Fitting room management system, fitting room management method and program

Abstract

To provide a fitting room management system which can grasp more accurate waiting time of a fitting room.SOLUTION: A fitting room management system includes: acquisition means for acquiring the kind of a commodity that a customer fits; prediction means for predicting utilization time of a fitting room of the customer, on the basis of the kind of the commodity; estimation means for estimating waiting time until another customer can utilize the fitting room, on the basis of the predicted utilization time; and output means for outputting the estimated waiting time.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to a fitting room management system and the like.

Background Art

[0002] Stores that sell clothing generally have fitting rooms. Customers bring products into the fitting rooms, try on the products, and consider purchasing the products.

[0003] In order to grasp the usage status of fitting rooms, the use of an information processing system is considered. Patent Document 1 discloses a fitting efficiency improvement system that causes a display device to display a standard waiting time for a fitting room. In Patent Document 1, as the standard waiting time, a value calculated by multiplying the current number of waiting groups by the average waiting time per group is used.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] The fitting time is assumed to be different for each customer. Therefore, when obtaining the waiting time of the fitting room, it is desirable that the difference in the usage time for each customer be reflected.

[0006] An object of the present disclosure is to provide a fitting room management system and the like that enable a more accurate grasp of the waiting time of a fitting room.

Means for Solving the Problems

[0007] The fitting room management system relating to this disclosure includes an acquisition means for acquiring the type of product a customer tries on, a prediction means for predicting the customer's time using the fitting room based on the type of product, an estimation means for estimating the waiting time until another customer can use the fitting room based on the predicted time, and an output means for outputting the estimated waiting time.

[0008] The fitting room management method described herein acquires the type of product a customer tries on, predicts the customer's fitting room usage time based on the type of product, estimates the waiting time until another customer can use the fitting room based on the predicted usage time, and outputs the estimated waiting time.

[0009] The program relating to this disclosure causes a computer to perform the following processes: acquire the type of product a customer tries on; predict the customer's fitting room usage time based on the type of product; estimate the waiting time until another customer can use the fitting room based on the predicted usage time; and output the estimated waiting time. The program may be stored on a computer-readable non-temporary recording medium. [Effects of the Invention]

[0010] This disclosure will enable a more accurate understanding of waiting times in fitting rooms. [Brief explanation of the drawing]

[0011] [Figure 1] This block diagram shows an example configuration of a fitting room management system according to the first embodiment. [Figure 2] This flowchart shows an example of the operation of the fitting room management system according to the first embodiment. [Figure 3] This block diagram shows an example configuration of a fitting room management system according to the third embodiment. [Figure 4] This diagram shows an example of a screen displayed on a store terminal. [Figure 5] This diagram shows an example of a screen displayed on a store terminal. [Figure 6]This figure shows an example of a screen displayed on a customer's mobile device. [Figure 7] This is a block diagram showing an example of a computer hardware configuration. [Modes for carrying out the invention]

[0012] [First Embodiment] The fitting room management system 100 according to the first embodiment predicts the time a customer will spend in a fitting room based on the type of items they try on, and estimates the waiting time for the fitting room based on the predicted time. The estimated waiting time is output to, for example, a store employee or the customer. Therefore, the fitting room management system 100 makes it possible for store employees and customers to understand the usage status of the fitting rooms.

[0013] Figure 1 is a block diagram showing an example configuration of the fitting room management system 100 according to the first embodiment. The fitting room management system 100 according to the first embodiment includes an acquisition unit 101, a prediction unit 102, an estimation unit 103, and an output unit 104.

[0014] The acquisition unit 101 acquires the type of product the customer is trying on. The product type is, for example, a general category used when classifying clothing. Specifically, the product type includes suits, jackets, shirts, pants, skirts, etc. The categories are not particularly limited. The level of classification is determined as appropriate.

[0015] The acquisition unit 101 may acquire the type of a product based on a product identifier that identifies the product. The product identifier is, for example, encoded as a barcode and printed on a tag attached to the product. Also, the product identifier may be stored in an RF (Radio Frequency) tag attached to the product. For reading these product identifiers, a store terminal (not shown) and a reader connected to the store terminal may be used. For example, the product identifier read by the reader through the operation of a store clerk is transmitted from the store terminal to the acquisition unit 101. The acquisition unit 101 refers to a database that stores the product identifier and the type of the product in association with each other, and acquires the type of the product corresponding to the received product identifier.

[0016] The acquisition unit 101 may acquire the type of the product by any other arbitrary method. For example, the acquisition unit 101 may acquire the type of the product based on the result of image recognition of an image of the product being tried on. The acquisition unit 101 may acquire the type of the product based on the result of image recognition. Alternatively, the acquisition unit 101 may identify a product identifier based on the result of image recognition, and identify the type of the product based on the identified product identifier.

[0017] When a customer tries on a plurality of products at a time, the acquisition unit 101, for example, acquires the type of each of the plurality of products for each customer. When a plurality of customers are waiting for the fitting room to be available, the acquisition unit 101 may acquire the type of the product that each of the plurality of waiting customers will try on. Alternatively, the acquisition unit 101 may acquire the type of the product that the customer who can first use the fitting room among the plurality of customers waiting in order will try on.

[0018] In the first embodiment, when the acquisition unit 101 acquires the type of the product that a customer tries on, a reservation for the customer to use the fitting room is accepted. Also, in the first embodiment, when the acquisition unit 101 acquires the type of the product that a customer tries on, the acquisition unit 101 may manage the order in which the customer uses the fitting room.

[0019] The prediction unit 102 predicts the usage time of the fitting room for a customer based on the type of product. The usage time of the fitting room is, for example, the time required from when the customer enters the fitting room until they leave. The prediction unit 102 predicts the usage time of the fitting room based on, for example, the time required for fitting, which is determined in advance for each type of product. For example, it may be determined as appropriate that it takes 3 minutes to try on one skirt. The time required for fitting may be determined according to the average time required for putting on and taking off corresponding to the type of product. In addition to the type of product, the prediction unit 102 may further use various other information related to fitting to predict the usage time of the fitting room.

[0020] In the first embodiment, for a customer for whom the type of product to be tried on has been acquired, the prediction unit 102 predicts the usage time of the fitting room for each customer. For a plurality of customers waiting for the fitting room to become available, when the type of product has been acquired, the prediction unit 102 may predict the usage time of each of the plurality of customers.

[0021] The estimation unit 103 estimates the waiting time for the fitting room based on the usage time predicted for each customer. The waiting time for the fitting room is, for example, the waiting time of another customer until the fitting room becomes available when the fitting room is being used by a customer.

[0022] Another customer for whom the estimation unit 103 targets the estimation of the waiting time is each of the plurality of customers waiting in line, the customer who is waiting in line first, or the customer who will wait in line at the end of the line. That is, when the usage time is predicted for each of the plurality of customers, the estimation unit 103 may estimate the waiting time of each customer waiting in line or the waiting time of the last customer based on the predicted usage time of each customer. In addition, the estimation unit 103 may estimate the waiting time of the customer who is waiting in line first based on the predicted usage time of the customer who is using the fitting room.

[0023] As an example, consider a case where the acquisition unit 101 acquires the type of product by reading the product identifier of the product each customer is trying on. Here, the acquisition unit 101 manages fitting room reservations in the order of each customer whose product identifier has been read. The estimation unit 103 may estimate the waiting time for a particular customer as the time elapsed from the time the type of product a customer is trying on is acquired until the total predicted usage time for other customers who will use the fitting room before that customer has elapsed.

[0024] As another example, consider a case where the type of product is obtained by reading the product identifier just before the customer enters the fitting room. The estimation unit 103 may estimate the waiting time for the first customer as the time from when the acquisition unit 101 obtains the type of product the customer is trying on until the usage time predicted by the prediction unit 102 has elapsed.

[0025] If a store has multiple fitting rooms, the estimation unit 103 may estimate the waiting time taking into account the number of fitting rooms. The estimation unit 103 may also estimate the waiting time for each fitting room.

[0026] The output unit 104 outputs the waiting time estimated by the estimation unit 103. The output unit 104 may also display the waiting time by outputting it to a display device (not shown), for example. The display device displays information to the store staff or customers. The display device may be the aforementioned store terminal operated by the store staff.

[0027] Waiting time may be expressed by the time another customer becomes available to use the fitting room. Alternatively, waiting time may be expressed by the remaining time until the fitting room becomes available. Furthermore, waiting time may be expressed by the estimated usage time for each customer.

[0028] The output unit 104 may output other information in addition to the waiting time for the fitting room. For example, the output unit 104 may output the type of product acquired by the acquisition unit 101 and the number of customers waiting to be displayed on the display device.

[0029] Figure 2 is a flowchart showing an example of the operation of the fitting room management system 100 according to the first embodiment. The fitting room management system 100 may, for example, start the operation shown in Figure 2 in response to receiving a product identifier from a reader.

[0030] The acquisition unit 101 acquires the type of product the customer is trying on (step S1). The acquisition unit 101 transmits the acquired product type to the prediction unit 102.

[0031] The prediction unit 102 predicts the customer's fitting room usage time based on the type of product received (step S2). The prediction unit 102 transmits the predicted fitting room usage time to the estimation unit 103.

[0032] The estimation unit 103 estimates the waiting time for the fitting room based on the predicted usage time (step S3). Here, if the fitting room is being used by a customer whose usage time is predicted, the estimation unit 103 estimates the waiting time for another customer until the fitting room becomes available to that customer. The estimation unit 103 transmits the estimated waiting time to the output unit 104.

[0033] The output unit 104 outputs the estimated waiting time (step S4). With this, the fitting room management system 100 completes the operation shown in Figure 2.

[0034] According to the first embodiment, the acquisition unit 101 acquires the type of product the customer tries on, and the prediction unit 102 predicts the customer's fitting room usage time based on the product type. Then, the estimation unit 103 estimates the waiting time for the fitting room based on the predicted usage time, and the output unit 104 outputs the estimated waiting time. Therefore, it becomes possible to grasp the waiting time for the fitting room more accurately.

[0035] Since the types of items that customers try on differ from person to person, it is expected that the time required for trying on clothes will also differ from person to person. According to the first embodiment, the prediction unit 102 predicts the time a customer will spend in the fitting room based on the type of item that the customer intends to try on. Therefore, the fitting room management system 100 is able to predict the time spent in the fitting room more accurately.

[0036] [Second Embodiment] The fitting room management system 100 according to the second embodiment predicts the usage time of the fitting room for each customer based on the customer's attributes. The configuration of the second embodiment is the same as that of the first embodiment. Therefore, a description of the similar configuration will be omitted.

[0037] The acquisition unit 101 acquires customer attributes in addition to the type of product. Customer attributes include, for example, the customer's gender, age, type of clothing, and past fitting history. The type of clothing is the type of clothing the customer is wearing. Similar to the type of product acquired by the acquisition unit 101, the type of clothing may be classified according to the categories used when classifying clothing. It is assumed that the time required for trying on clothes will differ depending on the type of clothing the customer is wearing. Past fitting history shows the products the customer has tried on in the past and the time spent in the fitting room when trying on those products. It is assumed that the predicted fitting room usage time will be similar to that of past usage times.

[0038] The acquisition unit 101 may acquire customer attributes based on images of the customer captured by the camera. For example, the acquisition unit 101 may acquire the customer's gender, age, and type of clothing recognized using existing image recognition technology. The acquisition unit 101 may also acquire the past try-on history of customers identified by biometric authentication such as facial recognition.

[0039] The acquisition unit 101 acquires this information so that it is possible to associate the type of product the customer is trying on with the customer's attributes. For example, the acquisition unit 101 may associate the type of product with the customer's attributes using a customer identifier.

[0040] The location of the camera used to photograph customers is not particularly limited. The camera may be connected to a store terminal that transmits product identifiers. In this case, the customer's image may be captured when the product identifier is read. The camera may also be installed at the entrance to a fitting room, etc.

[0041] The acquisition unit 101 may acquire customer attributes from a mobile terminal (not shown). The mobile terminal is a device such as a smartphone carried by the customer. Alternatively, the acquisition unit 101 may acquire a customer identifier from the mobile terminal and acquire the customer's past try-on history stored in association with the acquired customer identifier.

[0042] The prediction unit 102 predicts the fitting room usage time based on the type of product and, further, on the customer's attributes. The prediction unit 102 predicts the fitting room usage time based on the customer's gender, age, and the time required to try on clothes, which is predetermined for each type of clothing.

[0043] The estimation unit 103 estimates the waiting time for the fitting room based on the predicted usage time, similar to the first embodiment. The output unit 104 then outputs the estimated waiting time.

[0044] According to the second embodiment, the prediction unit 102 predicts the time a customer will spend in the fitting room based on the customer's attributes. It is assumed that the time required to try on clothes will vary depending on the customer's attributes. For example, it is assumed that the time required to try on clothes will vary depending on the type of clothing the customer is wearing. Therefore, the fitting room management system 100 according to the second embodiment can predict the time spent in the fitting room more accurately.

[0045] In one modified example, the prediction of usage time based on the type of product may be replaced with a prediction of usage time based on customer attributes. That is, the acquisition unit 101 may acquire both the type of product and the customer attributes, or it may acquire either one of them. Similarly, the prediction unit 102 may predict usage time based on both the type of product and the customer attributes, or it may predict usage time based on either one of them.

[0046] [Third Embodiment] The fitting room management system 100 according to the third embodiment estimates the waiting time for a fitting room based on the number of customers who have made reservations and the results of detecting entry into a fitting room. Figure 3 is a block diagram showing an example configuration of the fitting room management system 100 according to the third embodiment. Regarding the configuration of the third embodiment, the same configuration as that of the first embodiment will not be described. In addition to the configuration of the fitting room management system 100 according to the first embodiment, the fitting room management system 100 according to the third embodiment includes a reception unit 105 and a detection unit 106.

[0047] The reception unit 105 accepts fitting room reservations. A reservation is a request from a customer to the store to manage the order in which they can use the fitting rooms. The reception unit 105 accepts fitting room reservations, for example, from a store terminal installed in the store. The store terminal may be operated by a store employee or by a customer.

[0048] The reception desk 105 may issue a reception number to identify the received reservation. The reception desk 105 may also manage the order of customers by the reception number.

[0049] The acquisition unit 101 acquires the types of products that customers who have made reservations will try on. The acquisition unit 101 may acquire the types of products to try on for some of the customers whose reservations have been accepted. In other words, the acceptance of reservations and the acquisition of product types may be performed separately. For example, the acquisition unit 101 may acquire the types of products to try on for the customer who is first in line. In this case, the types of products to try on for the other customers do not need to be acquired.

[0050] In the third embodiment, the estimation unit 103 may estimate the waiting time for a fitting room based on the number of people who have made a reservation for a fitting room. For customers who have made a reservation but whose type of product to try on has not been obtained, the prediction unit 102 does not estimate the usage time based on the type of product. Therefore, for customers whose type of product to try on has not been obtained, the estimation unit 103 estimates the waiting time for a fitting room using a predetermined fitting room usage time. For example, the estimation unit 103 may estimate the waiting time for a fitting room by assuming that the usage time for customers whose type of product has not been obtained is uniformly 5 minutes. For customers whose type of product to try on has been obtained, the estimation unit 103 estimates the waiting time for a fitting room using the fitting room usage time predicted by the prediction unit 102.

[0051] The detection unit 106 detects entry into the fitting room. The detection unit 106 may also detect exit from the fitting room. The detection unit 106 detects entry into and exit from the fitting room using existing technology. For example, the detection unit 106 detects entry and exit based on a human presence sensor, a fitting room door opening / closing sensor, or the output of a reader that reads RF tags attached to products.

[0052] The estimation unit 103 may estimate the time from when a customer enters a fitting room until the predicted usage time for that customer has elapsed as the waiting time for the customer at the top of the queue.

[0053] The output unit 104 may output the availability status of the fitting rooms to the display device based on the detection results from the detection unit 106. For example, the output unit 104 may output to the display device whether each fitting room is in use or vacant.

[0054] Figures 4 and 5 show examples of screens output to the display device. The screens shown in Figures 4 and 5 include the availability status of fitting room 1 and fitting room 2. The display device may display the screen shown in Figure 5 if fitting room 2 becomes vacant after a predetermined time has elapsed since the screen shown in Figure 4 was displayed.

[0055] The screens shown in Figures 4 and 5 include information identifying each waiting customer's waiting time and the fitting room they are scheduled to be directed to. Furthermore, these screens include an estimated waiting time for the last customer in line when a new reservation is accepted.

[0056] Furthermore, the screens shown in Figures 4 and 5 include a "New Reservation" button. If the display device is the aforementioned store terminal, the reservation may be transmitted from the store terminal to the reception unit 105 in response to the "New Reservation" button being pressed.

[0057] According to the third embodiment, the reception unit 105 accepts reservations. Therefore, the fitting room management system 100 can manage the number of customers waiting to use a fitting room. Furthermore, according to the third embodiment, the estimation unit 103 estimates the waiting time for a fitting room using the usage time predicted based on the number of people who have made reservations for the fitting room, in addition to the usage time predicted based on the type of product. Therefore, even if the type of product to be tried on is not obtained for all customers waiting in line, the fitting room management system 100 can estimate the waiting time for a fitting room.

[0058] The reception unit 105 and the detection unit 106 may be provided as needed. In other words, the fitting room management system 100 according to the third embodiment may have a configuration that includes at least one of the reception unit 105 or the detection unit 106 in addition to the configuration of the fitting room management system 100 according to the first embodiment.

[0059] [Differentiation] Each of the above embodiments can be modified in various ways. Hereinafter, we will describe some modifications.

[0060] The product type may be more specific than the product category. For example, the product type may be classified by product identifier. In this case, the time required for trying on the product may be predetermined for each product identifier. That is, the prediction unit 102 predicts the time spent using the fitting room based on the product type classified by product identifier.

[0061] Furthermore, the types of items being tried on and the types of clothing worn by the customer may be classified by the number of buttons on the clothing. The prediction unit 102 may predict that the more buttons there are, the longer the time required for trying on the clothes.

[0062] The reception desk 105 may accept reservations for the use of fitting rooms from customers' mobile devices.

[0063] In the first embodiment, a case was described in which the product identifier is read by an employee and transmitted from the store terminal to the acquisition unit 101. Here, the product identifier may also be transmitted from the store terminal by a customer. Alternatively, the product identifier may be read using the customer's mobile device. For example, the acquisition unit 101 acquires the product identifier read using the camera on the mobile device.

[0064] Product identifiers may be obtained without the involvement of store staff or customers. For example, if product identifiers are stored in an RF tag attached to a product, the product identifiers may be read by an RF reader installed at a gate. In this case, product identifiers read when a customer passes through the gate on their way to a fitting room can be obtained. Alternatively, if an RF reader is installed in the fitting room, the acquisition unit 101 may acquire product identifiers read for products inside the fitting room.

[0065] The prediction unit 102 may predict fitting room usage time according to the season. For example, the prediction unit 102 may predict fitting room usage time such that the length of time spent in the fitting room changes depending on the type of product and the type of clothing worn by the customer, according to the season. Winter clothing is expected to take more time to put on and take off than summer clothing. Therefore, the prediction unit 102 may predict that the average fitting room usage time per customer will be longer in winter than in summer.

[0066] The output unit 104 may output the waiting time to the customer's mobile terminal. Figure 6 shows an example of a screen displayed on the mobile terminal in response to the output from the output unit 104.

[0067] The screen in Figure 6 includes the customer's waiting time, the number of other customers whose turn was taken before the customer, and the types and number of items to be tried on. The screen displayed on the mobile device may also include buttons for "move forward in line," "cancel try-on," and "add try-on items."

[0068] When the "Defer queue" button is pressed, the mobile terminal sends a queue deferral request to the reception unit 105. The reception unit 105 defers the customer's queue based on the request. The estimation unit 103 estimates the waiting time based on the deferred queue, and the output unit 104 outputs the updated waiting time to a display device such as a mobile terminal. By deferring the queue, the customer can, for example, consider purchasing or trying on other items in the store before entering the fitting room.

[0069] If the "Cancel Fitting" button is pressed, the mobile terminal sends a reservation cancellation request to the reception unit 105. The estimation unit 103 updates the waiting time based on the received reservation cancellation request.

[0070] When the "Add Try-On Item" button is pressed, for example, the mobile terminal displays a screen to read a new item identifier. The mobile terminal transmits the read item identifier to the acquisition unit 101. The acquisition unit 101 obtains the type of the added item, and the prediction unit 102 predicts the customer's fitting room usage time based on the type of the added item. The mobile terminal may also send a cancellation request for each item to the acquisition unit 101. The prediction unit 102 predicts the customer's fitting room usage time, taking into account the time required to try on the items for which a cancellation request has been obtained.

[0071] [Hardware configuration] In each of the embodiments described above, each component of the fitting room management system 100 represents a functional unit block. Some or all of the components of the fitting room management system 100 may be implemented by any combination of a computer 500 and a program.

[0072] Figure 7 is a block diagram showing an example of the hardware configuration of computer 500. Referring to Figure 7, computer 500 includes, for example, a processor 501, ROM (Read Only Memory) 502, RAM (Random Access Memory) 503, a program 504, a storage device 505, a drive device 507, a communication interface 508, an input device 509, an input / output interface 511, and a bus 512.

[0073] The processor 501 controls the entire computer 500. An example of a processor 501 is a CPU (Central Processing Unit). The number of processors 501 is not particularly limited; there may be one or more processors 501.

[0074] Program 504 includes instructions for implementing each function of the fitting room management system 100. Program 504 is pre-stored in ROM 502, RAM 503, and storage device 505. The processor 501 implements each function of the fitting room management system 100 by executing the instructions contained in program 504. RAM 503 may also store data processed in each function of the fitting room management system 100.

[0075] The drive device 507 reads and writes to the recording medium 506. The communication interface 508 provides an interface with the communication network. The input device 509 is, for example, a mouse or keyboard, and receives information input from the administrator. The output device 510 is, for example, a display, and outputs (displays) information to the administrator, store clerk, or customer. The input / output interface 511 provides an interface with peripheral devices. The bus 512 connects each of these hardware components. The program 504 may be supplied to the processor 501 via the communication network, or it may be stored in the recording medium 506 beforehand, read by the drive device 507, and supplied to the processor 501.

[0076] Note that the hardware configuration shown in Figure 7 is an example, and other components may be added, or some components may be omitted.

[0077] There are various ways to implement the fitting room management system 100. For example, the fitting room management system 100 may be implemented by any combination of different computers and programs for each component. Alternatively, the multiple components of the fitting room management system 100 may be implemented by any combination of a single computer and program.

[0078] Furthermore, at least a portion of the fitting room management system 100 may be provided in SaaS (Software as a Service) format. That is, at least a portion of the functions necessary to implement the fitting room management system 100 may be executed by software that runs over a network.

[0079] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the configuration and details of the present disclosure are possible, as can be understood by those skilled in the art within the scope of the present disclosure. Furthermore, the configurations in each embodiment can be combined with one another, as long as they do not depart from the scope of the present disclosure. [Explanation of Symbols]

[0080] 100 Fitting Room Management System 101 Acquisition Department 102 Prediction Section 103 Estimation part 104 Output section 105 Reception Department 106 Detection unit

Claims

1. An acquisition means for acquiring the type of product a customer tries on and the customer's attributes, including the type of clothing the customer is wearing. A prediction means for predicting the time a customer will spend in a fitting room, based on the type of product and the estimated time required to put on and take off each type of clothing using the customer's attributes, Estimation means for estimating the waiting time until another customer can use the fitting room, based on the predicted usage time, Output means for outputting the estimated waiting time and A fitting room management system equipped with the following features.

2. The prediction means predicts the usage time based on the time required for trying on the product, which is predetermined for each type of product. The fitting room management system according to claim 1.

3. The prediction means predicts the usage time of multiple customers waiting for a fitting room to become available. The estimation means estimates the waiting time based on the predicted usage time for each of the plurality of customers. The fitting room management system according to claim 1 or 2.

4. We will further implement a system for accepting reservations for fitting rooms. The estimation means further estimates the waiting time for customers who have made a reservation but whose type of product to try on has not been obtained, using a predetermined fitting room usage time. A fitting room management system according to any one of claims 1 to 3.

5. The system further includes a detection means for detecting when the customer enters the fitting room. The estimated waiting time is the time from when entry into the room is detected until the usage time predicted by the prediction means ends. A fitting room management system according to any one of claims 1 to 4.

6. The customer's attributes, including the type of product the customer is trying on and the type of clothing the customer is wearing, are obtained. Based on the type of product and the estimated time required to put on and take off each type of clothing using the customer's attributes, the customer's time spent in the fitting room is predicted. The waiting time until another customer can use the fitting room is estimated based on the predicted usage time. Output the estimated waiting time. Fitting room management methods.

7. The customer's attributes, including the type of product the customer is trying on and the type of clothing the customer is wearing, are obtained. Based on the type of product and the estimated time required to put on and take off each type of clothing using the customer's attributes, the customer's time spent in the fitting room is predicted. The waiting time until another customer can use the fitting room is estimated based on the predicted usage time. Output the estimated waiting time. A program that instructs a computer to perform a process.

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