System

Abstract

To provide a system for promoting management and efficient use of articles.SOLUTION: A means for taking a picture of an article and inputting basic information, a means for transmitting information of the article to a server, a means for analyzing the article information, generating a unique ID, and assigning a digital tag, a means for storing the article information in a database, a means for periodically updating the article database and maintaining information consistency, a means for searching for a specific article and displaying a search result, and a means for generating a clothing suggestion based on past use data and preferences of a user; A system, comprising: means for notifying; means for analyzing frequency of use data of an item to identify an item that is not in use; means for managing a rental or sale request; means for coordinating with a logistics service to arrange delivery of the item; and means for tracking and notifying delivery status.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] There is a problem with cluttered and inefficiently managed items in the home. This problem results in wasted time and effort for people who lead busy lives. Furthermore, with limited closet and storage space, many items go unused, resulting in wasted space. Furthermore, it is difficult to know where each item is, and searching for a specific item can be stressful. This situation is not suited to modern lifestyles that demand time management and space efficiency. [Means for solving the problem]

[0005] The present invention provides the following means to promote the management and efficient use of goods:

[0006] 1. A way to take a photo of an item and enter basic information.

[0007] 2. A means for transmitting information about the item to the server.

[0008] 3. A means of analyzing item information, generating a unique ID, and assigning a digital tag.

[0009] 4. A means of storing item information in a database.

[0010] 5. A means of regularly updating the goods database and maintaining the integrity of the information.

[0011] 6. A means of searching for specific items and displaying search results.

[0012] 7. A means of generating and communicating outfit suggestions based on the user's past usage data and preferences.

[0013] 8. A means of analyzing data on the frequency of use of items and identifying unused items.

[0014] 9. A means of managing rental and sales requests.

[0015] 10. A means of coordinating with logistics services to arrange delivery of goods.

[0016] 11. Means of tracking and notification of delivery status.

[0017] This allows users to easily check the location of items digitally, enabling efficient management. It also helps save time by suggesting outfits based on the user's preferences. Furthermore, by sharing or buying and selling unused items, it is possible to make effective use of space and reduce the burden on the environment.

[0018] "Goods" are physical items owned and used by an individual or household.

[0019] "Photography" is the act of using a camera to capture an image to visually record the appearance of an item.

[0020] "Basic information" refers to the minimum necessary information about an item, including the brand name, color, size, etc.

[0021] A "server" is a central system that stores data and provides processing and access to the data to client devices.

[0022] A "unique ID" is an identifier assigned to each item to uniquely identify it.

[0023] A "digital tag" is electronic identification information attached to an item, and is used to manage information about the item in conjunction with a database.

[0024] A "database" is a system for systematically storing information on a large number of items and for efficiently searching and updating information as needed.

[0025] "Integrity" refers to the state in which data is consistent and accurate, meaning that information does not contradict each other.

[0026] "Searching" is the act of locating information in a database based on specific criteria.

[0027] "Generative AI" is a type of artificial intelligence that generates predictions and suggestions based on a user's past data and preferences.

[0028] "Usage data" is information about how and how often an item is used.

[0029] "Suggestion" is the act of presenting options that meet the user's needs and preferences.

[0030] "Notification" is the act of sending a message to inform users of important information or updates.

[0031] "Frequency of use data" is information that indicates the number of times an item is used and the pattern of use during a specific period of time.

[0032] "Renting" is the act of letting someone else use an item you own for a certain period of time.

[0033] A "sales request" is the act of receiving an order or request from a person wishing to purchase an item.

[0034] "Logistics services" are specialized support systems for the delivery and storage of goods.

[0035] "Delivery" is the act of moving an item from one point to another.

[0036] "Status" is information that indicates the current state and progress.

[0037] "Tracking" is the act of continuously monitoring and recording the movement of goods. [Brief explanation of the drawings]

[0038] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0039] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0040] First, the terms used in the following description will be explained.

[0041] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0042] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0043] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0044] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0045] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0046] [First embodiment]

[0047] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0048] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0049] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0050] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0051] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0052] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0053] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0054] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0055] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0056] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0057] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0058] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0059] This invention relates to a 4D closet system that utilizes digital tags and generative AI. This system supports the management and efficient use of items and provides the following key functions to improve users' lives:

[0060] Product registration

[0061] First, we will explain the procedure for a user to register a newly purchased item in the system. The user takes a photo of the item using a smartphone or other device and enters the item information through the application. Specific items include the brand name, color, and size.

[0062] The device then sends the captured photo and the entered information to a server, which analyzes the information and generates a unique ID for the item, assigns a digital tag to the item, and stores the item information in a database.

[0063] Management of goods

[0064] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency of the information. When a user searches for a specific item, the server retrieves the corresponding item information from the database via the terminal and displays it to the user.

[0065] For example, when a user searches for "red shirt," the server extracts information about the corresponding shirt based on the keyword and sends the results to the user's terminal.

[0066] Product suggestions

[0067] Based on the user's preferences and past usage data, the AI ​​generator will suggest the outfit they would like to wear the next day. The server will use the AI ​​generator to analyze the user's past data and generate outfit combinations. This suggestion will be sent to the user's device, and the user can review the suggested outfit and accept or change it.

[0068] For example, if there is a special event the next day, the generative AI will suggest a set of shirt, pants, and shoes, and the user can review the suggestions and make any necessary changes in the application.

[0069] Distribution and sharing of goods

[0070] The server analyzes the frequency of use of items and allows users to lend or sell unused items to friends and family. The server analyzes the data on the frequency of use of items and provides users with a list of unused items. Users can submit requests for lending or selling items through the application.

[0071] For example, if a user has a shirt they haven't worn in a few months, they can send a request in the app to lend it to a friend. The server manages the request and notifies the user when the loan is complete.

[0072] Goods delivery management

[0073] Once the user has decided on the outfit they want to wear the next day, the server arranges for the items to be delivered. The user submits a delivery request through the app, and the server works with the logistics service to arrange for the items to be shipped from the warehouse.

[0074] In addition, the server tracks the delivery status in real time and notifies the user when the item arrives at the parcel locker, where the user can check the status and collect the item through the app.

[0075] For example, the shirt and pants that the user has selected for the next day's outfit will be delivered to the delivery locker the next morning, and the user can receive and wear them as is.

[0076] As described above, the system of the present invention supports the management and efficient use of items, and provides functions for making the most of a user's time and space.

[0077] The processing flow will be explained below.

[0078] Product registration

[0079] Step 1:

[0080] User: Activates the smartphone camera and takes a photo of the new item.

[0081] Step 2:

[0082] User: Opens the smartphone app and enters basic information such as "brand name," "color," and "size" along with a photo.

[0083] Step 3:

[0084] Terminal: Sends the entered information and photos to the server.

[0085] Step 4:

[0086] Server: Analyzes the received product information and generates a unique ID.

[0087] Step 5:

[0088] Server: Attaches digital tags to items and stores that information in a database.

[0089] Management of goods

[0090] Step 1:

[0091] Server: Regularly updates the product database to maintain consistency of information.

[0092] Step 2:

[0093] User: Uses the app to search for a specific item, for example, by entering the keyword "red shirt."

[0094] Step 3:

[0095] Server: Searches the database for relevant product information and sends the results to the terminal.

[0096] Step 4:

[0097] Terminal: Displays search results to the user.

[0098] Product suggestions

[0099] Step 1:

[0100] Server: Uses generative AI to analyze users' past usage data and preferences.

[0101] Step 2:

[0102] Server: Generates suggestions for the next day's outfit, taking into account the combination of items.

[0103] Step 3:

[0104] Server: Notifies the user's terminal of the generated proposal.

[0105] Step 4:

[0106] Device: The user reviews the suggestions and makes changes to the outfit if necessary.

[0107] Distribution and sharing of goods

[0108] Step 1:

[0109] Server: Analyzes the item usage frequency data and generates a list of unused items.

[0110] Step 2:

[0111] Users: Use the application to request loans or sales of unused items to friends and family.

[0112] Step 3:

[0113] Server: Manages rental and sales requests and tracks the necessary transactions.

[0114] Step 4:

[0115] Server: Sends notification to the user when the transaction is complete.

[0116] Goods delivery management

[0117] Step 1:

[0118] User: Uses the app to request delivery of the outfit they want to wear the next day.

[0119] Step 2:

[0120] Server: Works with logistics services to arrange delivery and ship items from the warehouse.

[0121] Step 3:

[0122] Server: Tracks the delivery status of goods and updates the information in real time.

[0123] Step 4:

[0124] Server: When the item arrives at the delivery locker, it sends a notification to the user.

[0125] Step 5:

[0126] User: Check delivery status and receive items in the app.

[0127] Through these steps, the system efficiently executes a series of processes from product registration to management, proposal, distribution, and delivery management, thereby significantly improving users' lives.

[0128] Example 1

[0129] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0130] Conventional item management systems make it difficult for users to efficiently register, manage, and use the items they purchase. They also lack advanced support, such as managing the circulation and lending of unused items, or suggesting outfits based on the user's preferences and past usage history. Furthermore, arranging delivery of items and tracking their status places a heavy burden on the user. The present invention aims to solve these problems and improve the quality of life for users.

[0131] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0132] In this invention, the server includes means for acquiring images of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique identifiers and assigning digital tags, means for saving the item information in data storage, means for periodically updating the item database and maintaining information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on the user's past usage data and personal preferences, means for analyzing item usage frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, and means for tracking and notifying delivery status. This allows users to centrally register, manage, use, distribute, and deliver items.

[0133] "Goods" are any tangible goods or items that are the subject of management and that a User possesses, uses, or distributes.

[0134] "Image capture" is the process of taking a photograph or video of an item using an electronic device.

[0135] "Basic information" refers to data necessary to identify and specify an item, and includes attributes such as brand name, color, and size.

[0136] A "server" is a remote computer system that processes information and stores data.

[0137] "Transmission" is the act of transferring data or information from one place to another.

[0138] "Analysis" is the process of analyzing received data to extract useful information.

[0139] A "unique identifier" is a specific number or code assigned to each item to uniquely identify it.

[0140] A "digital tag" is an electronic tag or label associated with an item that contains information in digital form.

[0141] "Data storage" is a physical or virtual location or device for storing information.

[0142] A "database" is an information system that systematically organizes a large amount of data and allows efficient access using queries.

[0143] "Integrity" refers to data that is accurate, consistent, and not altered or corrupted.

[0144] "Searching" is the act of searching a database or information system to find specific data.

[0145] A "suggestion" is a recommendation or recommendation made based on the results of the analysis.

[0146] "Notifications" are messages or alerts that inform users of important information.

[0147] "Frequency of use" is an index that indicates how often an item is used.

[0148] A "request" is a request or application to ask for something.

[0149] "Logistics services" are businesses or companies that manage and execute the transportation and delivery of goods.

[0150] "Tracking" is the process of monitoring and recording the location and condition of an item in real time.

[0151] This invention is a system for supporting the management and efficient use of goods, with the aim of improving the quality of life of users. This system can perform everything from product registration to management, distribution, and delivery in an integrated manner.

[0152] 1. Registration of goods

[0153] Users take a photo of a newly purchased item using a smartphone or other device. Next, they enter basic information about the item, such as its brand name, color, and size, through an application. The device then sends this information to a server. The server analyzes the received information, generates a unique identifier for the item, and assigns a digital tag to it. The item information is then stored in data storage.

[0154] 2. Management of items

[0155] After the product information is registered, the server periodically updates the product database to maintain the integrity of the information. When a user searches for a specific product using the application, the device sends the search keywords to the server, which then extracts the corresponding product information from the database, returns it to the device, and displays it to the user.

[0156] 3. Product Proposals

[0157] The server uses the generative AI model to analyze the user's past usage data and personal preferences. Based on this, the server generates outfit suggestions for the next day and notifies the user's device. For example, if there is a special event the next day, the generative AI will suggest a set of shirt, pants, and shoes. The user can review the suggestions in the app and make changes as needed.

[0158] 4. Distribution and sharing of goods

[0159] The server analyzes the usage frequency data of the items and identifies unused items. Users can then send requests to lend or sell items to relatives or acquaintances through the application. The server manages the requests and notifies the user when the lending or sale is completed.

[0160] 5. Goods delivery management

[0161] Users use the app to request delivery of the clothes they will wear the next day. The server works with the logistics service to arrange for the items to be shipped from the warehouse and tracks the delivery status in real time. Once the items arrive at the delivery locker, the server sends a notification to the user, who can then check the status on the app and collect the items.

[0162] This system is realized using various hardware and software. Specifically, devices such as smartphones and tablets are used, and an application acts as the interface between the user and the system. The server is equipped with software with advanced data analysis capabilities and a generative AI model.

[0163] Examples of concrete examples and prompts

[0164] 1. If a user buys a new red shirt, they take a photo with their smartphone and enter "Brand: ABC," "Color: Red," and "Size: M" into the app and submit it. The server analyzes the information, generates a unique identifier and digital tag, and stores them in a database.

[0165] Example prompt: "Please register for a new red ABC brand medium shirt."

[0166] 2. When a user searches for "red shirt," the server retrieves the relevant information from the database and sends it to the terminal, where the user can view the results.

[0167] Example prompt: "Search the database for red shirts and display a list."

[0168] 3. The day before a special event, the generative AI will suggest a set of shirts, pants, and shoes, and the user can review the suggestions in the app and make changes as needed.

[0169] Example prompt: "Please give me some outfit suggestions for tomorrow's special event."

[0170] Thus, the present invention is a multifunctional system that makes users' item management more efficient and improves their quality of life.

[0171] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0172] Product registration

[0173] Step 1:

[0174] The user takes a photo of the newly purchased item with their smartphone or device. The input is the image of the item, and the output is the captured image file.

[0175] Specific behavior: The user activates the smartphone camera and takes a photo of the red shirt. The image file is saved to the device.

[0176] Step 2:

[0177] The user launches the application and inputs a photograph of the item along with basic information such as the brand name, color, size, etc. The input is the item image and text data of the basic information, and the output is a transmission package containing this data.

[0178] Specific behavior: The user enters "Brand name: ABC", "Color: Red", and "Size: M" into the app, selects a photo, and presses the send button.

[0179] Step 3:

[0180] The terminal sends the entered information and photos to the server. The input is the transmission package, and the output is the data that arrives at the server.

[0181] Specific operation: The transmission package created by the terminal is sent to the server via the Internet.

[0182] Step 4:

[0183] The server analyzes the received photos and item information. The input is the received data, and the output is the analysis result data.

[0184] Specific operation: The server analyzes the photo using an image analysis algorithm and extracts information such as "red," "shirt," and "brand: ABC."

[0185] Step 5:

[0186] The server generates a unique identifier for the item based on the analysis results and assigns a digital tag to it. The input is the analysis results, and the output is the unique identifier and item information with the digital tag.

[0187] Specific operation: The server generates a unique ID (e.g., 123456), uses it to create a digital tag, and links it to the item information.

[0188] Step 6:

[0189] The server stores the product information in a data storage. The input is the product information with the digital tag, and the output is the data stored in the data storage.

[0190] Specific operation: The server writes the generated product information to the database.

[0191] Management of goods

[0192] Step 7:

[0193] The server periodically updates the product database to maintain consistency of information. The input is the existing product information, and the output is the updated database information.

[0194] Specific operation: The server runs an automatic script to check for updates to product information and update the database if necessary.

[0195] Step 8:

[0196] A user searches for a specific item within an application. The input is the search keyword, and the output is the search result data.

[0197] Specific behavior: The user types "red shirt" into the app's search box and presses the search button.

[0198] Step 9:

[0199] The terminal sends search keywords to the server. The input is the search keywords, and the output is the data sent to the server.

[0200] Specific operation: The device sends the search keywords to the server via the Internet.

[0201] Step 10:

[0202] The server extracts the relevant product information from the database and sends it to the terminal. The input is the search keyword, and the output is the search result data.

[0203] Specific operation: The server extracts data corresponding to "red shirt" from the database and sends it to the terminal.

[0204] Step 11:

[0205] The terminal displays the search results to the user. The input is the search result data, and the output is the information displayed to the user.

[0206] Specific operation: The device displays the search results on the app's display screen, and the user confirms them.

[0207] Product suggestions

[0208] Step 12:

[0209] The server uses the generated AI model to analyze the user's past usage data and personal preferences. The input is the past usage data, and the output is the analysis results.

[0210] Specific operation: The server launches the generative AI, inputs the user's past data (e.g., frequently worn colors and styles), and performs analysis.

[0211] Step 13:

[0212] The server generates the next day's outfit combination based on the analysis results. The input is the analysis results, and the output is the suggested outfit data.

[0213] Specific operation: The generative AI model proposes a set of "shirt, pants, shoes" and saves it as data.

[0214] Step 14:

[0215] The server notifies the user's terminal of the generated proposal. The input is the proposal data, and the output is the notification sent to the user's terminal.

[0216] Specific operation: The server sends the proposal to the device, and the device notifies the user, "This set is recommended for tomorrow's event."

[0217] Distribution and sharing of goods

[0218] Step 15:

[0219] The server analyzes the usage frequency data of the items and identifies unused items. The input is the usage frequency data, and the output is a list of unused items.

[0220] Specific operation: The server lists items that have not been used for a certain period of time and saves them as suggestions.

[0221] Step 16:

[0222] A user submits a rental or sale request through the application. The input is the request data and the output is the request sent to the server.

[0223] What happens: A user sends a request in the app to "lend a shirt to a friend."

[0224] Step 17:

[0225] The server manages the requests and notifies the user when the loan or sale is completed. The input is the request data and the output is the notification sent to the user.

[0226] What happens next: The server processes the request and sends a notification to the user saying, "Your shirt has been checked out."

[0227] Goods delivery management

[0228] Step 18:

[0229] A user uses the application to request delivery of the clothes they will wear the next day. The input is the delivery request data, and the output is the delivery request sent to the server.

[0230] Specific behavior: A user requests delivery of a shirt and pants to wear the next day through the app.

[0231] Step 19:

[0232] The server works with the logistics service to process the shipment of goods from the warehouse. The input is the delivery request data, and the output is the shipping instruction sent to the logistics service.

[0233] Specific operation: The server communicates with the logistics service and starts the shipping procedure for the item.

[0234] Step 20:

[0235] The server tracks the delivery status in real time and sends a notification to the user once the item arrives at the parcel locker. The input is the real-time delivery status data and the output is the notification sent to the user.

[0236] Specific behavior: The server tracks the delivery status of the items and sends a notification to the user saying, "The shirt and pants have arrived at the delivery locker."

[0237] (Application example 1)

[0238] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0239] Conventional closet management systems have the drawback of being time-consuming and inefficient, as registering and managing items is done manually. Furthermore, outfit suggestions based on user preferences and past usage data are often inappropriate, potentially reducing user satisfaction. Furthermore, managing requests for item rentals and sales is complicated, and delivery status tracking and notifications are not provided in real time, resulting in a lack of an improved user experience.

[0240] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0241] In this invention, the server includes means for taking photos of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique IDs, and assigning digital tags, means for saving the item information in a database, means for periodically updating the item database and maintaining information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on a user's past use data and preferences, means for analyzing item use frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, means for tracking and notifying delivery status, means for automatically registering items purchased by a user in cooperation with an online shopping site, and means for using a generation AI to suggest outfits based on a user's purchase history and preferences. This enables efficient item registration and management, accurate outfit suggestions based on a user's preferences and past data, and seamless management of item rental, sales, and delivery.

[0242] "Means for taking a photo of an item and entering basic information" refers to a device or interface that allows a user to take a picture of an item they own and enter basic information about that item (e.g., brand name, color, size, etc.).

[0243] "Means for transmitting information about an item to a server" refers to the communications infrastructure and protocols for transmitting the photographed image of the item and the input information to a central server.

[0244] "Means for analyzing item information, generating a unique ID, and assigning a digital tag" refers to algorithms or software that analyzes the transmitted item information and generates and assigns a unique identification number (ID) to the item.

[0245] The "means for storing product information in a database" refers to a system or procedure for storing the generated product information and unique ID in a database.

[0246] "Means for regularly updating the product database and maintaining the integrity of the information" means the mechanisms or protocols for periodically checking the information in the database to ensure that it accurately reflects new or changed information.

[0247] "Means for searching for specific items and means for displaying search results" refers to the search function that a user uses to find a specific item and the interface or method for visually displaying the results to the user.

[0248] "Means for generating and notifying clothing suggestions based on the user's past usage data and preferences" refers to a system or algorithm that analyzes the user's past behavioral data and preference trends, suggests clothing suitable for the user, and notifies the user of those suggestions.

[0249] "Means for analyzing item usage frequency data and identifying unused items" refers to technologies and methods for analyzing how frequently items are used and identifying items that have not been used for a long period of time.

[0250] A "means for managing rental and sale requests" is software or a process for accepting, tracking, and managing requests from users to rent or sell items.

[0251] The "means for arranging delivery of goods in cooperation with a logistics service" refers to an interface or system for efficiently arranging delivery of goods in cooperation with an external logistics service provider.

[0252] "Means for tracking and notifying delivery status" refers to technologies and means for monitoring the delivery status of goods in real time and providing that information to users.

[0253] "Means for linking with online shopping sites and automatically registering items purchased by users in the system" refers to a mechanism for integrating with online shopping platforms and automatically adding items purchased by users to the closet system.

[0254] "Means of using generative AI to suggest clothing based on a user's purchasing history and preferences" refers to algorithms and systems that utilize the latest artificial intelligence technology to suggest clothing based on a user's purchasing history and preferences.

[0255] The present invention provides a system for improving the efficiency of item management and user convenience. This system automates a series of processes, such as photographing items, registering information, saving data, proposing items, renting and selling items, and managing delivery. Specific embodiments are described below.

[0256] 1. Registration of goods

[0257] Using a device such as a smartphone, the user takes a photo of the item they have purchased and enters basic information such as brand name, color, and size. This information is sent from the device to a server. The server analyzes the received item information, generates a unique ID, and assigns it to the item. The item information with the digital tag attached is stored in a database. Hardware used includes devices such as smartphones and PCs, and software such as React Native, Node.js, Express, and MongoDB is used to send the item information.

[0258] 2. Management of items

[0259] The server periodically updates the database to maintain consistency of product information. When a user searches for a specific product, they enter a keyword through their device, and the server searches the database for the corresponding product and displays the results to the user. In this process, React Native is used as the search interface, and MongoDB is used for database search processing.

[0260] 3. Suggestion function

[0261] The server uses a generative AI model to suggest the outfit the user would like to wear the next day based on the user's past usage data, purchase history, and preferences. The generated suggestions are sent to the user's device. OpenAI (registered trademark) GPT-4 (registered trademark) is used as the generative AI model. As a specific example, the following prompt sentence is input to the generative AI model:

[0262] Suggest tomorrow's outfit based on the user's purchase history over the past six months, as well as their preferred colors and brands.

[0263] User Information:

[0264] Brand: [Luxury Brand A, Luxury Brand B]

[0265] Favorite colors: [red, blue]

[0266] Past purchase history: [Product ID 123, Product ID 456, Product ID 789]

[0267] Special Events: [None]

[0268] 4. Rental and sales

[0269] The server analyzes item usage frequency data and identifies items that have not been used for a long time. Based on this information, users can request to rent or sell items through the app. The server manages the requests and notifies the user when the request is completed. Node.js and MongoDB are used to manage rentals and sales.

[0270] 5. Delivery management

[0271] Once the user has decided on an outfit, the server connects with a logistics service to arrange delivery of the items. The delivery status is tracked in real time, and the user is notified when the item arrives at the parcel locker. Node.js is used to connect to an external logistics API to arrange delivery and track the status.

[0272] As described above, the system of the present invention seamlessly integrates the registration, management, proposal, rental, sale and delivery of goods, thereby greatly improving user convenience.

[0273] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0274] Step 1:

[0275] The user uses the device to take a photo of the item they purchased and enter basic information such as brand name, color, size, etc. This input information includes image data and text information of the item. This data is temporarily stored on the device.

[0276] Step 2:

[0277] The terminal sends the entered product information and image data to the server. At this time, an HTTP POST request is used to transfer form data including the product image data and metadata to the server. The input is the product information and image data provided by the user, and the output is stored on the server.

[0278] Step 3:

[0279] The server analyzes the received product information and generates a unique ID. This unique ID is used to uniquely identify the product information. In this process, the unique ID is generated using a UUID generation algorithm or similar. The input is the transmitted product information, and the output is the generated unique ID and product information.

[0280] Step 4:

[0281] The server assigns the generated unique ID to the item information and generates a digital tag. The digital tag is an important element for identifying the item and is expressed in the form of an RFID tag, barcode, etc. In this step, the algorithm for generating the digital tag runs. The input is item information with a unique ID, and the output is item information with a digital tag.

[0282] Step 5:

[0283] The server stores the item information with the digital tags in a database. The database used here is a NoSQL database such as MongoDB, and the data is stored in document format. The input is the item information with the digital tags, and the output is the item information stored in the database.

[0284] Step 6:

[0285] The server periodically updates the database to maintain consistency of the information. This process checks for duplicates and inconsistencies in the data, updating or deleting them as necessary. The input is the existing database, and the output is a consistent database.

[0286] Step 7:

[0287] When a user searches for a specific item, they enter keywords into their terminal and send a search request to the server. The server searches the database for the relevant item and returns the results to the terminal. The input is the keyword entered by the user, and the output is a list of search results.

[0288] Step 8:

[0289] The server uses a generative AI model to suggest an outfit for the next day based on the user's past usage data, purchase history, and preferences. This suggestion is sent to the user's device. The generative AI model used is OpenAI GPT-4. An example of a specific prompt is as follows:

[0290] Suggest tomorrow's outfit based on the user's purchase history over the past six months, as well as their preferred colors and brands.

[0291] User Information:

[0292] Brand: [Luxury Brand A, Luxury Brand B]

[0293] Favorite colors: [red, blue]

[0294] Past purchase history: [Product ID 123, Product ID 456, Product ID 789]

[0295] Special Events: [None]

[0296] The input is user data and the output is outfit suggestions.

[0297] Step 9:

[0298] The server analyzes the item usage frequency data and identifies items that have not been used for a long time. Based on this information, users can request to rent or sell items. The server manages the request and notifies the user when processing is complete. The input is the item usage frequency data, and the output is a list of unused items.

[0299] Step 10:

[0300] Once the user has decided on an outfit, the server works with the logistics service to arrange delivery of the items. This is done using a logistics API. The delivery status is tracked in real time, and the user is notified when the item arrives at the delivery locker. The input is the user's delivery request, and the output is a notification of the delivery status.

[0301] Through the above processing steps, the system of the present invention can efficiently register, manage, propose, rent, sell, and deliver products.

[0302] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0303] This invention relates to a 4D closet system that utilizes digital tags, generative AI, and an emotion engine. This system supports the management and efficient use of items, recognizes the user's emotional state, and provides functions to make the user's life more comfortable.

[0304] Product registration

[0305] First, we will explain the procedure for a user to register a newly purchased item in the system. The user takes a photo of the item using a smartphone or other device. Next, they enter information about the item through the application. Specific items include the brand name, color, and size.

[0306] The device sends the entered information and photo to a server, which analyzes the information and generates a unique ID for the item, attaches a digital tag to the item, and stores the information in a database.

[0307] Management of goods

[0308] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency. When a user searches for a specific item, the server retrieves the corresponding item information from the database via the terminal and displays it to the user.

[0309] For example, when a user searches for "black shirts," the server extracts information about the corresponding shirts based on the keywords and sends the results to the user's terminal.

[0310] Utilizing the Emotion Engine

[0311] The emotion engine captures the user's face with a camera and analyzes their emotional state in real time from facial expressions, voice, etc. The emotion data analyzed by the emotion engine is sent to the server. Based on the received emotion data, the server makes product recommendations that are best suited to the user's current situation.

[0312] For example, if a user is feeling stressed, the AI ​​can suggest clothing made of soft materials that will help them relax. The AI ​​takes this emotional data into account and optimizes the suggestions.

[0313] Product suggestions

[0314] Based on the user's preferences, past usage data, and emotional data obtained from the emotion engine, the generative AI suggests outfits for the next day. The server uses the generative AI to analyze the data and generate the optimal outfit combination. This suggestion is sent to the user's device, where the user can review the suggested outfit and accept or change it.

[0315] For example, if you have an important presentation the next day, the generative AI will suggest a formal shirt and slacks set, and you can review the suggestion and change to a more casual outfit if you feel like relaxing.

[0316] Distribution and sharing of goods

[0317] The server analyzes the frequency of use of items and allows users to lend or sell unused items to friends and family. The server analyzes the data on the frequency of use of items and provides users with a list of unused items. Users can submit requests for lending or selling items through the application.

[0318] For example, if a user has an unused shirt and wants to lend it to a friend, the server manages the request and notifies the user when the loan is complete.

[0319] Goods delivery management

[0320] Once the user has decided on the outfit they want to wear the next day, the server arranges for the items to be delivered. The user makes a delivery request through the app, and the server works with the logistics service to arrange for the items to be shipped from the warehouse.

[0321] In addition, the server tracks the delivery status in real time and notifies the user when the item arrives at the parcel locker, where the user can check the status and collect the item through the app.

[0322] For example, the shirt and pants that the user has selected for the next day's outfit will be delivered to the delivery locker the next morning, and the user can receive and wear them as is.

[0323] As described above, the system of the present invention utilizes digital tags, generative AI, and an emotion engine to support the management and efficient use of items, and by making suggestions that are optimal for the user's emotional state, can significantly improve the user's life.

[0324] The processing flow will be explained below.

[0325] Product registration

[0326] Step 1:

[0327] User: Activates the smartphone camera and takes a photo of the new item.

[0328] Step 2:

[0329] User: Opens the smartphone app and enters basic information such as "brand name," "color," and "size" along with a photo.

[0330] Step 3:

[0331] Terminal: Sends the entered information and photos to the server.

[0332] Step 4:

[0333] Server: Analyzes the received product information and generates a unique ID.

[0334] Step 5:

[0335] Server: Attaches digital tags to items and stores that information in a database.

[0336] Management of goods

[0337] Step 1:

[0338] Server: Regularly updates the product database to maintain consistency of information.

[0339] Step 2:

[0340] User: Uses the app to search for a specific item, for example, by entering the keyword "black shirt."

[0341] Step 3:

[0342] Server: Searches the database for relevant product information and sends the results to the terminal.

[0343] Step 4:

[0344] Terminal: Displays search results to the user.

[0345] Utilizing the Emotion Engine

[0346] Step 1:

[0347] User: Uses a smartphone or wearable device to capture facial expressions and voice via a camera and microphone.

[0348] Step 2:

[0349] Device: Captured facial expression and voice data is sent to the emotion engine.

[0350] Step 3:

[0351] Emotion engine: Analyzes the user's emotional state from facial expressions and voice.

[0352] Step 4:

[0353] Terminal: Transmits the analyzed emotion data to the server.

[0354] Step 5:

[0355] Server: Based on the received emotion data, it generates optimal product recommendations for the user.

[0356] Product suggestions

[0357] Step 1:

[0358] Server: Uses generative AI to comprehensively analyze users' past usage data, preferences, and emotional data.

[0359] Step 2:

[0360] Server: Generates suggestions for the next day's outfit, taking into account the combination of items.

[0361] Step 3:

[0362] Server: Notifies the user's terminal of the generated proposal.

[0363] Step 4:

[0364] Device: The user reviews the suggestions and makes changes to the outfit if necessary.

[0365] Distribution and sharing of goods

[0366] Step 1:

[0367] Server: Analyzes the item usage frequency data and generates a list of unused items.

[0368] Step 2:

[0369] Users: Use the application to request loans or sales of unused items to friends and family.

[0370] Step 3:

[0371] Server: Manages rental and sales requests and tracks the necessary transactions.

[0372] Step 4:

[0373] Server: Sends notification to the user when the transaction is complete.

[0374] Goods delivery management

[0375] Step 1:

[0376] User: Uses the app to request delivery of the outfit they want to wear the next day.

[0377] Step 2:

[0378] Server: Works with logistics services to arrange delivery and ship items from the warehouse.

[0379] Step 3:

[0380] Server: Tracks the delivery status of goods and updates the information in real time.

[0381] Step 4:

[0382] Server: When the item arrives at the delivery locker, it sends a notification to the user.

[0383] Step 5:

[0384] User: Check delivery status and receive items in the app.

[0385] Through these steps, the system efficiently executes a series of processes, from product registration and management, to proposals, distribution, and delivery management, thereby significantly improving users' lives. Furthermore, the use of an emotion engine enables optimal proposals based on the user's emotional state, improving user satisfaction.

[0386] Example 2

[0387] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0388] Conventional item management systems require users to spend a lot of time managing item details and are unable to provide suggestions that take into account their emotional state. Furthermore, they lack mechanisms for efficiently managing the frequency of use of items and effectively utilizing unused items. Therefore, there is a need for a system that can efficiently manage items and provide suggestions that are optimal for the user's emotional state.

[0389] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0390] In this invention, the server includes a means for periodically updating the product database and maintaining consistency of information, a means for searching for specific products and displaying search results, and a means for providing an emotion engine for analyzing the user's emotions and making suggestions based on the emotions, thereby enabling the management and effective use of products while making suggestions that take into account the user's emotional state.

[0391] An "item" is an item that is owned and managed by a user.

[0392] "Means for taking photographs" refers to a method of obtaining an image of an item using a device such as a camera or smartphone.

[0393] The "means for inputting basic information" refers to a method by which a user inputs detailed information about an item (such as brand name, color, size, etc.) through an application.

[0394] A "server" is a computer system that exists in the cloud or within a local network and stores, analyzes, and communicates data.

[0395] The "means for analyzing product information" is a method for analyzing product-related data within the server and performing classification and feature extraction.

[0396] The "means for generating a unique ID" is a method for generating a unique identifier for each item, making the item identifiable.

[0397] A "digital tagging means" is a method for electronically tagging information related to an item.

[0398] The "means for storing in the database" refers to a storage device for permanently storing product information and software for managing it.

[0399] "Means for regularly updating the product database" refers to a method for adding or amending new or changed information to the database to keep the information up to date.

[0400] The "means for displaying search results" is a method for displaying on the screen information about items obtained based on the search conditions entered by the user.

[0401] The "emotion engine" is a system that analyzes the user's emotions using input devices such as a camera or microphone, and makes appropriate suggestions based on the results.

[0402] The "means for analyzing usage frequency data" is a method for analyzing the usage history and frequency of an item and promoting effective use of the item.

[0403] A "means for managing rental and sales requests" is a method for accepting and processing requests from users and taking action as necessary.

[0404] "Means for linking with logistics services" refers to methods for communicating with external delivery companies and warehouse management systems to manage logistics processes.

[0405] "Means for tracking delivery status" refers to a method for monitoring the delivery status of an item in real time and notifying the user.

[0406] "Means of notification" refers to a method for sending information from the system to the user and encouraging them to take necessary action.

[0407] This invention relates to a 4D closet system that streamlines item management and makes optimal suggestions based on the user's emotional state. By utilizing digital tags, generative AI, and an emotion engine, this system analyzes item management and usage frequency, providing functions to make the user's life more comfortable.

[0408] Product registration

[0409] Users take a photo of their newly purchased item using a device such as a smartphone or tablet. After taking the photo, they enter information about the item, such as the brand name, color, and size, through an application. The entered information and photo are sent from the device to a server. The server analyzes the received information, generates a unique ID for the item, and assigns a digital tag. This information is then stored in a database.

[0410] Specific example of operation: When a user purchases a blue shirt, enters the information into the app, takes a photo, and sends it, the server assigns a unique ID to the blue shirt and sets a digital tag.

[0411] Management of goods

[0412] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency of the information. When searching for a specific item, the server extracts relevant item information based on the search keywords and sends the results to the user's device for display.

[0413] Specific example of operation: When a user searches for "black shirt" or "blue skirt," the server sends information about the corresponding items to the terminal and displays it.

[0414] Utilizing the Emotion Engine

[0415] The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice, and evaluates their emotional state in real time. The analyzed emotion data is sent to the server via the device. Based on this, the server makes product recommendations that are best suited to the user's current situation.

[0416] Specific example of operation: If the emotion engine analyzes that the user is feeling stressed, the server will suggest clothing made of soft materials that will help them relax.

[0417] Product suggestions

[0418] The server uses AI to analyze the user's preferences, past usage data, and emotional data to generate the optimal outfit combination. This suggestion is sent to the user's device, where the user can review it and accept or change it.

[0419] Example of how it works: If you have an important presentation the next day, the server will use generative AI to suggest a formal shirt and slacks set. If you're feeling more relaxed, you can also change to casual clothing.

[0420] Example prompts: "Suggest some outfits using a blue shirt.", "What outfits would help users relax when they're feeling stressed?"

[0421] The above is a specific embodiment of the present invention, which allows the user to receive recommendations for items that match their emotional state and preferences, and also allows for efficient item management.

[0422] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0423] Step 1:

[0424] A user uses a device such as a smartphone or tablet to take a photo of an item and enter basic information such as brand name, color, and size through an application. The input consists of manual input by the user and the photo taken. The device then sends this information and the photo to a server. The server analyzes the received information and generates a unique ID for the item. Specifically, the server uses an image analysis algorithm to extract the item's features from the photo and associates them with the basic information.

[0425] Input: Photo of the item, basic information entered by the user

[0426] Output: Analyzed product information, generation of unique ID

[0427] Step 2:

[0428] After the unique ID is generated for the item, the server assigns a digital tag to the item, which is used to facilitate item identification and tracking. The server associates the generated unique ID with the digital tag and stores it in a database.

[0429] Input: Unique ID, item analysis information

[0430] Output: Digital tag, stored in database

[0431] Step 3:

[0432] The server periodically updates the product database to maintain consistency. According to a set schedule, the server updates the database with newly added or modified product information. Specifically, the server performs a comparison between the clone data and the new data.

[0433] Input: New or modified item information

[0434] Output: Updated database

[0435] Step 4:

[0436] When a user searches for a specific item, they input search keywords using a terminal. The server receives this search request and extracts the relevant item information from the database. The server then sends the extracted results to the terminal, which then displays the search results to the user.

[0437] Input: Search keyword (from user)

[0438] Output: Search results (from server to device)

[0439] Step 5:

[0440] The device uses a camera and microphone to capture the user's facial expressions and voice, and sends this data to the emotion engine for real-time analysis. The emotion engine analyzes the user's emotional state from this input data and sends the data to the server. The server then uses the received emotion data to suggest the most suitable products for the user.

[0441] Input: User's facial expression and voice data

[0442] Output: Parsed emotion data

[0443] Step 6:

[0444] The server uses AI to analyze the user's past usage data, preferences, and emotional data. Based on the results of this analysis, the server generates suggestions for the user on what outfit to wear the next day. The suggestions are then sent to the user's device.

[0445] Input: Historical usage data, preferences, emotional data

[0446] Output: Outfit suggestions (from the generation AI to the device)

[0447] Step 7:

[0448] The server analyzes the usage frequency data of the items and generates a list of unused items. This list is sent to the terminal, and the user can check for missing items, lend them to a friend, or send a request to sell them. The server manages these requests and efficiently distributes the items.

[0449] Input: Frequency of use data

[0450] Output: List of unused items, management of sales and lending requests

[0451] Step 8:

[0452] When the user decides what to wear the next day, the device sends a delivery request to the server, which then coordinates with the logistics service to arrange for the item to be shipped from the warehouse. The server then tracks the delivery status in real time and notifies the user when the item arrives at the designated location.

[0453] Input: Delivery request (from user)

[0454] Output: Delivery status tracking and notification (from server to terminal)

[0455] (Application example 2)

[0456] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0457] In recent years, improving the efficiency of inventory management and user satisfaction at logistics centers have become important issues. However, conventional systems have been inadequate in managing inventory and proposing products that take customer sentiment into consideration. As a result, it has become difficult to address inventory overages and shortages, and to make personalized proposals based on customer preferences, resulting in a decline in overall operational efficiency and customer satisfaction. The present invention aims to solve these issues, enabling logistics centers to provide more efficient and personalized services.

[0458] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0459] In this invention, the server includes means for taking photos of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique IDs and assigning digital tags, means for saving the item information in a database, means for periodically updating the item database to maintain information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on a user's past usage data and preferences, means for analyzing item usage frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, means for tracking and notifying delivery status, means for using an emotion analysis engine to analyze emotions and suggest products that match the customer's mood, and means for analyzing item distribution data and customer emotion data and generating reports. This enables more efficient item management in logistics centers and personalized product suggestions based on customer emotions.

[0460] "Goods" is a general term that refers to various types of products, merchandise, packages, etc.

[0461] "Taking a photo" means acquiring image data using the camera function of a digital camera, smartphone, etc.

[0462] "Basic information" refers to basic and necessary information about an item, including, for example, "brand name," "color," and "size."

[0463] "Server" refers to a combination of hardware and software for storing, processing, and managing data.

[0464] A "unique ID" is a special identifier assigned to an item, data, etc. to uniquely identify it.

[0465] A "digital tag" is an electronic label or mark attached to an item that contains information including a unique ID.

[0466] A "database" is a system for effectively storing, searching, and managing various data.

[0467] "Information integrity" refers to keeping data accurate and consistent.

[0468] "Searching" is the act of finding specific information from a database.

[0469] "Search results" are a collection of data or information obtained through a search.

[0470] "Past usage data" is historical information about goods and services that a user has previously used.

[0471] "Preferences" refers to the user's personal tastes and preferences.

[0472] A "suggestion" is the act of recommending specific information or choices to a user.

[0473] "Notification" refers to an act or message that informs a user of specific information.

[0474] "Frequency of use data" is information on how often an item is used.

[0475] "Renting" means the act of letting someone else use an item temporarily.

[0476] "Sales Request" means a request or desire to purchase an item.

[0477] "Logistics services" refers to all services such as transporting, storing, and delivering goods.

[0478] "Delivery status" is information that indicates the stage at which an item is in the delivery process.

[0479] An "emotion analysis engine" is software or a system that analyzes human emotions based on data such as voice and images.

[0480] "Distribution data" is data about how an item is distributed.

[0481] "Data analysis" is the act of examining data in detail to find specific patterns and trends.

[0482] "Report generation" refers to the act of creating a report based on analysis results and statistical information.

[0483] "Generative AI" refers to artificial intelligence that makes optimal suggestions and predictions based on user data and behavioral patterns.

[0484] The present invention implements a "smart management application" that improves the efficiency of goods management in logistics centers and provides personalized product proposals to customers. This system is configured by combining the following hardware and software.

[0485] 1. A way to take a photo of an item and enter basic information

[0486] Hardware: Smartphones and tablets

[0487] Software: Camera application and data entry application

[0488] When a new item arrives at a distribution center, staff use their smartphones or tablets to take a photo of the item and enter basic information such as brand name and size, which is then sent to a server.

[0489] 2. Means for sending product information to the server

[0490] Hardware: Smartphones and tablets

[0491] Software: Data transmission application

[0492] The acquired item information is sent from the smartphone or tablet to a server, which analyzes the information, generates a unique ID, and assigns a digital tag to the item.

[0493] 3. A method for analyzing product information, generating unique IDs, and assigning digital tags

[0494] Software: Unique ID generation algorithm and digital tagging system

[0495] The analyzed product information is used to generate a unique ID on the server, and a digital tag is assigned to the product. This information is then stored in a database.

[0496] 4. A means of storing product information in a database

[0497] Hardware: Cloud Server

[0498] Software: Database management system (e.g., MySQL (registered trademark), Firebase)

[0499] The item information with the digital tag is stored in a database on a cloud server.

[0500] 5. A method for regularly updating the product database and maintaining the integrity of the information

[0501] Software: Data Update Algorithm

[0502] The server periodically updates the information in the database to ensure that the data remains consistent.

[0503] 6. A means of searching for specific items and displaying search results

[0504] Software: Product search application

[0505] When a staff member is looking for a specific item, the item search application is used to search the database for the relevant item information and display the results.

[0506] 7. A means to generate and notify clothing suggestions based on the user's past usage data and preferences

[0507] Software: Generative AI (e.g., PyTorch, TENSORFLOW®)

[0508] The generative AI generates optimal clothing and item suggestions based on the user's past usage data and preferences, and notifies them on the smartphone or tablet.

[0509] 8. A method for analyzing data on the frequency of use of items and identifying unused items

[0510] Software: Data analysis system

[0511] The server analyzes data on how frequently items are used and identifies unused items.

[0512] 9. A way to manage rental and sales requests

[0513] Software: Request Management Application

[0514] Users can rent out unused items or send sales requests, and the server manages this.

[0515] 10. Means of coordinating with logistics services to arrange delivery of goods

[0516] Software: Delivery Management System

[0517] The server works in conjunction with the logistics service to smoothly arrange for the delivery of goods.

[0518] 11. Means of tracking and notification of delivery status

[0519] Software: Shipping Tracking System

[0520] Track the status of your items in real time when they are delivered and notify the user.

[0521] 12. Using an emotion analysis engine to analyze emotions and suggest products that match the customer's mood

[0522] Software: Sentiment analysis engine (e.g., Azure® Cognitive Services, Google® Cloud AI)

[0523] An emotion analysis engine analyzes the customer's facial expressions and voice, and generative AI suggests products that match the customer's mood.

[0524] 13. Data analysis and report generation tools for analyzing product distribution data and customer sentiment data

[0525] Software: Data analysis tools

[0526] Conduct detailed analysis of product distribution data and customer sentiment data to generate monthly reports.

[0527] Examples:

[0528] For example, when a customer places an order, an emotion analysis engine analyzes their facial expressions via their smartphone camera. If the customer appears stressed, the generative AI will suggest products that will help them relax. Furthermore, this analysis, along with product distribution data, will identify overstocks and shortages, improving operational efficiency.

[0529] Example prompt sentence:

[0530] "We use photos of customers' faces and voice data to analyze their emotions in real time. Based on the analysis results, we suggest products that match the customer's mood. For example, if a customer is feeling stressed, we suggest products that will help them relax (such as aroma candles). How can we build the optimal generative model?"

[0531] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0532] Step 1:

[0533] Users take a photo of the item using a smartphone or tablet and enter basic information such as the brand name and size.

[0534] Input: Basic information such as item image, brand name, size, etc.

[0535] Output: Photos and basic information are saved within the application.

[0536] Specific operations: Upload a photo of the item you have taken to the application and enter basic information using the text input fields in the application.

[0537] Step 2:

[0538] The terminal transmits the acquired product information to the server.

[0539] Input: Item information (basic information such as photo, brand name, size, etc.).

[0540] Output: The item information is sent to the server.

[0541] Specific operation: Press the "Send" button in the application to send information to the server via the data transmission protocol.

[0542] Step 3:

[0543] The server analyzes the received item information, generates a unique ID, and assigns a digital tag.

[0544] Input: Item information (basic information such as photo, brand name, size, etc.).

[0545] Output: A unique ID and a digital tag are generated.

[0546] Specific operations: Analyzes item information, generates a unique identifier (unique ID), and executes an algorithm to assign that ID as a digital tag.

[0547] Step 4:

[0548] The server stores the generated unique ID and digital tag in a database along with the item information.

[0549] Input: Item information, unique ID and digital tag.

[0550] Output: Item information, unique ID and digital tag stored in a database.

[0551] Specific operation: Store the item information, generated unique ID and digital tag in a database using SQL queries, etc.

[0552] Step 5:

[0553] The server periodically updates the product database to maintain consistency of the information.

[0554] Input: Product information in the database.

[0555] Output: Updated item information in the database.

[0556] Specific operation: Using a database management system (DBMS), the scheduler periodically updates information and checks its consistency.

[0557] Step 6:

[0558] Users use a search application on their smartphone or tablet to search for a specific item and view the search results.

[0559] Input: Search keyword (e.g. black shirt).

[0560] Output: Product information displayed as search results.

[0561] Specific operation: Send a search query to the database, retrieve and display the corresponding item information.

[0562] Step 7:

[0563] The server uses generative AI to generate and notify the user of clothing suggestions based on their past usage data and preferences.

[0564] Input: User's past usage data, user preferences.

[0565] Output: Suggested outfit combinations.

[0566] Specific operation: Based on past usage data and user preferences, a generative AI model is used to generate optimal suggestions and notify the user's device.

[0567] Step 8:

[0568] The server analyzes data on how often items are used and identifies unused items.

[0569] Input: Frequency of use data for items.

[0570] Output: A list of unused items.

[0571] Specific operation: Analyzes usage frequency data using a data analysis algorithm and lists unused items.

[0572] Step 9:

[0573] Users send requests to rent or sell unused items through the application, and the server manages them.

[0574] Input: A rental or sale request.

[0575] Output: Management information for the request.

[0576] Specific operation: The user sends a request through the application interface, and the server records and manages it in a database.

[0577] Step 10:

[0578] The server coordinates with the logistics service to arrange delivery of the goods.

[0579] Input: Request for delivery arrangement.

[0580] Output: Notification of completion of delivery arrangements.

[0581] Specific operation: Uses the logistics service API to arrange delivery and track delivery status.

[0582] Step 11:

[0583] The server tracks the delivery status and notifies the user.

[0584] Input: Delivery status information.

[0585] Output: Delivery status notification.

[0586] Specific behavior: Tracks delivery information in real time and automatically notifies users when there is a status change.

[0587] Step 12:

[0588] The emotion analysis engine analyzes the customer's facial expressions and voice, and the server uses generative AI to suggest products that match the customer's mood.

[0589] Input: Customer facial expressions, voice data, and past usage data.

[0590] Output: Product suggestions that match the customer's mood.

[0591] Specific operation: Facial expressions and voice data are captured using the smartphone's camera and microphone, and analyzed by an emotion analysis engine. Based on this data, the generative AI makes optimal product suggestions.

[0592] Step 13:

[0593] The server analyzes product distribution data and customer sentiment data and generates monthly reports.

[0594] Input: Goods distribution data, customer sentiment data.

[0595] Output: Monthly report.

[0596] Specific actions: Use data analysis tools to perform detailed analysis of distribution data and sentiment data and generate visualized monthly reports.

[0597] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0598] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0599] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0600] [Second embodiment]

[0601] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0602] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0603] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0604] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0605] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0606] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0607] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0608] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0609] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0610] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0611] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0612] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0613] This invention relates to a 4D closet system that utilizes digital tags and generative AI. This system supports the management and efficient use of items and provides the following key functions to improve users' lives:

[0614] Product registration

[0615] First, we will explain the procedure for a user to register a newly purchased item in the system. The user takes a photo of the item using a smartphone or other device and enters the item information through the application. Specific items include the brand name, color, and size.

[0616] The device then sends the captured photo and the entered information to a server, which analyzes the information and generates a unique ID for the item, assigns a digital tag to the item, and stores the item information in a database.

[0617] Management of goods

[0618] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency of the information. When a user searches for a specific item, the server retrieves the corresponding item information from the database via the terminal and displays it to the user.

[0619] For example, when a user searches for "red shirt," the server extracts information about the corresponding shirt based on the keyword and sends the results to the user's terminal.

[0620] Product suggestions

[0621] Based on the user's preferences and past usage data, the AI ​​generator will suggest the outfit they would like to wear the next day. The server will use the AI ​​generator to analyze the user's past data and generate outfit combinations. This suggestion will be sent to the user's device, and the user can review the suggested outfit and accept or change it.

[0622] For example, if there is a special event the next day, the generative AI will suggest a set of shirt, pants, and shoes, and the user can review the suggestions and make any necessary changes in the application.

[0623] Distribution and sharing of goods

[0624] The server analyzes the frequency of use of items and allows users to lend or sell unused items to friends and family. The server analyzes the data on the frequency of use of items and provides users with a list of unused items. Users can submit requests for lending or selling items through the application.

[0625] For example, if a user has a shirt they haven't worn in a few months, they can send a request in the app to lend it to a friend. The server manages the request and notifies the user when the loan is complete.

[0626] Goods delivery management

[0627] Once the user has decided on the outfit they want to wear the next day, the server arranges for the items to be delivered. The user submits a delivery request through the app, and the server works with the logistics service to arrange for the items to be shipped from the warehouse.

[0628] In addition, the server tracks the delivery status in real time and notifies the user when the item arrives at the parcel locker, where the user can check the status and collect the item through the app.

[0629] For example, the shirt and pants that the user has selected for the next day's outfit will be delivered to the delivery locker the next morning, and the user can receive and wear them as is.

[0630] As described above, the system of the present invention supports the management and efficient use of items, and provides functions for making the most of a user's time and space.

[0631] The processing flow will be explained below.

[0632] Product registration

[0633] Step 1:

[0634] User: Activates the smartphone camera and takes a photo of the new item.

[0635] Step 2:

[0636] User: Opens the smartphone app and enters basic information such as "brand name," "color," and "size" along with a photo.

[0637] Step 3:

[0638] Terminal: Sends the entered information and photos to the server.

[0639] Step 4:

[0640] Server: Analyzes the received product information and generates a unique ID.

[0641] Step 5:

[0642] Server: Attaches digital tags to items and stores that information in a database.

[0643] Management of goods

[0644] Step 1:

[0645] Server: Regularly updates the product database to maintain consistency of information.

[0646] Step 2:

[0647] User: Uses the app to search for a specific item, for example, by entering the keyword "red shirt."

[0648] Step 3:

[0649] Server: Searches the database for relevant product information and sends the results to the terminal.

[0650] Step 4:

[0651] Terminal: Displays search results to the user.

[0652] Product suggestions

[0653] Step 1:

[0654] Server: Uses generative AI to analyze users' past usage data and preferences.

[0655] Step 2:

[0656] Server: Generates suggestions for the next day's outfit, taking into account the combination of items.

[0657] Step 3:

[0658] Server: Notifies the user's terminal of the generated proposal.

[0659] Step 4:

[0660] Device: The user reviews the suggestions and makes changes to the outfit if necessary.

[0661] Distribution and sharing of goods

[0662] Step 1:

[0663] Server: Analyzes the item usage frequency data and generates a list of unused items.

[0664] Step 2:

[0665] Users: Use the application to request loans or sales of unused items to friends and family.

[0666] Step 3:

[0667] Server: Manages rental and sales requests and tracks the necessary transactions.

[0668] Step 4:

[0669] Server: Sends notification to the user when the transaction is complete.

[0670] Goods delivery management

[0671] Step 1:

[0672] User: Uses the app to request delivery of the outfit they want to wear the next day.

[0673] Step 2:

[0674] Server: Works with logistics services to arrange delivery and ship items from the warehouse.

[0675] Step 3:

[0676] Server: Tracks the delivery status of goods and updates the information in real time.

[0677] Step 4:

[0678] Server: When the item arrives at the delivery locker, it sends a notification to the user.

[0679] Step 5:

[0680] User: Check delivery status and receive items in the app.

[0681] Through these steps, the system efficiently executes a series of processes from product registration to management, proposal, distribution, and delivery management, thereby significantly improving users' lives.

[0682] Example 1

[0683] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0684] Conventional item management systems make it difficult for users to efficiently register, manage, and use the items they purchase. They also lack advanced support, such as managing the circulation and lending of unused items, or suggesting outfits based on the user's preferences and past usage history. Furthermore, arranging delivery of items and tracking their status places a heavy burden on the user. The present invention aims to solve these problems and improve the quality of life for users.

[0685] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0686] In this invention, the server includes means for acquiring images of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique identifiers and assigning digital tags, means for saving the item information in data storage, means for periodically updating the item database and maintaining information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on the user's past usage data and personal preferences, means for analyzing item usage frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, and means for tracking and notifying delivery status. This allows users to centrally register, manage, use, distribute, and deliver items.

[0687] "Goods" are any tangible goods or items that are the subject of management and that a User possesses, uses, or distributes.

[0688] "Image capture" is the process of taking a photograph or video of an item using an electronic device.

[0689] "Basic information" refers to data necessary to identify and specify an item, and includes attributes such as brand name, color, and size.

[0690] A "server" is a remote computer system that processes information and stores data.

[0691] "Transmission" is the act of transferring data or information from one place to another.

[0692] "Analysis" is the process of analyzing received data to extract useful information.

[0693] A "unique identifier" is a specific number or code assigned to each item to uniquely identify it.

[0694] A "digital tag" is an electronic tag or label associated with an item that contains information in digital form.

[0695] "Data storage" is a physical or virtual location or device for storing information.

[0696] A "database" is an information system that systematically organizes a large amount of data and allows efficient access using queries.

[0697] "Integrity" refers to data that is accurate, consistent, and not altered or corrupted.

[0698] "Searching" is the act of searching a database or information system to find specific data.

[0699] A "suggestion" is a recommendation or recommendation made based on the results of the analysis.

[0700] "Notifications" are messages or alerts that inform users of important information.

[0701] "Frequency of use" is an index that indicates how often an item is used.

[0702] A "request" is a request or application to ask for something.

[0703] "Logistics services" are businesses or companies that manage and execute the transportation and delivery of goods.

[0704] "Tracking" is the process of monitoring and recording the location and condition of an item in real time.

[0705] This invention is a system for supporting the management and efficient use of goods, with the aim of improving the quality of life of users. This system can perform everything from product registration to management, distribution, and delivery in an integrated manner.

[0706] 1. Registration of goods

[0707] Users take a photo of a newly purchased item using a smartphone or other device. Next, they enter basic information about the item, such as its brand name, color, and size, through an application. The device then sends this information to a server. The server analyzes the received information, generates a unique identifier for the item, and assigns a digital tag to it. The item information is then stored in data storage.

[0708] 2. Management of items

[0709] After the product information is registered, the server periodically updates the product database to maintain the integrity of the information. When a user searches for a specific product using the application, the device sends the search keywords to the server, which then extracts the corresponding product information from the database, returns it to the device, and displays it to the user.

[0710] 3. Product Proposals

[0711] The server uses the generative AI model to analyze the user's past usage data and personal preferences. Based on this, the server generates outfit suggestions for the next day and notifies the user's device. For example, if there is a special event the next day, the generative AI will suggest a set of shirt, pants, and shoes. The user can review the suggestions in the app and make changes as needed.

[0712] 4. Distribution and sharing of goods

[0713] The server analyzes the usage frequency data of the items and identifies unused items. Users can then send requests to lend or sell items to relatives or acquaintances through the application. The server manages the requests and notifies the user when the lending or sale is completed.

[0714] 5. Goods delivery management

[0715] Users use the app to request delivery of the clothes they will wear the next day. The server works with the logistics service to arrange for the items to be shipped from the warehouse and tracks the delivery status in real time. Once the items arrive at the delivery locker, the server sends a notification to the user, who can then check the status on the app and collect the items.

[0716] This system is realized using various hardware and software. Specifically, devices such as smartphones and tablets are used, and an application acts as the interface between the user and the system. The server is equipped with software with advanced data analysis capabilities and a generative AI model.

[0717] Examples of concrete examples and prompts

[0718] 1. If a user buys a new red shirt, they take a photo with their smartphone and enter "Brand: ABC," "Color: Red," and "Size: M" into the app and submit it. The server analyzes the information, generates a unique identifier and digital tag, and stores them in a database.

[0719] Example prompt: "Please register for a new red ABC brand medium shirt."

[0720] 2. When a user searches for "red shirt," the server retrieves the relevant information from the database and sends it to the terminal, where the user can view the results.

[0721] Example prompt: "Search the database for red shirts and display a list."

[0722] 3. The day before a special event, the generative AI will suggest a set of shirts, pants, and shoes, and the user can review the suggestions in the app and make changes as needed.

[0723] Example prompt: "Please give me some outfit suggestions for tomorrow's special event."

[0724] Thus, the present invention is a multifunctional system that makes users' item management more efficient and improves their quality of life.

[0725] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0726] Product registration

[0727] Step 1:

[0728] The user takes a photo of the newly purchased item with their smartphone or device. The input is the image of the item, and the output is the captured image file.

[0729] Specific behavior: The user activates the smartphone camera and takes a photo of the red shirt. The image file is saved to the device.

[0730] Step 2:

[0731] The user launches the application and inputs a photograph of the item along with basic information such as the brand name, color, size, etc. The input is the item image and text data of the basic information, and the output is a transmission package containing this data.

[0732] Specific behavior: The user enters "Brand name: ABC", "Color: Red", and "Size: M" into the app, selects a photo, and presses the send button.

[0733] Step 3:

[0734] The terminal sends the entered information and photos to the server. The input is the transmission package, and the output is the data that arrives at the server.

[0735] Specific operation: The transmission package created by the terminal is sent to the server via the Internet.

[0736] Step 4:

[0737] The server analyzes the received photos and item information. The input is the received data, and the output is the analysis result data.

[0738] Specific operation: The server analyzes the photo using an image analysis algorithm and extracts information such as "red," "shirt," and "brand: ABC."

[0739] Step 5:

[0740] The server generates a unique identifier for the item based on the analysis results and assigns a digital tag to it. The input is the analysis results, and the output is the unique identifier and item information with the digital tag.

[0741] Specific operation: The server generates a unique ID (e.g., 123456), uses it to create a digital tag, and links it to the item information.

[0742] Step 6:

[0743] The server stores the product information in a data storage. The input is the product information with the digital tag, and the output is the data stored in the data storage.

[0744] Specific operation: The server writes the generated product information to the database.

[0745] Management of goods

[0746] Step 7:

[0747] The server periodically updates the product database to maintain consistency of information. The input is the existing product information, and the output is the updated database information.

[0748] Specific operation: The server runs an automatic script to check for updates to product information and update the database if necessary.

[0749] Step 8:

[0750] A user searches for a specific item within an application. The input is the search keyword, and the output is the search result data.

[0751] Specific behavior: The user types "red shirt" into the app's search box and presses the search button.

[0752] Step 9:

[0753] The terminal sends search keywords to the server. The input is the search keywords, and the output is the data sent to the server.

[0754] Specific operation: The device sends the search keywords to the server via the Internet.

[0755] Step 10:

[0756] The server extracts the relevant product information from the database and sends it to the terminal. The input is the search keyword, and the output is the search result data.

[0757] Specific operation: The server extracts data corresponding to "red shirt" from the database and sends it to the terminal.

[0758] Step 11:

[0759] The terminal displays the search results to the user. The input is the search result data, and the output is the information displayed to the user.

[0760] Specific operation: The device displays the search results on the app's display screen, and the user confirms them.

[0761] Product suggestions

[0762] Step 12:

[0763] The server uses the generated AI model to analyze the user's past usage data and personal preferences. The input is the past usage data, and the output is the analysis results.

[0764] Specific operation: The server launches the generative AI, inputs the user's past data (e.g., frequently worn colors and styles), and performs analysis.

[0765] Step 13:

[0766] The server generates the next day's outfit combination based on the analysis results. The input is the analysis results, and the output is the suggested outfit data.

[0767] Specific operation: The generative AI model proposes a set of "shirt, pants, shoes" and saves it as data.

[0768] Step 14:

[0769] The server notifies the user's terminal of the generated proposal. The input is the proposal data, and the output is the notification sent to the user's terminal.

[0770] Specific operation: The server sends the proposal to the device, and the device notifies the user, "This set is recommended for tomorrow's event."

[0771] Distribution and sharing of goods

[0772] Step 15:

[0773] The server analyzes the usage frequency data of the items and identifies unused items. The input is the usage frequency data, and the output is a list of unused items.

[0774] Specific operation: The server lists items that have not been used for a certain period of time and saves them as suggestions.

[0775] Step 16:

[0776] A user submits a rental or sale request through the application. The input is the request data and the output is the request sent to the server.

[0777] What happens: A user sends a request in the app to "lend a shirt to a friend."

[0778] Step 17:

[0779] The server manages the requests and notifies the user when the loan or sale is completed. The input is the request data and the output is the notification sent to the user.

[0780] What happens next: The server processes the request and sends a notification to the user saying, "Your shirt has been checked out."

[0781] Goods delivery management

[0782] Step 18:

[0783] A user uses the application to request delivery of the clothes they will wear the next day. The input is the delivery request data, and the output is the delivery request sent to the server.

[0784] Specific behavior: A user requests delivery of a shirt and pants to wear the next day through the app.

[0785] Step 19:

[0786] The server works with the logistics service to process the shipment of goods from the warehouse. The input is the delivery request data, and the output is the shipping instruction sent to the logistics service.

[0787] Specific operation: The server communicates with the logistics service and starts the shipping procedure for the item.

[0788] Step 20:

[0789] The server tracks the delivery status in real time and sends a notification to the user once the item arrives at the parcel locker. The input is the real-time delivery status data and the output is the notification sent to the user.

[0790] Specific behavior: The server tracks the delivery status of the items and sends a notification to the user saying, "The shirt and pants have arrived at the delivery locker."

[0791] (Application example 1)

[0792] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0793] Conventional closet management systems have the drawback of being time-consuming and inefficient, as registering and managing items is done manually. Furthermore, outfit suggestions based on user preferences and past usage data are often inappropriate, potentially reducing user satisfaction. Furthermore, managing requests for item rentals and sales is complicated, and delivery status tracking and notifications are not provided in real time, resulting in a lack of an improved user experience.

[0794] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0795] In this invention, the server includes means for taking photos of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique IDs, and assigning digital tags, means for saving the item information in a database, means for periodically updating the item database and maintaining information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on a user's past use data and preferences, means for analyzing item use frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, means for tracking and notifying delivery status, means for automatically registering items purchased by a user in cooperation with an online shopping site, and means for using a generation AI to suggest outfits based on a user's purchase history and preferences. This enables efficient item registration and management, accurate outfit suggestions based on a user's preferences and past data, and seamless management of item rental, sales, and delivery.

[0796] "Means for taking a photo of an item and entering basic information" refers to a device or interface that allows a user to take a picture of an item they own and enter basic information about that item (e.g., brand name, color, size, etc.).

[0797] "Means for transmitting information about an item to a server" refers to the communications infrastructure and protocols for transmitting the photographed image of the item and the input information to a central server.

[0798] "Means for analyzing item information, generating a unique ID, and assigning a digital tag" refers to algorithms or software that analyzes the transmitted item information and generates and assigns a unique identification number (ID) to the item.

[0799] The "means for storing product information in a database" refers to a system or procedure for storing the generated product information and unique ID in a database.

[0800] "Means for regularly updating the product database and maintaining the integrity of the information" means the mechanisms or protocols for periodically checking the information in the database to ensure that it accurately reflects new or changed information.

[0801] "Means for searching for specific items and means for displaying search results" refers to the search function that a user uses to find a specific item and the interface or method for visually displaying the results to the user.

[0802] "Means for generating and notifying clothing suggestions based on the user's past usage data and preferences" refers to a system or algorithm that analyzes the user's past behavioral data and preference trends, suggests clothing suitable for the user, and notifies the user of those suggestions.

[0803] "Means for analyzing item usage frequency data and identifying unused items" refers to technologies and methods for analyzing how frequently items are used and identifying items that have not been used for a long period of time.

[0804] A "means for managing rental and sale requests" is software or a process for accepting, tracking, and managing requests from users to rent or sell items.

[0805] The "means for arranging delivery of goods in cooperation with a logistics service" refers to an interface or system for efficiently arranging delivery of goods in cooperation with an external logistics service provider.

[0806] "Means for tracking and notifying delivery status" refers to technologies and means for monitoring the delivery status of goods in real time and providing that information to users.

[0807] "Means for linking with online shopping sites and automatically registering items purchased by users in the system" refers to a mechanism for integrating with online shopping platforms and automatically adding items purchased by users to the closet system.

[0808] "Means of using generative AI to suggest clothing based on a user's purchasing history and preferences" refers to algorithms and systems that utilize the latest artificial intelligence technology to suggest clothing based on a user's purchasing history and preferences.

[0809] The present invention provides a system for improving the efficiency of item management and user convenience. This system automates a series of processes, such as photographing items, registering information, saving data, proposing items, renting and selling items, and managing delivery. Specific embodiments are described below.

[0810] 1. Registration of goods

[0811] Using a device such as a smartphone, the user takes a photo of the item they have purchased and enters basic information such as brand name, color, and size. This information is sent from the device to a server. The server analyzes the received item information, generates a unique ID, and assigns it to the item. The item information with the digital tag attached is stored in a database. Hardware used includes devices such as smartphones and PCs, and software such as React Native, Node.js, Express, and MongoDB is used to send the item information.

[0812] 2. Management of items

[0813] The server periodically updates the database to maintain consistency of product information. When a user searches for a specific product, they enter a keyword through their device, and the server searches the database for the corresponding product and displays the results to the user. In this process, React Native is used as the search interface, and MongoDB is used for database search processing.

[0814] 3. Suggestion function

[0815] The server uses a generative AI model to suggest outfits for the next day based on the user's past usage data, purchase history, and preferences. The generated suggestions are sent to the user's device. OpenAI GPT-4 is used as the generative AI model. As a concrete example, the following prompt sentence is input to the generative AI model:

[0816] Suggest tomorrow's outfit based on the user's purchase history over the past six months, as well as their preferred colors and brands.

[0817] User Information:

[0818] Brand: [Luxury Brand A, Luxury Brand B]

[0819] Favorite colors: [red, blue]

[0820] Past purchase history: [Product ID 123, Product ID 456, Product ID 789]

[0821] Special Events: [None]

[0822] 4. Rental and sales

[0823] The server analyzes item usage frequency data and identifies items that have not been used for a long time. Based on this information, users can request to rent or sell items through the app. The server manages the requests and notifies the user when the request is completed. Node.js and MongoDB are used to manage rentals and sales.

[0824] 5. Delivery management

[0825] Once the user has decided on an outfit, the server connects with a logistics service to arrange delivery of the items. The delivery status is tracked in real time, and the user is notified when the item arrives at the parcel locker. Node.js is used to connect to an external logistics API to arrange delivery and track the status.

[0826] As described above, the system of the present invention seamlessly integrates the registration, management, proposal, rental, sale and delivery of goods, thereby greatly improving user convenience.

[0827] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0828] Step 1:

[0829] The user uses the device to take a photo of the item they purchased and enter basic information such as brand name, color, size, etc. This input information includes image data and text information of the item. This data is temporarily stored on the device.

[0830] Step 2:

[0831] The terminal sends the entered product information and image data to the server. At this time, an HTTP POST request is used to transfer form data including the product image data and metadata to the server. The input is the product information and image data provided by the user, and the output is stored on the server.

[0832] Step 3:

[0833] The server analyzes the received product information and generates a unique ID. This unique ID is used to uniquely identify the product information. In this process, the unique ID is generated using a UUID generation algorithm or similar. The input is the transmitted product information, and the output is the generated unique ID and product information.

[0834] Step 4:

[0835] The server assigns the generated unique ID to the item information and generates a digital tag. The digital tag is an important element for identifying the item and is expressed in the form of an RFID tag, barcode, etc. In this step, the algorithm for generating the digital tag runs. The input is item information with a unique ID, and the output is item information with a digital tag.

[0836] Step 5:

[0837] The server stores the item information with the digital tags in a database. The database used here is a NoSQL database such as MongoDB, and the data is stored in document format. The input is the item information with the digital tags, and the output is the item information stored in the database.

[0838] Step 6:

[0839] The server periodically updates the database to maintain consistency of the information. This process checks for duplicates and inconsistencies in the data, updating or deleting them as necessary. The input is the existing database, and the output is a consistent database.

[0840] Step 7:

[0841] When a user searches for a specific item, they enter keywords into their terminal and send a search request to the server. The server searches the database for the relevant item and returns the results to the terminal. The input is the keyword entered by the user, and the output is a list of search results.

[0842] Step 8:

[0843] The server uses a generative AI model to suggest an outfit for the next day based on the user's past usage data, purchase history, and preferences. This suggestion is sent to the user's device. The generative AI model used is OpenAI GPT-4. An example of a specific prompt is as follows:

[0844] Suggest tomorrow's outfit based on the user's purchase history over the past six months, as well as their preferred colors and brands.

[0845] User Information:

[0846] Brand: [Luxury Brand A, Luxury Brand B]

[0847] Favorite colors: [red, blue]

[0848] Past purchase history: [Product ID 123, Product ID 456, Product ID 789]

[0849] Special Events: [None]

[0850] The input is user data and the output is outfit suggestions.

[0851] Step 9:

[0852] The server analyzes the item usage frequency data and identifies items that have not been used for a long time. Based on this information, users can request to rent or sell items. The server manages the request and notifies the user when processing is complete. The input is the item usage frequency data, and the output is a list of unused items.

[0853] Step 10:

[0854] Once the user has decided on an outfit, the server works with the logistics service to arrange delivery of the items. This is done using a logistics API. The delivery status is tracked in real time, and the user is notified when the item arrives at the delivery locker. The input is the user's delivery request, and the output is a notification of the delivery status.

[0855] Through the above processing steps, the system of the present invention can efficiently register, manage, propose, rent, sell, and deliver products.

[0856] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0857] This invention relates to a 4D closet system that utilizes digital tags, generative AI, and an emotion engine. This system supports the management and efficient use of items, recognizes the user's emotional state, and provides functions to make the user's life more comfortable.

[0858] Product registration

[0859] First, we will explain the procedure for a user to register a newly purchased item in the system. The user takes a photo of the item using a smartphone or other device. Next, they enter information about the item through the application. Specific items include the brand name, color, and size.

[0860] The device sends the entered information and photo to a server, which analyzes the information and generates a unique ID for the item, attaches a digital tag to the item, and stores the information in a database.

[0861] Management of goods

[0862] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency. When a user searches for a specific item, the server retrieves the corresponding item information from the database via the terminal and displays it to the user.

[0863] For example, when a user searches for "black shirts," the server extracts information about the corresponding shirts based on the keywords and sends the results to the user's terminal.

[0864] Utilizing the Emotion Engine

[0865] The emotion engine captures the user's face with a camera and analyzes their emotional state in real time from facial expressions, voice, etc. The emotion data analyzed by the emotion engine is sent to the server. Based on the received emotion data, the server makes product recommendations that are best suited to the user's current situation.

[0866] For example, if a user is feeling stressed, the AI ​​can suggest clothing made of soft materials that will help them relax. The AI ​​takes this emotional data into account and optimizes the suggestions.

[0867] Product suggestions

[0868] Based on the user's preferences, past usage data, and emotional data obtained from the emotion engine, the generative AI suggests outfits for the next day. The server uses the generative AI to analyze the data and generate the optimal outfit combination. This suggestion is sent to the user's device, where the user can review the suggested outfit and accept or change it.

[0869] For example, if you have an important presentation the next day, the generative AI will suggest a formal shirt and slacks set, and you can review the suggestion and change to a more casual outfit if you feel like relaxing.

[0870] Distribution and sharing of goods

[0871] The server analyzes the frequency of use of items and allows users to lend or sell unused items to friends and family. The server analyzes the data on the frequency of use of items and provides users with a list of unused items. Users can submit requests for lending or selling items through the application.

[0872] For example, if a user has an unused shirt and wants to lend it to a friend, the server manages the request and notifies the user when the loan is complete.

[0873] Goods delivery management

[0874] Once the user has decided on the outfit they want to wear the next day, the server arranges for the items to be delivered. The user makes a delivery request through the app, and the server works with the logistics service to arrange for the items to be shipped from the warehouse.

[0875] In addition, the server tracks the delivery status in real time and notifies the user when the item arrives at the parcel locker, where the user can check the status and collect the item through the app.

[0876] For example, the shirt and pants that the user has selected for the next day's outfit will be delivered to the delivery locker the next morning, and the user can receive and wear them as is.

[0877] As described above, the system of the present invention utilizes digital tags, generative AI, and an emotion engine to support the management and efficient use of items, and by making suggestions that are optimal for the user's emotional state, can significantly improve the user's life.

[0878] The processing flow will be explained below.

[0879] Product registration

[0880] Step 1:

[0881] User: Activates the smartphone camera and takes a photo of the new item.

[0882] Step 2:

[0883] User: Opens the smartphone app and enters basic information such as "brand name," "color," and "size" along with a photo.

[0884] Step 3:

[0885] Terminal: Sends the entered information and photos to the server.

[0886] Step 4:

[0887] Server: Analyzes the received product information and generates a unique ID.

[0888] Step 5:

[0889] Server: Attaches digital tags to items and stores that information in a database.

[0890] Management of goods

[0891] Step 1:

[0892] Server: Regularly updates the product database to maintain consistency of information.

[0893] Step 2:

[0894] User: Uses the app to search for a specific item, for example, by entering the keyword "black shirt."

[0895] Step 3:

[0896] Server: Searches the database for relevant product information and sends the results to the terminal.

[0897] Step 4:

[0898] Terminal: Displays search results to the user.

[0899] Utilizing the Emotion Engine

[0900] Step 1:

[0901] User: Uses a smartphone or wearable device to capture facial expressions and voice via a camera and microphone.

[0902] Step 2:

[0903] Device: Captured facial expression and voice data is sent to the emotion engine.

[0904] Step 3:

[0905] Emotion engine: Analyzes the user's emotional state from facial expressions and voice.

[0906] Step 4:

[0907] Terminal: Transmits the analyzed emotion data to the server.

[0908] Step 5:

[0909] Server: Based on the received emotion data, it generates optimal product recommendations for the user.

[0910] Product suggestions

[0911] Step 1:

[0912] Server: Uses generative AI to comprehensively analyze users' past usage data, preferences, and emotional data.

[0913] Step 2:

[0914] Server: Generates suggestions for the next day's outfit, taking into account the combination of items.

[0915] Step 3:

[0916] Server: Notifies the user's terminal of the generated proposal.

[0917] Step 4:

[0918] Device: The user reviews the suggestions and makes changes to the outfit if necessary.

[0919] Distribution and sharing of goods

[0920] Step 1:

[0921] Server: Analyzes the item usage frequency data and generates a list of unused items.

[0922] Step 2:

[0923] Users: Use the application to request loans or sales of unused items to friends and family.

[0924] Step 3:

[0925] Server: Manages rental and sales requests and tracks the necessary transactions.

[0926] Step 4:

[0927] Server: Sends notification to the user when the transaction is complete.

[0928] Goods delivery management

[0929] Step 1:

[0930] User: Uses the app to request delivery of the outfit they want to wear the next day.

[0931] Step 2:

[0932] Server: Works with logistics services to arrange delivery and ship items from the warehouse.

[0933] Step 3:

[0934] Server: Tracks the delivery status of goods and updates the information in real time.

[0935] Step 4:

[0936] Server: When the item arrives at the delivery locker, it sends a notification to the user.

[0937] Step 5:

[0938] User: Check delivery status and receive items in the app.

[0939] Through these steps, the system efficiently executes a series of processes, from product registration and management, to proposals, distribution, and delivery management, thereby significantly improving users' lives. Furthermore, the use of an emotion engine enables optimal proposals based on the user's emotional state, improving user satisfaction.

[0940] Example 2

[0941] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0942] Conventional item management systems require users to spend a lot of time managing item details and are unable to provide suggestions that take into account their emotional state. Furthermore, they lack mechanisms for efficiently managing the frequency of use of items and effectively utilizing unused items. Therefore, there is a need for a system that can efficiently manage items and provide suggestions that are optimal for the user's emotional state.

[0943] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0944] In this invention, the server includes a means for periodically updating the product database and maintaining consistency of information, a means for searching for specific products and displaying search results, and a means for providing an emotion engine for analyzing the user's emotions and making suggestions based on the emotions, thereby enabling the management and effective use of products while making suggestions that take into account the user's emotional state.

[0945] An "item" is an item that is owned and managed by a user.

[0946] "Means for taking photographs" refers to a method of obtaining an image of an item using a device such as a camera or smartphone.

[0947] The "means for inputting basic information" refers to a method by which a user inputs detailed information about an item (such as brand name, color, size, etc.) through an application.

[0948] A "server" is a computer system that exists in the cloud or within a local network and stores, analyzes, and communicates data.

[0949] The "means for analyzing product information" is a method for analyzing product-related data within the server and performing classification and feature extraction.

[0950] The "means for generating a unique ID" is a method for generating a unique identifier for each item, making the item identifiable.

[0951] A "digital tagging means" is a method for electronically tagging information related to an item.

[0952] The "means for storing in the database" refers to a storage device for permanently storing product information and software for managing it.

[0953] "Means for regularly updating the product database" refers to a method for adding or amending new or changed information to the database to keep the information up to date.

[0954] The "means for displaying search results" is a method for displaying on the screen information about items obtained based on the search conditions entered by the user.

[0955] The "emotion engine" is a system that analyzes the user's emotions using input devices such as a camera or microphone, and makes appropriate suggestions based on the results.

[0956] The "means for analyzing usage frequency data" is a method for analyzing the usage history and frequency of an item and promoting effective use of the item.

[0957] A "means for managing rental and sales requests" is a method for accepting and processing requests from users and taking action as necessary.

[0958] "Means for linking with logistics services" refers to methods for communicating with external delivery companies and warehouse management systems to manage logistics processes.

[0959] "Means for tracking delivery status" refers to a method for monitoring the delivery status of an item in real time and notifying the user.

[0960] "Means of notification" refers to a method for sending information from the system to the user and encouraging them to take necessary action.

[0961] This invention relates to a 4D closet system that streamlines item management and makes optimal suggestions based on the user's emotional state. By utilizing digital tags, generative AI, and an emotion engine, this system analyzes item management and usage frequency, providing functions to make the user's life more comfortable.

[0962] Product registration

[0963] Users take a photo of their newly purchased item using a device such as a smartphone or tablet. After taking the photo, they enter information about the item, such as the brand name, color, and size, through an application. The entered information and photo are sent from the device to a server. The server analyzes the received information, generates a unique ID for the item, and assigns a digital tag. This information is then stored in a database.

[0964] Specific example of operation: When a user purchases a blue shirt, enters the information into the app, takes a photo, and sends it, the server assigns a unique ID to the blue shirt and sets a digital tag.

[0965] Management of goods

[0966] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency of the information. When searching for a specific item, the server extracts relevant item information based on the search keywords and sends the results to the user's device for display.

[0967] Specific example of operation: When a user searches for "black shirt" or "blue skirt," the server sends information about the corresponding items to the terminal and displays it.

[0968] Utilizing the Emotion Engine

[0969] The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice, and evaluates their emotional state in real time. The analyzed emotion data is sent to the server via the device. Based on this, the server makes product recommendations that are best suited to the user's current situation.

[0970] Specific example of operation: If the emotion engine analyzes that the user is feeling stressed, the server will suggest clothing made of soft materials that will help them relax.

[0971] Product suggestions

[0972] The server uses AI to analyze the user's preferences, past usage data, and emotional data to generate the optimal outfit combination. This suggestion is sent to the user's device, where the user can review it and accept or change it.

[0973] Example of how it works: If you have an important presentation the next day, the server will use generative AI to suggest a formal shirt and slacks set. If you're feeling more relaxed, you can also change to casual clothing.

[0974] Example prompts: "Suggest some outfits using a blue shirt.", "What outfits would help users relax when they're feeling stressed?"

[0975] The above is a specific embodiment of the present invention, which allows the user to receive recommendations for items that match their emotional state and preferences, and also allows for efficient item management.

[0976] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0977] Step 1:

[0978] A user uses a device such as a smartphone or tablet to take a photo of an item and enter basic information such as brand name, color, and size through an application. The input consists of manual input by the user and the photo taken. The device then sends this information and the photo to a server. The server analyzes the received information and generates a unique ID for the item. Specifically, the server uses an image analysis algorithm to extract the item's features from the photo and associates them with the basic information.

[0979] Input: Photo of the item, basic information entered by the user

[0980] Output: Analyzed product information, generation of unique ID

[0981] Step 2:

[0982] After the unique ID is generated for the item, the server assigns a digital tag to the item, which is used to facilitate item identification and tracking. The server associates the generated unique ID with the digital tag and stores it in a database.

[0983] Input: Unique ID, item analysis information

[0984] Output: Digital tag, stored in database

[0985] Step 3:

[0986] The server periodically updates the product database to maintain consistency. According to a set schedule, the server updates the database with newly added or modified product information. Specifically, the server performs a comparison between the clone data and the new data.

[0987] Input: New or modified item information

[0988] Output: Updated database

[0989] Step 4:

[0990] When a user searches for a specific item, they input search keywords using a terminal. The server receives this search request and extracts the relevant item information from the database. The server then sends the extracted results to the terminal, which then displays the search results to the user.

[0991] Input: Search keyword (from user)

[0992] Output: Search results (from server to device)

[0993] Step 5:

[0994] The device uses a camera and microphone to capture the user's facial expressions and voice, and sends this data to the emotion engine for real-time analysis. The emotion engine analyzes the user's emotional state from this input data and sends the data to the server. The server then uses the received emotion data to suggest the most suitable products for the user.

[0995] Input: User's facial expression and voice data

[0996] Output: Parsed emotion data

[0997] Step 6:

[0998] The server uses AI to analyze the user's past usage data, preferences, and emotional data. Based on the results of this analysis, the server generates suggestions for the user on what outfit to wear the next day. The suggestions are then sent to the user's device.

[0999] Input: Historical usage data, preferences, emotional data

[1000] Output: Outfit suggestions (from the generation AI to the device)

[1001] Step 7:

[1002] The server analyzes the usage frequency data of the items and generates a list of unused items. This list is sent to the terminal, and the user can check for missing items, lend them to a friend, or send a request to sell them. The server manages these requests and efficiently distributes the items.

[1003] Input: Frequency of use data

[1004] Output: List of unused items, management of sales and lending requests

[1005] Step 8:

[1006] When the user decides what to wear the next day, the device sends a delivery request to the server, which then coordinates with the logistics service to arrange for the item to be shipped from the warehouse. The server then tracks the delivery status in real time and notifies the user when the item arrives at the designated location.

[1007] Input: Delivery request (from user)

[1008] Output: Delivery status tracking and notification (from server to terminal)

[1009] (Application example 2)

[1010] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1011] In recent years, improving the efficiency of inventory management and user satisfaction at logistics centers have become important issues. However, conventional systems have been inadequate in managing inventory and proposing products that take customer sentiment into consideration. As a result, it has become difficult to address inventory overages and shortages, and to make personalized proposals based on customer preferences, resulting in a decline in overall operational efficiency and customer satisfaction. The present invention aims to solve these issues, enabling logistics centers to provide more efficient and personalized services.

[1012] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1013] In this invention, the server includes means for taking photos of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique IDs and assigning digital tags, means for saving the item information in a database, means for periodically updating the item database to maintain information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on a user's past usage data and preferences, means for analyzing item usage frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, means for tracking and notifying delivery status, means for using an emotion analysis engine to analyze emotions and suggest products that match the customer's mood, and means for analyzing item distribution data and customer emotion data and generating reports. This enables more efficient item management in logistics centers and personalized product suggestions based on customer emotions.

[1014] "Goods" is a general term that refers to various types of products, merchandise, packages, etc.

[1015] "Taking a photo" means acquiring image data using the camera function of a digital camera, smartphone, etc.

[1016] "Basic information" refers to basic and necessary information about an item, including, for example, "brand name," "color," and "size."

[1017] "Server" refers to a combination of hardware and software for storing, processing, and managing data.

[1018] A "unique ID" is a special identifier assigned to an item, data, etc. to uniquely identify it.

[1019] A "digital tag" is an electronic label or mark attached to an item that contains information including a unique ID.

[1020] A "database" is a system for effectively storing, searching, and managing various data.

[1021] "Information integrity" refers to keeping data accurate and consistent.

[1022] "Searching" is the act of finding specific information from a database.

[1023] "Search results" are a collection of data or information obtained through a search.

[1024] "Past usage data" is historical information about goods and services that a user has previously used.

[1025] "Preferences" refers to the user's personal tastes and preferences.

[1026] A "suggestion" is the act of recommending specific information or choices to a user.

[1027] "Notification" refers to an act or message that informs a user of specific information.

[1028] "Frequency of use data" is information on how often an item is used.

[1029] "Renting" means the act of letting someone else use an item temporarily.

[1030] "Sales Request" means a request or desire to purchase an item.

[1031] "Logistics services" refers to all services such as transporting, storing, and delivering goods.

[1032] "Delivery status" is information that indicates the stage at which an item is in the delivery process.

[1033] An "emotion analysis engine" is software or a system that analyzes human emotions based on data such as voice and images.

[1034] "Distribution data" is data about how an item is distributed.

[1035] "Data analysis" is the act of examining data in detail to find specific patterns and trends.

[1036] "Report generation" refers to the act of creating a report based on analysis results and statistical information.

[1037] "Generative AI" refers to artificial intelligence that makes optimal suggestions and predictions based on user data and behavioral patterns.

[1038] The present invention implements a "smart management application" that improves the efficiency of goods management in logistics centers and provides personalized product proposals to customers. This system is configured by combining the following hardware and software.

[1039] 1. A way to take a photo of an item and enter basic information

[1040] Hardware: Smartphones and tablets

[1041] Software: Camera application and data entry application

[1042] When a new item arrives at a distribution center, staff use their smartphones or tablets to take a photo of the item and enter basic information such as brand name and size, which is then sent to a server.

[1043] 2. Means for sending product information to the server

[1044] Hardware: Smartphones and tablets

[1045] Software: Data transmission application

[1046] The acquired item information is sent from the smartphone or tablet to a server, which analyzes the information, generates a unique ID, and assigns a digital tag to the item.

[1047] 3. A method for analyzing product information, generating unique IDs, and assigning digital tags

[1048] Software: Unique ID generation algorithm and digital tagging system

[1049] The analyzed product information is used to generate a unique ID on the server, and a digital tag is assigned to the product. This information is then stored in a database.

[1050] 4. A means of storing product information in a database

[1051] Hardware: Cloud Server

[1052] Software: Database management system (e.g., MySQL, Firebase)

[1053] The item information with the digital tag is stored in a database on a cloud server.

[1054] 5. A method for regularly updating the product database and maintaining the integrity of the information

[1055] Software: Data Update Algorithm

[1056] The server periodically updates the information in the database to ensure that the data remains consistent.

[1057] 6. A means of searching for specific items and displaying search results

[1058] Software: Product search application

[1059] When a staff member is looking for a specific item, the item search application is used to search the database for the relevant item information and display the results.

[1060] 7. A means to generate and notify clothing suggestions based on the user's past usage data and preferences

[1061] Software: Generative AI (e.g., PyTorch, TensorFlow)

[1062] The generative AI generates optimal clothing and item suggestions based on the user's past usage data and preferences, and notifies them on the smartphone or tablet.

[1063] 8. A method for analyzing data on the frequency of use of items and identifying unused items

[1064] Software: Data analysis system

[1065] The server analyzes data on how frequently items are used and identifies unused items.

[1066] 9. A way to manage rental and sales requests

[1067] Software: Request Management Application

[1068] Users can rent out unused items or send sales requests, and the server manages this.

[1069] 10. Means of coordinating with logistics services to arrange delivery of goods

[1070] Software: Delivery Management System

[1071] The server works in conjunction with the logistics service to smoothly arrange for the delivery of goods.

[1072] 11. Means of tracking and notification of delivery status

[1073] Software: Shipping Tracking System

[1074] Track the status of your items in real time when they are delivered and notify the user.

[1075] 12. Using an emotion analysis engine to analyze emotions and suggest products that match the customer's mood

[1076] Software: Sentiment analysis engine (e.g., Azure Cognitive Services, Google Cloud AI)

[1077] An emotion analysis engine analyzes the customer's facial expressions and voice, and generative AI suggests products that match the customer's mood.

[1078] 13. Data analysis and report generation tools for analyzing product distribution data and customer sentiment data

[1079] Software: Data analysis tools

[1080] Conduct detailed analysis of product distribution data and customer sentiment data to generate monthly reports.

[1081] Examples:

[1082] For example, when a customer places an order, an emotion analysis engine analyzes their facial expressions via their smartphone camera. If the customer appears stressed, the generative AI will suggest products that will help them relax. Furthermore, this analysis, along with product distribution data, will identify overstocks and shortages, improving operational efficiency.

[1083] Example prompt sentence:

[1084] "We use photos of customers' faces and voice data to analyze their emotions in real time. Based on the analysis results, we suggest products that match the customer's mood. For example, if a customer is feeling stressed, we suggest products that will help them relax (such as aroma candles). How can we build the optimal generative model?"

[1085] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1086] Step 1:

[1087] Users take a photo of the item using a smartphone or tablet and enter basic information such as the brand name and size.

[1088] Input: Basic information such as item image, brand name, size, etc.

[1089] Output: Photos and basic information are saved within the application.

[1090] Specific operations: Upload a photo of the item you have taken to the application and enter basic information using the text input fields in the application.

[1091] Step 2:

[1092] The terminal transmits the acquired product information to the server.

[1093] Input: Item information (basic information such as photo, brand name, size, etc.).

[1094] Output: The item information is sent to the server.

[1095] Specific operation: Press the "Send" button in the application to send information to the server via the data transmission protocol.

[1096] Step 3:

[1097] The server analyzes the received item information, generates a unique ID, and assigns a digital tag.

[1098] Input: Item information (basic information such as photo, brand name, size, etc.).

[1099] Output: A unique ID and a digital tag are generated.

[1100] Specific operations: Analyzes item information, generates a unique identifier (unique ID), and executes an algorithm to assign that ID as a digital tag.

[1101] Step 4:

[1102] The server stores the generated unique ID and digital tag in a database along with the item information.

[1103] Input: Item information, unique ID and digital tag.

[1104] Output: Item information, unique ID and digital tag stored in a database.

[1105] Specific operation: Store the item information, generated unique ID and digital tag in a database using SQL queries, etc.

[1106] Step 5:

[1107] The server periodically updates the product database to maintain consistency of the information.

[1108] Input: Product information in the database.

[1109] Output: Updated item information in the database.

[1110] Specific operation: Using a database management system (DBMS), the scheduler periodically updates information and checks its consistency.

[1111] Step 6:

[1112] Users use a search application on their smartphone or tablet to search for a specific item and view the search results.

[1113] Input: Search keyword (e.g. black shirt).

[1114] Output: Product information displayed as search results.

[1115] Specific operation: Send a search query to the database, retrieve and display the corresponding item information.

[1116] Step 7:

[1117] The server uses generative AI to generate and notify the user of clothing suggestions based on their past usage data and preferences.

[1118] Input: User's past usage data, user preferences.

[1119] Output: Suggested outfit combinations.

[1120] Specific operation: Based on past usage data and user preferences, a generative AI model is used to generate optimal suggestions and notify the user's device.

[1121] Step 8:

[1122] The server analyzes data on how often items are used and identifies unused items.

[1123] Input: Frequency of use data for items.

[1124] Output: A list of unused items.

[1125] Specific operation: Analyzes usage frequency data using a data analysis algorithm and lists unused items.

[1126] Step 9:

[1127] Users send requests to rent or sell unused items through the application, and the server manages them.

[1128] Input: A rental or sale request.

[1129] Output: Management information for the request.

[1130] Specific operation: The user sends a request through the application interface, and the server records and manages it in a database.

[1131] Step 10:

[1132] The server coordinates with the logistics service to arrange delivery of the goods.

[1133] Input: Request for delivery arrangement.

[1134] Output: Notification of completion of delivery arrangements.

[1135] Specific operation: Uses the logistics service API to arrange delivery and track delivery status.

[1136] Step 11:

[1137] The server tracks the delivery status and notifies the user.

[1138] Input: Delivery status information.

[1139] Output: Delivery status notification.

[1140] Specific behavior: Tracks delivery information in real time and automatically notifies users when there is a status change.

[1141] Step 12:

[1142] The emotion analysis engine analyzes the customer's facial expressions and voice, and the server uses generative AI to suggest products that match the customer's mood.

[1143] Input: Customer facial expressions, voice data, and past usage data.

[1144] Output: Product suggestions that match the customer's mood.

[1145] Specific operation: Facial expressions and voice data are captured using the smartphone's camera and microphone, and analyzed by an emotion analysis engine. Based on this data, the generative AI makes optimal product suggestions.

[1146] Step 13:

[1147] The server analyzes product distribution data and customer sentiment data and generates monthly reports.

[1148] Input: Goods distribution data, customer sentiment data.

[1149] Output: Monthly report.

[1150] Specific actions: Use data analysis tools to perform detailed analysis of distribution data and sentiment data and generate visualized monthly reports.

[1151] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1152] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1153] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1154] [Third embodiment]

[1155] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1156] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1157] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1158] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1159] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1160] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1161] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1162] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1163] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1164] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1165] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1166] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1167] This invention relates to a 4D closet system that utilizes digital tags and generative AI. This system supports the management and efficient use of items and provides the following key functions to improve users' lives:

[1168] Product registration

[1169] First, we will explain the procedure for a user to register a newly purchased item in the system. The user takes a photo of the item using a smartphone or other device and enters the item information through the application. Specific items include the brand name, color, and size.

[1170] The device then sends the captured photo and the entered information to a server, which analyzes the information and generates a unique ID for the item, assigns a digital tag to the item, and stores the item information in a database.

[1171] Management of goods

[1172] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency of the information. When a user searches for a specific item, the server retrieves the corresponding item information from the database via the terminal and displays it to the user.

[1173] For example, when a user searches for "red shirt," the server extracts information about the corresponding shirt based on the keyword and sends the results to the user's terminal.

[1174] Product suggestions

[1175] Based on the user's preferences and past usage data, the AI ​​generator will suggest the outfit they would like to wear the next day. The server will use the AI ​​generator to analyze the user's past data and generate outfit combinations. This suggestion will be sent to the user's device, and the user can review the suggested outfit and accept or change it.

[1176] For example, if there is a special event the next day, the generative AI will suggest a set of shirt, pants, and shoes, and the user can review the suggestions and make any necessary changes in the application.

[1177] Distribution and sharing of goods

[1178] The server analyzes the frequency of use of items and allows users to lend or sell unused items to friends and family. The server analyzes the data on the frequency of use of items and provides users with a list of unused items. Users can submit requests for lending or selling items through the application.

[1179] For example, if a user has a shirt they haven't worn in a few months, they can send a request in the app to lend it to a friend. The server manages the request and notifies the user when the loan is complete.

[1180] Goods delivery management

[1181] Once the user has decided on the outfit they want to wear the next day, the server arranges for the items to be delivered. The user submits a delivery request through the app, and the server works with the logistics service to arrange for the items to be shipped from the warehouse.

[1182] In addition, the server tracks the delivery status in real time and notifies the user when the item arrives at the parcel locker, where the user can check the status and collect the item through the app.

[1183] For example, the shirt and pants that the user has selected for the next day's outfit will be delivered to the delivery locker the next morning, and the user can receive and wear them as is.

[1184] As described above, the system of the present invention supports the management and efficient use of items, and provides functions for making the most of a user's time and space.

[1185] The processing flow will be explained below.

[1186] Product registration

[1187] Step 1:

[1188] User: Activates the smartphone camera and takes a photo of the new item.

[1189] Step 2:

[1190] User: Opens the smartphone app and enters basic information such as "brand name," "color," and "size" along with a photo.

[1191] Step 3:

[1192] Terminal: Sends the entered information and photos to the server.

[1193] Step 4:

[1194] Server: Analyzes the received product information and generates a unique ID.

[1195] Step 5:

[1196] Server: Attaches digital tags to items and stores that information in a database.

[1197] Management of goods

[1198] Step 1:

[1199] Server: Regularly updates the product database to maintain consistency of information.

[1200] Step 2:

[1201] User: Uses the app to search for a specific item, for example, by entering the keyword "red shirt."

[1202] Step 3:

[1203] Server: Searches the database for relevant product information and sends the results to the terminal.

[1204] Step 4:

[1205] Terminal: Displays search results to the user.

[1206] Product suggestions

[1207] Step 1:

[1208] Server: Uses generative AI to analyze users' past usage data and preferences.

[1209] Step 2:

[1210] Server: Generates suggestions for the next day's outfit, taking into account the combination of items.

[1211] Step 3:

[1212] Server: Notifies the user's terminal of the generated proposal.

[1213] Step 4:

[1214] Device: The user reviews the suggestions and makes changes to the outfit if necessary.

[1215] Distribution and sharing of goods

[1216] Step 1:

[1217] Server: Analyzes the item usage frequency data and generates a list of unused items.

[1218] Step 2:

[1219] Users: Use the application to request loans or sales of unused items to friends and family.

[1220] Step 3:

[1221] Server: Manages rental and sales requests and tracks the necessary transactions.

[1222] Step 4:

[1223] Server: Sends notification to the user when the transaction is complete.

[1224] Goods delivery management

[1225] Step 1:

[1226] User: Uses the app to request delivery of the outfit they want to wear the next day.

[1227] Step 2:

[1228] Server: Works with logistics services to arrange delivery and ship items from the warehouse.

[1229] Step 3:

[1230] Server: Tracks the delivery status of goods and updates the information in real time.

[1231] Step 4:

[1232] Server: When the item arrives at the delivery locker, it sends a notification to the user.

[1233] Step 5:

[1234] User: Check delivery status and receive items in the app.

[1235] Through these steps, the system efficiently executes a series of processes from product registration to management, proposal, distribution, and delivery management, thereby significantly improving users' lives.

[1236] Example 1

[1237] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1238] Conventional item management systems make it difficult for users to efficiently register, manage, and use the items they purchase. They also lack advanced support, such as managing the circulation and lending of unused items, or suggesting outfits based on the user's preferences and past usage history. Furthermore, arranging delivery of items and tracking their status places a heavy burden on the user. The present invention aims to solve these problems and improve the quality of life for users.

[1239] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1240] In this invention, the server includes means for acquiring images of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique identifiers and assigning digital tags, means for saving the item information in data storage, means for periodically updating the item database and maintaining information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on the user's past usage data and personal preferences, means for analyzing item usage frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, and means for tracking and notifying delivery status. This allows users to centrally register, manage, use, distribute, and deliver items.

[1241] "Goods" are any tangible goods or items that are the subject of management and that a User possesses, uses, or distributes.

[1242] "Image capture" is the process of taking a photograph or video of an item using an electronic device.

[1243] "Basic information" refers to data necessary to identify and specify an item, and includes attributes such as brand name, color, and size.

[1244] A "server" is a remote computer system that processes information and stores data.

[1245] "Transmission" is the act of transferring data or information from one place to another.

[1246] "Analysis" is the process of analyzing received data to extract useful information.

[1247] A "unique identifier" is a specific number or code assigned to each item to uniquely identify it.

[1248] A "digital tag" is an electronic tag or label associated with an item that contains information in digital form.

[1249] "Data storage" is a physical or virtual location or device for storing information.

[1250] A "database" is an information system that systematically organizes a large amount of data and allows efficient access using queries.

[1251] "Integrity" refers to data that is accurate, consistent, and not altered or corrupted.

[1252] "Searching" is the act of searching a database or information system to find specific data.

[1253] A "suggestion" is a recommendation or recommendation made based on the results of the analysis.

[1254] "Notifications" are messages or alerts that inform users of important information.

[1255] "Frequency of use" is an index that indicates how often an item is used.

[1256] A "request" is a request or application to ask for something.

[1257] "Logistics services" are businesses or companies that manage and execute the transportation and delivery of goods.

[1258] "Tracking" is the process of monitoring and recording the location and condition of an item in real time.

[1259] This invention is a system for supporting the management and efficient use of goods, with the aim of improving the quality of life of users. This system can perform everything from product registration to management, distribution, and delivery in an integrated manner.

[1260] 1. Registration of goods

[1261] Users take a photo of a newly purchased item using a smartphone or other device. Next, they enter basic information about the item, such as its brand name, color, and size, through an application. The device then sends this information to a server. The server analyzes the received information, generates a unique identifier for the item, and assigns a digital tag to it. The item information is then stored in data storage.

[1262] 2. Management of items

[1263] After the product information is registered, the server periodically updates the product database to maintain the integrity of the information. When a user searches for a specific product using the application, the device sends the search keywords to the server, which then extracts the corresponding product information from the database, returns it to the device, and displays it to the user.

[1264] 3. Product Proposals

[1265] The server uses the generative AI model to analyze the user's past usage data and personal preferences. Based on this, the server generates outfit suggestions for the next day and notifies the user's device. For example, if there is a special event the next day, the generative AI will suggest a set of shirt, pants, and shoes. The user can review the suggestions in the app and make changes as needed.

[1266] 4. Distribution and sharing of goods

[1267] The server analyzes the usage frequency data of the items and identifies unused items. Users can then send requests to lend or sell items to relatives or acquaintances through the application. The server manages the requests and notifies the user when the lending or sale is completed.

[1268] 5. Goods delivery management

[1269] Users use the app to request delivery of the clothes they will wear the next day. The server works with the logistics service to arrange for the items to be shipped from the warehouse and tracks the delivery status in real time. Once the items arrive at the delivery locker, the server sends a notification to the user, who can then check the status on the app and collect the items.

[1270] This system is realized using various hardware and software. Specifically, devices such as smartphones and tablets are used, and an application acts as the interface between the user and the system. The server is equipped with software with advanced data analysis capabilities and a generative AI model.

[1271] Examples of concrete examples and prompts

[1272] 1. If a user buys a new red shirt, they take a photo with their smartphone and enter "Brand: ABC," "Color: Red," and "Size: M" into the app and submit it. The server analyzes the information, generates a unique identifier and digital tag, and stores them in a database.

[1273] Example prompt: "Please register for a new red ABC brand medium shirt."

[1274] 2. When a user searches for "red shirt," the server retrieves the relevant information from the database and sends it to the terminal, where the user can view the results.

[1275] Example prompt: "Search the database for red shirts and display a list."

[1276] 3. The day before a special event, the generative AI will suggest a set of shirts, pants, and shoes, and the user can review the suggestions in the app and make changes as needed.

[1277] Example prompt: "Please give me some outfit suggestions for tomorrow's special event."

[1278] Thus, the present invention is a multifunctional system that makes users' item management more efficient and improves their quality of life.

[1279] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1280] Product registration

[1281] Step 1:

[1282] The user takes a photo of the newly purchased item with their smartphone or device. The input is the image of the item, and the output is the captured image file.

[1283] Specific behavior: The user activates the smartphone camera and takes a photo of the red shirt. The image file is saved to the device.

[1284] Step 2:

[1285] The user launches the application and inputs a photograph of the item along with basic information such as the brand name, color, size, etc. The input is the item image and text data of the basic information, and the output is a transmission package containing this data.

[1286] Specific behavior: The user enters "Brand name: ABC", "Color: Red", and "Size: M" into the app, selects a photo, and presses the send button.

[1287] Step 3:

[1288] The terminal sends the entered information and photos to the server. The input is the transmission package, and the output is the data that arrives at the server.

[1289] Specific operation: The transmission package created by the terminal is sent to the server via the Internet.

[1290] Step 4:

[1291] The server analyzes the received photos and item information. The input is the received data, and the output is the analysis result data.

[1292] Specific operation: The server analyzes the photo using an image analysis algorithm and extracts information such as "red," "shirt," and "brand: ABC."

[1293] Step 5:

[1294] The server generates a unique identifier for the item based on the analysis results and assigns a digital tag to it. The input is the analysis results, and the output is the unique identifier and item information with the digital tag.

[1295] Specific operation: The server generates a unique ID (e.g., 123456), uses it to create a digital tag, and links it to the item information.

[1296] Step 6:

[1297] The server stores the product information in a data storage. The input is the product information with the digital tag, and the output is the data stored in the data storage.

[1298] Specific operation: The server writes the generated product information to the database.

[1299] Management of goods

[1300] Step 7:

[1301] The server periodically updates the product database to maintain consistency of information. The input is the existing product information, and the output is the updated database information.

[1302] Specific operation: The server runs an automatic script to check for updates to product information and update the database if necessary.

[1303] Step 8:

[1304] A user searches for a specific item within an application. The input is the search keyword, and the output is the search result data.

[1305] Specific behavior: The user types "red shirt" into the app's search box and presses the search button.

[1306] Step 9:

[1307] The terminal sends search keywords to the server. The input is the search keywords, and the output is the data sent to the server.

[1308] Specific operation: The device sends the search keywords to the server via the Internet.

[1309] Step 10:

[1310] The server extracts the relevant product information from the database and sends it to the terminal. The input is the search keyword, and the output is the search result data.

[1311] Specific operation: The server extracts data corresponding to "red shirt" from the database and sends it to the terminal.

[1312] Step 11:

[1313] The terminal displays the search results to the user. The input is the search result data, and the output is the information displayed to the user.

[1314] Specific operation: The device displays the search results on the app's display screen, and the user confirms them.

[1315] Product suggestions

[1316] Step 12:

[1317] The server uses the generated AI model to analyze the user's past usage data and personal preferences. The input is the past usage data, and the output is the analysis results.

[1318] Specific operation: The server launches the generative AI, inputs the user's past data (e.g., frequently worn colors and styles), and performs analysis.

[1319] Step 13:

[1320] The server generates the next day's outfit combination based on the analysis results. The input is the analysis results, and the output is the suggested outfit data.

[1321] Specific operation: The generative AI model proposes a set of "shirt, pants, shoes" and saves it as data.

[1322] Step 14:

[1323] The server notifies the user's terminal of the generated proposal. The input is the proposal data, and the output is the notification sent to the user's terminal.

[1324] Specific operation: The server sends the proposal to the device, and the device notifies the user, "This set is recommended for tomorrow's event."

[1325] Distribution and sharing of goods

[1326] Step 15:

[1327] The server analyzes the usage frequency data of the items and identifies unused items. The input is the usage frequency data, and the output is a list of unused items.

[1328] Specific operation: The server lists items that have not been used for a certain period of time and saves them as suggestions.

[1329] Step 16:

[1330] A user submits a rental or sale request through the application. The input is the request data and the output is the request sent to the server.

[1331] What happens: A user sends a request in the app to "lend a shirt to a friend."

[1332] Step 17:

[1333] The server manages the requests and notifies the user when the loan or sale is completed. The input is the request data and the output is the notification sent to the user.

[1334] What happens next: The server processes the request and sends a notification to the user saying, "Your shirt has been checked out."

[1335] Goods delivery management

[1336] Step 18:

[1337] A user uses the application to request delivery of the clothes they will wear the next day. The input is the delivery request data, and the output is the delivery request sent to the server.

[1338] Specific behavior: A user requests delivery of a shirt and pants to wear the next day through the app.

[1339] Step 19:

[1340] The server works with the logistics service to process the shipment of goods from the warehouse. The input is the delivery request data, and the output is the shipping instruction sent to the logistics service.

[1341] Specific operation: The server communicates with the logistics service and starts the shipping procedure for the item.

[1342] Step 20:

[1343] The server tracks the delivery status in real time and sends a notification to the user once the item arrives at the parcel locker. The input is the real-time delivery status data and the output is the notification sent to the user.

[1344] Specific behavior: The server tracks the delivery status of the items and sends a notification to the user saying, "The shirt and pants have arrived at the delivery locker."

[1345] (Application example 1)

[1346] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1347] Conventional closet management systems have the drawback of being time-consuming and inefficient, as registering and managing items is done manually. Furthermore, outfit suggestions based on user preferences and past usage data are often inappropriate, potentially reducing user satisfaction. Furthermore, managing requests for item rentals and sales is complicated, and delivery status tracking and notifications are not provided in real time, resulting in a lack of an improved user experience.

[1348] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1349] In this invention, the server includes means for taking photos of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique IDs, and assigning digital tags, means for saving the item information in a database, means for periodically updating the item database and maintaining information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on a user's past use data and preferences, means for analyzing item use frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, means for tracking and notifying delivery status, means for automatically registering items purchased by a user in cooperation with an online shopping site, and means for using a generation AI to suggest outfits based on a user's purchase history and preferences. This enables efficient item registration and management, accurate outfit suggestions based on a user's preferences and past data, and seamless management of item rental, sales, and delivery.

[1350] "Means for taking a photo of an item and entering basic information" refers to a device or interface that allows a user to take a picture of an item they own and enter basic information about that item (e.g., brand name, color, size, etc.).

[1351] "Means for transmitting information about an item to a server" refers to the communications infrastructure and protocols for transmitting the photographed image of the item and the input information to a central server.

[1352] "Means for analyzing item information, generating a unique ID, and assigning a digital tag" refers to algorithms or software that analyzes the transmitted item information and generates and assigns a unique identification number (ID) to the item.

[1353] The "means for storing product information in a database" refers to a system or procedure for storing the generated product information and unique ID in a database.

[1354] "Means for regularly updating the product database and maintaining the integrity of the information" means the mechanisms or protocols for periodically checking the information in the database to ensure that it accurately reflects new or changed information.

[1355] "Means for searching for specific items and means for displaying search results" refers to the search function that a user uses to find a specific item and the interface or method for visually displaying the results to the user.

[1356] "Means for generating and notifying clothing suggestions based on the user's past usage data and preferences" refers to a system or algorithm that analyzes the user's past behavioral data and preference trends, suggests clothing suitable for the user, and notifies the user of those suggestions.

[1357] "Means for analyzing item usage frequency data and identifying unused items" refers to technologies and methods for analyzing how frequently items are used and identifying items that have not been used for a long period of time.

[1358] A "means for managing rental and sale requests" is software or a process for accepting, tracking, and managing requests from users to rent or sell items.

[1359] The "means for arranging delivery of goods in cooperation with a logistics service" refers to an interface or system for efficiently arranging delivery of goods in cooperation with an external logistics service provider.

[1360] "Means for tracking and notifying delivery status" refers to technologies and means for monitoring the delivery status of goods in real time and providing that information to users.

[1361] "Means for linking with online shopping sites and automatically registering items purchased by users in the system" refers to a mechanism for integrating with online shopping platforms and automatically adding items purchased by users to the closet system.

[1362] "Means of using generative AI to suggest clothing based on a user's purchasing history and preferences" refers to algorithms and systems that utilize the latest artificial intelligence technology to suggest clothing based on a user's purchasing history and preferences.

[1363] The present invention provides a system for improving the efficiency of item management and user convenience. This system automates a series of processes, such as photographing items, registering information, saving data, proposing items, renting and selling items, and managing delivery. Specific embodiments are described below.

[1364] 1. Registration of goods

[1365] Using a device such as a smartphone, the user takes a photo of the item they have purchased and enters basic information such as brand name, color, and size. This information is sent from the device to a server. The server analyzes the received item information, generates a unique ID, and assigns it to the item. The item information with the digital tag attached is stored in a database. Hardware used includes devices such as smartphones and PCs, and software such as React Native, Node.js, Express, and MongoDB is used to send the item information.

[1366] 2. Management of items

[1367] The server periodically updates the database to maintain consistency of product information. When a user searches for a specific product, they enter a keyword through their device, and the server searches the database for the corresponding product and displays the results to the user. In this process, React Native is used as the search interface, and MongoDB is used for database search processing.

[1368] 3. Suggestion function

[1369] The server uses a generative AI model to suggest outfits for the next day based on the user's past usage data, purchase history, and preferences. The generated suggestions are sent to the user's device. OpenAI GPT-4 is used as the generative AI model. As a concrete example, the following prompt sentence is input to the generative AI model:

[1370] Suggest tomorrow's outfit based on the user's purchase history over the past six months, as well as their preferred colors and brands.

[1371] User Information:

[1372] Brand: [Luxury Brand A, Luxury Brand B]

[1373] Favorite colors: [red, blue]

[1374] Past purchase history: [Product ID 123, Product ID 456, Product ID 789]

[1375] Special Events: [None]

[1376] 4. Rental and sales

[1377] The server analyzes item usage frequency data and identifies items that have not been used for a long time. Based on this information, users can request to rent or sell items through the app. The server manages the requests and notifies the user when the request is completed. Node.js and MongoDB are used to manage rentals and sales.

[1378] 5. Delivery management

[1379] Once the user has decided on an outfit, the server connects with a logistics service to arrange delivery of the items. The delivery status is tracked in real time, and the user is notified when the item arrives at the parcel locker. Node.js is used to connect to an external logistics API to arrange delivery and track the status.

[1380] As described above, the system of the present invention seamlessly integrates the registration, management, proposal, rental, sale and delivery of goods, thereby greatly improving user convenience.

[1381] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1382] Step 1:

[1383] The user uses the device to take a photo of the item they purchased and enter basic information such as brand name, color, size, etc. This input information includes image data and text information of the item. This data is temporarily stored on the device.

[1384] Step 2:

[1385] The terminal sends the entered product information and image data to the server. At this time, an HTTP POST request is used to transfer form data including the product image data and metadata to the server. The input is the product information and image data provided by the user, and the output is stored on the server.

[1386] Step 3:

[1387] The server analyzes the received product information and generates a unique ID. This unique ID is used to uniquely identify the product information. In this process, the unique ID is generated using a UUID generation algorithm or similar. The input is the transmitted product information, and the output is the generated unique ID and product information.

[1388] Step 4:

[1389] The server assigns the generated unique ID to the item information and generates a digital tag. The digital tag is an important element for identifying the item and is expressed in the form of an RFID tag, barcode, etc. In this step, the algorithm for generating the digital tag runs. The input is item information with a unique ID, and the output is item information with a digital tag.

[1390] Step 5:

[1391] The server stores the item information with the digital tags in a database. The database used here is a NoSQL database such as MongoDB, and the data is stored in document format. The input is the item information with the digital tags, and the output is the item information stored in the database.

[1392] Step 6:

[1393] The server periodically updates the database to maintain consistency of the information. This process checks for duplicates and inconsistencies in the data, updating or deleting them as necessary. The input is the existing database, and the output is a consistent database.

[1394] Step 7:

[1395] When a user searches for a specific item, they enter keywords into their terminal and send a search request to the server. The server searches the database for the relevant item and returns the results to the terminal. The input is the keyword entered by the user, and the output is a list of search results.

[1396] Step 8:

[1397] The server uses a generative AI model to suggest an outfit for the next day based on the user's past usage data, purchase history, and preferences. This suggestion is sent to the user's device. The generative AI model used is OpenAI GPT-4. An example of a specific prompt is as follows:

[1398] Suggest tomorrow's outfit based on the user's purchase history over the past six months, as well as their preferred colors and brands.

[1399] User Information:

[1400] Brand: [Luxury Brand A, Luxury Brand B]

[1401] Favorite colors: [red, blue]

[1402] Past purchase history: [Product ID 123, Product ID 456, Product ID 789]

[1403] Special Events: [None]

[1404] The input is user data and the output is outfit suggestions.

[1405] Step 9:

[1406] The server analyzes the item usage frequency data and identifies items that have not been used for a long time. Based on this information, users can request to rent or sell items. The server manages the request and notifies the user when processing is complete. The input is the item usage frequency data, and the output is a list of unused items.

[1407] Step 10:

[1408] Once the user has decided on an outfit, the server works with the logistics service to arrange delivery of the items. This is done using a logistics API. The delivery status is tracked in real time, and the user is notified when the item arrives at the delivery locker. The input is the user's delivery request, and the output is a notification of the delivery status.

[1409] Through the above processing steps, the system of the present invention can efficiently register, manage, propose, rent, sell, and deliver products.

[1410] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1411] This invention relates to a 4D closet system that utilizes digital tags, generative AI, and an emotion engine. This system supports the management and efficient use of items, recognizes the user's emotional state, and provides functions to make the user's life more comfortable.

[1412] Product registration

[1413] First, we will explain the procedure for a user to register a newly purchased item in the system. The user takes a photo of the item using a smartphone or other device. Next, they enter information about the item through the application. Specific items include the brand name, color, and size.

[1414] The device sends the entered information and photo to a server, which analyzes the information and generates a unique ID for the item, attaches a digital tag to the item, and stores the information in a database.

[1415] Management of goods

[1416] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency. When a user searches for a specific item, the server retrieves the corresponding item information from the database via the terminal and displays it to the user.

[1417] For example, when a user searches for "black shirts," the server extracts information about the corresponding shirts based on the keywords and sends the results to the user's terminal.

[1418] Utilizing the Emotion Engine

[1419] The emotion engine captures the user's face with a camera and analyzes their emotional state in real time from facial expressions, voice, etc. The emotion data analyzed by the emotion engine is sent to the server. Based on the received emotion data, the server makes product recommendations that are best suited to the user's current situation.

[1420] For example, if a user is feeling stressed, the AI ​​can suggest clothing made of soft materials that will help them relax. The AI ​​takes this emotional data into account and optimizes the suggestions.

[1421] Product suggestions

[1422] Based on the user's preferences, past usage data, and emotional data obtained from the emotion engine, the generative AI suggests outfits for the next day. The server uses the generative AI to analyze the data and generate the optimal outfit combination. This suggestion is sent to the user's device, where the user can review the suggested outfit and accept or change it.

[1423] For example, if you have an important presentation the next day, the generative AI will suggest a formal shirt and slacks set, and you can review the suggestion and change to a more casual outfit if you feel like relaxing.

[1424] Distribution and sharing of goods

[1425] The server analyzes the frequency of use of items and allows users to lend or sell unused items to friends and family. The server analyzes the data on the frequency of use of items and provides users with a list of unused items. Users can submit requests for lending or selling items through the application.

[1426] For example, if a user has an unused shirt and wants to lend it to a friend, the server manages the request and notifies the user when the loan is complete.

[1427] Goods delivery management

[1428] Once the user has decided on the outfit they want to wear the next day, the server arranges for the items to be delivered. The user makes a delivery request through the app, and the server works with the logistics service to arrange for the items to be shipped from the warehouse.

[1429] In addition, the server tracks the delivery status in real time and notifies the user when the item arrives at the parcel locker, where the user can check the status and collect the item through the app.

[1430] For example, the shirt and pants that the user has selected for the next day's outfit will be delivered to the delivery locker the next morning, and the user can receive and wear them as is.

[1431] As described above, the system of the present invention utilizes digital tags, generative AI, and an emotion engine to support the management and efficient use of items, and by making suggestions that are optimal for the user's emotional state, can significantly improve the user's life.

[1432] The processing flow will be explained below.

[1433] Product registration

[1434] Step 1:

[1435] User: Activates the smartphone camera and takes a photo of the new item.

[1436] Step 2:

[1437] User: Opens the smartphone app and enters basic information such as "brand name," "color," and "size" along with a photo.

[1438] Step 3:

[1439] Terminal: Sends the entered information and photos to the server.

[1440] Step 4:

[1441] Server: Analyzes the received product information and generates a unique ID.

[1442] Step 5:

[1443] Server: Attaches digital tags to items and stores that information in a database.

[1444] Management of goods

[1445] Step 1:

[1446] Server: Regularly updates the product database to maintain consistency of information.

[1447] Step 2:

[1448] User: Uses the app to search for a specific item, for example, by entering the keyword "black shirt."

[1449] Step 3:

[1450] Server: Searches the database for relevant product information and sends the results to the terminal.

[1451] Step 4:

[1452] Terminal: Displays search results to the user.

[1453] Utilizing the Emotion Engine

[1454] Step 1:

[1455] User: Uses a smartphone or wearable device to capture facial expressions and voice via a camera and microphone.

[1456] Step 2:

[1457] Device: Captured facial expression and voice data is sent to the emotion engine.

[1458] Step 3:

[1459] Emotion engine: Analyzes the user's emotional state from facial expressions and voice.

[1460] Step 4:

[1461] Terminal: Transmits the analyzed emotion data to the server.

[1462] Step 5:

[1463] Server: Based on the received emotion data, it generates optimal product recommendations for the user.

[1464] Product suggestions

[1465] Step 1:

[1466] Server: Uses generative AI to comprehensively analyze users' past usage data, preferences, and emotional data.

[1467] Step 2:

[1468] Server: Generates suggestions for the next day's outfit, taking into account the combination of items.

[1469] Step 3:

[1470] Server: Notifies the user's terminal of the generated proposal.

[1471] Step 4:

[1472] Device: The user reviews the suggestions and makes changes to the outfit if necessary.

[1473] Distribution and sharing of goods

[1474] Step 1:

[1475] Server: Analyzes the item usage frequency data and generates a list of unused items.

[1476] Step 2:

[1477] Users: Use the application to request loans or sales of unused items to friends and family.

[1478] Step 3:

[1479] Server: Manages rental and sales requests and tracks the necessary transactions.

[1480] Step 4:

[1481] Server: Sends notification to the user when the transaction is complete.

[1482] Goods delivery management

[1483] Step 1:

[1484] User: Uses the app to request delivery of the outfit they want to wear the next day.

[1485] Step 2:

[1486] Server: Works with logistics services to arrange delivery and ship items from the warehouse.

[1487] Step 3:

[1488] Server: Tracks the delivery status of goods and updates the information in real time.

[1489] Step 4:

[1490] Server: When the item arrives at the delivery locker, it sends a notification to the user.

[1491] Step 5:

[1492] User: Check delivery status and receive items in the app.

[1493] Through these steps, the system efficiently executes a series of processes, from product registration and management, to proposals, distribution, and delivery management, thereby significantly improving users' lives. Furthermore, the use of an emotion engine enables optimal proposals based on the user's emotional state, improving user satisfaction.

[1494] Example 2

[1495] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1496] Conventional item management systems require users to spend a lot of time managing item details and are unable to provide suggestions that take into account their emotional state. Furthermore, they lack mechanisms for efficiently managing the frequency of use of items and effectively utilizing unused items. Therefore, there is a need for a system that can efficiently manage items and provide suggestions that are optimal for the user's emotional state.

[1497] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1498] In this invention, the server includes a means for periodically updating the product database and maintaining consistency of information, a means for searching for specific products and displaying search results, and a means for providing an emotion engine for analyzing the user's emotions and making suggestions based on the emotions, thereby enabling the management and effective use of products while making suggestions that take into account the user's emotional state.

[1499] An "item" is an item that is owned and managed by a user.

[1500] "Means for taking photographs" refers to a method of obtaining an image of an item using a device such as a camera or smartphone.

[1501] The "means for inputting basic information" refers to a method by which a user inputs detailed information about an item (such as brand name, color, size, etc.) through an application.

[1502] A "server" is a computer system that exists in the cloud or within a local network and stores, analyzes, and communicates data.

[1503] The "means for analyzing product information" is a method for analyzing product-related data within the server and performing classification and feature extraction.

[1504] The "means for generating a unique ID" is a method for generating a unique identifier for each item, making the item identifiable.

[1505] A "digital tagging means" is a method for electronically tagging information related to an item.

[1506] The "means for storing in the database" refers to a storage device for permanently storing product information and software for managing it.

[1507] "Means for regularly updating the product database" refers to a method for adding or amending new or changed information to the database to keep the information up to date.

[1508] The "means for displaying search results" is a method for displaying on the screen information about items obtained based on the search conditions entered by the user.

[1509] The "emotion engine" is a system that analyzes the user's emotions using input devices such as a camera or microphone, and makes appropriate suggestions based on the results.

[1510] The "means for analyzing usage frequency data" is a method for analyzing the usage history and frequency of an item and promoting effective use of the item.

[1511] A "means for managing rental and sales requests" is a method for accepting and processing requests from users and taking action as necessary.

[1512] "Means for linking with logistics services" refers to methods for communicating with external delivery companies and warehouse management systems to manage logistics processes.

[1513] "Means for tracking delivery status" refers to a method for monitoring the delivery status of an item in real time and notifying the user.

[1514] "Means of notification" refers to a method for sending information from the system to the user and encouraging them to take necessary action.

[1515] This invention relates to a 4D closet system that streamlines item management and makes optimal suggestions based on the user's emotional state. By utilizing digital tags, generative AI, and an emotion engine, this system analyzes item management and usage frequency, providing functions to make the user's life more comfortable.

[1516] Product registration

[1517] Users take a photo of their newly purchased item using a device such as a smartphone or tablet. After taking the photo, they enter information about the item, such as the brand name, color, and size, through an application. The entered information and photo are sent from the device to a server. The server analyzes the received information, generates a unique ID for the item, and assigns a digital tag. This information is then stored in a database.

[1518] Specific example of operation: When a user purchases a blue shirt, enters the information into the app, takes a photo, and sends it, the server assigns a unique ID to the blue shirt and sets a digital tag.

[1519] Management of goods

[1520] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency of the information. When searching for a specific item, the server extracts relevant item information based on the search keywords and sends the results to the user's device for display.

[1521] Specific example of operation: When a user searches for "black shirt" or "blue skirt," the server sends information about the corresponding items to the terminal and displays it.

[1522] Utilizing the Emotion Engine

[1523] The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice, and evaluates their emotional state in real time. The analyzed emotion data is sent to the server via the device. Based on this, the server makes product recommendations that are best suited to the user's current situation.

[1524] Specific example of operation: If the emotion engine analyzes that the user is feeling stressed, the server will suggest clothing made of soft materials that will help them relax.

[1525] Product suggestions

[1526] The server uses AI to analyze the user's preferences, past usage data, and emotional data to generate the optimal outfit combination. This suggestion is sent to the user's device, where the user can review it and accept or change it.

[1527] Example of how it works: If you have an important presentation the next day, the server will use generative AI to suggest a formal shirt and slacks set. If you're feeling more relaxed, you can also change to casual clothing.

[1528] Example prompts: "Suggest some outfits using a blue shirt.", "What outfits would help users relax when they're feeling stressed?"

[1529] The above is a specific embodiment of the present invention, which allows the user to receive recommendations for items that match their emotional state and preferences, and also allows for efficient item management.

[1530] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1531] Step 1:

[1532] A user uses a device such as a smartphone or tablet to take a photo of an item and enter basic information such as brand name, color, and size through an application. The input consists of manual input by the user and the photo taken. The device then sends this information and the photo to a server. The server analyzes the received information and generates a unique ID for the item. Specifically, the server uses an image analysis algorithm to extract the item's features from the photo and associates them with the basic information.

[1533] Input: Photo of the item, basic information entered by the user

[1534] Output: Analyzed product information, generation of unique ID

[1535] Step 2:

[1536] After the unique ID is generated for the item, the server assigns a digital tag to the item, which is used to facilitate item identification and tracking. The server associates the generated unique ID with the digital tag and stores it in a database.

[1537] Input: Unique ID, item analysis information

[1538] Output: Digital tag, stored in database

[1539] Step 3:

[1540] The server periodically updates the product database to maintain consistency. According to a set schedule, the server updates the database with newly added or modified product information. Specifically, the server performs a comparison between the clone data and the new data.

[1541] Input: New or modified item information

[1542] Output: Updated database

[1543] Step 4:

[1544] When a user searches for a specific item, they input search keywords using a terminal. The server receives this search request and extracts the relevant item information from the database. The server then sends the extracted results to the terminal, which then displays the search results to the user.

[1545] Input: Search keyword (from user)

[1546] Output: Search results (from server to device)

[1547] Step 5:

[1548] The device uses a camera and microphone to capture the user's facial expressions and voice, and sends this data to the emotion engine for real-time analysis. The emotion engine analyzes the user's emotional state from this input data and sends the data to the server. The server then uses the received emotion data to suggest the most suitable products for the user.

[1549] Input: User's facial expression and voice data

[1550] Output: Parsed emotion data

[1551] Step 6:

[1552] The server uses AI to analyze the user's past usage data, preferences, and emotional data. Based on the results of this analysis, the server generates suggestions for the user on what outfit to wear the next day. The suggestions are then sent to the user's device.

[1553] Input: Historical usage data, preferences, emotional data

[1554] Output: Outfit suggestions (from the generation AI to the device)

[1555] Step 7:

[1556] The server analyzes the usage frequency data of the items and generates a list of unused items. This list is sent to the terminal, and the user can check for missing items, lend them to a friend, or send a request to sell them. The server manages these requests and efficiently distributes the items.

[1557] Input: Frequency of use data

[1558] Output: List of unused items, management of sales and lending requests

[1559] Step 8:

[1560] When the user decides what to wear the next day, the device sends a delivery request to the server, which then coordinates with the logistics service to arrange for the item to be shipped from the warehouse. The server then tracks the delivery status in real time and notifies the user when the item arrives at the designated location.

[1561] Input: Delivery request (from user)

[1562] Output: Delivery status tracking and notification (from server to terminal)

[1563] (Application example 2)

[1564] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1565] In recent years, improving the efficiency of inventory management and user satisfaction at logistics centers have become important issues. However, conventional systems have been inadequate in managing inventory and proposing products that take customer sentiment into consideration. As a result, it has become difficult to address inventory overages and shortages, and to make personalized proposals based on customer preferences, resulting in a decline in overall operational efficiency and customer satisfaction. The present invention aims to solve these issues, enabling logistics centers to provide more efficient and personalized services.

[1566] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1567] In this invention, the server includes means for taking photos of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique IDs and assigning digital tags, means for saving the item information in a database, means for periodically updating the item database to maintain information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on a user's past usage data and preferences, means for analyzing item usage frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, means for tracking and notifying delivery status, means for using an emotion analysis engine to analyze emotions and suggest products that match the customer's mood, and means for analyzing item distribution data and customer emotion data and generating reports. This enables more efficient item management in logistics centers and personalized product suggestions based on customer emotions.

[1568] "Goods" is a general term that refers to various types of products, merchandise, packages, etc.

[1569] "Taking a photo" means acquiring image data using the camera function of a digital camera, smartphone, etc.

[1570] "Basic information" refers to basic and necessary information about an item, including, for example, "brand name," "color," and "size."

[1571] "Server" refers to a combination of hardware and software for storing, processing, and managing data.

[1572] A "unique ID" is a special identifier assigned to an item, data, etc. to uniquely identify it.

[1573] A "digital tag" is an electronic label or mark attached to an item that contains information including a unique ID.

[1574] A "database" is a system for effectively storing, searching, and managing various data.

[1575] "Information integrity" refers to keeping data accurate and consistent.

[1576] "Searching" is the act of finding specific information from a database.

[1577] "Search results" are a collection of data or information obtained through a search.

[1578] "Past usage data" is historical information about goods and services that a user has previously used.

[1579] "Preferences" refers to the user's personal tastes and preferences.

[1580] A "suggestion" is the act of recommending specific information or choices to a user.

[1581] "Notification" refers to an act or message that informs a user of specific information.

[1582] "Frequency of use data" is information on how often an item is used.

[1583] "Renting" means the act of letting someone else use an item temporarily.

[1584] "Sales Request" means a request or desire to purchase an item.

[1585] "Logistics services" refers to all services such as transporting, storing, and delivering goods.

[1586] "Delivery status" is information that indicates the stage at which an item is in the delivery process.

[1587] An "emotion analysis engine" is software or a system that analyzes human emotions based on data such as voice and images.

[1588] "Distribution data" is data about how an item is distributed.

[1589] "Data analysis" is the act of examining data in detail to find specific patterns and trends.

[1590] "Report generation" refers to the act of creating a report based on analysis results and statistical information.

[1591] "Generative AI" refers to artificial intelligence that makes optimal suggestions and predictions based on user data and behavioral patterns.

[1592] The present invention implements a "smart management application" that improves the efficiency of goods management in logistics centers and provides personalized product proposals to customers. This system is configured by combining the following hardware and software.

[1593] 1. A way to take a photo of an item and enter basic information

[1594] Hardware: Smartphones and tablets

[1595] Software: Camera application and data entry application

[1596] When a new item arrives at a distribution center, staff use their smartphones or tablets to take a photo of the item and enter basic information such as brand name and size, which is then sent to a server.

[1597] 2. Means for sending product information to the server

[1598] Hardware: Smartphones and tablets

[1599] Software: Data transmission application

[1600] The acquired item information is sent from the smartphone or tablet to a server, which analyzes the information, generates a unique ID, and assigns a digital tag to the item.

[1601] 3. A method for analyzing product information, generating unique IDs, and assigning digital tags

[1602] Software: Unique ID generation algorithm and digital tagging system

[1603] The analyzed product information is used to generate a unique ID on the server, and a digital tag is assigned to the product. This information is then stored in a database.

[1604] 4. A means of storing product information in a database

[1605] Hardware: Cloud Server

[1606] Software: Database management system (e.g., MySQL, Firebase)

[1607] The item information with the digital tag is stored in a database on a cloud server.

[1608] 5. A method for regularly updating the product database and maintaining the integrity of the information

[1609] Software: Data Update Algorithm

[1610] The server periodically updates the information in the database to ensure that the data remains consistent.

[1611] 6. A means of searching for specific items and displaying search results

[1612] Software: Product search application

[1613] When a staff member is looking for a specific item, the item search application is used to search the database for the relevant item information and display the results.

[1614] 7. A means to generate and notify clothing suggestions based on the user's past usage data and preferences

[1615] Software: Generative AI (e.g., PyTorch, TensorFlow)

[1616] The generative AI generates optimal clothing and item suggestions based on the user's past usage data and preferences, and notifies them on the smartphone or tablet.

[1617] 8. A method for analyzing data on the frequency of use of items and identifying unused items

[1618] Software: Data analysis system

[1619] The server analyzes data on how frequently items are used and identifies unused items.

[1620] 9. A way to manage rental and sales requests

[1621] Software: Request Management Application

[1622] Users can rent out unused items or send sales requests, and the server manages this.

[1623] 10. Means of coordinating with logistics services to arrange delivery of goods

[1624] Software: Delivery Management System

[1625] The server works in conjunction with the logistics service to smoothly arrange for the delivery of goods.

[1626] 11. Means of tracking and notification of delivery status

[1627] Software: Shipping Tracking System

[1628] Track the status of your items in real time when they are delivered and notify the user.

[1629] 12. Using an emotion analysis engine to analyze emotions and suggest products that match the customer's mood

[1630] Software: Sentiment analysis engine (e.g., Azure Cognitive Services, Google Cloud AI)

[1631] An emotion analysis engine analyzes the customer's facial expressions and voice, and generative AI suggests products that match the customer's mood.

[1632] 13. Data analysis and report generation tools for analyzing product distribution data and customer sentiment data

[1633] Software: Data analysis tools

[1634] Conduct detailed analysis of product distribution data and customer sentiment data to generate monthly reports.

[1635] Examples:

[1636] For example, when a customer places an order, an emotion analysis engine analyzes their facial expressions via their smartphone camera. If the customer appears stressed, the generative AI will suggest products that will help them relax. Furthermore, this analysis, along with product distribution data, will identify overstocks and shortages, improving operational efficiency.

[1637] Example prompt sentence:

[1638] "We use photos of customers' faces and voice data to analyze their emotions in real time. Based on the analysis results, we suggest products that match the customer's mood. For example, if a customer is feeling stressed, we suggest products that will help them relax (such as aroma candles). How can we build the optimal generative model?"

[1639] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1640] Step 1:

[1641] Users take a photo of the item using a smartphone or tablet and enter basic information such as the brand name and size.

[1642] Input: Basic information such as item image, brand name, size, etc.

[1643] Output: Photos and basic information are saved within the application.

[1644] Specific operations: Upload a photo of the item you have taken to the application and enter basic information using the text input fields in the application.

[1645] Step 2:

[1646] The terminal transmits the acquired product information to the server.

[1647] Input: Item information (basic information such as photo, brand name, size, etc.).

[1648] Output: The item information is sent to the server.

[1649] Specific operation: Press the "Send" button in the application to send information to the server via the data transmission protocol.

[1650] Step 3:

[1651] The server analyzes the received item information, generates a unique ID, and assigns a digital tag.

[1652] Input: Item information (basic information such as photo, brand name, size, etc.).

[1653] Output: A unique ID and a digital tag are generated.

[1654] Specific operations: Analyzes item information, generates a unique identifier (unique ID), and executes an algorithm to assign that ID as a digital tag.

[1655] Step 4:

[1656] The server stores the generated unique ID and digital tag in a database along with the item information.

[1657] Input: Item information, unique ID and digital tag.

[1658] Output: Item information, unique ID and digital tag stored in a database.

[1659] Specific operation: Store the item information, generated unique ID and digital tag in a database using SQL queries, etc.

[1660] Step 5:

[1661] The server periodically updates the product database to maintain consistency of the information.

[1662] Input: Product information in the database.

[1663] Output: Updated item information in the database.

[1664] Specific operation: Using a database management system (DBMS), the scheduler periodically updates information and checks its consistency.

[1665] Step 6:

[1666] Users use a search application on their smartphone or tablet to search for a specific item and view the search results.

[1667] Input: Search keyword (e.g. black shirt).

[1668] Output: Product information displayed as search results.

[1669] Specific operation: Send a search query to the database, retrieve and display the corresponding item information.

[1670] Step 7:

[1671] The server uses generative AI to generate and notify the user of clothing suggestions based on their past usage data and preferences.

[1672] Input: User's past usage data, user preferences.

[1673] Output: Suggested outfit combinations.

[1674] Specific operation: Based on past usage data and user preferences, a generative AI model is used to generate optimal suggestions and notify the user's device.

[1675] Step 8:

[1676] The server analyzes data on how often items are used and identifies unused items.

[1677] Input: Frequency of use data for items.

[1678] Output: A list of unused items.

[1679] Specific operation: Analyzes usage frequency data using a data analysis algorithm and lists unused items.

[1680] Step 9:

[1681] Users send requests to rent or sell unused items through the application, and the server manages them.

[1682] Input: A rental or sale request.

[1683] Output: Management information for the request.

[1684] Specific operation: The user sends a request through the application interface, and the server records and manages it in a database.

[1685] Step 10:

[1686] The server coordinates with the logistics service to arrange delivery of the goods.

[1687] Input: Request for delivery arrangement.

[1688] Output: Notification of completion of delivery arrangements.

[1689] Specific operation: Uses the logistics service API to arrange delivery and track delivery status.

[1690] Step 11:

[1691] The server tracks the delivery status and notifies the user.

[1692] Input: Delivery status information.

[1693] Output: Delivery status notification.

[1694] Specific behavior: Tracks delivery information in real time and automatically notifies users when there is a status change.

[1695] Step 12:

[1696] The emotion analysis engine analyzes the customer's facial expressions and voice, and the server uses generative AI to suggest products that match the customer's mood.

[1697] Input: Customer facial expressions, voice data, and past usage data.

[1698] Output: Product suggestions that match the customer's mood.

[1699] Specific operation: Facial expressions and voice data are captured using the smartphone's camera and microphone, and analyzed by an emotion analysis engine. Based on this data, the generative AI makes optimal product suggestions.

[1700] Step 13:

[1701] The server analyzes product distribution data and customer sentiment data and generates monthly reports.

[1702] Input: Goods distribution data, customer sentiment data.

[1703] Output: Monthly report.

[1704] Specific actions: Use data analysis tools to perform detailed analysis of distribution data and sentiment data and generate visualized monthly reports.

[1705] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1706] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1707] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1708] [Fourth embodiment]

[1709] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1710] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1711] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1712] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1713] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1714] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1715] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1716] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1717] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1718] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1719] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1720] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1721] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1722] This invention relates to a 4D closet system that utilizes digital tags and generative AI. This system supports the management and efficient use of items and provides the following key functions to improve users' lives:

[1723] Product registration

[1724] First, we will explain the procedure for a user to register a newly purchased item in the system. The user takes a photo of the item using a smartphone or other device and enters the item information through the application. Specific items include the brand name, color, and size.

[1725] The device then sends the captured photo and the entered information to a server, which analyzes the information and generates a unique ID for the item, assigns a digital tag to the item, and stores the item information in a database.

[1726] Management of goods

[1727] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency of the information. When a user searches for a specific item, the server retrieves the corresponding item information from the database via the terminal and displays it to the user.

[1728] For example, when a user searches for "red shirt," the server extracts information about the corresponding shirt based on the keyword and sends the results to the user's terminal.

[1729] Product suggestions

[1730] Based on the user's preferences and past usage data, the AI ​​generator will suggest the outfit they would like to wear the next day. The server will use the AI ​​generator to analyze the user's past data and generate outfit combinations. This suggestion will be sent to the user's device, and the user can review the suggested outfit and accept or change it.

[1731] For example, if there is a special event the next day, the generative AI will suggest a set of shirt, pants, and shoes, and the user can review the suggestions and make any necessary changes in the application.

[1732] Distribution and sharing of goods

[1733] The server analyzes the frequency of use of items and allows users to lend or sell unused items to friends and family. The server analyzes the data on the frequency of use of items and provides users with a list of unused items. Users can submit requests for lending or selling items through the application.

[1734] For example, if a user has a shirt they haven't worn in a few months, they can send a request in the app to lend it to a friend. The server manages the request and notifies the user when the loan is complete.

[1735] Goods delivery management

[1736] Once the user has decided on the outfit they want to wear the next day, the server arranges for the items to be delivered. The user submits a delivery request through the app, and the server works with the logistics service to arrange for the items to be shipped from the warehouse.

[1737] In addition, the server tracks the delivery status in real time and notifies the user when the item arrives at the parcel locker, where the user can check the status and collect the item through the app.

[1738] For example, the shirt and pants that the user has selected for the next day's outfit will be delivered to the delivery locker the next morning, and the user can receive and wear them as is.

[1739] As described above, the system of the present invention supports the management and efficient use of items, and provides functions for making the most of a user's time and space.

[1740] The processing flow will be explained below.

[1741] Product registration

[1742] Step 1:

[1743] User: Activates the smartphone camera and takes a photo of the new item.

[1744] Step 2:

[1745] User: Opens the smartphone app and enters basic information such as "brand name," "color," and "size" along with a photo.

[1746] Step 3:

[1747] Terminal: Sends the entered information and photos to the server.

[1748] Step 4:

[1749] Server: Analyzes the received product information and generates a unique ID.

[1750] Step 5:

[1751] Server: Attaches digital tags to items and stores that information in a database.

[1752] Management of goods

[1753] Step 1:

[1754] Server: Regularly updates the product database to maintain consistency of information.

[1755] Step 2:

[1756] User: Uses the app to search for a specific item, for example, by entering the keyword "red shirt."

[1757] Step 3:

[1758] Server: Searches the database for relevant product information and sends the results to the terminal.

[1759] Step 4:

[1760] Terminal: Displays search results to the user.

[1761] Product suggestions

[1762] Step 1:

[1763] Server: Uses generative AI to analyze users' past usage data and preferences.

[1764] Step 2:

[1765] Server: Generates suggestions for the next day's outfit, taking into account the combination of items.

[1766] Step 3:

[1767] Server: Notifies the user's terminal of the generated proposal.

[1768] Step 4:

[1769] Device: The user reviews the suggestions and makes changes to the outfit if necessary.

[1770] Distribution and sharing of goods

[1771] Step 1:

[1772] Server: Analyzes the item usage frequency data and generates a list of unused items.

[1773] Step 2:

[1774] Users: Use the application to request loans or sales of unused items to friends and family.

[1775] Step 3:

[1776] Server: Manages rental and sales requests and tracks the necessary transactions.

[1777] Step 4:

[1778] Server: Sends notification to the user when the transaction is complete.

[1779] Goods delivery management

[1780] Step 1:

[1781] User: Uses the app to request delivery of the outfit they want to wear the next day.

[1782] Step 2:

[1783] Server: Works with logistics services to arrange delivery and ship items from the warehouse.

[1784] Step 3:

[1785] Server: Tracks the delivery status of goods and updates the information in real time.

[1786] Step 4:

[1787] Server: When the item arrives at the delivery locker, it sends a notification to the user.

[1788] Step 5:

[1789] User: Check delivery status and receive items in the app.

[1790] Through these steps, the system efficiently executes a series of processes from product registration to management, proposal, distribution, and delivery management, thereby significantly improving users' lives.

[1791] Example 1

[1792] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1793] Conventional item management systems make it difficult for users to efficiently register, manage, and use the items they purchase. They also lack advanced support, such as managing the circulation and lending of unused items, or suggesting outfits based on the user's preferences and past usage history. Furthermore, arranging delivery of items and tracking their status places a heavy burden on the user. The present invention aims to solve these problems and improve the quality of life for users.

[1794] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1795] In this invention, the server includes means for acquiring images of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique identifiers and assigning digital tags, means for saving the item information in data storage, means for periodically updating the item database and maintaining information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on the user's past usage data and personal preferences, means for analyzing item usage frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, and means for tracking and notifying delivery status. This allows users to centrally register, manage, use, distribute, and deliver items.

[1796] "Goods" are any tangible goods or items that are the subject of management and that a User possesses, uses, or distributes.

[1797] "Image capture" is the process of taking a photograph or video of an item using an electronic device.

[1798] "Basic information" refers to data necessary to identify and specify an item, and includes attributes such as brand name, color, and size.

[1799] A "server" is a remote computer system that processes information and stores data.

[1800] "Transmission" is the act of transferring data or information from one place to another.

[1801] "Analysis" is the process of analyzing received data to extract useful information.

[1802] A "unique identifier" is a specific number or code assigned to each item to uniquely identify it.

[1803] A "digital tag" is an electronic tag or label associated with an item that contains information in digital form.

[1804] "Data storage" is a physical or virtual location or device for storing information.

[1805] A "database" is an information system that systematically organizes a large amount of data and allows efficient access using queries.

[1806] "Integrity" refers to data that is accurate, consistent, and not altered or corrupted.

[1807] "Searching" is the act of searching a database or information system to find specific data.

[1808] A "suggestion" is a recommendation or recommendation made based on the results of the analysis.

[1809] "Notifications" are messages or alerts that inform users of important information.

[1810] "Frequency of use" is an index that indicates how often an item is used.

[1811] A "request" is a request or application to ask for something.

[1812] "Logistics services" are businesses or companies that manage and execute the transportation and delivery of goods.

[1813] "Tracking" is the process of monitoring and recording the location and condition of an item in real time.

[1814] This invention is a system for supporting the management and efficient use of goods, with the aim of improving the quality of life of users. This system can perform everything from product registration to management, distribution, and delivery in an integrated manner.

[1815] 1. Registration of goods

[1816] Users take a photo of a newly purchased item using a smartphone or other device. Next, they enter basic information about the item, such as its brand name, color, and size, through an application. The device then sends this information to a server. The server analyzes the received information, generates a unique identifier for the item, and assigns a digital tag to it. The item information is then stored in data storage.

[1817] 2. Management of items

[1818] After the product information is registered, the server periodically updates the product database to maintain the integrity of the information. When a user searches for a specific product using the application, the device sends the search keywords to the server, which then extracts the corresponding product information from the database, returns it to the device, and displays it to the user.

[1819] 3. Product Proposals

[1820] The server uses the generative AI model to analyze the user's past usage data and personal preferences. Based on this, the server generates outfit suggestions for the next day and notifies the user's device. For example, if there is a special event the next day, the generative AI will suggest a set of shirt, pants, and shoes. The user can review the suggestions in the app and make changes as needed.

[1821] 4. Distribution and sharing of goods

[1822] The server analyzes the usage frequency data of the items and identifies unused items. Users can then send requests to lend or sell items to relatives or acquaintances through the application. The server manages the requests and notifies the user when the lending or sale is completed.

[1823] 5. Goods delivery management

[1824] Users use the app to request delivery of the clothes they will wear the next day. The server works with the logistics service to arrange for the items to be shipped from the warehouse and tracks the delivery status in real time. Once the items arrive at the delivery locker, the server sends a notification to the user, who can then check the status on the app and collect the items.

[1825] This system is realized using various hardware and software. Specifically, devices such as smartphones and tablets are used, and an application acts as the interface between the user and the system. The server is equipped with software with advanced data analysis capabilities and a generative AI model.

[1826] Examples of concrete examples and prompts

[1827] 1. If a user buys a new red shirt, they take a photo with their smartphone and enter "Brand: ABC," "Color: Red," and "Size: M" into the app and submit it. The server analyzes the information, generates a unique identifier and digital tag, and stores them in a database.

[1828] Example prompt: "Please register for a new red ABC brand medium shirt."

[1829] 2. When a user searches for "red shirt," the server retrieves the relevant information from the database and sends it to the terminal, where the user can view the results.

[1830] Example prompt: "Search the database for red shirts and display a list."

[1831] 3. The day before a special event, the generative AI will suggest a set of shirts, pants, and shoes, and the user can review the suggestions in the app and make changes as needed.

[1832] Example prompt: "Please give me some outfit suggestions for tomorrow's special event."

[1833] Thus, the present invention is a multifunctional system that makes users' item management more efficient and improves their quality of life.

[1834] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1835] Product registration

[1836] Step 1:

[1837] The user takes a photo of the newly purchased item with their smartphone or device. The input is the image of the item, and the output is the captured image file.

[1838] Specific behavior: The user activates the smartphone camera and takes a photo of the red shirt. The image file is saved to the device.

[1839] Step 2:

[1840] The user launches the application and inputs a photograph of the item along with basic information such as the brand name, color, size, etc. The input is the item image and text data of the basic information, and the output is a transmission package containing this data.

[1841] Specific behavior: The user enters "Brand name: ABC", "Color: Red", and "Size: M" into the app, selects a photo, and presses the send button.

[1842] Step 3:

[1843] The terminal sends the entered information and photos to the server. The input is the transmission package, and the output is the data that arrives at the server.

[1844] Specific operation: The transmission package created by the terminal is sent to the server via the Internet.

[1845] Step 4:

[1846] The server analyzes the received photos and item information. The input is the received data, and the output is the analysis result data.

[1847] Specific operation: The server analyzes the photo using an image analysis algorithm and extracts information such as "red," "shirt," and "brand: ABC."

[1848] Step 5:

[1849] The server generates a unique identifier for the item based on the analysis results and assigns a digital tag to it. The input is the analysis results, and the output is the unique identifier and item information with the digital tag.

[1850] Specific operation: The server generates a unique ID (e.g., 123456), uses it to create a digital tag, and links it to the item information.

[1851] Step 6:

[1852] The server stores the product information in a data storage. The input is the product information with the digital tag, and the output is the data stored in the data storage.

[1853] Specific operation: The server writes the generated product information to the database.

[1854] Management of goods

[1855] Step 7:

[1856] The server periodically updates the product database to maintain consistency of information. The input is the existing product information, and the output is the updated database information.

[1857] Specific operation: The server runs an automatic script to check for updates to product information and update the database if necessary.

[1858] Step 8:

[1859] A user searches for a specific item within an application. The input is the search keyword, and the output is the search result data.

[1860] Specific behavior: The user types "red shirt" into the app's search box and presses the search button.

[1861] Step 9:

[1862] The terminal sends search keywords to the server. The input is the search keywords, and the output is the data sent to the server.

[1863] Specific operation: The device sends the search keywords to the server via the Internet.

[1864] Step 10:

[1865] The server extracts the relevant product information from the database and sends it to the terminal. The input is the search keyword, and the output is the search result data.

[1866] Specific operation: The server extracts data corresponding to "red shirt" from the database and sends it to the terminal.

[1867] Step 11:

[1868] The terminal displays the search results to the user. The input is the search result data, and the output is the information displayed to the user.

[1869] Specific operation: The device displays the search results on the app's display screen, and the user confirms them.

[1870] Product suggestions

[1871] Step 12:

[1872] The server uses the generated AI model to analyze the user's past usage data and personal preferences. The input is the past usage data, and the output is the analysis results.

[1873] Specific operation: The server launches the generative AI, inputs the user's past data (e.g., frequently worn colors and styles), and performs analysis.

[1874] Step 13:

[1875] The server generates the next day's outfit combination based on the analysis results. The input is the analysis results, and the output is the suggested outfit data.

[1876] Specific operation: The generative AI model proposes a set of "shirt, pants, shoes" and saves it as data.

[1877] Step 14:

[1878] The server notifies the user's terminal of the generated proposal. The input is the proposal data, and the output is the notification sent to the user's terminal.

[1879] Specific operation: The server sends the proposal to the device, and the device notifies the user, "This set is recommended for tomorrow's event."

[1880] Distribution and sharing of goods

[1881] Step 15:

[1882] The server analyzes the usage frequency data of the items and identifies unused items. The input is the usage frequency data, and the output is a list of unused items.

[1883] Specific operation: The server lists items that have not been used for a certain period of time and saves them as suggestions.

[1884] Step 16:

[1885] A user submits a rental or sale request through the application. The input is the request data and the output is the request sent to the server.

[1886] What happens: A user sends a request in the app to "lend a shirt to a friend."

[1887] Step 17:

[1888] The server manages the requests and notifies the user when the loan or sale is completed. The input is the request data and the output is the notification sent to the user.

[1889] What happens next: The server processes the request and sends a notification to the user saying, "Your shirt has been checked out."

[1890] Goods delivery management

[1891] Step 18:

[1892] A user uses the application to request delivery of the clothes they will wear the next day. The input is the delivery request data, and the output is the delivery request sent to the server.

[1893] Specific behavior: A user requests delivery of a shirt and pants to wear the next day through the app.

[1894] Step 19:

[1895] The server works with the logistics service to process the shipment of goods from the warehouse. The input is the delivery request data, and the output is the shipping instruction sent to the logistics service.

[1896] Specific operation: The server communicates with the logistics service and starts the shipping procedure for the item.

[1897] Step 20:

[1898] The server tracks the delivery status in real time and sends a notification to the user once the item arrives at the parcel locker. The input is the real-time delivery status data and the output is the notification sent to the user.

[1899] Specific behavior: The server tracks the delivery status of the items and sends a notification to the user saying, "The shirt and pants have arrived at the delivery locker."

[1900] (Application example 1)

[1901] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1902] Conventional closet management systems have the drawback of being time-consuming and inefficient, as registering and managing items is done manually. Furthermore, outfit suggestions based on user preferences and past usage data are often inappropriate, potentially reducing user satisfaction. Furthermore, managing requests for item rentals and sales is complicated, and delivery status tracking and notifications are not provided in real time, resulting in a lack of an improved user experience.

[1903] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1904] In this invention, the server includes means for taking photos of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique IDs, and assigning digital tags, means for saving the item information in a database, means for periodically updating the item database and maintaining information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on a user's past use data and preferences, means for analyzing item use frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, means for tracking and notifying delivery status, means for automatically registering items purchased by a user in cooperation with an online shopping site, and means for using a generation AI to suggest outfits based on a user's purchase history and preferences. This enables efficient item registration and management, accurate outfit suggestions based on a user's preferences and past data, and seamless management of item rental, sales, and delivery.

[1905] "Means for taking a photo of an item and entering basic information" refers to a device or interface that allows a user to take a picture of an item they own and enter basic information about that item (e.g., brand name, color, size, etc.).

[1906] "Means for transmitting information about an item to a server" refers to the communications infrastructure and protocols for transmitting the photographed image of the item and the input information to a central server.

[1907] "Means for analyzing item information, generating a unique ID, and assigning a digital tag" refers to algorithms or software that analyzes the transmitted item information and generates and assigns a unique identification number (ID) to the item.

[1908] The "means for storing product information in a database" refers to a system or procedure for storing the generated product information and unique ID in a database.

[1909] "Means for regularly updating the product database and maintaining the integrity of the information" means the mechanisms or protocols for periodically checking the information in the database to ensure that it accurately reflects new or changed information.

[1910] "Means for searching for specific items and means for displaying search results" refers to the search function that a user uses to find a specific item and the interface or method for visually displaying the results to the user.

[1911] "Means for generating and notifying clothing suggestions based on the user's past usage data and preferences" refers to a system or algorithm that analyzes the user's past behavioral data and preference trends, suggests clothing suitable for the user, and notifies the user of those suggestions.

[1912] "Means for analyzing item usage frequency data and identifying unused items" refers to technologies and methods for analyzing how frequently items are used and identifying items that have not been used for a long period of time.

[1913] A "means for managing rental and sale requests" is software or a process for accepting, tracking, and managing requests from users to rent or sell items.

[1914] The "means for arranging delivery of goods in cooperation with a logistics service" refers to an interface or system for efficiently arranging delivery of goods in cooperation with an external logistics service provider.

[1915] "Means for tracking and notifying delivery status" refers to technologies and means for monitoring the delivery status of goods in real time and providing that information to users.

[1916] "Means for linking with online shopping sites and automatically registering items purchased by users in the system" refers to a mechanism for integrating with online shopping platforms and automatically adding items purchased by users to the closet system.

[1917] "Means of using generative AI to suggest clothing based on a user's purchasing history and preferences" refers to algorithms and systems that utilize the latest artificial intelligence technology to suggest clothing based on a user's purchasing history and preferences.

[1918] The present invention provides a system for improving the efficiency of item management and user convenience. This system automates a series of processes, such as photographing items, registering information, saving data, proposing items, renting and selling items, and managing delivery. Specific embodiments are described below.

[1919] 1. Registration of goods

[1920] Using a device such as a smartphone, the user takes a photo of the item they have purchased and enters basic information such as brand name, color, and size. This information is sent from the device to a server. The server analyzes the received item information, generates a unique ID, and assigns it to the item. The item information with the digital tag attached is stored in a database. Hardware used includes devices such as smartphones and PCs, and software such as React Native, Node.js, Express, and MongoDB is used to send the item information.

[1921] 2. Management of items

[1922] The server periodically updates the database to maintain consistency of product information. When a user searches for a specific product, they enter a keyword through their device, and the server searches the database for the corresponding product and displays the results to the user. In this process, React Native is used as the search interface, and MongoDB is used for database search processing.

[1923] 3. Suggestion function

[1924] The server uses a generative AI model to suggest outfits for the next day based on the user's past usage data, purchase history, and preferences. The generated suggestions are sent to the user's device. OpenAI GPT-4 is used as the generative AI model. As a concrete example, the following prompt sentence is input to the generative AI model:

[1925] Suggest tomorrow's outfit based on the user's purchase history over the past six months, as well as their preferred colors and brands.

[1926] User Information:

[1927] Brand: [Luxury Brand A, Luxury Brand B]

[1928] Favorite colors: [red, blue]

[1929] Past purchase history: [Product ID 123, Product ID 456, Product ID 789]

[1930] Special Events: [None]

[1931] 4. Rental and sales

[1932] The server analyzes item usage frequency data and identifies items that have not been used for a long time. Based on this information, users can request to rent or sell items through the app. The server manages the requests and notifies the user when the request is completed. Node.js and MongoDB are used to manage rentals and sales.

[1933] 5. Delivery management

[1934] Once the user has decided on an outfit, the server connects with a logistics service to arrange delivery of the items. The delivery status is tracked in real time, and the user is notified when the item arrives at the parcel locker. Node.js is used to connect to an external logistics API to arrange delivery and track the status.

[1935] As described above, the system of the present invention seamlessly integrates the registration, management, proposal, rental, sale and delivery of goods, thereby greatly improving user convenience.

[1936] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1937] Step 1:

[1938] The user uses the device to take a photo of the item they purchased and enter basic information such as brand name, color, size, etc. This input information includes image data and text information of the item. This data is temporarily stored on the device.

[1939] Step 2:

[1940] The terminal sends the entered product information and image data to the server. At this time, an HTTP POST request is used to transfer form data including the product image data and metadata to the server. The input is the product information and image data provided by the user, and the output is stored on the server.

[1941] Step 3:

[1942] The server analyzes the received product information and generates a unique ID. This unique ID is used to uniquely identify the product information. In this process, the unique ID is generated using a UUID generation algorithm or similar. The input is the transmitted product information, and the output is the generated unique ID and product information.

[1943] Step 4:

[1944] The server assigns the generated unique ID to the item information and generates a digital tag. The digital tag is an important element for identifying the item and is expressed in the form of an RFID tag, barcode, etc. In this step, the algorithm for generating the digital tag runs. The input is item information with a unique ID, and the output is item information with a digital tag.

[1945] Step 5:

[1946] The server stores the item information with the digital tags in a database. The database used here is a NoSQL database such as MongoDB, and the data is stored in document format. The input is the item information with the digital tags, and the output is the item information stored in the database.

[1947] Step 6:

[1948] The server periodically updates the database to maintain consistency of the information. This process checks for duplicates and inconsistencies in the data, updating or deleting them as necessary. The input is the existing database, and the output is a consistent database.

[1949] Step 7:

[1950] When a user searches for a specific item, they enter keywords into their terminal and send a search request to the server. The server searches the database for the relevant item and returns the results to the terminal. The input is the keyword entered by the user, and the output is a list of search results.

[1951] Step 8:

[1952] The server uses a generative AI model to suggest an outfit for the next day based on the user's past usage data, purchase history, and preferences. This suggestion is sent to the user's device. The generative AI model used is OpenAI GPT-4. An example of a specific prompt is as follows:

[1953] Suggest tomorrow's outfit based on the user's purchase history over the past six months, as well as their preferred colors and brands.

[1954] User Information:

[1955] Brand: [Luxury Brand A, Luxury Brand B]

[1956] Favorite colors: [red, blue]

[1957] Past purchase history: [Product ID 123, Product ID 456, Product ID 789]

[1958] Special Events: [None]

[1959] The input is user data and the output is outfit suggestions.

[1960] Step 9:

[1961] The server analyzes the item usage frequency data and identifies items that have not been used for a long time. Based on this information, users can request to rent or sell items. The server manages the request and notifies the user when processing is complete. The input is the item usage frequency data, and the output is a list of unused items.

[1962] Step 10:

[1963] Once the user has decided on an outfit, the server works with the logistics service to arrange delivery of the items. This is done using a logistics API. The delivery status is tracked in real time, and the user is notified when the item arrives at the delivery locker. The input is the user's delivery request, and the output is a notification of the delivery status.

[1964] Through the above processing steps, the system of the present invention can efficiently register, manage, propose, rent, sell, and deliver products.

[1965] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1966] This invention relates to a 4D closet system that utilizes digital tags, generative AI, and an emotion engine. This system supports the management and efficient use of items, recognizes the user's emotional state, and provides functions to make the user's life more comfortable.

[1967] Product registration

[1968] First, we will explain the procedure for a user to register a newly purchased item in the system. The user takes a photo of the item using a smartphone or other device. Next, they enter information about the item through the application. Specific items include the brand name, color, and size.

[1969] The device sends the entered information and photo to a server, which analyzes the information and generates a unique ID for the item, attaches a digital tag to the item, and stores the information in a database.

[1970] Management of goods

[1971] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency. When a user searches for a specific item, the server retrieves the corresponding item information from the database via the terminal and displays it to the user.

[1972] For example, when a user searches for "black shirts," the server extracts information about the corresponding shirts based on the keywords and sends the results to the user's terminal.

[1973] Utilizing the Emotion Engine

[1974] The emotion engine captures the user's face with a camera and analyzes their emotional state in real time from facial expressions, voice, etc. The emotion data analyzed by the emotion engine is sent to the server. Based on the received emotion data, the server makes product recommendations that are best suited to the user's current situation.

[1975] For example, if a user is feeling stressed, the AI ​​can suggest clothing made of soft materials that will help them relax. The AI ​​takes this emotional data into account and optimizes the suggestions.

[1976] Product suggestions

[1977] Based on the user's preferences, past usage data, and emotional data obtained from the emotion engine, the generative AI suggests outfits for the next day. The server uses the generative AI to analyze the data and generate the optimal outfit combination. This suggestion is sent to the user's device, where the user can review the suggested outfit and accept or change it.

[1978] For example, if you have an important presentation the next day, the generative AI will suggest a formal shirt and slacks set, and you can review the suggestion and change to a more casual outfit if you feel like relaxing.

[1979] Distribution and sharing of goods

[1980] The server analyzes the frequency of use of items and allows users to lend or sell unused items to friends and family. The server analyzes the data on the frequency of use of items and provides users with a list of unused items. Users can submit requests for lending or selling items through the application.

[1981] For example, if a user has an unused shirt and wants to lend it to a friend, the server manages the request and notifies the user when the loan is complete.

[1982] Goods delivery management

[1983] Once the user has decided on the outfit they want to wear the next day, the server arranges for the items to be delivered. The user makes a delivery request through the app, and the server works with the logistics service to arrange for the items to be shipped from the warehouse.

[1984] In addition, the server tracks the delivery status in real time and notifies the user when the item arrives at the parcel locker, where the user can check the status and collect the item through the app.

[1985] For example, the shirt and pants that the user has selected for the next day's outfit will be delivered to the delivery locker the next morning, and the user can receive and wear them as is.

[1986] As described above, the system of the present invention utilizes digital tags, generative AI, and an emotion engine to support the management and efficient use of items, and by making suggestions that are optimal for the user's emotional state, can significantly improve the user's life.

[1987] The processing flow will be explained below.

[1988] Product registration

[1989] Step 1:

[1990] User: Activates the smartphone camera and takes a photo of the new item.

[1991] Step 2:

[1992] User: Opens the smartphone app and enters basic information such as "brand name," "color," and "size" along with a photo.

[1993] Step 3:

[1994] Terminal: Sends the entered information and photos to the server.

[1995] Step 4:

[1996] Server: Analyzes the received product information and generates a unique ID.

[1997] Step 5:

[1998] Server: Attaches digital tags to items and stores that information in a database.

[1999] Management of goods

[2000] Step 1:

[2001] Server: Regularly updates the product database to maintain consistency of information.

[2002] Step 2:

[2003] User: Uses the app to search for a specific item, for example, by entering the keyword "black shirt."

[2004] Step 3:

[2005] Server: Searches the database for relevant product information and sends the results to the terminal.

[2006] Step 4:

[2007] Terminal: Displays search results to the user.

[2008] Utilizing the Emotion Engine

[2009] Step 1:

[2010] User: Uses a smartphone or wearable device to capture facial expressions and voice via a camera and microphone.

[2011] Step 2:

[2012] Device: Captured facial expression and voice data is sent to the emotion engine.

[2013] Step 3:

[2014] Emotion engine: Analyzes the user's emotional state from facial expressions and voice.

[2015] Step 4:

[2016] Terminal: Transmits the analyzed emotion data to the server.

[2017] Step 5:

[2018] Server: Based on the received emotion data, it generates optimal product recommendations for the user.

[2019] Product suggestions

[2020] Step 1:

[2021] Server: Uses generative AI to comprehensively analyze users' past usage data, preferences, and emotional data.

[2022] Step 2:

[2023] Server: Generates suggestions for the next day's outfit, taking into account the combination of items.

[2024] Step 3:

[2025] Server: Notifies the user's terminal of the generated proposal.

[2026] Step 4:

[2027] Device: The user reviews the suggestions and makes changes to the outfit if necessary.

[2028] Distribution and sharing of goods

[2029] Step 1:

[2030] Server: Analyzes the item usage frequency data and generates a list of unused items.

[2031] Step 2:

[2032] Users: Use the application to request loans or sales of unused items to friends and family.

[2033] Step 3:

[2034] Server: Manages rental and sales requests and tracks the necessary transactions.

[2035] Step 4:

[2036] Server: Sends notification to the user when the transaction is complete.

[2037] Goods delivery management

[2038] Step 1:

[2039] User: Uses the app to request delivery of the outfit they want to wear the next day.

[2040] Step 2:

[2041] Server: Works with logistics services to arrange delivery and ship items from the warehouse.

[2042] Step 3:

[2043] Server: Tracks the delivery status of goods and updates the information in real time.

[2044] Step 4:

[2045] Server: When the item arrives at the delivery locker, it sends a notification to the user.

[2046] Step 5:

[2047] User: Check delivery status and receive items in the app.

[2048] Through these steps, the system efficiently executes a series of processes, from product registration and management, to proposals, distribution, and delivery management, thereby significantly improving users' lives. Furthermore, the use of an emotion engine enables optimal proposals based on the user's emotional state, improving user satisfaction.

[2049] Example 2

[2050] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2051] Conventional item management systems require users to spend a lot of time managing item details and are unable to provide suggestions that take into account their emotional state. Furthermore, they lack mechanisms for efficiently managing the frequency of use of items and effectively utilizing unused items. Therefore, there is a need for a system that can efficiently manage items and provide suggestions that are optimal for the user's emotional state.

[2052] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2053] In this invention, the server includes a means for periodically updating the product database and maintaining consistency of information, a means for searching for specific products and displaying search results, and a means for providing an emotion engine for analyzing the user's emotions and making suggestions based on the emotions, thereby enabling the management and effective use of products while making suggestions that take into account the user's emotional state.

[2054] An "item" is an item that is owned and managed by a user.

[2055] "Means for taking photographs" refers to a method of obtaining an image of an item using a device such as a camera or smartphone.

[2056] The "means for inputting basic information" refers to a method by which a user inputs detailed information about an item (such as brand name, color, size, etc.) through an application.

[2057] A "server" is a computer system that exists in the cloud or within a local network and stores, analyzes, and communicates data.

[2058] The "means for analyzing product information" is a method for analyzing product-related data within the server and performing classification and feature extraction.

[2059] The "means for generating a unique ID" is a method for generating a unique identifier for each item, making the item identifiable.

[2060] A "digital tagging means" is a method for electronically tagging information related to an item.

[2061] The "means for storing in the database" refers to a storage device for permanently storing product information and software for managing it.

[2062] "Means for regularly updating the product database" refers to a method for adding or amending new or changed information to the database to keep the information up to date.

[2063] The "means for displaying search results" is a method for displaying on the screen information about items obtained based on the search conditions entered by the user.

[2064] The "emotion engine" is a system that analyzes the user's emotions using input devices such as a camera or microphone, and makes appropriate suggestions based on the results.

[2065] The "means for analyzing usage frequency data" is a method for analyzing the usage history and frequency of an item and promoting effective use of the item.

[2066] A "means for managing rental and sales requests" is a method for accepting and processing requests from users and taking action as necessary.

[2067] "Means for linking with logistics services" refers to methods for communicating with external delivery companies and warehouse management systems to manage logistics processes.

[2068] "Means for tracking delivery status" refers to a method for monitoring the delivery status of an item in real time and notifying the user.

[2069] "Means of notification" refers to a method for sending information from the system to the user and encouraging them to take necessary action.

[2070] This invention relates to a 4D closet system that streamlines item management and makes optimal suggestions based on the user's emotional state. By utilizing digital tags, generative AI, and an emotion engine, this system analyzes item management and usage frequency, providing functions to make the user's life more comfortable.

[2071] Product registration

[2072] Users take a photo of their newly purchased item using a device such as a smartphone or tablet. After taking the photo, they enter information about the item, such as the brand name, color, and size, through an application. The entered information and photo are sent from the device to a server. The server analyzes the received information, generates a unique ID for the item, and assigns a digital tag. This information is then stored in a database.

[2073] Specific example of operation: When a user purchases a blue shirt, enters the information into the app, takes a photo, and sends it, the server assigns a unique ID to the blue shirt and sets a digital tag.

[2074] Management of goods

[2075] After an item is registered, the user can manage it using the application. The server periodically updates the item database to maintain consistency of the information. When searching for a specific item, the server extracts relevant item information based on the search keywords and sends the results to the user's device for display.

[2076] Specific example of operation: When a user searches for "black shirt" or "blue skirt," the server sends information about the corresponding items to the terminal and displays it.

[2077] Utilizing the Emotion Engine

[2078] The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice, and evaluates their emotional state in real time. The analyzed emotion data is sent to the server via the device. Based on this, the server makes product recommendations that are best suited to the user's current situation.

[2079] Specific example of operation: If the emotion engine analyzes that the user is feeling stressed, the server will suggest clothing made of soft materials that will help them relax.

[2080] Product suggestions

[2081] The server uses AI to analyze the user's preferences, past usage data, and emotional data to generate the optimal outfit combination. This suggestion is sent to the user's device, where the user can review it and accept or change it.

[2082] Example of how it works: If you have an important presentation the next day, the server will use generative AI to suggest a formal shirt and slacks set. If you're feeling more relaxed, you can also change to casual clothing.

[2083] Example prompts: "Suggest some outfits using a blue shirt.", "What outfits would help users relax when they're feeling stressed?"

[2084] The above is a specific embodiment of the present invention, which allows the user to receive recommendations for items that match their emotional state and preferences, and also allows for efficient item management.

[2085] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2086] Step 1:

[2087] A user uses a device such as a smartphone or tablet to take a photo of an item and enter basic information such as brand name, color, and size through an application. The input consists of manual input by the user and the photo taken. The device then sends this information and the photo to a server. The server analyzes the received information and generates a unique ID for the item. Specifically, the server uses an image analysis algorithm to extract the item's features from the photo and associates them with the basic information.

[2088] Input: Photo of the item, basic information entered by the user

[2089] Output: Analyzed product information, generation of unique ID

[2090] Step 2:

[2091] After the unique ID is generated for the item, the server assigns a digital tag to the item, which is used to facilitate item identification and tracking. The server associates the generated unique ID with the digital tag and stores it in a database.

[2092] Input: Unique ID, item analysis information

[2093] Output: Digital tag, stored in database

[2094] Step 3:

[2095] The server periodically updates the product database to maintain consistency. According to a set schedule, the server updates the database with newly added or modified product information. Specifically, the server performs a comparison between the clone data and the new data.

[2096] Input: New or modified item information

[2097] Output: Updated database

[2098] Step 4:

[2099] When a user searches for a specific item, they input search keywords using a terminal. The server receives this search request and extracts the relevant item information from the database. The server then sends the extracted results to the terminal, which then displays the search results to the user.

[2100] Input: Search keyword (from user)

[2101] Output: Search results (from server to device)

[2102] Step 5:

[2103] The device uses a camera and microphone to capture the user's facial expressions and voice, and sends this data to the emotion engine for real-time analysis. The emotion engine analyzes the user's emotional state from this input data and sends the data to the server. The server then uses the received emotion data to suggest the most suitable products for the user.

[2104] Input: User's facial expression and voice data

[2105] Output: Parsed emotion data

[2106] Step 6:

[2107] The server uses AI to analyze the user's past usage data, preferences, and emotional data. Based on the results of this analysis, the server generates suggestions for the user on what outfit to wear the next day. The suggestions are then sent to the user's device.

[2108] Input: Historical usage data, preferences, emotional data

[2109] Output: Outfit suggestions (from the generation AI to the device)

[2110] Step 7:

[2111] The server analyzes the usage frequency data of the items and generates a list of unused items. This list is sent to the terminal, and the user can check for missing items, lend them to a friend, or send a request to sell them. The server manages these requests and efficiently distributes the items.

[2112] Input: Frequency of use data

[2113] Output: List of unused items, management of sales and lending requests

[2114] Step 8:

[2115] When the user decides what to wear the next day, the device sends a delivery request to the server, which then coordinates with the logistics service to arrange for the item to be shipped from the warehouse. The server then tracks the delivery status in real time and notifies the user when the item arrives at the designated location.

[2116] Input: Delivery request (from user)

[2117] Output: Delivery status tracking and notification (from server to terminal)

[2118] (Application example 2)

[2119] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2120] In recent years, improving the efficiency of inventory management and user satisfaction at logistics centers have become important issues. However, conventional systems have been inadequate in managing inventory and proposing products that take customer sentiment into consideration. As a result, it has become difficult to address inventory overages and shortages, and to make personalized proposals based on customer preferences, resulting in a decline in overall operational efficiency and customer satisfaction. The present invention aims to solve these issues, enabling logistics centers to provide more efficient and personalized services.

[2121] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2122] In this invention, the server includes means for taking photos of items and inputting basic information, means for transmitting item information to the server, means for analyzing the item information, generating unique IDs and assigning digital tags, means for saving the item information in a database, means for periodically updating the item database to maintain information consistency, means for searching for specific items and displaying search results, means for generating and notifying outfit suggestions based on a user's past usage data and preferences, means for analyzing item usage frequency data and identifying unused items, means for managing rental and sales requests, means for arranging item delivery in cooperation with a logistics service, means for tracking and notifying delivery status, means for using an emotion analysis engine to analyze emotions and suggest products that match the customer's mood, and means for analyzing item distribution data and customer emotion data and generating reports. This enables more efficient item management in logistics centers and personalized product suggestions based on customer emotions.

[2123] "Goods" is a general term that refers to various types of products, merchandise, packages, etc.

[2124] "Taking a photo" means acquiring image data using the camera function of a digital camera, smartphone, etc.

[2125] "Basic information" refers to basic and necessary information about an item, including, for example, "brand name," "color," and "size."

[2126] "Server" refers to a combination of hardware and software for storing, processing, and managing data.

[2127] A "unique ID" is a special identifier assigned to an item, data, etc. to uniquely identify it.

[2128] A "digital tag" is an electronic label or mark attached to an item that contains information including a unique ID.

[2129] A "database" is a system for effectively storing, searching, and managing various data.

[2130] "Information integrity" refers to keeping data accurate and consistent.

[2131] "Searching" is the act o...

Claims

1. a means for taking a photo of the item and entering basic information; means for transmitting information about the item to a server; A means for analyzing the product information, generating a unique ID, and assigning a digital tag; means for storing the item information in a database; A means of regularly updating the article database and maintaining the integrity of the information; means for searching for a particular item and displaying search results; means for generating and notifying outfit suggestions based on the user's past usage data and preferences; A means of analyzing data on the frequency of use of items and identifying unused items; A means to manage loan and sale requests; A means of coordinating with logistics services to arrange delivery of goods; A means of tracking and notifying you of delivery status; A system including:

2. 10. The system of claim 1, further comprising means for analyzing item usage frequency data and managing requests to rent or sell unused items to family and friends.

3. The system described in claim 1 further comprises a means for using a generating AI to suggest items for the outfit the user would like to wear the next day based on the user's past usage data and preferences, and notifying the user of the combination of items taking into consideration.

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