Garment cleaning management system and method based on RFID

Abstract

The invention discloses a garment cleaning management system and method based on RFID, and relates to the technical field of garment cleaning management. The system comprises 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 mode recommendation module, a cleaning mode confirmation module, a difference image data module, an image indication module and a cleaning management module. According to the RFID-based clothing cleaning management system and method, 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, whether clothing needing to be cleaned by a customer is damaged or not before cleaning can be quickly determined; and the damage type matched with the clothes is searched through the dragonfly population algorithm, so that the possibility of falling into local optimum during searching is reduced, and the damage type judgment precision is improved.

Description

Technical Field

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

[0002] In order to keep the clothes clean and tidy, users will clean or maintain the clothes every once in a while. For some clothes that are inconvenient to clean by themselves, users generally send the clothes to professional clothing cleaning shops for cleaning or maintenance. Clothing cleaning shops receive a large number of clothes for cleaning every day, so it is extremely important to manage the clothes that need to be cleaned, ensure the effect of clothing cleaning and meet the needs of customers. 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 for business management of the cleaning center, including user management, authority management, cleaning equipment management, cleaning process management, equipment alarm, information reminder, and data report management. At the same time, the B / S application system provides an open data service interface for data communication 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, notify services, evaluate quality, intelligently send and receive, and accurately count inventory for different object roles.

[0003] However, it is not convenient 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 targeted cleaning and maintenance of the clothes according to the conditions of the clothes. Summary of the invention

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

[0005] In order to achieve the above-mentioned object, the present invention provides the following technical solutions: a cleaning clothing management system based on RFID, 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 choice at the reserved address after the customer's clothing is cleaned, the membership level is used to record the customer's rights and interests information, and the order progress is used to record the progress information of the customer's clothing cleaning and the payment status information of the order, etc.;

[0007] The clothing information module is used to obtain clothing data that customers need to clean, and the clothing data includes clothing category data and category quantity data, wherein each clothing category corresponding to each clothing category data corresponds to one category data data, such as the clothing category data is "shirt" and its corresponding category quantity data is "2", which means that there are 2 "shirts";

[0008] The RFID information module is used to prepare the RFID chip to be physically bound to the clothing, and associate the RFID chip identification information with the corresponding clothing data and the customer 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 to the clothing washing management data. When acquiring clothing images, the clothing needs to be laid flat to take 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 out the clothing damage category corresponding to the clothing damage category feature image data matching 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 garments to generate difference image data after washing;

[0014] The image indication module is used to search for the image part 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 also used 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 matching the post-cleaning difference image data, generate clothing cleaning damage category data and update it to the clothing cleaning management data;

[0016] 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.

[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 quantity data of each category of clothes through manual judgment, and generate a collection of clothing category data and category quantity data u=1, 2, 3,…,ζ, where represents the u-th clothing category data, represents the number of clothes 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 RFID chip to be physically bound to the clothing, and associate the RFID chip identification information with the corresponding clothing data and the customer 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 clothing, such as placing the RFID chip and the clothing together, or fixing the RFID chip to the clothing with a buckle, a clip, etc. Preferably, each piece of clothing 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 identify the corresponding clothing cleaning management data according to the RFID chip identification information after reading the RFID chip.

[0025] Furthermore, the image acquisition module is used to acquire image data of clothing before and after washing, respectively 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, obtaining clothing image data before washing through clothing images taken by a high-definition camera, and generating a 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, obtaining clothing image data after washing through clothing images taken by a high-definition camera, and generating a clothing image data set after washing 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, performing 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 RFID chip identification information, and searching 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] Further, the image data processing module is used to perform search processing based on the clothing damage category feature image data and the clothing image data before washing, search out the clothing damage category corresponding to the clothing damage category feature image data matching the clothing image data before washing, generate user clothing damage category data and update it to the clothing washing management data, including the following steps:

[0031] S41, constructing a 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 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 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 at 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 of the dragonfly population with the best historical fitness;

[0037] S425, the dragonfly performs exploration and utilization behaviors in the F search space:

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

[0039]

[0040] Among them, α is the speed inertia weight, which is used to balance the proportion of exploration and utilization, rand() is a random number generation function, which is used to introduce uncertainty in a larger range to promote exploration, Ξ1=Θ1·Ψ1, 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 jump out of the local optimum;

[0041] Utilize behavior: Dragonflies search in F space according to their individual best position and the optimal position of the population X g Adjust the flight strategy and approach D yonghu The clothing damage category feature image data f with the best matching 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 F search space, Ξ2=Θ2·Ψ2, Ξ3=Θ3·Ψ3, Θ2 and Θ3 are constants used to control the influence 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 when it is 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 population's best position X 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 characteristic data of the rth type of clothing cleaning method, is 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, selecting the required clothing cleaning method in G', and generating 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 The image difference is generated after cleaning difference image data E chayi ;

[0058] S62. Positioning E based on template matching algorithm chayi In the corresponding yonghu Zhonge o The position of E chayi In the corresponding yonghu Zhonge o The positions in the image are visually marked to generate the difference marked 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] Further, 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 the cleaning method of 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 according to one item in the clothing cleaning management data, including the following steps:

[0060] S71, based on the dragonfly population algorithm, search for the same chayi Matching f p , generate clothing washing damage category data F sunhuai , and update 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 item in the search result, 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 damaged position mark 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 basic information of the customer and the data of the clothing that the customer needs to clean;

[0065] S2, preparing an RFID chip to be physically bound to the clothing, and associating the RFID chip identification information with the corresponding clothing data and the customer's basic information data to generate clothing cleaning management data;

[0066] 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 the clothing washing management data;

[0067] S4, performing search processing based on the clothing damage category feature image data and the clothing image data before washing, searching for the clothing damage category corresponding to the clothing damage category feature image data matching the clothing image data before washing, generating user clothing damage category data and updating it to the clothing washing management data;

[0068] S5, performing search processing based on clothing feature data of clothing cleaning methods, clothing category data and user clothing damage category data, searching for clothing cleaning methods corresponding to clothing feature data of clothing cleaning methods that match clothing category data and user clothing damage category data, generating clothing cleaning method recommendation data, visually displaying the clothing cleaning management data and 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 it to the clothing cleaning management data;

[0069] S6, performing difference analysis on the image data before and after washing to generate difference image data after washing, searching the image data after washing for image parts corresponding to the difference image data after washing and marking them, generating difference marked image data and updating them to the clothing washing management data;

[0070] S7, searching and processing the clothing damage category feature image data and the post-cleaning difference image data, searching for the clothing damage category corresponding to the clothing damage category feature image data matching the post-cleaning difference image data, generating clothing cleaning damage category data and updating it to the clothing cleaning management data, selecting the cleaning method of the corresponding clothing according to the clothing cleaning method feedback data in the clothing cleaning management data, and retrieving the corresponding remaining items in the clothing cleaning management data according to one of the items in the clothing cleaning management data.

[0071] 1. Compared with the prior art, 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, and search for the damage category matching the clothing through the dragonfly population algorithm, which reduces the possibility of falling into the local optimum during the search and improves the accuracy of damage type judgment.

[0072] 2. Compared with the prior art, 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 clothing damage categories and images of 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 status of the customer's clothing while taking into account the customer's opinions.

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

[0074] 4. Compared with the prior art, the RFID-based clothing cleaning management system and method provided by the present invention conveniently integrates various types of information of customers' corresponding cleaning clothing according to clothing cleaning management data through the cleaning management module, which is convenient for 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 drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0076] Figure 1 A system structure block diagram provided for 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 technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the 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 directly connected, or indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0080] Example embodiments will be described more fully below 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. On the contrary, the purpose of providing these embodiments is to make the present disclosure thorough and complete and to enable those skilled in the art to fully understand the scope of the present disclosure.

[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 clothing cleaning status. The address is used to facilitate mailing the cleaned clothing to the customer according to the reserved address selected by the customer after the customer's 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 information of the order.

[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 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".

[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 quantity data of each category of clothes through manual judgment, and generate a collection of clothing category data and category quantity data u=1, 2, 3,…,ζ, where represents the u-th clothing category data, represents the number of clothes 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 with the clothing, and associate the RFID chip identification information with the corresponding clothing data and the 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, etc. 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 identify the corresponding clothing cleaning management data according to the RFID chip identification information after reading the RFID chip.

[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 and after washing, and update them to clothing washing management data. When acquiring clothing images, the clothing needs to be laid flat to take images of the entire clothing and various parts, including the following steps:

[0095] S31, obtaining clothing image data before washing through clothing images taken by a high-definition camera, and generating a 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, obtaining clothing image data after washing through clothing images taken by a high-definition camera, and generating a clothing image data set after washing 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, performing 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 RFID chip identification information, and searching 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 image data before washing, search out the clothing damage category corresponding to the clothing damage category feature image data matching the clothing image data before washing, generate user clothing damage category data and update it to the clothing washing management data, including the following steps:

[0100] S41, constructing a 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 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 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 at 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 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 of 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 flies randomly in the F search space, which simulates the dragonfly flying randomly in a larger range to search for prey. This can expand the search range to ensure that the algorithm does not fall into the local optimal situation. The speed update formula of the dragonfly in the exploration behavior is as follows:

[0108]

[0109] Among them, α is the speed inertia weight, which is used to balance the proportion of exploration and utilization, rand() is a random number generation function, which is used to introduce uncertainty in a larger range to promote exploration, Ξ1=Θ1·Ψ1, 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 jump out of the local optimum;

[0110] Utilize behavior: Dragonflies search in F space according to their individual best position and the optimal position of the population X g Adjust the flight strategy and approach D yonghu The clothing damage category feature image data f with the best matching 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 F search space, Ξ2=Θ2·Ψ2, Ξ3=Θ3·Ψ3, Θ2 and Θ3 are constants used to control the influence 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 when it is 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 population's best position X 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 the 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 characteristic data of the rth type of clothing cleaning method, is 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 matching 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 part corresponding to the difference image data after washing in the image data of the washed clothes and mark it, generate the difference mark image data and update it to the clothing washing management data;

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

[0130] S61, Identify D based on the twin network algorithm yonghu Medium o With E yonghu Zhonge o The image difference is generated after cleaning difference image data E chayi ;

[0131] S62. Positioning E based on template matching algorithm chayi In the corresponding yonghu Zhonge o The position in E chayi In the corresponding yonghu Zhonge o The positions in the image are visually marked to generate the difference marked 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 also used 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 matching the post-cleaning difference image data, generate clothing cleaning damage category data and update it to the clothing cleaning management data;

[0133] The cleaning management module is used to select a cleaning method for corresponding clothing according to 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] Further, 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 the cleaning method of 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 according to one item in the clothing cleaning management data, including the following steps:

[0135] S71. Based on the dragonfly population algorithm, search for the same chayi Matching f p , generate clothing washing damage category data F sunhuai , and update 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 item in the search result, 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 damaged position mark 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 basic information of the customer and the data of the clothing that the customer needs to clean;

[0140] S2, prepare the RFID chip and the clothing to be physically bound, 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;

[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 search processing based on the clothing damage category feature image data and the clothing image data before washing, searching for the clothing damage category corresponding to the clothing damage category feature image data matching the clothing image data before washing, generating user clothing damage category data and updating it to the clothing washing management data;

[0143] S5, performing search processing based on clothing feature data of clothing cleaning methods, clothing category data and user clothing damage category data, searching for clothing cleaning methods corresponding to clothing feature data of clothing cleaning methods that match clothing category data and user clothing damage category data, generating clothing cleaning method recommendation data, visually displaying clothing cleaning management data and 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 it to the clothing cleaning management data;

[0144] S6, performing difference analysis on the image data before and after washing to generate difference image data after washing, searching the image data after washing for the image part corresponding to the difference image data after washing and marking it, generating difference marked image data and updating it to the clothing washing management data;

[0145] S7, searching and processing the clothing damage category feature image data and the post-cleaning difference image data, searching for the clothing damage category corresponding to the clothing damage category feature image data matching the post-cleaning difference image data, generating clothing cleaning damage category data and updating it to the clothing cleaning management data, selecting the cleaning method of the corresponding clothing according to the clothing cleaning method feedback data in the clothing cleaning management data, and retrieving the corresponding remaining items in the clothing cleaning management data according to one of the items in the clothing cleaning management data.

[0146] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

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, and the clothing data includes clothing category data and category quantity data; The RFID information module is used to prepare the RFID chip to be physically bound to the clothing, and associate the RFID chip identification information with the corresponding clothing data and the customer basic information data to generate clothing cleaning management data; 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 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 out the clothing damage category corresponding to the clothing damage category feature image data matching 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 garments to generate difference image data after washing; The image indication module is used to search for the image part 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 also used 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 matching the post-cleaning difference image data, generate clothing cleaning damage category data and update it to the clothing cleaning management data; 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.

2. The RFID-based cleaning clothing management system according to claim 1, characterized in that: The customer information module and the clothing information module include 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,…,ζ, where represents the u-th clothing category data, represents the number of clothes 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 ).

3. The RFID-based cleaning clothing management system according to claim 2 is characterized in that: The RFID information module is used to prepare the RFID chip to be physically bound to the clothing, and associate the RFID chip identification information with the corresponding clothing data and the customer basic information data to generate clothing cleaning management data, including the following steps: 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; S22, physically binding the RFID chip to the clothing; 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).

4. The RFID-based cleaning clothing management system according to claim 3 is characterized in that: The image acquisition module is used to acquire image data of clothing before and after washing, respectively generate image data before washing and image data after washing, and update them to the clothing washing management data, including the following steps: S31, obtaining clothing image data before washing, generating a clothing image data set D before washing = (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; S32, obtain the image data of the garment after washing, 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; S33, performing 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 RFID chip identification information, and searching 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 ).

5. The RFID-based cleaning clothing management system according to claim 4 is 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 image data before washing, search out the clothing damage category corresponding to the clothing damage category feature image data matching the clothing image data before washing, generate user clothing damage category data and update it to the clothing washing management data, including the following steps: S41, constructing a 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; S42, based on the dragonfly population algorithm, search for the same 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 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 of the dragonfly population with the best historical fitness; S425, the dragonfly performs exploration and utilization behaviors 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: Among them, α is the speed inertia weight, rand() is a random number generation function, Ξ1=Θ1·Ψ1, Θ1 is a constant, Ψ1 is a random number; Utilize behavior: Dragonflies search in F space according to their individual best position and the optimal position of the population X g Adjust the flight strategy and approach D yonghu The clothing damage category feature image data f with the best matching 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 when it is 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 population's best position X 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.

6. The RFID-based cleaning clothing management system according to claim 5, 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 = (g1, ..., g r , …, g θ ), r=1, 2, 3,…, θ, g r represents the clothing feature data of the rth type of clothing cleaning method, θ is the maximum number of categories of clothing feature data of clothing cleaning method; 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 represents the cleaning method of the r1th and r2th category clothing, 1≤r1≤r≤r2≤θ; S54, selecting the required clothing cleaning method in G', and generating 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 ).

7. The RFID-based cleaning clothing management system according to claim 6 is characterized in that: The difference image data module and the image indication module include the following steps: S61, Identify D based on the twin network algorithm yonghu Medium o With E yonghu Zhonge o The image difference is generated after cleaning difference image data E chayi ; S62. Positioning E based on template matching algorithm chayi In the corresponding yonghu Zhonge o The position of E chayi In the corresponding yonghu Zhonge o The positions in the image are visually marked to generate the difference marked 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 ).

8. The RFID-based cleaning clothing management system according to claim 7, characterized in that: 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 the cleaning method of 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 according to one item in the clothing cleaning management data, including the following steps: S71, based on the dragonfly population algorithm, search for the same chayi Matching f p , generate clothing washing damage category data F sunhuai , and update 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 item in the search results will be retrieved.

9. The RFID-based cleaning clothing management method is applicable to the RFID-based cleaning clothing management system according to any one of claims 1 to 8, characterized in that: The following steps are involved: S1. Obtain basic information of the customer and the data of the clothing that the customer needs to clean; S2, preparing an RFID chip to be physically bound to the clothing, and associating the RFID chip identification information with the corresponding clothing data and the customer's basic information data to generate clothing cleaning management data; 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 the clothing washing management data; S4, performing search processing based on the clothing damage category feature image data and the clothing image data before washing, searching for the clothing damage category corresponding to the clothing damage category feature image data matching the clothing image data before washing, generating user clothing damage category data and updating it to the clothing washing management data; S5, performing search processing based on clothing feature data of clothing cleaning methods, clothing category data and user clothing damage category data, searching for clothing cleaning methods corresponding to clothing feature data of clothing cleaning methods that match clothing category data and user clothing damage category data, generating clothing cleaning method recommendation data, visually displaying the clothing cleaning management data and 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 it to the clothing cleaning management data; S6, performing difference analysis on the image data before and after washing to generate difference image data after washing, searching the image data after washing for image parts corresponding to the difference image data after washing and marking them, generating difference marked image data and updating them to the clothing washing management data; S7, searching and processing the clothing damage category feature image data and the post-cleaning difference image data, searching for the clothing damage category corresponding to the clothing damage category feature image data matching the post-cleaning difference image data, generating clothing cleaning damage category data and updating it to the clothing cleaning management data, selecting the cleaning method of the corresponding clothing according to the clothing cleaning method feedback data in the clothing cleaning management data, and retrieving the corresponding remaining items in the clothing cleaning management data according to one of the items in the clothing cleaning management data.

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