Coin laundry use guide method

Abstract

To provide a coin laundry application enabling a user of a coin laundry to use the coin laundry by understanding optimal utilization method.SOLUTION: A coin laundry use guide method guides a user about a utilization method of laundry devices 131, 134. A method for making the laundry device wash or wash and dry laundry suitably for the laundry is precondition. The coin laundry use guide method includes: a step to transmit the precondition from a management device 101 to an operation condition generation device 102; a step to transmit an image of the laundry photographed by a camera of a portable terminal 105 to the operation condition generation device 102; a step in which the operation condition generation device 102 generates information for guiding a utilization method of the laundry devices 131, 134 to wash or wash and dry the laundry based on the precondition and the image; and a step to transmit the guide information from the operation condition generation device 102 to the portable terminal 105.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] An embodiment of the present invention relates to a coin laundry application that provides coin laundry usage guidance to a mobile device or the like of a coin laundry user. [Background technology]

[0002] Nowadays, coin laundromats are offering a wide range of services, especially for futons, with washing machines that can wash futons and carpets, and dryers specifically for futons becoming more common. The machines in the stores are also being designed to accommodate these, with dedicated courses set up so that an unspecified number of people can use them in various ways.

[0003] Along with these innovations, a technology has been proposed to guide users in coin laundries, enabling them to do their own laundry by providing them with images of laundry procedures tailored to the type of futon.

[0004] For example, Patent Document 1 discloses a coin laundry operation guidance system that includes an image service means that stores multiple images to assist laundry operations when washing and drying, according to the type of futon, and a portable device that reads an identification code corresponding to the type of futon to be washed and dried from an identification code table installed within the coin laundry store, and obtains the image corresponding to that identification code from the image service means. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2022-011561 Summary of the Invention [Problem to be solved by the invention]

[0006] However, when actually using the technology of Patent Document 1, support from an external operator etc. is required. Also, while the functions etc. have been enhanced to meet such a wide variety of needs, there has been an increase in the number of matters that require attention, and many pop-ups have been put up in stores to guide users to use the system correctly.

[0007] As a result, it is difficult for users to understand which machine and which setting to use for washing and drying, what precautions to take, etc. This creates a problem where it is difficult to know how to do what you want to do.

[0008] Therefore, an embodiment of the present invention aims to provide a coin laundry application that allows coin laundry users to understand the optimal way to use the coin laundry. [Means for solving the problem]

[0009] In this embodiment, a coin laundry system is provided which includes a plurality of laundry machines which are operated for a fee, a management device which directly or indirectly controls the laundry machines, a mobile terminal with a built-in camera owned by a user who uses the laundry machines, and an operating condition creation device which creates an optimal solution based on preconditions. The coin laundry usage guidance method provides guidance to the user on how to use the laundry machines, and includes the steps of: setting a method of washing or washing and drying the items to be washed using the laundry machines as the precondition; transmitting the precondition from the management device to the operating condition creation device; transmitting an image of the items to be washed taken with the camera of the mobile terminal to the operating condition creation device; generating information by the operating condition creation device to guide the user on how to use the laundry machines to wash or wash and dry the items based on the preconditions and the image; and transmitting the guidance information from the operating condition creation device to the mobile terminal. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a schematic diagram showing an example of the configuration of a coin laundry operation guidance system according to a first embodiment of the present invention; [Figure 2] 4 is a flowchart showing a processing procedure for creating a precondition and registering it in the operating condition creating device according to the first embodiment of the present invention. FIG. [Figure 3] FIG. 2 is a schematic diagram showing an example of display of prerequisites by a coin laundry application according to the first embodiment of the present invention. [Figure 4] FIG. 4 is a sequence diagram showing a processing procedure for recognizing tag information from an image and selecting the size of a washing machine or dryer according to the first embodiment of the present invention. [Figure 5] FIG. 2 is a schematic diagram showing an example of a display of a futon tag read by a coin laundry application according to the first embodiment of the present invention. [Figure 6] FIG. 2 is a schematic diagram showing an example of a display in which an OCR recognition result is obtained and a command is issued by a coin laundry application according to the first embodiment of the present invention. [Figure 7] FIG. 2 is a schematic diagram showing an example of a display of the recognition results of OCR performed by a coin laundry application according to the first embodiment of the present invention when a tag is read. [Figure 8] 10 is a schematic diagram showing an example of a display in which the recognition result of OCR by the coin laundry application according to the first embodiment of the present invention is sent and an "answer" is obtained from the operating condition creation device. FIG. [Figure 9] FIG. 2 is a schematic diagram showing an example of a feedback request displayed by a coin laundry application according to the first embodiment of the present invention. [Figure 10] FIG. 10 is a sequence diagram showing a processing procedure for selecting a laundry processing step from an image of an item to be washed according to a second embodiment of the present invention. [Figure 11] FIG. 10 is a schematic diagram showing an example of a display of an image of laundry for which prerequisites have been created by a coin laundry application according to a second embodiment of the present invention. [Figure 12]FIG. 10 is a schematic diagram showing an example of a display in which the OCR recognition result of the coin laundry application according to the second embodiment of the present invention is sent and an "answer" is obtained from the operating condition creation device. [Figure 13] FIG. 11 is a sequence diagram showing a processing procedure for selecting a laundry processing step from an image of an item to be washed according to a third embodiment of the present invention. [Figure 14] FIG. 11 is a schematic diagram showing an example of a display of an image of laundry for which prerequisites have been created by a coin laundry application according to a third embodiment of the present invention. [Figure 15] FIG. 11 is a schematic diagram showing an example of a display in which a "solution" is obtained by a coin laundry application according to a third embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0011] Preferred embodiments for carrying out the present invention will be described below with reference to the drawings. Note that the embodiments described below are examples of typical embodiments of the present invention, and do not limit the scope of the present invention, and various combinations, modifications, and changes are possible within the scope of the gist of the present invention.

[0012] 1. First Embodiment A coin laundry operation guide system according to a first embodiment of the present invention will be described with reference to FIGS. 1 to 9. FIG.

[0013] <1-1. Configuration of the coin laundry operation guidance system> An example of the configuration of a coin laundry operation guidance system according to a first embodiment of the present invention will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of the configuration of a coin laundry operation guidance system 100 according to this embodiment.

[0014] As shown in Figure 1, the coin laundry operation guidance system 100 comprises a management device (server) 101, an operating condition creation device (AI device) 102, a coin laundry store 103, a setting terminal 104, and a coin laundry user's mobile terminal 105. The management device 101, operating condition creation device (AI device) 102, coin laundry store 103, setting terminal 104, and mobile terminal 105 are all interconnected via a network.

[0015] Management device 101 is a server device or the like that directly or indirectly controls multiple laundry devices in coin laundry store 103. The laundry devices include, for example, washer-dryer 131, dryer 134, and washing machine. When a customer who visits coin laundry store 103 puts laundry and money into washer-dryer 131 or dryer 134 and washes or dries the laundry, management device 101 directly controls washer-dryer 131 and dryer 134. Management device 101 also indirectly controls washer-dryer 131 and dryer 134 via mobile terminal 105 and setting terminal 104.

[0016] The operating condition creation device (AI device) 102 is a cloud server or the like that creates an optimal solution based on preconditions using, for example, artificial intelligence (AI) software such as ChatGPT (registered trademark) or Claude (registered trademark). The AI ​​device 102 includes a database (DB) that stores learned data based on preconditions.

[0017] The coin laundry store 103 is a store that has multiple laundry machines that can be operated for a fee and that allow users (consumers who use the washer-dryers 131) to wash or dry clothes, etc. The coin laundry store 103 is equipped with multiple washer-dryers 131 (1, 2, . . . , n), multiple dryers 134 (1, 2, . . . , m), multiple washing machines, and one or more payment machines 132 (1, 2, . . . , j). The coin laundry store 103 is equipped with a QR code 133 for accessing the management device 101. The QR code 133 is a two-dimensional identification code that is displayed on a wall inside the coin laundry store 103, or on the payment machine 132, washer-dryers 131, or dryers 134.

[0018] The setting terminal 104 is composed of a store mobile terminal 135 (such as a smartphone) and a personal computer 136. The setting terminal 104 is equipped with a store management application, and the store management application runs in the store mobile terminal 135 and the personal computer 136. The setting terminal 104 creates preconditions for the user to use the washer / dryer 131 and registers the preconditions in the AI ​​device via the management device 101. The setting terminal 104 is operated by the store manager or store owner of the coin laundry store 103, or the manufacturer that provides the washer-dryer 131, management device 101, etc. (the store manager, store owner, and manufacturer are collectively referred to as the laundry manager). The setting terminal 104 works in conjunction with the management device 101 and, in addition to configuring the AI ​​device 102, also controls the coin laundry store's washer-dryers 131, dryers 134, and payment machines 132, manages sales, and monitors their operating status using a store management application. The prerequisites are sent to the AI ​​device 102 from the store's mobile terminal 135 or personal computer 136 via a wired or wireless network, either via the management device 101 or without going through the management device 101. The store mobile terminal 135 is a smartphone or the like owned by the laundry manager of the coin laundry store 103, and is equipped with an input / output screen and a built-in camera.

[0019] Mobile terminal 105 is a smartphone or the like owned by a user of coin laundry store 103, and is equipped with an input / output screen and a built-in camera. Mobile terminal 105 has a mobile terminal application installed by the user for communicating with management device 101 to operate washer-dryer 131. The mobile terminal application transmits input information from mobile terminal 105 and image information captured by the camera to management device 101, and controls mobile terminal 105 to receive and display an input screen for operating washer-dryer 131, information indicating the end of washer-dryer 131 operation, a usage fee for washer-dryer 131, etc. from management device 101. A user who wishes to receive guidance on how to use a washer / dryer for clothes or futons, etc., inquires about recommended washer / dryer and washing conditions from AI device 102 via mobile terminal 105 or management device 101 before using washer / dryer 131. Based on the washer / dryer and washing conditions suitable for the clothes or futon recommended by the AI ​​device (the "solution" information from the AI ​​device), the user can select the equipment to be used, operating time, number of operations, detergent, fabric softener, etc., and then wash and dry the clothes.

[0020] The mobile terminal application installed on the mobile terminal 105, the store operation application installed on the setting terminal 104, and the application running in the management device 101 are all included in the laundry application.

[0021] <1-2. Prerequisite registration procedure> Next, a processing procedure for creating a precondition according to this embodiment and registering it in the AI ​​device 102 will be described with reference to FIGS.

[0022] Figure 2 is a flowchart of processing between the setting terminal 104 and the AI ​​device 102. It shows the process in which a laundry manager creates prerequisites for a user to use the washer-dryer 131 and registers them in the AI ​​device 102 via a store management application installed on the setting terminal 104. In S101, the store management application queries the AI ​​device 102 via the management device 101.

[0023] In S102, when the AI ​​device 102 receives inquiry information from the store management application via the management device 101, it transmits a response message to the setting terminal 104 via the management device 101 indicating that the inquiry information has been received.

[0024] In S103, the laundry manager creates prerequisites for the AI ​​device 102 to learn. The prerequisites indicate data that the AI ​​device 102 learns about the equipment and washing / drying methods recommended to the user when the user uses the washer / dryer 131 to wash or dry clothes, etc. In this embodiment, the prerequisites include conditions related to the size (weight) of the futon, images related to the type of laundry, images related to stains, etc.

[0025] The laundry manager creates the prerequisites on the store mobile terminal 135 of the setting terminal 104 or on the personal computer 136. The sentences explaining the washing and drying methods that serve as the prerequisites are created on the personal computer 136. In addition, images of each type of laundry, images that serve as the basis for estimating the weight of the laundry, images of stains on clothes and bedding, etc. are taken with the built-in camera of the store mobile terminal 135 and used as the prerequisites. In S104, the created preconditions are registered in the management device 101.

[0026] Fig. 3 shows an example of prerequisites that apply when washing a down comforter registered in the management device 101. The S size, M size, and L size indicate the size of the washer / dryer. For example, the S size can wash and dry down comforters up to 15 kg, the M size can wash and dry down comforters up to 27 kg, and the L size can wash and dry down comforters up to 35 kg. This is an example in which the conditions for washing and drying for each size are defined in a document.

[0027] In S105 of FIG. 2, the AI ​​device 102 performs the registration procedure based on the transmitted prerequisite registration information.

[0028] In S106, the AI ​​device 102 constructs a database (DB) for storing data that has been learned based on the preconditions.

[0029] <1-3. Operation of the operation guidance system> Next, referring to Figures 4 to 9, a processing procedure for selecting the size of a washing machine or dryer from the OCR output of tag information attached to the end of a futon according to this embodiment will be described. Figure 4 is a sequence diagram showing the processing procedure for selecting the size of a washing machine from the OCR (Optical Character Recognition) output of tag information according to this embodiment. Note that instead of OCR, it is also possible for an AI device to recognize character information from an image of the tag information attached to the end of a futon captured by mobile terminal 105, and select the size of a washing machine or dryer.

[0030] A user accesses the management device 101 from a mobile terminal application installed on the mobile terminal 105, and from the management device 101 accesses the AI ​​device 102 that stores data that has been trained based on preconditions.

[0031] Then, when the AI ​​device 102 receives the access information from the mobile terminal application and transmits a response message to the mobile terminal 105 indicating that the information has been received, the process begins.

[0032] As shown in FIG. 4, in S131, the user takes an image of a tag of an item to be washed or dried, such as a futon tag, using a camera built into the mobile terminal 105, for example, from a mobile terminal application on the mobile terminal 105, such as a smartphone, and reads the tag.

[0033] As shown in FIG. 5, on the mobile terminal application of the mobile terminal 105, for example, a quality label tag fixed to the end of a feather comforter is photographed with a built-in camera and the image is read.

[0034] In S132 of FIG. 4, the mobile terminal 105 transmits the image of the captured and read futon tag to the management device 101 such as an application server.

[0035] In S133, the management device 101 uses the image of the futon tag and a prompt to request the AI ​​device 102 to suggest the optimal washing or drying course. At this time, the management device 101 can perform character recognition on the futon tag using OCR technology or the like, and then use the prompt to request the AI ​​device 102 to suggest the optimal course. A prompt is an instruction or question that a user inputs through the management device 101 in a system that interacts with the AI ​​device 102.

[0036] 6 shows an example of a prompt to the AI ​​device 102. The display screen of the management device 101 displays a prompt that instructs the AI ​​device 102 to obtain character recognition results using OCR technology from an image of, for example, a futon tag. Figure 7 shows the results of character recognition performed by extracting characters using OCR technology from the image of the futon tag shown in Figure 5. The character information obtained by OCR technology is transmitted together with a prompt from the AI ​​device 102.

[0037] In S134 of FIG. 4, the management device 101 transmits to the AI ​​device 102 an image of the futon tag that has undergone character recognition using OCR technology and a command prompt. Instead of character recognition using OCR technology, the management device 101 can also send an image of the futon tag taken with the mobile terminal 105 to the AI ​​device 102, and have the AI ​​device 102 read the text information in the image through analysis. When having the AI ​​device 102 read the text information through image analysis, the management device 101 sends the AI ​​device 102 an image of the futon tag taken and a command (asking the AI ​​device 102 about the appropriate washing method for washing the futon).

[0038] In S135, the AI ​​device 102 uses ChatGPT or the like to create a solution based on the preconditions stored in the database for the futon tag and command prompt sent from the management device 101.

[0039] In S136, the AI ​​device 102 transmits the created solution (analysis result) to the management device 101, and the management device 101 receives the analysis result transmitted from the AI ​​device 102.

[0040] In S137, the management device 101 checks whether the received analysis result is an inappropriate answer, such as whether it contains NG words or inappropriate phrases or descriptions. If the answer is inappropriate, the management device 101 corrects or deletes the inappropriate part, or queries the AI ​​device 102 again to correct the inappropriate part.

[0041] In S138, the management device 101 transmits an "appropriate answer" in which the inappropriate parts have been corrected or deleted to the mobile terminal 105, and causes the mobile terminal 105 to display a recommended washing and drying course or washing and drying method for the user to wash and dry the futon.

[0042] Figure 8 shows an example of a recommended washing program for a user to wash and dry a futon. Figure 8(A) shows the analysis results of the futon washing and drying method, washer-dryer size, etc., obtained from the AI ​​device 102, received by the management device 101. From the results of Figure 8(A), a recommended washing and drying program such as that shown in Figure 8(B) is displayed on the display device of the mobile terminal 105 used by the user.

[0043] In S139 of FIG. 4, the user who has received the optimal course reads the QR code 133 of the payment machine 132 provided in the coin laundry store 103 with the mobile terminal 105 and accesses the management device 101.

[0044] The mobile terminal 105 receives a list of washer-dryers 131 available for use within the coin laundry store 103 from the accessed management device 101. A list is displayed on the mobile terminal 105 so that the user can see the operating status of the multiple washer-dryers 131 (131-1, 131-2, . . . 131-n) and multiple dryers 134 (134-1, 134-2, . . . 134-m) installed within the coin laundry store 103. For example, icons are displayed to indicate that the washer-dryer 131-1 is operating but unavailable for use by the user, and that the washer-dryer 131-n is available for use by the user, allowing the user to easily determine whether or not the machine is available for use.

[0045] The user selects a washer-dryer 131 from the list of washer-dryers 131 (131-1, 131-2, ..., 131-n) received by the mobile terminal 105, according to the course recommended by the AI ​​device 102 displayed on the mobile terminal application of the mobile terminal 105. The user places the futon in the selected washer-dryer 131 and pays the fee using the mobile terminal application of the mobile terminal 105, or pays the fee using cash, credit card, etc. using the payment machine 132. After payment is complete, the laundry is processed using the washing course or washing-drying course specified by the user. After the washing and drying processes are completed, the user removes the laundry from the washer-dryer 131 or dryer 134.

[0046] In S140 of Figure 4, the management device 101 displays a questionnaire pop-up on the mobile terminal 105 via a mobile terminal application, requesting feedback on whether the AI ​​device 102's suggestion was good or not after the user has performed laundry or drying (see Figure 9(A)).

[0047] In S141, the user responds by inputting feedback on the proposed optimum course into the mobile terminal 105 in accordance with the contents of the pop-up.

[0048] In S142, the mobile terminal 105 transmits the content of the feedback from the user to the management device 101.

[0049] In S143, the management device 101 transmits the content of the feedback from the user to the AI ​​device 102 and also sends a reply to the mobile terminal 105 indicating that the feedback has been received. Upon receiving the reply, the mobile terminal 105 displays a pop-up on the display screen expressing gratitude for the feedback. In this case, the management device 101 can cause the mobile terminal 105 to display a message of thanks for the feedback (see FIG. 9(B)).

[0050] In S144, the AI ​​device 102 stores the received feedback content in addition to the preconditions learned in advance in a database. By additionally learning the feedback content, the AI ​​device 102 will be able to present a more appropriate solution to the user the next time it receives an inquiry.

[0051] <1-4. Washer / Dryer Operation Guide> Next, operation guidance for washer / dryer 131 by the mobile terminal application of mobile terminal 105 according to this embodiment will be described.

[0052] First, we will explain how to wash your futon, the machines to use, the courses, etc.

[0053] A user who wishes to receive instructions on how to use the washer / dryer 131 and dryer 134 starts up mobile device 105 on which a mobile device application has been installed. After starting up, the user uses the built-in camera of mobile device 105 to photograph a tag attached to the edge of the futon and capture the image. The captured image is sent to management device 101, where it is converted into text data using the OCR technology of management device 101. This text data (text information) is then sent to AI device (operating condition creation device) 102, which analyzes the text data and selects the appropriate model and course in the store for washing the futon. The selected appropriate model and washing course are displayed as washing method instructions on the user's mobile device application via management device 101.

[0054] Regarding how to wash the futon, in addition to providing optimal guidance based on the image captured using the built-in camera in the mobile terminal 105, a method of providing optimal guidance based on several options or input is also used. In short, since there are cases where the text written on the tag on the futon is difficult to read and it is expected that diagnosis based on the image will be difficult, a service of providing optimal guidance based on options is also provided.

[0055] Next, the guidance on the washing and washing / drying courses or the drying time will be described.

[0056] When the user has launched the mobile terminal application on the mobile terminal 105, they press a specific button to move to the user support screen. On the support screen, they select an appropriate category from a broad range of categories. After making their selection, the user answers a number of questions, which allows the mobile terminal application to provide optimal guidance.

[0057] For example, the user selects "bedding" from categories such as "bedding," "general clothing," and "large items." Next, you can select from "futon mattress," "comforter," "blanket," etc., and enter or select the necessary information such as "number of sheets" and "material," and you will be given instructions such as "Please use the □□ course on machine number ○○."

[0058] Additionally, if there are any precautions to take regarding how to wash or how to load the drum, the mobile device application will similarly provide such a notice.

[0059] Next, the operation time of the dryer and the like will be described.

[0060] In particular, when drying ordinary clothes in the dryer 134, customers using the dryer for the first time may not know how long to run it for. With the mobile terminal application running on the mobile terminal 105, the user operates the built-in camera of the mobile terminal 105 to capture a photograph of the state of the clothes placed in the drum. The captured image is sent to the management device 101, and then to the AI ​​device 102. The AI ​​device 102 performs an image diagnosis on the transmitted image, recognizes the approximate load (clothing weight), and guides the user to the appropriate drying time based on pre-registered data.

[0061] At this time, the user is asked to select or input in the mobile terminal application whether the items to be dried are ordinary clothes, stickers, blankets, bedding, etc.

[0062] Next, guidance on the washing or washing and drying course (such as a small amount course or a standard course) will be described.

[0063] As with the guidance on the operating time of the above-mentioned dryer, a photograph of the material to be dried placed in the drum is taken as an image, and it is determined whether the small amount course or the standard course is appropriate, and guidance is given on the mobile terminal application of the mobile terminal 105.

[0064] The type of material to be dried can be selected or input on the mobile terminal application. In addition to taking a photo image, the same guidance can also be provided by selecting or inputting the amount of material to be dried.

[0065] Next, the settlement and payment using the mobile terminal application of the mobile terminal 105 will be described.

[0066] The information about the operating times of the dryer and other appliances, as well as the washing and washing / drying courses, can be linked to payment and settlement using a mobile device application, for example. After selecting any in-store appliance, putting in clothes and closing the door, the mobile device application allows you to select either washing, drying, or washing / drying at the next step after selecting the appliance (there is no course selection for dryers).

[0067] The mobile device application then uses the built-in camera to capture an image so that the amount of items placed in the drum can be seen, and image recognition automatically sets the appropriate amount of water, time, etc., and once the amount is confirmed, payment can proceed, providing appropriate support throughout the mobile device application payment sequence.

[0068] Next, the notification of the additional drying time will be described.

[0069] After drying, the user takes out the futon and takes a picture of it with the built-in camera of the mobile terminal 105, and sends the picture to the management device 101. The management device 101 and AI device 102 process the image of the picture to detect the degree of wetness, and if there are any areas that are still wet, the mobile terminal application displays a message indicating how many more minutes are needed to dry the futon.

[0070] Additionally, weather information can be obtained from the web using the store's location information, and a preset discount rate for each weather type can be automatically applied to payments made via a mobile device application depending on the weather. For example, use of laundromats is expected to increase during rainy times or days or on days when high pollen counts are predicted, but use of laundromats tends to decrease during sunny times or days when pollen counts are low. If sunny weather is predicted, the store management application sets the discount rate for the washer / dryer 131 and dryer 134 lower than when rainy weather is predicted, and notifies the mobile device 105 of the changed discount rate. The changed discount rate can be displayed on the mobile device application to encourage users to visit the laundromat store.

[0071] The coin laundry operation guidance system 100 according to this embodiment includes a laundry application, and can provide coin laundry users with guidance on how to use the washer / dryer and dryer more appropriately.

[0072] With the coin laundry operation guidance system 100 according to this embodiment, a user of a coin laundry store 103 can take a photo of a futon tag or the like using a mobile device application, and the information obtained from the image can be used to receive guidance on the appropriate washing method, the equipment to be used, the washing program, etc., on the mobile device application. Also, by taking a photo of the items to be washed or dried placed in the drum using the mobile device application, the appropriate operating time, the washing program, etc. can be provided on the mobile device application. Furthermore, by answering a few questions on the mobile device application, the user can receive guidance on the optimal service.

[0073] In this way, the user can use the mobile terminal application on the mobile terminal 105 to operate the washer-dryer 103 according to the analysis results by the AI ​​device 102 (operating condition creation device), so that the user can understand the optimal way to use the coin laundry.

[0074] Furthermore, by using the mobile device application according to this embodiment to take a photo of the object to be dried after drying, it is possible to determine whether it is completely dry and to receive guidance on how much additional drying time is required. For example, after drying, the user can take out the futon and take a photo of it with the camera in the mobile device and send it to the AI ​​device 102. The AI ​​device 102 processes the photo image to detect the wetness of the object to be dried, and if there are any areas that are still not dry, the mobile device application will provide guidance on how many more minutes are needed to dry it.

[0075] The coin laundry operation guidance system 100 can also determine the weather conditions around the coin laundry store 103 within the mobile device application and automatically apply a preset discount rate depending on the weather. For example, weather conditions can be obtained from the web using the location information of the coin laundry store 103, and a preset discount rate for each weather type can be automatically applied to payments made through the mobile device application depending on the weather. In addition, by displaying this information on the mobile device application, it is possible to encourage use of the coin laundry store 103.

[0076] 2. Second Embodiment The operation of the coin laundry operation guidance system according to the second embodiment of the present invention will be described with reference to Figs. 10 to 12. Fig. 10 is a sequence diagram showing the processing procedure for selecting a laundry process from an image of laundry according to this embodiment. In Fig. 10, the weight of the laundry is estimated by taking a photo of the laundry inside the drum of the washer-dryer 131. Note that another method for measuring the weight of the laundry is to estimate the weight of the laundry by measuring the current when the motor rotates the washing drum with the laundry placed inside.

[0077] A user accesses the management device 101 from a mobile terminal application installed on the mobile terminal 105, and from the management device 101 accesses the AI ​​device 102 that stores data that has been trained based on preconditions.

[0078] Then, when the AI ​​device 102 receives the access information from the mobile terminal application and transmits a response message to the mobile terminal 105 indicating that the information has been received, the process begins.

[0079] As shown in FIG. 10, in S201, the user takes an image of the laundry or drying items in a washer-dryer 131 installed in a coin laundry store 103, for example, using the built-in camera of the mobile terminal 105 from the mobile terminal application on the mobile terminal 105, and reads the image.

[0080] As shown in FIG. 11, the setting terminal 104, which includes the store mobile terminal 135 and the personal computer 136, creates preconditions from images of laundry or drying items. To create the preconditions, the laundry manager creates multiple clusters of laundry (C1, C2, . . . Cn), measures the weight of each cluster C1, C2, . . . Cn, and takes images of each cluster of laundry (C1, C2, . . . Cn). As preconditions, the image of each cluster is associated with its weight. Images of each type of clothing and bedding are also taken, and the material, color, etc. of each clothing and bedding are associated with the image to create preconditions. Specific examples of clothing and bedding include dress shirts, T-shirts, handkerchiefs, towels, socks, sheets, and towel blankets. The created preconditions are learned by the AI ​​device 102 via the management device 101.

[0081] Another method for estimating the weight of laundry placed in the drum of the washer-dryer 131 or dryer 134 is to estimate it from the difference in current flowing through the motor required to rotate a drum containing laundry and a drum containing laundry. In this case, the relationship between the mass of laundry and the motor current is a prerequisite.

[0082] In S202, the mobile terminal 105 transmits to the management device 101 the image of the items to be washed or dried that has been captured and read.

[0083] In S203, the management device 101 transmits an image of the laundry or drying items and a command prompt to the AI ​​device 102, requesting it to propose an optimal washing or drying course. The management device 101 then causes the AI ​​device 102 to estimate the weight of the laundry items placed in the laundry device from the captured image.

[0084] When the weight is estimated based on the current flowing through the motor required to rotate the drum, the value of the current flowing through the motor is transmitted to the AI ​​device 102 in accordance with an image of the items to be washed or dried.

[0085] In S204, the AI ​​device 102 uses Chat GPT or the like to create a solution based on the preconditions stored in the database in response to the image of the items to be washed or dried and the command prompt sent from the management device 101.

[0086] In S205, the AI ​​device 102 transmits the created solution (analysis result) to the management device 101, and the management device 101 receives the analysis result transmitted from the AI ​​device 102.

[0087] In S206, the management device 101 checks whether the received analysis result is an inappropriate answer, such as whether it contains NG words or inappropriate language or descriptions. If the answer is inappropriate, the management device 101 corrects or deletes the inappropriate part, or queries the AI ​​device 102 again.

[0088] In S207, the management device 101 transmits an "appropriate answer" in which the inappropriate part has been corrected or deleted to the mobile terminal 105, and causes the mobile terminal 105 to display the recommended selected course.

[0089] FIG. 12 shows the analysis results obtained from ChatGPT of the AI ​​device 102 received by the management device 101 in the second embodiment.

[0090] In S208 of FIG. 10, the user who has received the optimal course reads the QR code 133 of the payment machine 132 installed in the coin laundry store 103 with the mobile terminal 105 and accesses the management device 101.

[0091] The mobile terminal 105 receives a list of washer-dryers 131 available for use in the coin laundry store 103 from the accessed management device 101.

[0092] From the list of washer-dryers 131 received on mobile terminal 105, the user selects a washer-dryer 131 that has the optimal course displayed on the mobile terminal application available and that can accept laundry such as clothes and bedding. After loading laundry into the washer-dryer 131 selected by the user, the user pays the fee at payment machine 132 and operates washer-dryer 131. The user can also use the payment function of mobile terminal 105 to make payment.

[0093] In S209, after the user has performed the washing or drying, the mobile terminal 105 displays a pop-up requesting feedback on whether the suggestion made by the AI ​​device 102 was good or not, similar to the pop-up display shown in FIG. 9(A).

[0094] In S210, the user responds by inputting feedback on the proposed optimum course into the mobile terminal 105 in accordance with the contents of the pop-up.

[0095] In S211, the mobile terminal 105 transmits the content of the feedback from the user to the management device 101.

[0096] In S212, the management device 101 transmits the content of the feedback from the user to the AI ​​device 102 and also sends a reply to the mobile terminal 105 indicating that the feedback has been received. Upon receiving the reply, the mobile terminal 105 can display a pop-up message on its display screen expressing gratitude for the feedback. This is similar to the pop-up display shown in FIG. 9(B).

[0097] In S213, the AI ​​device 102 stores the content of the received feedback in addition to the preconditions learned in advance in a database.

[0098] According to the coin laundry operation guidance system of this embodiment, as in the first embodiment, users of the coin laundry store 103 can use the mobile device application on the mobile device 105 to understand the optimal way to use the coin laundry.

[0099] 3. Third Embodiment The operation of the coin laundry operation guidance system according to the third embodiment of the present invention will be described with reference to Fig. 13 to Fig. 15. Fig. 13 is a sequence diagram showing the processing procedure for selecting a laundry process from an image of an item to be washed according to this embodiment.

[0100] A user accesses the management device 101 from a mobile terminal application installed on the mobile terminal 105, and from the management device 101 accesses the AI ​​device 102 that stores data that has been trained based on preconditions.

[0101] Then, when the AI ​​device 102 receives the access information from the mobile terminal application and transmits a response message to the mobile terminal 105 indicating that the information has been received, the process begins.

[0102] As shown in FIG. 13, in S301, the user takes an image of the stains on the laundry in, for example, a washer / dryer 131 installed in a coin laundry store 103 from the mobile terminal application of the mobile terminal 105, and reads the image.

[0103] Figure 14 shows the types of stains and dirt that can be found on clothing and how to remove each type of stain or dirt. The laundry manager uses a setting terminal 104, which includes a store mobile terminal 135 and a personal computer 136, to take pictures of stains and dirt on the laundry and create preconditions by associating each stain and dirt with a method for removing it. The created preconditions are sent to the AI ​​device 102 via the management device 101, and the AI ​​device 102 learns them.

[0104] In S302, the mobile terminal 105 transmits the captured image of the dirt on the laundry to the management device 101. In this way, by taking a photo of the degree of dirt on the laundry using the mobile terminal application, the AI ​​device 102 can analyze the degree of dirt and recommend the optimal course to be selected.

[0105] In S303, the management device 101 transmits an image of the stains on the laundry and a command prompt to the AI ​​device 102, requesting it to propose an optimal washing course.

[0106] In S304, the AI ​​device 102 uses ChatGPT or the like to create a solution based on the preconditions stored in the database in response to the image of the stains on the laundry item and the command prompt sent from the management device 101.

[0107] In S305, the AI ​​device 102 transmits the created solution (analysis result) to the management device 101, and the management device 101 receives the analysis result transmitted from the AI ​​device 102.

[0108] In S306, the management device 101 checks whether the received analysis result is an inappropriate answer, such as whether it contains NG words or inappropriate language or descriptions. If the answer is inappropriate, the management device 101 corrects or deletes the inappropriate part, or queries the AI ​​device 102 again.

[0109] In S307, the management device 101 transmits an "appropriate answer" in which the inappropriate part has been corrected or deleted to the mobile terminal 105, and causes the mobile terminal 105 to display the recommended selected course.

[0110] Fig. 15(A) shows the analysis results obtained from ChatGPT of the AI ​​device 102 received by the management device 101 in the third embodiment. Fig. 15(B) shows an example of a recommended stain removal method and washing program received by the user on the mobile terminal 105 in the third embodiment.

[0111] In S308 , the user who has received the optimal course reads the QR code 133 of the payment machine 132 installed in the coin laundry store 103 with the mobile terminal 105 and accesses the management device 101 .

[0112] The mobile terminal 105 receives a list of washer-dryers 131 available for use in the coin laundry store 103 from the accessed management device 101.

[0113] From the list of washer-dryers 131 received by mobile terminal 105, the user selects a washer-dryer 131 that has the optimal course displayed on the mobile terminal application and that can accept laundry items such as clothes and bedding. After the user places the stained or dirty laundry items into the washer-dryer 131 selected by the user, the user sets the course and pays the fee at payment machine 132 to operate washer-dryer 131. The user can also make payment using the payment function of mobile terminal 105.

[0114] In S309, after the user has performed the washing or drying, the mobile terminal 105 displays a pop-up requesting feedback on whether the suggestion made by the AI ​​device 102 was good or not, similar to the pop-up display shown in FIG. 9(A).

[0115] In S310, the user responds by inputting feedback on the proposed optimum course into the mobile terminal 105 in accordance with the contents of the pop-up.

[0116] In S311, the mobile terminal 105 transmits the content of the feedback from the user to the management device 101.

[0117] In S312, the management device 101 transmits the content of the feedback from the user to the AI ​​device 102 and also sends a reply to the mobile terminal 105 indicating that the feedback has been received. Upon receiving the reply, the mobile terminal 105 can display a pop-up message on its display screen expressing gratitude for the feedback. This is similar to the pop-up display shown in FIG. 9(B).

[0118] In S313, the AI ​​device 102 stores the content of the received feedback in addition to the preconditions learned in advance in a database.

[0119] According to the coin laundry operation guidance system of this embodiment, as in the first embodiment, users of the coin laundry store 103 can use the mobile device application on the mobile device 105 to understand the optimal way to use the coin laundry.

[0120] The embodiments of the present invention are presented as examples and are not intended to limit the scope of the invention. These novel embodiments may be embodied in various other forms, and various omissions, substitutions, and modifications may be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, and are also included in the scope of the inventions and their equivalents as defined in the claims.

[0121] The present invention can have the following configuration. (1) a plurality of laundry devices operated for a fee; a management device that controls the laundry machine; a mobile terminal equipped with a built-in camera and owned by a user of the laundry machine; an operating condition creation device that creates an optimal solution based on preconditions; and a coin laundry usage guidance method that guides the user on how to use the laundry device in a coin laundry system, comprising: a step of setting a washing or washing-drying method suitable for the laundry by the laundry machine as the precondition, and transmitting the precondition from the management device to the operating condition creation device; transmitting an image of the laundry taken by the camera of the mobile terminal to the operating condition creation device; generating information for guiding how to use the laundry machine to wash or wash-dry the laundry items based on the prerequisites and the image by the operating condition creation device; transmitting the information to be guided from the operating condition creating device to the mobile terminal; Instructions on how to use coin laundries, including: (2) The coin laundry usage guidance method described in (1) includes a step in which the operating condition creation device extracts information regarding the handling of the laundry contained in the image of the laundry. (3) The coin laundry usage guidance method described in (1) or (2) includes a step in which the management device extracts character information contained in the image of the laundry item using optical character recognition technology, and transmits the extracted character information together with the image to the operating condition creation device. (4) A coin laundry usage guidance method described in any one of (1) to (3), including a step in which the operating condition creation device receives feedback from the user after washing or drying, and creates the solution based on the prerequisites and the feedback. (5) A method for providing guidance on using a coin laundry described in any one of (1) to (4), wherein the prerequisite is an image of the soiled state of the item to be washed or the item to be dried. (6) A method for providing guidance on how to use a coin laundry described in any one of (1) to (5), wherein the information providing guidance on how to use the laundry is at least one of how to wash, the equipment to be used, the appropriate operating time, and the washing course. [Explanation of symbols]

[0122] 100 Coin laundry operation guidance system 101 Management device (server device) 102 Operating condition creation device (AI device) 103 Coin laundry stores 104 Setting terminal 105 Mobile Devices 131 Washer-dryer (laundry equipment) 132 Payment machine 133 QR Code 134 Dryer (laundry equipment) 135 Mobile terminals for stores 136 Personal Computers

Claims

1. a plurality of laundry devices operated for a fee; a management device that controls the laundry machine; a mobile terminal equipped with a built-in camera and owned by a user of the laundry machine; an operating condition creation device that creates an optimal solution based on preconditions; and a coin laundry usage guidance method that guides the user on how to use the laundry device in a coin laundry system, comprising: a step of setting a washing or washing-drying method suitable for the laundry by the laundry machine as the precondition, and transmitting the precondition from the management device to the operating condition creation device; transmitting an image of the laundry taken by the camera of the mobile terminal to the operating condition creation device; generating information for guiding how to use the laundry machine to wash or wash-dry the laundry items based on the prerequisites and the image by the operating condition creation device; transmitting the information to be guided from the operating condition creating device to the mobile terminal; Instructions on how to use coin laundries, including:

2. The coin laundry usage guidance method according to claim 1, further comprising a step in which the operating condition creation device extracts information regarding laundry handling contained in the image of the laundry.

3. The coin laundry usage guidance method described in claim 1, including a step in which the operating condition creation device receives feedback from the user after washing or drying is performed, and creates the solution based on the prerequisites and the feedback.

Images