system

Abstract

The present invention relates to the field of data processing, and the present invention relates to a method and system for anti-counterfeiting and traceability of a water dispenser filter element. The filter element preparation traceability matrix is ​​generated by acquiring the production equipment information of the filter element, and the micro-texture image of the filter element surface is randomly collected. The surface texture features are extracted using the local binary pattern algorithm and the grayscale co-occurrence matrix algorithm to generate a filter element surface feature sequence. Subsequently, the filter element surface feature sequence is fused with the filter element preparation traceability matrix to generate a unique filter element feature matrix, which is encrypted to generate an encrypted traceability code, which is stored in a cloud platform and an electronic tag of the filter element. Finally, the authenticity of the filter element can be effectively verified by reading the encrypted traceability code in the electronic tag and matching it with the cloud platform. This method realizes the unique identification of the filter element by combining production information and random surface texture features, and significantly improves the reliability of anti-counterfeiting and traceability.

Description

Technical Field

[0001] The invention relates to the field of data processing, and in particular to an anti-counterfeiting and tracing method for a filter element of a water dispenser. Background Art

[0002] Water dispensers have become an indispensable device in modern homes and offices. Their main function is to filter impurities and pollutants in tap water to provide safe and clean drinking water. As a key component, the performance of water dispenser filter cartridges directly affects the quality of water. At present, water dispenser filter cartridges on the market are mainly divided into two categories: PP cotton filter cartridges and activated carbon filter cartridges. PP cotton filter cartridges can effectively remove large particles of impurities in water, such as silt, rust, etc. The other type is activated carbon filter cartridges, which have strong adsorption capacity and can remove odors, chlorine and other small molecular organic matter in water, thereby improving the taste and quality of water. With the expansion of the water dispenser filter cartridge market, the problem of counterfeit and shoddy filter cartridges has become increasingly serious, which not only affects the health of consumers, but also damages the brand reputation. Traditional filter cartridge anti-counterfeiting technology mainly relies on attaching electronic tags, anti-counterfeiting codes, etc. to the filter cartridges, and these tags or anti-counterfeiting codes are embedded with unique identification information. Consumers verify the authenticity of the filter cartridge by scanning the electronic tag. However, the existing electronic tag anti-counterfeiting technology has great safety risks. Since the information in electronic tags can be copied and forged, especially the relatively simple forgery of QR codes, malicious elements can crack the data in the tags and forge labels that are similar to the authentic ones.

[0003] For example, the Chinese patent document with the announcement number CN111553717B discloses an anti-counterfeiting traceability method for objects, which generates an anti-counterfeiting pattern by combining anti-counterfeiting data resource information with the numbering information compiled in real time at the object generation site, and uses anti-counterfeiting materials to display the anti-counterfeiting pattern on the corresponding object or its packaging. However, this method has some technical defects: the numbering information compiled in real time on site is traceable and has certain rules. Even if it is protected by encryption technology, malicious people may obtain the content represented by the pattern through certain analytical means to discover the numbering rules and then imitate the anti-counterfeiting information. Summary of the invention

[0004] In view of the problem that the above-mentioned anti-counterfeiting information may be cracked, in the first aspect, the present invention proposes a water dispenser filter element anti-counterfeiting traceability method, comprising: obtaining the production equipment number of the water dispenser filter element, recording key parameters in each preparation process of the filter element, the key parameters including the process start time, the process end time and the process parameters of the production equipment; the process parameters including the average temperature and average pressure of the equipment; generating a filter element preparation traceability matrix based on the production equipment number and the key parameters; after the filter element is prepared, randomly obtaining a macro image of a pixel block of a set size on the surface of the filter element, extracting texture information of the macro image, Generate a filter element surface feature sequence; splice the filter element surface feature sequence into the filter element preparation traceability matrix to obtain a filter element feature matrix; encrypt the filter element feature matrix to generate an encrypted traceability code, and store the encrypted traceability code in the cloud platform and the electronic tag of the filter element; when the user verifies, read the encrypted traceability code in the electronic tag on the filter element packaging and match it with the encrypted traceability code in the cloud platform. In response to a successful match, return a verification success signal, and return the filter element preparation process information according to the filter element preparation traceability matrix associated with the encrypted traceability code; in response to a failed match, return a verification failure signal.

[0005] The anti-counterfeiting and traceability method for the filter element of the water dispenser of the present invention combines the production equipment information with the macro image information randomly sampled from the surface of the filter element to generate a unique filter element feature matrix and encrypt it. Compared with the traditional anti-counterfeiting method that relies on a single production data or surface feature, the feature matrix generated by the present invention uses multi-dimensional data fusion to ensure that each filter element has a unique anti-counterfeiting mark, which greatly improves the difficulty of anti-counterfeiting. By generating an encrypted traceability code and storing it in the cloud platform and electronic tag, the counterfeiting and tampering of the data is prevented, thereby effectively ensuring the authenticity and traceability of the filter element.

[0006] Furthermore, the method for obtaining the filter element surface feature sequence includes: using a local binary LBP algorithm to obtain local texture features of the macro image to obtain an LBP matrix; using a K-Means clustering algorithm to obtain a set number of clusters in the LBP matrix, and the center points of the clusters constitute a center point sequence; based on a gray level co-occurrence matrix, the overall texture features of the macro image are obtained to obtain an eigenvalue sequence, and the eigenvalue sequence includes contrast, energy, entropy, inverse variance and correlation; and multiplying the center point sequence by the elements in the eigenvalue sequence to obtain a filter element surface feature sequence.

[0007] By using the LBP algorithm to extract the local texture features of the filter element surface and the grayscale co-occurrence matrix to obtain the overall texture features, and combining the two to generate a filter element surface feature sequence, the present invention achieves an accurate description of the complex texture of the filter element surface on the basis of the prior art, thereby improving the accuracy and uniqueness of the filter element anti-counterfeiting traceability.

[0008] Furthermore, randomly acquiring a macro image of a pixel block of a set size on the filter element surface also includes: randomly sampling the filter element surface to acquire a pixel point as the focus of a high-precision industrial macro camera; and using the high-precision industrial macro camera to shoot a macro image of the filter element surface of a preset pixel block size.

[0009] Random sampling of the filter element surface and acquisition of macro images avoids the problem of image feature repeatability that may be caused by uniform sampling positions. By randomly selecting sampling points, the uniqueness of each filter element image feature is increased, further enhancing the effectiveness of anti-counterfeiting.

[0010] Furthermore, the macro image also includes a preprocessing operation: using a Gaussian filtering algorithm to perform denoising, and using an adaptive histogram equalization algorithm to enhance image contrast.

[0011] The macro image is preprocessed by Gaussian filtering and adaptive histogram equalization, which reduces image noise and enhances contrast, thereby improving the accuracy of subsequent texture feature extraction. Compared with the image without filtering and enhancement processing, the image features extracted by the present invention are more stable and easier to identify.

[0012] Furthermore, encrypting the filter element characteristic matrix also includes: performing Z-score normalization on the filter element characteristic matrix, arranging all data in the standardized filter element characteristic matrix in order from left to right and from top to bottom to obtain a data string; and encrypting the data string using a SHA-256 hash function.

[0013] By performing Z-score standardization on the filter element characteristic matrix and using SHA-256 hash function encryption, the confidentiality and irreversibility of the data are ensured. Compared with simple data encryption methods, the encryption method of the present invention is more secure and prevents the possibility of information leakage and forgery.

[0014] Furthermore, the encrypted traceability code is destroyed from the cloud platform after successful verification.

[0015] Furthermore, the filter element characteristic matrix is ​​stored in a local server of the factory.

[0016] In the second aspect, the present invention provides an anti-counterfeiting and traceability system for a water dispenser filter cartridge, comprising a mainboard control unit electrically connected to a display control unit and a communication unit; a cloud platform wirelessly connected to the communication unit and a user terminal device via a network; further comprising a radio frequency card reader module for reading identification information of an electronic tag bound to the water dispenser filter cartridge, and transmitting the identification information to the mainboard control unit; the mainboard control unit is configured to receive the identification information and transmit it to the communication unit; and is also configured to receive a verification result and send it to a display control unit; the display control unit is configured to display the verification result of the electronic tag; the communication unit comprises a networking module for sending the identification information to a cloud platform via a network; the cloud platform is configured to receive the identification information sent by the communication unit or the user terminal device, and compare the identification information with an encrypted traceability code in the cloud platform according to a water dispenser filter cartridge anti-counterfeiting and traceability method; in response to the existence of a matching result, a verification success signal is returned to the mainboard control unit.

[0017] Furthermore, the communication unit also includes a Bluetooth module, which is used to connect to the user terminal device through the Bluetooth protocol when the drinking water device has no network service; and send the identification information to the cloud platform through the user terminal device.

[0018] The technical effects of the present invention are:

[0019] The present invention realizes the unique identification of the filter element by integrating the equipment information in the filter element production process with the microscopic texture features on the filter element surface, significantly improving the reliability of anti-counterfeiting traceability. The local binary pattern algorithm and the grayscale co-occurrence matrix algorithm are used in combination with a high-precision industrial macro camera to extract the complex texture features on the filter element surface and fuse them with the operating parameters of the production equipment to generate a unique filter element feature matrix. The feature matrix is ​​then encrypted to generate an encrypted traceability code to ensure that the anti-counterfeiting identification of each filter element is both unique and difficult to imitate. This innovative method overcomes the problem of easy cracking of anti-counterfeiting information in the prior art, and enhances the security and traceability accuracy of the filter element anti-counterfeiting system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0021] Figure 1 It is a flow chart schematically showing the anti-counterfeiting and traceability method of the filter element of the drinking fountain in an embodiment of the present invention;

[0022] Figure 2 is a schematic grayscale diagram schematically showing a container for placing a filter element of a water dispenser in an embodiment of the present invention;

[0023] Figure 3 is a schematic grayscale diagram schematically showing a PP cotton filter element in an embodiment of the present invention;

[0024] Figure 4 is a schematic grayscale diagram schematically showing an activated carbon filter element in an embodiment of the present invention;

[0025] Figure 5 is a grayscale image schematically showing a surface of an activated carbon filter element of a pixel block of a set size in an embodiment of the present invention;

[0026] Figure 6 It is a structural block diagram schematically showing the anti-counterfeiting and traceability system of the water dispenser filter element in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0028] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0029] Example of anti-counterfeiting and traceability method for water dispenser filter element:

[0030] like Figure 1 As shown, the anti-counterfeiting and traceability method of the water dispenser filter element of the present invention comprises:

[0031] S1. Obtain data related to the production process of the water dispenser filter element; obtain a pixel block of a set size on the surface of the water dispenser filter element.

[0032] S101. Obtain data related to the production process of water dispenser filter cartridges.

[0033] As people pay more and more attention to their health, the demand for safe and clean drinking water continues to grow. Common drinking water equipment in homes or offices on the market contain one or more filter cartridges to filter odors, organic matter or pollutants in tap water. The container where the filter cartridge is placed is generally columnar, such as Figure 2 As shown, water flows in from one end of the container and flows out from the side or the other end of the container, thereby completing the filtration of drinking water. There are mainly two types of filter elements that can be placed in the container: one is a PP cotton filter element, such as Figure 3 As shown in the figure, it is prepared by spinning a polypropylene material, which can filter larger impurity particles in the water, such as mud, rust or suspended matter; the other type is an activated carbon filter element, such as Figure 4As shown, it is made of raw materials such as coconut shells, high-quality coal, and wood, and is prepared through high-temperature carbonization and activation processes. It can absorb smaller pollutants in the water, remove odor, color, chlorine, etc., and improve the taste of drinking water.

[0034] In this embodiment, the filter element of the water dispenser needs to be traced for anti-counterfeiting. Therefore, in the filter element production process, the equipment status and operating parameters are collected, including but not limited to temperature, pressure, production time, equipment number, etc. In one embodiment, since the preparation process of the activated carbon filter element is more complicated than that of the PP cotton filter element, the preparation process of activated carbon is taken as an example, as follows:

[0035] In the process of preparing a batch of activated carbon filter elements, the raw materials need to be carbonized first, and the carbonization equipment number is recorded during the carbonization process. , Carbonization process start time , End time and average temperature ; Then the initially formed carbide is activated at high temperature, and the activation equipment number is also recorded in this process , process start time , End time and average temperature ; The prepared activated carbon particles need to be mixed with the binder and the mixing equipment number should be recorded and the mixing start time , End time ; The mixed materials need to be placed in a mold, usually a cylindrical mold, and compressed by high pressure, and the compression equipment number is recorded , compression start time , compression end time and average pressure ; Then, solidify the formed filter element and record the solidification equipment number. , Curing start time and curing end time Finally, the activated carbon filter element is wrapped with non-woven fabric and filter screen to prevent the activated carbon particles inside from falling off during use. The prepared activated carbon filter element needs to undergo final performance testing before leaving the factory, including but not limited to adsorption capacity testing, permeation flow testing, etc. In this embodiment, the performance deviation index of the filter element is recorded. , that is, the degree of deviation between the filter element test results and the preset test standards.

[0036] For The parameters involved in the production process of activated carbon filter elements are integrated into a filter element preparation traceability matrix , including the start and end time of each process, equipment information, etc., as shown below:

[0037]

[0038] Each row in the matrix represents the information involved in a process. Take the first row of data in the matrix as an example: , this row of data represents the first The carbonization equipment number of the activated carbon in the activated carbon filter is The carbonization start time is The time when carbonization ends is The average temperature during carbonization is It should be noted that the time involved in the matrix is ​​in the form of a 24-decimal timestamp, and the "0" element in the matrix is ​​filled with zeros to facilitate subsequent matrix calculations.

[0039] The factory transmits all the above equipment parameters and time parameters to the local server through the Industrial Internet of Things (IIoT) technology. Conventional anti-counterfeiting methods include: constructing all the above parameters into an array or sequence, encrypting them using the existing encryption protocol, and synchronously saving the encrypted information to the electronic tag of the filter element and the cloud platform. The user uses the terminal to scan the electronic tag, and the background compares the information in the electronic tag with the data stored in the cloud platform, and returns the verification result to the terminal, thereby realizing the anti-counterfeiting function. However, the existing technology can easily obtain the data information stored in the background of the electronic tag, and then use one or more decryption algorithms to decrypt it. Since all the above data are obtained based on the equipment process parameters and time, there is a certain regularity, and the decrypted information can be easily imitated. However, for the activated carbon filter element, the final step of its preparation also includes wrapping it with non-woven fabric and filter mesh. Based on this step, pixel blocks of a set size can be randomly sampled on the surface of the activated carbon filter element, such as Figure 5 As shown. Since the semantic information of the image in the randomly sampled pixel block on any activated carbon filter is complex and non-repetitive, it can be converted into data and fused with the above-collected device parameters to improve the anti-counterfeiting effect.

[0040] S102: Obtain a pixel block of a set size on the surface of the water dispenser filter.

[0041] Due to the complex structure of the filter surface, if each filter is scanned as a whole, the amount of data information generated is huge, which not only increases the time complexity of encryption, but also increases the storage pressure of the cloud platform; and when using a high-precision industrial macro camera to shoot the surface image of the water dispenser filter, due to the small focal length of the macro camera, when shooting the entire filter, the area not near the focus will have a depth of field phenomenon and is easy to blur. In summary, first define the sampling area of ​​the filter surface, that is, the entire cylindrical surface of the columnar filter; then randomly sample on its surface to obtain a pixel point as the shooting focus; then use a high-precision industrial macro camera to shoot a pixel block image of 50px×50px. In addition to 50px×50px, the above pixel block size can also be 40px×40px, 60px×60px, and 70px×70px, etc. The implementer can adjust it according to the camera parameters and filter size.

[0042] Random sampling of the filter element surface and acquisition of macro images avoids the problem of image feature repeatability that may be caused by uniform sampling positions. By randomly selecting sampling points, the uniqueness of each filter element image feature is increased, further enhancing the effectiveness of anti-counterfeiting.

[0043] S2. Obtain the filter element feature matrix based on the image within the pixel block on the surface of the water dispenser filter element.

[0044] In step S102, a pixel block of 50px×50px is randomly obtained on the surface of each activated carbon filter. For each pixel block, a Gaussian filter algorithm can be used to perform denoising to reduce the impact of noise on subsequent feature extraction; then an adaptive histogram equalization technique can be used to enhance the local contrast of the image within the pixel block, thereby improving the visibility of the surface texture.

[0045] The macro image is preprocessed by Gaussian filtering and adaptive histogram equalization, which reduces image noise and enhances contrast, thereby improving the accuracy of subsequent texture feature extraction. Compared with the image without filtering and enhancement processing, the image features extracted by the present invention are more stable and easier to identify.

[0046] When the same device is wrapping the activated carbon inside, due to the certain errors of the device itself and the fact that it cannot ensure that each hole of the non-woven fabric and each pore of the filter mesh are combined into the same structure during wrapping, even if the same process parameters are used for processing, different texture distribution states will be presented under the shooting of a high-precision industrial macro camera. By randomly selecting the shooting position of the pixel blocks on the surface of the activated carbon filter element, it is further ensured that the semantic information of each pixel block will not be repeated. Observation Figure 5 It can be found that its surface not only has holes of non-woven fabric, but also has larger pores of filter mesh, which contains a large number of texture features.

[0047] For texture features, the most commonly used and simple algorithm is the local binary pattern (LBP) texture feature extraction algorithm, which can convert the microscopic texture of the activated carbon filter surface into digital features. The input of the algorithm is the pre-processed activated carbon filter pixel block, and the output of the algorithm is the LBP value matrix corresponding to the pixel block, that is, each pixel in the pixel block corresponds to an LBP value. As a well-known technology, this algorithm will not be described here.

[0048] When using the LBP algorithm, it obtains the binary representation sequence of the central pixel by comparing the central pixel with the neighboring pixels. The possible situation is: there are two pixels whose surrounding brightness features are not the same, but because the comparison results of these two pixels with the pixels in their respective neighborhoods are the same, the LBP values ​​of these two different pixels are the same. Therefore, the grayscale co-occurrence matrix can be further selected to supplement the texture features of the pixel block to ensure the accuracy and uniqueness of the semantic description of the pixel block. The input of the grayscale co-occurrence matrix algorithm is the pre-processed activated carbon filter pixel block, and the output of the algorithm includes: the contrast reflecting the image clarity and the depth of the texture grooves ; Energy that reflects the coarseness and fineness of image texture ; Entropy that reflects the complexity of image grayscale distribution ; Inverse variance reflecting local changes in image texture ; Reflects the correlation of the similarity of the image gray levels in the row or column direction As a well-known technology, this algorithm will not be described in detail here.

[0049] In summary, for the activated carbon filter element, and the LBP matrix of its surface pixel block is recorded as , the matrix size is , as shown below:

[0050]

[0051] The eigenvalue sequence obtained through the gray level co-occurrence matrix is ​​recorded as , as shown below:

[0052]

[0053] The above LBP matrix reflects the local texture characteristics of the pixel blocks on the surface of the activated carbon filter element, while the eigenvalue sequence obtained by the gray level co-occurrence matrix reflects the overall texture characteristics of the pixel blocks on the surface of the activated carbon filter element. Activated carbon filter element surface feature sequence , used to represent the semantic information contained in the pixel block on the filter surface. In the process, it is necessary to preserve the local texture features and overall texture features of the pixel blocks on the filter surface as much as possible. First, the matrix The main LBP values ​​in are: Use K-Means clustering algorithm to cluster the matrix The data in the cluster are clustered. In this embodiment, the K value can be an empirical value of 5, which can be selected by the implementer according to the actual situation. The output of the algorithm is the center points of the five clusters. These five center points are arranged in the order of the size of the clusters to obtain a center point sequence ,have:

[0054]

[0055] in Expressing the After clustering the LBP matrix of the activated carbon filter surface pixel blocks The center value of the cluster; then the obtained center point sequence Each element in the sequence is in the order of the label and the eigenvalue sequence Multiply each element to get the filter surface feature sequence , as shown below:

[0056]

[0057] in , , the other calculation processes will not be described in detail.

[0058] By using the LBP algorithm to extract the local texture features of the filter element surface and the grayscale co-occurrence matrix to obtain the overall texture features, and combining the two to generate a filter element surface feature sequence, the present invention achieves an accurate description of the complex texture of the filter element surface on the basis of the prior art, thereby improving the accuracy and uniqueness of the filter element anti-counterfeiting traceability.

[0059] In summary, for the activated carbon filter elements with traceability matrix for filter preparation And the filter surface feature sequence , the filter surface feature sequence Insert the filter to prepare the traceability matrix The next line in the process of wrapping non-woven fabric and filter screen is obtained, and the characteristic matrix of activated carbon filter element is recorded as , as shown below:

[0060]

[0061] The matrix includes the equipment parameters and process time involved in the preparation of activated carbon filter elements, as well as the feature sequence generated based on its surface characteristics. That is to say, each activated carbon filter element has only one unique feature matrix.

[0062] It should be noted that for any PP cotton filter element, the process of obtaining the feature matrix is ​​the same as that of the activated carbon filter element. The difference is that the preparation process of the PP cotton filter element is shorter, so the corresponding feature matrix data volume is relatively small; but the PP cotton filter element is obtained by winding and spinning, such as Figure 3 As shown, its surface texture features are also relatively rich and complex. Correspondingly, when obtaining the surface feature sequence of its filter element, different PP cotton filter elements will also have different feature sequences, so each PP cotton filter element also has only a unique feature matrix.

[0063] S3. Obtain the encrypted traceability code based on the filter element feature matrix.

[0064] In step S2, a filter element feature matrix is ​​obtained for each filter element. First, the filter element feature matrix associated with the filter element is saved in the local server to prevent cloud leakage; then the filter element feature matrix is ​​encrypted. Taking the activated carbon filter element as an example: Filter element characteristics matrix for activated carbon filters The data in the matrix is ​​processed using the Z-score normalization algorithm, and then all the data in the normalized matrix are arranged in order from left to right and from top to bottom to obtain a long data string, which is encrypted using the SHA-256 hash function. The function input is the long data string obtained from the matrix, and the output is a 256-bit hash value. The encryption function is a well-known technology and will not be described here. Filter element characteristics matrix for activated carbon filters The encrypted hash value is recorded as the encrypted traceability code Finally, the encrypted traceability code associated with the activated carbon filter element is saved in the cloud platform, and the encrypted traceability code is burned into the electronic label on the filter element packaging. That is to say, the encrypted traceability code of each filter element only exists in the identification information of the cloud platform and the packaging electronic label.

[0065] By performing Z-score standardization on the filter element characteristic matrix and encrypting it using the SHA-256 hash function, the confidentiality and irreversibility of the data are ensured. Compared with simple data encryption methods, the encryption method of the present invention is more secure and prevents the possibility of information leakage and forgery.

[0066] S4. Obtain the identification information of the electronic tag on the filter element packaging and match it with the encrypted traceability code in the cloud platform to achieve anti-counterfeiting operation.

[0067] After the user purchases the filter element, the package contains an electronic tag sealing area. After tearing off the sealant, the electronic tag is placed on the radio frequency card reading area of ​​the water dispenser. The built-in RFID reader in this area can obtain the identification information in the electronic tag, which is a string or code containing an encrypted traceability code. In one embodiment, the water dispenser device has a networking module, and the identification information in the electronic tag can be sent to the cloud platform to match the encrypted traceability code stored in the cloud platform. If there is a match, the user is informed through the display panel of the water dispenser device that the filter element is authentic; if there is no match, the user is informed through the display panel that the purchased filter element is a replica. At the same time, the user can also use the terminal to connect to the network of the water dispenser, and the verification results are synchronously displayed on the manufacturer's webpage or applet on the terminal.

[0068] In another embodiment, the water dispenser device fails to connect to the Internet. At this time, the Bluetooth module is enabled and the user is required to use an Internet-connected terminal to establish a Bluetooth connection with the water dispenser. The user then opens the corresponding manufacturer's web page or applet through the Internet-connected terminal. The RFID reader built into the radio frequency card reading area of ​​the water dispenser reads the identification information in the electronic tag on the filter element packaging and sends it to the user's Internet-connected terminal through the Bluetooth module. The identification information is sent to the cloud platform through the Internet-connected terminal, thereby realizing anti-counterfeiting verification of the filter element. The verification results are synchronously displayed on the user terminal and the water dispenser display panel.

[0069] It should be noted that after each encrypted traceability code in the cloud platform is matched, it will be destroyed in the database to prevent secondary use. In addition, when the user uses the terminal to connect to the water dispenser, the time to replace the filter element will be synchronized with the manufacturer's webpage or applet logged in by the user to remind the next time to replace the filter element. At the same time, since each filter element contains a unique filter element characteristic matrix and a unique encrypted traceability code, after the identification information in the electronic tag is matched with the encrypted traceability code of the cloud platform, the filter element characteristic matrix associated with the encrypted traceability code can be decoded to obtain the filter element preparation related parameters and process time. Therefore, when the user is connected to the water dispenser through the terminal, he can also trace the filter element through the manufacturer's webpage or applet to display the filter element preparation process.

[0070] The anti-counterfeiting and traceability method for the filter element of the water dispenser of the present invention combines the production equipment information with the macro image information randomly sampled from the surface of the filter element to generate a unique filter element feature matrix and encrypt it. Compared with the traditional anti-counterfeiting method that relies on a single production data or surface feature, the feature matrix generated by the present invention uses multi-dimensional data fusion to ensure that each filter element has a unique anti-counterfeiting mark, which greatly improves the difficulty of anti-counterfeiting. By generating an encrypted traceability code and storing it in the cloud platform and electronic tag, the counterfeiting and tampering of the data is prevented, thereby effectively ensuring the authenticity and traceability of the filter element.

[0071] Example of anti-counterfeiting and traceability system for water dispenser filter:

[0072] On the other hand, the present invention also provides a water dispenser filter anti-counterfeiting and traceability system. Figure 6 As shown, the mainboard control unit is electrically connected to the display control unit and the communication unit; the cloud platform is wirelessly connected to the communication unit and the user terminal device through the network; and it also includes a radio frequency card reader module for reading the identification information of the electronic tag bound to the water dispenser filter element and transmitting the identification information to the mainboard control unit.

[0073] The mainboard control unit is the core control module of the entire system, responsible for coordinating and managing the communication and operation between the various functional modules of the system. When the radio frequency card reader module reads the electronic tag identification information on the water dispenser filter, the information will be immediately transmitted to the mainboard control unit. The mainboard control unit will first pre-process the information, and then distribute it to the networking module and Bluetooth module for further operation. In addition, the mainboard control unit is also responsible for receiving the verification results from the cloud platform and passing the results to the display control unit so that the verification status of the filter element can be displayed to the user in real time.

[0074] The RFID card reader module is responsible for reading the identification information in the electronic tag bound to the water dispenser filter. The module obtains a unique identification code from the electronic tag of the filter through near field communication (NFC) or radio frequency identification (RFID) technology. These identification codes are regarded as the "identity" information of the filter and are key data for verifying the authenticity of the filter. The read identification information is then transmitted to the mainboard control unit for processing.

[0075] The display control unit is mainly used to intuitively display the results of the filter element verification. When the mainboard control unit receives the verification results from the cloud platform, the display control unit will display the corresponding information according to the results. For example, if the filter element is genuine, the display will display "Verification passed" or "Filter element is genuine"; if the filter element is a replica, it will display "Verification failed" or "Filter element is a replica". This instant feedback mechanism can help users quickly determine the authenticity of the filter element and ensure the safety of their drinking water.

[0076] The communication unit includes a networking module, which is responsible for sending the identification information of the filter element to the cloud platform for verification through the network. The module can be connected to the Internet through Wi-Fi or 4G communication network to achieve rapid data transmission. The communication unit also includes a Bluetooth module, which plays an important supplementary role when the water dispenser equipment has no network service or the network connection is unstable. The Bluetooth module is wirelessly connected to the user's terminal device (such as a smartphone or tablet) through the Bluetooth protocol. When the system detects that data transmission cannot be completed through the networking module, the Bluetooth module will automatically activate and send the identification information of the filter element to the user's terminal device. Subsequently, the user terminal device uploads this information to the cloud platform through the mobile network to complete the verification process. This design ensures that the system can still operate normally in an environment without a network, and ensures that the anti-counterfeiting verification of the filter element is not restricted by network conditions.

[0077] The cloud platform is the data processing and verification center of the entire anti-counterfeiting and traceability system. After receiving the filter element identification information uploaded by the networking module or the user terminal device, it will first parse and process the information. Then, the cloud platform compares the identification information with the encrypted traceability code stored in its database to determine the authenticity of the filter element. If the match is successful, the cloud platform will generate a verification pass signal and return the signal to the mainboard control unit; if the match fails, it will return a verification failure signal. This cloud-based verification mechanism ensures that the system's anti-counterfeiting function can be updated and expanded in real time, while being able to adapt to large-scale user needs.

[0078] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus or device. For example, a computer-readable storage medium may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random-Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high-bandwidth memory HBM (High-Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc., or any other medium that can be used to store the required information and can be accessed by an application, a module, or both. Any such computer storage medium may be part of a device or accessible or connectable to a device. Any application or module described in the present invention may be implemented using computer-readable / executable instructions that may be stored or otherwise maintained by such a computer-readable medium.

[0079] In the description of this specification, "plurality" or "several" means at least two, such as two, three or more, etc., unless otherwise clearly and specifically defined.

[0080] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

Claims

1. A water dispenser filter anti-counterfeiting and traceability method, characterized in that: The method comprises: Obtain the production equipment number of the water dispenser filter element, record the key parameters in each filter element preparation process, the key parameters include the process start time, process end time and process parameters of the production equipment; the process parameters include the average temperature and average pressure of the equipment; generate the filter element preparation traceability matrix based on the production equipment number and the key parameters; After the filter element is prepared, a macro image of a pixel block of a set size on the surface of the filter element is randomly obtained, including: randomly sampling on the surface of the filter element to obtain a pixel point as the focus of a high-precision industrial macro camera; using the high-precision industrial macro camera to shoot a macro image of the filter element surface with a preset pixel block size; extracting the texture information of the macro image to generate a filter element surface feature sequence, including: using a local binary LBP algorithm to obtain local texture features of the macro image to obtain an LBP matrix; using a K-Means clustering algorithm to obtain a set number of clusters in the LBP matrix, and the center points of the clusters constitute a center point sequence; based on the gray level co-occurrence matrix, the overall texture features of the macro image are obtained to obtain an eigenvalue sequence, and the eigenvalue sequence includes contrast, energy, entropy, inverse variance and correlation; bitwise multiplication of the center point sequence and the elements in the eigenvalue sequence to obtain a filter element surface feature sequence; splicing the filter element surface feature sequence into the filter element preparation traceability matrix to obtain a filter element feature matrix; the filter element feature matrix is ​​stored in the local server of the factory; Encrypting the filter element characteristic matrix to generate an encrypted traceability code, and storing the encrypted traceability code in a cloud platform and an electronic tag of the filter element; During user verification, the encrypted traceability code in the electronic tag on the filter element packaging is read and matched with the encrypted traceability code in the cloud platform. In response to a successful match, a verification success signal is returned, and the filter element preparation process information is returned based on the filter element preparation traceability matrix associated with the encrypted traceability code; in response to a matching failure, a verification failure signal is returned.

2. A water dispenser filter anti-counterfeiting and traceability method according to claim 1, characterized in that: The macro image also includes a pre-processing operation: using a Gaussian filtering algorithm to perform denoising, and using an adaptive histogram equalization algorithm to enhance image contrast.

3. The anti-counterfeiting and tracing method of a water dispenser filter according to claim 1, characterized in that: Encrypting the filter element characteristic matrix includes: The filter element characteristic matrix is ​​subjected to Z-score standardization processing, and all data in the standardized filter element characteristic matrix are arranged in sequence from left to right and from top to bottom to obtain a data string; the data string is encrypted using the SHA-256 hash function.

4. The anti-counterfeiting and tracing method of a water dispenser filter according to claim 1, characterized in that: The encrypted traceability code is destroyed from the cloud platform after successful verification.

5. A water dispenser filter cartridge anti-counterfeiting and traceability system, comprising a mainboard control unit electrically connected to a display control unit and a communication unit; a cloud platform wirelessly connected to the communication unit and a user terminal device via a network; and a radio frequency card reader module for reading identification information of an electronic tag bound to the water dispenser filter cartridge and transmitting the identification information to the mainboard control unit; The mainboard control unit is used to receive the identification information and transmit it to the communication unit; it is also used to receive the verification result and send it to the display control unit; The display control unit is used to display the verification result of the electronic tag; The communication unit includes a networking module for sending the identification information to a cloud platform via a network; The cloud platform is used to receive identification information sent by a communication unit or a user terminal device, and compare the identification information with the encrypted traceability code in the cloud platform according to a water dispenser filter anti-counterfeiting and traceability method as described in claim 1; in response to a matching result, a verification success signal is returned to the mainboard control unit.

6. The anti-counterfeiting and traceability system for water dispenser filter cartridges according to claim 5 is characterized in that The communication unit also includes a Bluetooth module, which is used to connect to the user terminal device through the Bluetooth protocol when the drinking water device has no network service; and send the identification information to the cloud platform through the user terminal device.

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