RFID-based cleaning clothing management system and method

Abstract

The present invention discloses an RFID-based clothing cleaning management system and method, which relate to the technical field of clothing cleaning management. The system includes a customer information module, a clothing information module, an RFID information module, an image acquisition module, an image data processing module, a user clothing damage category data module, a cleaning method recommendation module, a cleaning method confirmation module, a difference image data module, an image indication module, and a cleaning management module. The RFID-based clothing cleaning management system and method can quickly determine whether clothing that a customer needs to clean is damaged before cleaning through the customer information module, the clothing information module, the RFID information module, the image acquisition module, the image data processing module, and the user clothing damage category data module, and searches for damage categories that match the clothing through a dragonfly population algorithm, thereby reducing the possibility of falling into a local optimum during the search and improving the accuracy of damage type judgment.

Description

Technical Field

[0001] The present invention relates to the technical field of clothing cleaning management, and in particular to an RFID-based clothing cleaning management system and method. Background Art

[0002] In order to keep clothes clean and tidy, users will clean or maintain their clothes at regular intervals. For some clothes that are inconvenient to clean by themselves, users generally send their clothes to professional clothes cleaning shops for cleaning or maintenance. Clothes cleaning shops receive a large number of clothes for cleaning every day, so how to manage the clothes that need to be cleaned, ensure the effect of clothes cleaning and meet customer needs is extremely important. The prior art with publication number CN114254994A discloses a personal protective equipment cleaning management system, including a B / S application system, a store management module, a system management module, a business configuration module, a customer management module and a report management module; the B / S application system is used to perform business management of the cleaning center, including user management, authority management, cleaning equipment management, cleaning process management, equipment alarms, information reminders, and data report management. At the same time, the B / S application system provides an open data service interface for data exchange and information association with preset software programs and data acquisition and analysis services. It can solve the daily business management needs of the cleaning center and meet the purpose of traceability, queryability, statistics, analysis and management of the cleaned clothing and equipment. At the same time, it can present data, provide service notifications, evaluate quality, intelligently send and receive, and accurately count inventory for different object roles.

[0003] However, it is inconvenient to take photos of the clothes that need to be cleaned before and after cleaning to strengthen management, and it is also impossible to analyze the clothes based on the photos taken to determine the differences and problems before and after cleaning, which is not conducive to cleaning and maintaining the clothes in a targeted manner according to the conditions of the clothes. Summary of the Invention

[0004] The purpose of the present invention is to provide an RFID-based clothing cleaning management system and method to address the above-mentioned deficiencies in the prior art.

[0005] To achieve the above-mentioned object, the present invention provides the following technical solution: an RFID-based clothing cleaning management system, comprising a customer information module, a clothing information module, an RFID information module, an image acquisition module, an image data processing module, a user clothing damage category data module, a cleaning method recommendation module, a cleaning method confirmation module, a difference image data module, an image indication module, and a cleaning management module;

[0006] The customer information module is used to obtain basic customer information data, which includes customer name, contact number, address, membership level, and order progress level information. The contact number is used to facilitate contacting the customer to inform the customer of information such as the status of clothing cleaning. The address is used to facilitate mailing the cleaned clothing to the customer according to the customer's selected address after the clothing is cleaned. The membership level is used to record the customer's rights and interests information. The order progress is used to record the progress information of the customer's clothing cleaning and the payment status of the order.

[0007] The clothing information module is used to obtain clothing data that the customer needs to clean, and the clothing data includes clothing category data and category quantity data, wherein each clothing category data corresponds to a clothing category and a category data data. For example, if the clothing category data is "shirt" and its corresponding category quantity data is "2", it means that there are 2 "shirts";

[0008] The RFID information module is used to prepare the physical binding of the RFID chip to the clothing, and associate the RFID chip identification information with the corresponding clothing data and the customer's basic information data to generate clothing cleaning management data;

[0009] The image acquisition module is used to acquire image data of clothing before and after washing through a high-definition camera, generate image data before washing and image data after washing, and update them into the clothing washing management data. When acquiring clothing images, the clothing needs to be laid flat to capture images of the entire clothing and various parts.

[0010] The image data processing module is used to perform search processing based on the clothing damage category feature image data and the clothing pre-washing image data, search for the clothing damage category corresponding to the clothing damage category feature image data that matches the clothing pre-washing image data, generate user clothing damage category data, and update it to the clothing washing management data;

[0011] The cleaning method recommendation module is used to perform search processing based on clothing cleaning method clothing feature data, clothing category data and user clothing damage category data, search for clothing cleaning methods corresponding to clothing cleaning method clothing feature data that matches the clothing category data and user clothing damage category data, and generate clothing cleaning method recommendation data;

[0012] The cleaning method confirmation module is used to visually display the clothing cleaning management data and clothing cleaning method recommendation data to the user, obtain the clothing cleaning method selected by the user, generate clothing cleaning method feedback data and update it to the clothing cleaning management data;

[0013] The difference image data module is used to perform difference analysis on the image data before and after washing of the garment to generate difference image data after washing;

[0014] The image indication module is used to search for the image portion corresponding to the post-cleaning difference image data in the post-cleaning image data of the clothing and mark it, generate the difference mark image data and update it to the clothing cleaning management data;

[0015] The image data processing module is further configured to search and process the clothing damage category feature image data and the post-cleaning difference image data, search for the clothing damage category corresponding to the clothing damage category feature image data that matches the post-cleaning difference image data, generate clothing cleaning damage category data, and update the data into the clothing cleaning management data;

[0016] The cleaning management module is used to select a cleaning method for the corresponding clothing according to the clothing cleaning method feedback data in the clothing cleaning management data, and retrieve the corresponding remaining items in the clothing cleaning management data according to one item in the clothing cleaning management data.

[0017] Furthermore, the customer information module and the clothing information module include the following steps:

[0018] S11. Manually collect and input basic customer information to construct customer basic information data A;

[0019] S12. Obtain the category data of the clothes that the customer needs to clean and the number of clothes in each category through manual judgment, and generate a clothing category data set and category quantity data u=1, 2, 3,…,ζ, where Represents the u-th clothing category data, represents the number of clothing corresponding to the u-th clothing category data, and ζ represents the maximum number of categories of clothing category data;

[0020] S13, clothing category data set B 1 With category quantity data B 2 Corresponding combination, generate clothing data B = (B 1 , B 2 ).

[0021] Furthermore, the RFID information module is used to prepare the physical binding of the RFID chip to the clothing, and associate the RFID chip identification information with the corresponding clothing data and the customer's basic information data to generate clothing cleaning management data, including the following steps:

[0022] S21, construct RFID chip identification information set C = (c1, ..., c o,…,c ω ),o=1,2,3,…,ω,c o represents the identification information of the oth RFID chip, and ω represents the maximum number of RFID chips;

[0023] S22, physically binding the RFID chip to the garment, such as placing the RFID chip and the garment together, or fixing the RFID chip to the garment with a buckle, a clip, or the like. Preferably, each garment is physically bound to one RFID chip;

[0024] S23. Associate the RFID chip identification information with the corresponding clothing data B and customer basic information data A, collect and combine the clothing data B and customer basic information data A associated with the same RFID chip identification information, and generate clothing cleaning management data K = (A, B). The RFID chip identification information of each RFID chip is unique, which makes it convenient to read the RFID chip and identify the corresponding clothing cleaning management data according to the RFID chip identification information.

[0025] Furthermore, the image acquisition module is used to acquire image data of clothing before and after washing, generate image data before washing and image data after washing, and update them into the clothing washing management data, including the following steps:

[0026] S31, obtain clothing image data before washing through the clothing image taken by the high-definition camera, and generate the clothing image data set before washing D = (d1, ..., d o ,…,d ω ), where d o represents the image data of the garment before washing that is physically bound to the oth RFID chip;

[0027] S32, obtain the image data of the garment after washing by taking the garment image with a high-definition camera, and generate the image data set E=(e1, ..., e o ,…,e ω ), where e o represents the image data of the garment after washing that is physically bound to the oth RFID chip;

[0028] S33: Perform character matching search processing on the clothing cleaning management data K, the clothing pre-cleaning image data set D, and the clothing post-cleaning image data set E for the RFID chip identification information, and search for the user's clothing pre-cleaning image data set D with the same RFID chip identification information as K. yonghu and the user's clothing washed image data set E yonghu ;

[0029] S34, collecting the image data set D of the user's clothing before washing yonghuand the user's clothing washed image data set E yonghu Update to the clothing cleaning management data K, that is, K = (A, B, D yonghu , E yonghu ).

[0030] Furthermore, the image data processing module is used to perform search processing based on the clothing damage category feature image data and the clothing pre-wash image data, search for the clothing damage category corresponding to the clothing damage category feature image data that matches the clothing pre-wash image data, generate user clothing damage category data, and update it to the clothing washing management data, including the following steps:

[0031] S41, constructing clothing damage category feature image data set F = (f1, ..., f p ,…,f υ ), p = 1, 2, 3, ..., υ, where f p represents the p-th category of clothing damage category feature image data, υ represents the maximum number of categories of clothing damage category feature image data;

[0032] S42, based on the dragonfly population algorithm, search for the same population as D in F. yonghu Matched clothing damage category feature image data f p , generate user clothing damage category data F yonghu , including the following steps:

[0033] S421, based on convolutional neural network to D yonghu Perform feature extraction to generate the image feature data set D′ of the user’s clothing before washing yonghu ;

[0034] S422, initialize the parameters of the dragonfly population algorithm, update the maximum number of iterations, and the number of dragonfly populations;

[0035] S423, initializing the position of the dragonfly population in the F search space, that is, updating the dragonflies to randomly selected positions in the F search space;

[0036] S424, calculate the fitness of the dragonfly in the F search space and obtain the best position of the individual and the optimal position of the population X g , is the position of the i-th dragonfly when its historical fitness is the best, X g is the position in the dragonfly population with the best historical fitness;

[0037] S425. The dragonfly performs exploration and utilization in the F search space:

[0038] Exploration behavior: The dragonfly randomly flies in the F search space, simulating a dragonfly randomly flying in a larger range to search for prey. This can expand the search range and ensure that the algorithm does not fall into a local optimum. The speed update formula of the dragonfly in the exploration behavior is as follows:

[0039]

[0040] Where α is the speed inertia weight, which is used to balance the proportion of exploration and exploitation. rand() is a random number generation function used to introduce uncertainty in a larger range to promote exploration. Ξ1 = Θ1·Ψ1, where Θ1 is a constant used to control the intensity of exploration behavior, and Ψ1 is a random number used to introduce greater randomness to help the dragonfly escape the local optimum.

[0041] Utilization behavior: Dragonfly in F search space according to individual best position and the optimal position of the population X g Adjust the flight strategy to approach D yonghu Matched clothing damage category feature image data f with the best fitness p , the speed update formula of the dragonfly using the behavior is as follows:

[0042]

[0043] Among them, X i represents the position of the i-th dragonfly in the search space F, Ξ2 = Θ2·Ψ2, Ξ3 = Θ3·Ψ3, Θ2 and Θ3 are constants used to control the effects of the individual optimal position and the population optimal position on the dragonfly speed, respectively, and Ψ2 and Ψ3 are random numbers used to increase the randomness of the search.

[0044] The speed update formula of the dragonfly combining exploration behavior and utilization behavior is as follows:

[0045]

[0046] The position update formula of the dragonfly combining exploration behavior and utilization behavior is as follows:

[0047] X n =X n +v i ;

[0048] S426, calculate the fitness of the dragonfly's current position, and calculate the fitness of the current position to be better than the individual's best position When the fitness is , use the current position to update the individual best position The fitness at the current position is better than the population's best position X g When the fitness is , use the current position to update the optimal position X of the population g ;

[0049] S427, determine whether the maximum number of iterations has been reached, if so, output the optimal position X of the population g Corresponding clothing damage category feature image data f p Generate user clothing damage category data F yonghu Update to the clothing cleaning management data, that is, K = (A, B, D yonghu , E yonghu , F yonghu ), if not, return to step S425.

[0050] Furthermore, the cleaning method recommendation module and the cleaning method confirmation module include the following steps:

[0051] S51. Clothing category data and user clothing damage category data F yonghu Collect and combine to generate clothing cleaning method identification data

[0052] S52. Construct clothing cleaning method clothing feature data set g r Represents the clothing feature data of the rth type of clothing cleaning method, The maximum number of categories of clothing feature data for clothing cleaning methods, where each g r Corresponding to a clothing cleaning method, there is Types of clothing cleaning methods;

[0053] S53, searching for clothing cleaning method clothing feature data g matching P in the G search space based on the dragonfly population algorithm r , generate clothing cleaning method recommendation data G′=(g′ r1 ,…,g′ r2 ), where g′ r1 and g′ r2 Indicates the cleaning methods for category r1 and r2 clothing.

[0054] S54, select the required clothing cleaning method in G' and generate clothing cleaning method feedback data G fankui ;

[0055] S55, the G fankui Update to the clothing cleaning management data K, that is, K = (A, B, D yonghu , E yonghu , F yonghu , G fankui ).

[0056] Furthermore, the difference image data module and the image indication module include the following steps:

[0057] S61, based on the twin network algorithm to identify D yonghu Medium o With E yonghu Zhonge o Image difference, generate cleaned difference image data E chayi ;

[0058] S62. Positioning E based on template matching algorithm chayi In the corresponding yonghu Zhonge o Position in the chayi In the corresponding yonghu Zhonge o The position in the image is visually marked to generate the difference mark image data E biaoji And update to the clothing cleaning management data, that is, K=(A, B, D yonghu , E yonghu , F yonghu , G fankui , E biaoji ).

[0059] Furthermore, the image data processing module generates clothing cleaning damage category data and updates it to the clothing cleaning management data, and the cleaning management module selects a cleaning method for the corresponding clothing according to the clothing cleaning method feedback data in the clothing cleaning management data, and retrieves the corresponding remaining items in the clothing cleaning management data based on one item in the clothing cleaning management data, including the following steps:

[0060] S71, based on the dragonfly population algorithm, search for the same species as E in the F search space. chayi Matching f p , generate clothing washing damage category data F sunhuai , and update it to K, that is, K=(A,B,D yonghu , E yonghu , F yonghu , G fankui , E biaoji , F sunhuai );

[0061] S72, select and G according to K fankui Use the corresponding clothing cleaning method to clean the corresponding category of clothing;

[0062] S73, according to A, B, D in K yonghu 、E yonghu 、F yonghu , G fankui 、E biaoji 、Fsunhuai For any one of the items, the corresponding remaining items can be retrieved. For example, the customer's clothing data, clothing image data before cleaning, clothing image data after cleaning, clothing damage type before cleaning, the cleaning method selected by the customer, the difference marked image data of the damage position mark of the clothing after cleaning, and the clothing damage type corresponding to the difference marked image data can be retrieved from the corresponding customer basic information data, so as to facilitate the understanding of the cleaning progress and clothing status based on these data and make targeted adjustment plans.

[0063] The RFID-based cleaning clothing management method includes the following steps:

[0064] S1. Obtain the basic information of the customer and the data of the clothes that the customer needs to clean;

[0065] S2. Prepare an RFID chip to be physically bound to the garment, and associate the RFID chip identification information with the corresponding garment data and the customer's basic information data to generate garment cleaning management data;

[0066] S3, obtaining image data of the garment before and after washing, generating image data before washing and image data after washing respectively, and updating them into the garment washing management data;

[0067] S4. Performing a search process based on the clothing damage category feature image data and the clothing pre-wash image data to search for a clothing damage category corresponding to the clothing damage category feature image data that matches the clothing pre-wash image data, generating user clothing damage category data and updating the data into the clothing washing management data;

[0068] S5. Performing a search process based on the clothing cleaning method clothing feature data, the clothing category data, and the user's clothing damage category data to search for a clothing cleaning method corresponding to the clothing cleaning method clothing feature data that matches the clothing category data and the user's clothing damage category data, generating clothing cleaning method recommendation data, visually displaying the clothing cleaning management data and the clothing cleaning method recommendation data to the user, obtaining the user's selected clothing cleaning method, generating clothing cleaning method feedback data, and updating the data to the clothing cleaning management data;

[0069] S6, performing difference analysis on the garment image data before and after washing to generate post-wash difference image data, searching for image portions corresponding to the post-wash difference image data in the post-wash image data and marking the portions, generating difference marked image data and updating the difference marked image data to the garment washing management data;

[0070] S7. Search and process the clothing damage category feature image data and the post-cleaning difference image data to find the clothing damage category corresponding to the clothing damage category feature image data that matches the post-cleaning difference image data, generate clothing cleaning damage category data and update it into the clothing cleaning management data, select a cleaning method for the corresponding clothing based on the clothing cleaning method feedback data in the clothing cleaning management data, and retrieve the corresponding remaining items in the clothing cleaning management data based on one item in the clothing cleaning management data.

[0071] 1. Compared with the existing technology, the RFID-based clothing cleaning management system and method provided by the present invention can quickly determine whether the clothing that the customer needs to clean is damaged before cleaning through the customer information module, clothing information module, RFID information module, image acquisition module, image data processing module, and user clothing damage category data module. It also searches for the damage category that matches the clothing through the dragonfly population algorithm, reducing the possibility of falling into local optimality during the search and improving the accuracy of damage type judgment.

[0072] 2. Compared with the existing technology, the RFID-based clothing cleaning management system and method provided by the present invention can recommend appropriate cleaning methods for customers to choose based on the clothing damage category and the image of the clothing before cleaning through the user clothing damage category data module, cleaning method recommendation module, and cleaning method confirmation module, so that the cleaning method is more suitable for the current condition of the customer's clothing while taking into account the customer's opinions.

[0073] 3. Compared with the existing technology, the RFID-based clothing cleaning management system and method provided by the present invention can detect and indicate damage to clothing caused by cleaning through the difference image data module and image indication module, making it convenient to proactively discuss solutions with customers based on the damage.

[0074] 4. Compared with the existing technology, the RFID-based clothing cleaning management system and method provided by the present invention conveniently integrates various types of information corresponding to the customer's cleaning clothing according to the clothing cleaning management data through the cleaning management module, facilitates quick retrieval and viewing, understands the current cleaning situation and improves management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0076] Figure 1 A block diagram of the system structure provided by an embodiment of the present invention;

[0077] Figure 2A diagram of the method steps provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0078] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0079] In the description of the present invention, it should be understood that the terms "first" and "second" are only used for descriptive purposes and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the said features. In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a communication between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0080] Example embodiments will be described more fully hereinafter with reference to the accompanying drawings, but the example embodiments may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the scope of this disclosure to those skilled in the art.

[0081] In the absence of conflict, the various embodiments of the present disclosure and the various features therein may be combined with each other.

[0082] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0083] See also Figure 1-Figure 2 ,The RFID-based cleaning clothing management system includes a customer information module, a clothing information module, an RFID information module, an image acquisition module, an image data processing module, a user clothing damage category data module, a cleaning method recommendation module, a cleaning method confirmation module, a difference image data module, an image indication module, and a cleaning management module;

[0084] The customer information module is used to obtain basic customer information data, including customer name, contact number, address, membership level, and order progress level information. The contact number is used to facilitate contacting customers to inform them of information such as the status of clothing cleaning. The address is used to facilitate mailing the cleaned clothing to the customer according to the customer's selected address after the clothing is cleaned. The membership level is used to record customer rights and interests information. The order progress is used to record the progress of the customer's clothing cleaning and order payment information.

[0085] The clothing information module is used to obtain clothing data that customers need to clean. The clothing data includes clothing category data and category quantity data. Each clothing category data corresponds to one category data. For example, if the clothing category data is "shirt" and its corresponding category quantity data is "2", it means that there are 2 "shirts";

[0086] Furthermore, the customer information module and the clothing information module include the following steps:

[0087] S11. Manually collect and input basic customer information to construct customer basic information data A;

[0088] S12. Obtain the category data of the clothes that the customer needs to clean and the number of clothes in each category through manual judgment, and generate a clothing category data set and category quantity data u=1, 2, 3,…,ζ, where Represents the u-th clothing category data, represents the number of clothing corresponding to the u-th clothing category data, and ζ represents the maximum number of categories of clothing category data;

[0089] S13, the clothing category data set B1 and the category quantity data B2 are combined accordingly to generate clothing data B = (B 1 , B 2 ).

[0090] The RFID information module is used to prepare the physical binding of the RFID chip to the clothing, and associate the RFID chip identification information with the corresponding clothing data and customer basic information data to generate clothing cleaning management data, including the following steps:

[0091] S21, construct RFID chip identification information set C = (c1, ..., c o ,…,c ω ),o=1,2,3,…,ω,c o represents the identification information of the oth RFID chip, and ω represents the maximum number of RFID chips;

[0092] S22. Physically binding the RFID chip to the clothing, such as placing the RFID chip and the clothing together, or fixing the RFID chip to the clothing with a buckle, a clip, or the like. Preferably, each piece of clothing is physically bound to one RFID chip;

[0093] S23. Associate the RFID chip identification information with the corresponding clothing data B and customer basic information data A, collect and combine the clothing data B and customer basic information data A associated with the same RFID chip identification information, and generate clothing cleaning management data K = (A, B). The RFID chip identification information of each RFID chip is unique, which makes it convenient to read the RFID chip and identify the corresponding clothing cleaning management data according to the RFID chip identification information.

[0094] The image acquisition module is used to acquire image data of clothing before and after washing through a high-definition camera, generate image data before washing and image data after washing, and update them into the clothing washing management data. When acquiring clothing images, the clothing needs to be laid flat to capture images of the entire clothing and various parts. The steps include:

[0095] S31, obtain clothing image data before washing through the clothing image taken by the high-definition camera, and generate the clothing image data set before washing D = (d1, ..., d o ,…,d ω ), where d o represents the image data of the garment before washing that is physically bound to the oth RFID chip;

[0096] S32, obtain the image data of the garment after washing by taking the garment image with a high-definition camera, and generate the image data set E=(e1, ..., e o ,…,e ω ), where e o represents the image data of the garment after washing that is physically bound to the oth RFID chip;

[0097] S33: Perform character matching search processing on the clothing cleaning management data K, the clothing pre-cleaning image data set D, and the clothing post-cleaning image data set E for the RFID chip identification information, and search for the user's clothing pre-cleaning image data set D with the same RFID chip identification information as K. yonghu and the user's clothing washed image data set E yonghu ;

[0098] S34, collecting the image data set D of the user's clothing before washing yonghu and the user's clothing washed image data set E yonghu Update to the clothing cleaning management data K, that is, K = (A, B, D yonghu , E yonghu ).

[0099] The image data processing module is used to perform search processing based on the clothing damage category feature image data and the clothing pre-wash image data, search for the clothing damage category corresponding to the clothing damage category feature image data that matches the clothing pre-wash image data, generate user clothing damage category data, and update it to the clothing washing management data, including the following steps:

[0100] S41, constructing clothing damage category feature image data set F = (f1, ..., f p ,…,f υ ), p = 1, 2, 3, ..., υ, where f p represents the p-th category of clothing damage category feature image data, υ represents the maximum number of categories of clothing damage category feature image data;

[0101] S42, based on the dragonfly population algorithm, search for the same population as D in F. yonghu Matched clothing damage category feature image data f p , generate user clothing damage category data F yonghu , including the following steps:

[0102] S421, based on convolutional neural network to D yonghu Perform feature extraction to generate the image feature data set D′ of the user’s clothing before washing yonghu ;

[0103] S422, initialize the parameters of the dragonfly population algorithm, update the maximum number of iterations, and the number of dragonfly populations;

[0104] S423, initializing the position of the dragonfly population in the F search space, that is, updating the dragonfly to a randomly selected position in the F search space;

[0105] S424. Calculate the fitness of the dragonfly in the F search space and obtain the optimal position of the individual and the optimal position of the population X g , is the position of the i-th dragonfly when its historical fitness is the best, X g is the position in the dragonfly population with the best historical fitness;

[0106] S425, Dragonfly performs exploration and utilization behaviors in the F search space:

[0107] Exploration behavior: The dragonfly randomly flies in the F search space, simulating a dragonfly randomly flying in a larger range to search for prey. This can expand the search range and ensure that the algorithm does not fall into a local optimum. The speed update formula of the dragonfly in the exploration behavior is as follows:

[0108]

[0109] Where α is the speed inertia weight, which is used to balance the proportion of exploration and exploitation. rand() is a random number generation function used to introduce uncertainty in a larger range to promote exploration. Ξ1 = Θ1·Ψ1, where Θ1 is a constant used to control the intensity of exploration behavior, and Ψ1 is a random number used to introduce greater randomness to help the dragonfly escape the local optimum.

[0110] Utilization behavior: Dragonfly in F search space according to individual best position and the optimal position of the population X g Adjust the flight strategy to approach D yonghu Matched clothing damage category feature image data f with the best fitness p , the speed update formula of the dragonfly using the behavior is as follows:

[0111]

[0112] Among them, X i represents the position of the i-th dragonfly in the search space F, Ξ2 = Θ2·Ψ2, Ξ3 = Θ3·Ψ3, Θ2 and Θ3 are constants used to control the effects of the individual optimal position and the population optimal position on the dragonfly speed, respectively, and Ψ2 and Ψ3 are random numbers used to increase the randomness of the search.

[0113] The speed update formula of the dragonfly combining exploration behavior and utilization behavior is as follows:

[0114]

[0115] The position update formula of the dragonfly combining exploration behavior and utilization behavior is as follows:

[0116] X n =X n +v i ;

[0117] S426, calculate the fitness of the dragonfly's current position, and calculate the fitness of the current position to be better than the individual's best position When the fitness is , use the current position to update the individual best position The fitness at the current position is better than the population's best position X g When the fitness is , use the current position to update the optimal position X of the population g ;

[0118] S427, determine whether the maximum number of iterations has been reached, if so, output the optimal position X of the population g Corresponding clothing damage category feature image data f p Generate user clothing damage category data F yonghu Update to the clothing cleaning management data, that is, K = (A, B, D yonghu, E yonghu , F yonghu ), if not, return to step S425.

[0119] The cleaning method recommendation module is used to perform search processing based on clothing cleaning method clothing feature data, clothing category data and user clothing damage category data, search for clothing cleaning methods corresponding to clothing cleaning method clothing feature data that matches the clothing category data and user clothing damage category data, and generate clothing cleaning method recommendation data;

[0120] The cleaning method confirmation module is used to visualize the clothing cleaning management data and clothing cleaning method recommendation data to the user, obtain the clothing cleaning method selected by the user, generate clothing cleaning method feedback data and update it to the clothing cleaning management data;

[0121] Furthermore, the cleaning method recommendation module and the cleaning method confirmation module include the following steps:

[0122] S51. Clothing category data and user clothing damage category data F yonghu Collect and combine to generate clothing cleaning method identification data

[0123] S52. Construct clothing cleaning method clothing feature data set g r Represents the clothing feature data of the rth type of clothing cleaning method, The maximum number of categories of clothing feature data for clothing cleaning methods, where each g r Corresponding to a clothing cleaning method, there is Types of clothing cleaning methods;

[0124] S53, based on the dragonfly population algorithm, search for clothing cleaning method clothing feature data g that matches P in the G search space r , generate clothing cleaning method recommendation data G′=(g′ r1 ,…,g′ r2 ), where g′ r1 and g′ r2 Indicates the cleaning methods for category r1 and r2 clothing.

[0125] S54, select the required clothing cleaning method in G' and generate clothing cleaning method feedback data G fankui ;

[0126] S55, G fankui Update to the clothing cleaning management data K, that is, K = (A, B, D yonghu , E yonghu , Fyonghu , G fankui ).

[0127] The difference image data module is used to perform difference analysis on the image data before and after washing of the garments to generate difference image data after washing;

[0128] The image indication module is used to search for the image portion corresponding to the difference image data after washing in the image data of the garment after washing and mark it, generate the difference mark image data and update it to the garment washing management data;

[0129] Furthermore, the difference image data module and the image indication module include the following steps:

[0130] S61, based on the twin network algorithm to identify D yonghu Medium o With E yonghu Zhonge o Image difference, generate cleaned difference image data E chayi ;

[0131] S62. Positioning E based on template matching algorithm chayi In the corresponding yonghu Zhonge o Position in the chayi In the corresponding yonghu Zhonge o The position in the image is visually marked to generate the difference mark image data E biaoji And update to the clothing cleaning management data, that is, K = (A, B, D yonghu , E yonghu , F yonghu , G fankui , E biaoji ).

[0132] The image data processing module is further configured to search and process the clothing damage category feature image data and the post-cleaning difference image data, search for the clothing damage category corresponding to the clothing damage category feature image data that matches the post-cleaning difference image data, generate clothing cleaning damage category data, and update the data into the clothing cleaning management data;

[0133] The cleaning management module is used to select a cleaning method for corresponding clothing according to the clothing cleaning method feedback data in the clothing cleaning management data, and retrieve the corresponding remaining items in the clothing cleaning management data according to one item in the clothing cleaning management data.

[0134] Furthermore, the image data processing module generates clothing cleaning damage category data and updates it to the clothing cleaning management data, and the cleaning management module selects a cleaning method for the corresponding clothing according to the clothing cleaning method feedback data in the clothing cleaning management data, and retrieves the corresponding remaining items in the clothing cleaning management data based on one item in the clothing cleaning management data, including the following steps:

[0135] S71, based on the dragonfly population algorithm, search for the same species as E in the F search space. chayi Matching f p , generate clothing washing damage category data F sunhuai , and update it to K, that is, K=(A,B,D yonghu , E yonghu , F yonghu , G fankui , E biaoji , F sunhuai );

[0136] S72, based on K selection and G fankui Use the corresponding clothing cleaning method to clean the corresponding category of clothing;

[0137] S73, according to A, B, D in K yonghu 、E yonghu 、F yonghu , G fankui 、E biaoji 、F sunhuai For any one of the items, the corresponding remaining items can be retrieved. For example, the customer's clothing data, clothing image data before cleaning, clothing image data after cleaning, clothing damage type before cleaning, the cleaning method selected by the customer, the difference marked image data of the damage position mark of the clothing after cleaning, and the clothing damage type corresponding to the difference marked image data can be retrieved from the corresponding customer basic information data, so as to facilitate the understanding of the cleaning progress and clothing status based on these data and make targeted adjustment plans.

[0138] The RFID-based cleaning clothing management method includes the following steps:

[0139] S1. Obtain the basic information of the customer and the data of the clothes that the customer needs to clean;

[0140] S2. Prepare an RFID chip and physically bind it to the garment, and associate the RFID chip identification information with the corresponding garment data and the customer's basic information data to generate garment cleaning management data;

[0141] S3, obtaining image data of clothing before and after washing, generating image data before washing and image data after washing respectively, and updating them into clothing washing management data;

[0142] S4. Performing a search process based on the clothing damage category feature image data and the clothing pre-wash image data to search for the clothing damage category corresponding to the clothing damage category feature image data that matches the clothing pre-wash image data, generating user clothing damage category data and updating it to the clothing washing management data;

[0143] S5. Performing a search process based on the clothing cleaning method clothing feature data, clothing category data, and user clothing damage category data, searching for a clothing cleaning method corresponding to the clothing cleaning method clothing feature data that matches the clothing category data and the user clothing damage category data, generating clothing cleaning method recommendation data, visually displaying the clothing cleaning management data and the clothing cleaning method recommendation data to the user, obtaining the clothing cleaning method selected by the user, generating clothing cleaning method feedback data, and updating the data to the clothing cleaning management data;

[0144] S6, performing difference analysis on the garment image data before and after washing to generate post-wash difference image data, searching for image portions corresponding to the post-wash difference image data in the post-wash image data and marking them, generating difference marked image data and updating them to the garment washing management data;

[0145] S7. Search and process the clothing damage category feature image data and the post-cleaning difference image data, search for the clothing damage category corresponding to the clothing damage category feature image data that matches the post-cleaning difference image data, generate clothing cleaning damage category data and update it to the clothing cleaning management data, select the corresponding clothing cleaning method based on the clothing cleaning method feedback data in the clothing cleaning management data, and retrieve the corresponding remaining items in the clothing cleaning management data based on one of the items in the clothing cleaning management data.

[0146] The above description is merely illustrative of certain exemplary embodiments of the present invention. It goes without saying that those skilled in the art will be able to modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims.

Claims

1. RFID-based cleaning clothing management system, characterized by: It includes customer information module, clothing information module, RFID information module, image acquisition module, image data processing module, user clothing damage category data module, cleaning method recommendation module, cleaning method confirmation module, difference image data module, image indication module, and cleaning management module; The customer information module is used to obtain basic customer information data; The clothing information module is used to obtain clothing data that customers need to clean, wherein the clothing data includes clothing category data and category quantity data; and comprises the following steps: S11. Constructing customer basic information data A; S12. Obtain the category data of the clothes that the customer needs to clean and the number of clothes in each category, and generate a collection of clothing category data. and category quantity data u=1, 2, 3, L, ζ, where Represents the u-th clothing category data, represents the number of clothing corresponding to the u-th clothing category data, and ζ represents the maximum number of categories of clothing category data; S13, clothing category data set B 1 With category quantity data B 2 Corresponding combination, generate clothing data B = (B 1 , B 2 ); The RFID information module is used to prepare the physical binding of the RFID chip to the clothing, and associate the RFID chip identification information with the corresponding clothing data and the customer's basic information data to generate clothing cleaning management data; the module includes the following steps: S21, construct RFID chip identification information set C = (c1, L, c o ,L,c ω ), o=1, 2, 3, L, ω, c o represents the identification information of the oth RFID chip, and ω represents the maximum number of RFID chips; S22, physically binding the RFID chip to the clothing; S23. Associating the RFID chip identification information with the corresponding clothing data B and customer basic information data A, collecting and combining the clothing data B and customer basic information data A associated with the same RFID chip identification information, and generating clothing cleaning management data K = (A, B); The image acquisition module is used to acquire image data of clothing before and after washing, generate image data before washing and image data after washing respectively, and update them into the clothing washing management data; The following steps are involved: S31, obtain the clothing image data before washing, generate the clothing image data set before washing D = (d1, L, d o , L, d ω ), where d o represents the image data of the garment before washing that is physically bound to the oth RFID chip; S32, obtain the image data of the garment after washing, and generate the image data set E=(e1, L, e o ,L,e ω ), where e o represents the image data of the garment after washing that is physically bound to the oth RFID chip; S33: Perform character matching search processing on the clothing cleaning management data K, the clothing pre-cleaning image data set D, and the clothing post-cleaning image data set E for the RFID chip identification information, and search for the user's clothing pre-cleaning image data set D with the same RFID chip identification information as K. yonghu and the user's clothing washed image data set E yonghu ; S34, collecting the image data set D of the user's clothing before washing yonghu and the user's clothing washed image data set E yonghu Update to the clothing cleaning management data K, that is, K = (A, B, D yonghu , E yonghu ); The image data processing module is used to perform search processing based on the clothing damage category feature image data and the clothing pre-washing image data, search for the clothing damage category corresponding to the clothing damage category feature image data that matches the clothing pre-washing image data, generate user clothing damage category data, and update it to the clothing washing management data; The cleaning method recommendation module is used to perform search processing based on clothing cleaning method clothing feature data, clothing category data and user clothing damage category data, search for clothing cleaning methods corresponding to clothing cleaning method clothing feature data that matches the clothing category data and user clothing damage category data, and generate clothing cleaning method recommendation data; The cleaning method confirmation module is used to visually display the clothing cleaning management data and clothing cleaning method recommendation data to the user, obtain the clothing cleaning method selected by the user, generate clothing cleaning method feedback data and update it to the clothing cleaning management data; The difference image data module is used to perform difference analysis on the image data before and after washing of the garment to generate difference image data after washing; The image indication module is used to search for the image portion corresponding to the post-cleaning difference image data in the post-cleaning image data of the clothing and mark it, generate the difference mark image data and update it to the clothing cleaning management data; The image data processing module is further configured to search and process the clothing damage category feature image data and the post-cleaning difference image data, search for the clothing damage category corresponding to the clothing damage category feature image data that matches the post-cleaning difference image data, generate clothing cleaning damage category data, and update the data into the clothing cleaning management data; The cleaning management module is used to select a cleaning method for the corresponding clothing according to the clothing cleaning method feedback data in the clothing cleaning management data, and retrieve the corresponding remaining items in the clothing cleaning management data according to one item in the clothing cleaning management data.

2. The RFID-based laundry management system according to claim 1, characterized in that: The image data processing module is used to perform search processing based on the clothing damage category feature image data and the clothing pre-wash image data, search for the clothing damage category corresponding to the clothing damage category feature image data that matches the clothing pre-wash image data, generate user clothing damage category data, and update it to the clothing washing management data, including the following steps: S41, construct clothing damage category feature image data set F = (f1, L, f p , L, f υ ), p = 1, 2, 3, L, υ, where f p represents the p-th category of clothing damage category feature image data, υ represents the maximum number of categories of clothing damage category feature image data; S42, based on the dragonfly population algorithm, search for the same population as D in F. yonghu Matched clothing damage category feature image data f p , generate user clothing damage category data F yonghu , including the following steps: S421, based on convolutional neural network to D yonghu Perform feature extraction to generate the image feature data set D′ of the user’s clothing before washing yonghu ; S422, initialize the parameters of the dragonfly population algorithm, update the maximum number of iterations, and the number of dragonfly populations; S423, initializing the position of the dragonfly population in the F search space; S424, calculate the fitness of the dragonfly in the F search space and obtain the best position of the individual and the optimal position of the population X g , is the position of the i-th dragonfly when its historical fitness is the best, X g is the position in the dragonfly population with the best historical fitness; S425. The dragonfly performs exploration and utilization in the F search space: Exploration behavior: The dragonfly flies randomly in the F search space. The speed update formula of the dragonfly in the exploration behavior is as follows: Where α is the velocity inertia weight, rand() is a random number generation function, Ξ1=Θ1·Ψ1, Θ1 is a constant, Ψ1 is a random number; Utilization behavior: Dragonfly in F search space according to individual best position and the optimal position of the population X g Adjust the flight strategy to approach D yonghu Matched clothing damage category feature image data f with the best fitness p , the speed update formula of the dragonfly using the behavior is as follows: Among them, X i represents the position of the i-th dragonfly in the F search space, Ξ2=Θ2·Ψ2, Ξ3=Θ3·Ψ3, Θ2, Θ3 are constants, Ψ2, Ψ3 are random numbers, The speed update formula of the dragonfly combining exploration behavior and utilization behavior is as follows: The position update formula of the dragonfly combining exploration behavior and utilization behavior is as follows: X n =X n +v i ; S426, calculate the fitness of the dragonfly's current position, and calculate the fitness of the current position to be better than the individual's best position When the fitness is , use the current position to update the individual best position The fitness at the current position is better than the population's best position X g When the fitness is , use the current position to update the optimal position X of the population g ; S427, determine whether the maximum number of iterations has been reached, if so, output the optimal position X of the population g Corresponding clothing damage category feature image data f p Generate user clothing damage category data F yonghu Update to the clothing cleaning management data, that is, K = (A, B, D yonghu , E yonghu , F yonghu ), if not, return to step S425.

3. The RFID-based laundry management system according to claim 2, characterized in that: The cleaning method recommendation module and the cleaning method confirmation module include the following steps: S51. Clothing category data and user clothing damage category data F yonghu Collect and combine to generate clothing cleaning method identification data S52. Construct clothing cleaning method clothing feature data set g r Represents the clothing feature data of the rth type of clothing cleaning method, The maximum number of categories of clothing feature data for clothing cleaning methods; S53, searching for clothing cleaning method clothing feature data g matching P in the G search space based on the dragonfly population algorithm r , generate clothing cleaning method recommendation data G′=(g′ r1 , L, g′ r2 ), where g′ r1 and g′ r2 Indicates the cleaning methods for category r1 and r2 clothing. S54, select the required clothing cleaning method in G' and generate clothing cleaning method feedback data G fankui ; S55, the G fankui Update to the clothing cleaning management data K, that is, K = (A, B, D yonghu , E yonghu , F yonghu , G fankui ).

4. The RFID-based laundry management system according to claim 3, characterized in that: The difference image data module and the image indication module include the following steps: S61, based on the twin network algorithm to identify D yonghu Medium o With E yonghu Zhonge o Image difference, generate cleaned difference image data E chayi ; S62. Positioning E based on template matching algorithm chayi In the corresponding yonghu Zhonge o Position in the chayi In the corresponding yonghu Zhonge o The position in the image is visually marked to generate the difference mark image data E biaoji And update to the clothing cleaning management data, that is, K=(A, B, D yonghu , E yonghu , F yonghu , G fankui , E biaoji ).

5. The RFID-based laundry management system according to claim 4, characterized in that: The image data processing module generates clothing cleaning damage category data and updates the data to the clothing cleaning management data, and the cleaning management module selects a cleaning method for the corresponding clothing according to the clothing cleaning method feedback data in the clothing cleaning management data, and retrieves the corresponding remaining items in the clothing cleaning management data based on one item in the clothing cleaning management data, including the following steps: S71, based on the dragonfly population algorithm, search for the same species as E in the F search space. chayi Matching f p , generate clothing washing damage category data F sunhuai , and update it to K, that is, K=(A,B,D yonghu , E yonghu , F yonghu , G fankui , E biaoji , F sunhuai ); S72, select and G according to K fankui Use the corresponding clothing cleaning method to clean the corresponding category of clothing; S73, according to A, B, D in K yonghu 、E yonghu 、F yonghu , G fankui 、E biaoji 、F sunhuai Any one of them, retrieve the corresponding other items.

6. An RFID-based laundry management method, applicable to the RFID-based laundry management system according to any one of claims 1 to 5, characterized in that: The following steps are involved: S1. Obtain the basic information of the customer and the data of the clothes that the customer needs to clean; S2. Prepare an RFID chip to be physically bound to the garment, and associate the RFID chip identification information with the corresponding garment data and the customer's basic information data to generate garment cleaning management data; S3, obtaining image data of the garment before and after washing, generating image data before washing and image data after washing respectively, and updating them into the garment washing management data; S4. Performing a search process based on the clothing damage category feature image data and the clothing pre-wash image data to search for a clothing damage category corresponding to the clothing damage category feature image data that matches the clothing pre-wash image data, generating user clothing damage category data and updating the data into the clothing washing management data; S5. Performing a search process based on the clothing cleaning method clothing feature data, the clothing category data, and the user's clothing damage category data to search for a clothing cleaning method corresponding to the clothing cleaning method clothing feature data that matches the clothing category data and the user's clothing damage category data, generating clothing cleaning method recommendation data, visually displaying the clothing cleaning management data and the clothing cleaning method recommendation data to the user, obtaining the user's selected clothing cleaning method, generating clothing cleaning method feedback data, and updating the data to the clothing cleaning management data; S6, performing difference analysis on the garment image data before and after washing to generate post-wash difference image data, searching for image portions corresponding to the post-wash difference image data in the post-wash image data and marking the portions, generating difference marked image data and updating the difference marked image data to the garment washing management data; S7. Search and process the clothing damage category feature image data and the post-cleaning difference image data to find the clothing damage category corresponding to the clothing damage category feature image data that matches the post-cleaning difference image data, generate clothing cleaning damage category data and update it into the clothing cleaning management data, select a cleaning method for the corresponding clothing based on the clothing cleaning method feedback data in the clothing cleaning management data, and retrieve the corresponding remaining items in the clothing cleaning management data based on one item in the clothing cleaning management data.

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