System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting up-to-date weather data; means for managing data on a user's clothing; means for generating optimal coordination based on the data; means for displaying the generated coordination; means for storing coordination selected by the user; means for providing an option to rent or purchase fashion items; means for transmitting order data to affiliated external brands; and means for suggesting new coordination after a new item arrives.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] Choosing the right clothing for the temperature and weather is a difficult task for many people, especially when considering fashion. The sheer number of options can be overwhelming and stressful. Ambiguous clothing standards, such as business casual, can also be a time-consuming and labor-intensive part of daily life. Furthermore, consumers need a way to efficiently access the latest fashion items while maintaining optimal fashion at all times, but existing systems are unable to adequately meet these needs. [Means for solving the problem]

[0005] This invention is a system in which AI suggests optimal outfits based on conditions such as temperature, weather, and destination. The system includes means for collecting the latest weather data, managing data on the user's clothing, generating optimal outfits based on this data, displaying the generated outfits, saving the outfits selected by the user, providing options to rent or purchase fashion items, sending order data to partnering external brands, and suggesting new outfits after new items arrive. It also includes means for learning past weather data and fashion information, and means for the user to input daily temperature, weather, and destination. This increases the efficiency of daily outfit selection, allowing users to easily achieve the perfect fashion at all times.

[0006] "Weather data" refers to weather information such as temperature, weather, humidity, and wind speed obtained from an external weather data API.

[0007] "Coordination" refers to the process of users choosing clothing by combining tops, bottoms, shoes, accessories, etc. to create a single style.

[0008] "AI algorithm" refers to a calculation method that uses artificial intelligence to analyze data and suggest optimal outfits.

[0009] A "subscription service" refers to a flat-rate service that allows users to rent or purchase new fashion items on a regular basis.

[0010] "Affiliated external brands" refers to companies and brands that collaborate with the system to receive apparel products.

[0011] "User data" refers to data registered by the user, including information about the clothes they own and their favorite styles.

[0012] "Inputting temperature, weather, and destination" refers to the operation in which the user inputs the day's weather information and planned destination into the application.

[0013] "Training data" refers to a data set that AI uses to learn from past data.

[0014] "Database" refers to the collection of digital information that the system uses to efficiently manage and store user data, weather data, and information on affiliated external brands. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] MODE FOR CARRYING OUT THE INVENTION

[0037] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day. This system is made up of three components: a server, a terminal, and a user, who exchange information with each other, and each component plays a specific role.

[0038] Server Roles

[0039] The server is the core of the system and performs the following functions:

[0040] 1. Weather data collection: Integrate with external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.). The collected data is used as a basis for learning from past trends and patterns.

[0041] 2. User Data Management: Manages a database of users' clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[0042] 3. Generating outfit suggestions: Using AI algorithms, the system generates optimal outfit suggestions based on weather data, user data, and destination information, eliminating the need for users to worry about choosing their daily outfits.

[0043] 4. Saving outfits: The outfits selected by the user are saved in a database and used as learning data for future suggestions.

[0044] 5. Offering rental and purchase options: We partner with third-party brands to offer users the option to rent or purchase the latest fashion items of their choice.

[0045] Device Role

[0046] The terminal operated by the user has the following functions:

[0047] 1. User Authentication: Provides an authentication process for users to log in to their accounts. The authentication information is sent to the server and verified there.

[0048] 2. Sending input information: The user inputs the day's temperature, weather, destination, etc. and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[0049] 3. Display of outfits: The outfits sent from the server are visually displayed. The suggestions are displayed in a format that is easy for the user to check, helping them make a selection.

[0050] 4. Order Processing: If you select the rental or purchase option, the order data is sent to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[0051] User Roles

[0052] Users operate the system and fulfill the following roles:

[0053] 1. Initial setup and registration: When using the app for the first time, you will need to register your clothing and preferred style. This data will be managed on the server and used to suggest outfits.

[0054] 2. Daily input and confirmation: Enter the daily weather conditions and destination, and check the coordinates returned by the server. If you like it, send your decision to the server via your device.

[0055] 3. Rent and Buy: Choose your option to rent or buy a new fashion item and follow the necessary steps.

[0056] Specific examples

[0057] A day in the life of User A

[0058] 1. Morning

[0059] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[0060] User: User A enters his / her user ID and password and taps the login button.

[0061] Device: Sends authentication information to the server.

[0062] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[0063] Device: Displays login success and displays the home screen.

[0064] 2. Enter your information

[0065] User: User A enters the information "sunny," "25 degrees," and "office" on the home screen.

[0066] Terminal: Sends this information to the server.

[0067] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[0068] 3. Coordination suggestions

[0069] Server: Referencing User A's registered database, the AI ​​algorithm generates the optimal outfit based on past data, suggesting combinations of T-shirt, jacket, pants, and shoes.

[0070] Server: Sends the generated coordinates to the terminal.

[0071] Device: Display suggested outfits.

[0072] User: User A reviews the suggestions and selects the outfit if they like it.

[0073] Terminal: Sends the selected coordinates to the server and stores them.

[0074] 4. Use of Subscription Services

[0075] User: User A rents the suggested new jacket through a subscription service.

[0076] Terminal: Sends rental orders to the server.

[0077] Server: Sends order data to partner brands and initiates shipping procedures.

[0078] In this way, User A can streamline their daily clothing selection and always maintain the best fashion. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[0079] The processing flow will be explained below.

[0080] Step 1:

[0081] On the device: The user opens the application and the login screen appears. The user enters their user ID and password and taps the login button.

[0082] Step 2:

[0083] Terminal: Sends the entered user ID and password to the server.

[0084] Step 3:

[0085] Server: Compares the received user ID and password with the database. If the login is successful, sends the user data to the terminal. If not successful, sends an error message to the terminal.

[0086] Step 4:

[0087] Device: If login is successful, display the home screen.

[0088] Step 5:

[0089] User: Enters the weather for the day, temperature, and destination (e.g., office, casual outing, formal event).

[0090] Step 6:

[0091] Terminal: Sends the entered information to the server.

[0092] Step 7:

[0093] Server: Accesses external weather data API to collect the latest weather information (temperature, weather conditions), and compares this information with user input.

[0094] Step 8:

[0095] Server: Refers to the database of the user's clothing and uses AI algorithms to generate optimal outfits based on past weather data and fashion information. For example, it suggests shirts, jackets, pants, shoes, etc.

[0096] Step 9:

[0097] Server: Sends the generated coordinates to the terminal.

[0098] Step 10:

[0099] Device: Visually displays the received outfits, showing a list of combinations of shirts, jackets, pants, shoes, etc.

[0100] Step 11:

[0101] User: Select the outfit they like from the ones presented. Once they have made their selection, they tap the confirm button.

[0102] Step 12:

[0103] Terminal: Sends the selected coordinate information to the server.

[0104] Step 13:

[0105] Server: The selected coordinates are saved in a database and used as learning data for future suggestions.

[0106] Step 14:

[0107] User: Selects a subscription option to rent or purchase new fashion items included in the suggested outfits.

[0108] Step 15:

[0109] Terminal: Sends rental or purchase order data to the server.

[0110] Step 16:

[0111] Server: Sends order data to partner external brands and initiates shipping procedures.

[0112] Step 17:

[0113] User: After receiving new items, the user uses the application again to receive new outfit suggestions based on the new items.

[0114] In this way, a system is realized that allows users to efficiently choose their daily outfits and always enjoy the most appropriate fashion.

[0115] Example 1

[0116] 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."

[0117] In modern society, choosing the best outfit for each day based on weather conditions and schedules is a tedious task for many users. Managing existing clothing and renting or purchasing new fashion items can also be time-consuming. There is a need for a way to efficiently solve these issues, simplify daily outfit selection, and ensure optimal fashion at all times.

[0118] 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.

[0119] In this invention, the server includes means for collecting the latest weather data, means for managing the user's clothing data, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing the option to rent or purchase fashion items, means for transmitting order data to affiliated external suppliers, means for proposing new outfits after new items arrive, means for transmitting daily temperature, weather, and destination information entered by the user, means for comparing the weather data with the user's clothing data, and means for generating outfits using an AI algorithm. This allows users to easily select optimal outfits based on daily weather conditions and plans, and enables efficient clothing management and the rental or purchase of new items.

[0120] "Weather data" is information about weather conditions such as temperature, weather, humidity, and wind speed.

[0121] "User's clothing data" refers to data including details of clothing owned by the user, such as style, size, and color.

[0122] The "coordination generation means" is a system that automatically suggests optimal outfit combinations based on weather data and the user's clothing data.

[0123] The "means for displaying generated coordinated outfits" is an interface for visually displaying to the user the outfit combinations proposed by the server or terminal.

[0124] The "coordinate storage means" is a system that stores the outfit combinations selected by the user in a database.

[0125] "Rental or purchase option providing means" refers to a system that provides a user with the option to rent or purchase a suggested fashion item.

[0126] "Order data transmission means" refers to a means for transmitting a user's rental or purchase order to an affiliated external supplier.

[0127] The "new coordination suggestion method" is a system that suggests new outfit combinations that include new items after the user receives them.

[0128] The "means for transmitting daily temperature, weather, and destination information" is a system that transmits information about the temperature, weather, and destination of the day entered by the user to the server.

[0129] The "means for comparing weather data with user's clothing data" is a means for comparing collected weather data with the user's clothing data to select the optimal outfit.

[0130] "A means for generating coordination using an AI algorithm" is a system that uses an artificial intelligence algorithm to generate optimal clothing combinations.

[0131] The present invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day. This system is made up of three components: a server, a terminal, and a user, who exchange information with each other, and each component plays a specific role.

[0132] Server Roles

[0133] Weather data collection

[0134] The server connects to external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.) using software such as the OpenWeatherMap API or WeatherStack API. The collected data is stored in a database and used as a basis for learning from past trends and patterns.

[0135] Managing User Data

[0136] The server manages a database of the user's clothing and style preferences, which is used to keep the user's inventory of clothing items up to date.

[0137] Generating outfit suggestions

[0138] The server uses AI algorithms to generate optimal trips based on weather data, user data, and destination information, using machine learning frameworks such as TensorFlow and PyTorch.

[0139] Save your outfit

[0140] The coordination selected by the user is stored in a database and used as learning data to help with future suggestions.

[0141] Offering rental and purchase options

[0142] The server works with affiliated external suppliers, such as general online fashion stores, to provide users with the option to rent or purchase selected latest fashion items.

[0143] Device Role

[0144] User authentication

[0145] The device provides an authentication process for the user to log into their account, and the authentication information is sent to the server where it is verified.

[0146] Sending input information

[0147] The user inputs the temperature, weather, destination, and other information for that day, and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[0148] Displaying outfits

[0149] The terminal visually displays the coordinates sent from the server, and displays the suggestions in a format that is easy for the user to check.

[0150] Order Processing

[0151] If the user selects the rental or purchase option, the terminal sends the order data to the server, which then sends the order to the partner external supplier and initiates the delivery process.

[0152] User Roles

[0153] Initial Setup and Registration

[0154] When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits.

[0155] Daily input and confirmation

[0156] Users input the daily weather conditions and destinations, check the outfits sent back from the server, and if they like the outfit, they send their decision to the server via their device.

[0157] Rental and Purchase

[0158] Users select the option to rent or purchase a new fashion item and complete the necessary steps.

[0159] Examples of specific examples and prompt usage

[0160] As an example of actual use, we will explain specific situations in which users use the app.

[0161] A day in the life of User A

[0162] morning

[0163] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[0164] User: Enter your user ID and password and tap the login button.

[0165] Device: Sends authentication information to the server.

[0166] Server: Checks the authentication information against a database and sends the user data to the device if the login is successful.

[0167] Terminal: Displays login success and displays the home screen.

[0168] Entering information

[0169] User: User A enters the information "Sunny", "25 degrees", and "Office" on the home screen.

[0170] Device: Sends this information to the server.

[0171] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[0172] Coordination suggestions

[0173] Server: Referencing User A's registered database, the AI ​​algorithm generates the optimal outfit based on past data, suggesting combinations of T-shirt, jacket, pants, and shoes.

[0174] Server: Sends the generated coordinates to the device.

[0175] Device: Display suggested outfits.

[0176] User: User A reviews the suggestions and selects the outfit if they like it.

[0177] Device: Sends the selected coordinates to the server and saves them.

[0178] Use of subscription services

[0179] User: User A rents a suggested new jacket through a subscription service.

[0180] Terminal: Sends rental orders to the server.

[0181] Server: Sends order data to partner brands and initiates the shipping process.

[0182] Examples of prompt statements

[0183] An example of a prompt that a user might enter into the system is:

[0184] "Tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and humidity of 70%. Please suggest some business casual attire."

[0185] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0186] Step 1:

[0187] User authentication

[0188] Device: The user launches the app and sees the login screen.

[0189] Input: User ID and password

[0190] Output: Sends login information to the server

[0191] User: Enter your user ID and password and tap the login button.

[0192] Device: Sends authentication information to the server.

[0193] Input: User ID and password

[0194] Output: Sending authentication information

[0195] Server: Checks the authentication information against the database, and if the login is successful, sends the user data to the terminal.

[0196] Input: Credentials

[0197] Data calculation: User ID and password verification

[0198] Output: Login success or failure information

[0199] Device: Displays login success and displays the home screen.

[0200] Input: Login success information

[0201] Output: Login success screen displayed

[0202] Step 2:

[0203] Entering information

[0204] User: The user enters the information "sunny," "25 degrees," and "office" from the home screen.

[0205] Input: Temperature, weather, destination information

[0206] Output: Preparing input information for transmission

[0207] Terminal: Sends this information to the server.

[0208] Input: User input information

[0209] Data calculation: Format conversion of input information

[0210] Output: Send to server

[0211] Step 3:

[0212] Meteorological data collection and collation

[0213] Server: Collects the latest weather information from an external weather data API.

[0214] Input: Request to external weather API

[0215] Output: Latest weather data

[0216] Server: Stores the collected weather data in a database.

[0217] Input: Collected weather data

[0218] Data processing: saving to database

[0219] Output: Save completion information

[0220] Server: Matches the information entered by the user with the collected weather data.

[0221] Input: User input information, latest weather data

[0222] Data calculation: Check whether the input information matches the weather data

[0223] Output: Matching result

[0224] Step 4:

[0225] Generating outfit suggestions

[0226] Server: Refers to the user's clothing database to obtain the user's clothing and preferred styles.

[0227] Input: User database query

[0228] Output: Clothing data

[0229] Server: Using AI algorithms, it generates optimal coordination based on weather data, user data, and destination information.

[0230] Input: Weather data, clothing data, destination information

[0231] Data calculation: Coordination suggestions based on AI models

[0232] Output: Generated coordinates

[0233] Server: Sends the generated coordinates to the terminal.

[0234] Input: Generated coordinates

[0235] Output: Send to terminal

[0236] Step 5:

[0237] View and select suggestions

[0238] Terminal: Visually displays the proposed coordination.

[0239] Input: Generated coordinate information

[0240] Output: Display of proposal

[0241] User: Check the suggestions and select the outfit they like.

[0242] Input: Proposal

[0243] Output: Selection information

[0244] Terminal: Sends the selected coordinates to the server.

[0245] Input: User selection information

[0246] Output: Send to server

[0247] Server: Saves the selected coordinates in the user database.

[0248] Input: Selected coordinate information

[0249] Data processing: saving to database

[0250] Output: Save completion information

[0251] Step 6:

[0252] Use of subscription service (optional)

[0253] User: Select the option to rent or buy the suggested new item.

[0254] Input: Rental or purchase selection information

[0255] Output: Order information ready to send

[0256] Terminal: Sends rental or purchase orders to the server.

[0257] Input: User's order information

[0258] Output: Send to server

[0259] Server: Sends order information to affiliated external suppliers and initiates delivery procedures.

[0260] Input: Order Information

[0261] Output: Sending order information to partner suppliers, information on starting delivery procedures

[0262] (Application example 1)

[0263] 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."

[0264] Conventional clothing suggestion systems have not been able to provide sufficient support for users in choosing the most appropriate outfit based on the day's weather conditions and destination. Furthermore, the process of suggesting, renting, and purchasing the latest fashion items is cumbersome, reducing user convenience. Therefore, there was a need for a system that could suggest optimal outfits based on weather conditions and destination, and easily rent or purchase fashion items.

[0265] 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.

[0266] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing an option to rent or purchase fashion items, means for transmitting order data to affiliated external brands, means for proposing new outfits after new items arrive, means for generating outfits using a generative AI model, and means for collecting user input via prompt text. This allows the user to receive optimal outfit suggestions based on weather conditions and destination, and further allows the user to easily rent or purchase the suggested fashion items.

[0267] "Means for collecting weather data" refers to a system for obtaining the latest information such as temperature, weather, humidity, and wind speed from external weather data providers.

[0268] "A means of managing clothing data" is a system for registering and storing the types of clothing owned by users, their attributes, and preferred styles in a database.

[0269] The "means for generating coordination" is an algorithm or program that suggests optimal clothing combinations based on collected weather data and managed clothing data.

[0270] The "means for displaying coordinates" refers to a display device or application for visually presenting the generated coordinates to the user.

[0271] The "means for saving outfits" refers to a system that records the outfits selected by the user in a database for use in future suggestions and analysis.

[0272] "Means for providing rental or purchase options" refers to an interface and system that allows users to choose between renting or purchasing suggested fashion items.

[0273] "Means for sending order data to external brands" refers to a system that sends order information for the items selected by the user to partner brands or retailers and initiates the purchase or rental process.

[0274] The "means for suggesting new coordination" is an algorithm or program for regenerating the latest coordination including newly arrived items and suggesting it to the user.

[0275] A "generative AI model" is an artificial intelligence algorithm that learns from large amounts of data and generates outfits.

[0276] A "means for collecting user input via prompt sentences" is a system for analyzing information entered by a user in natural language and obtaining and processing the required data.

[0277] This invention is a system that allows users to choose the best outfit based on the day's weather conditions and destination. The system is made up of three components: a server, a device, and a user, each of which plays a specific role. It is particularly notable for collecting user input via a generative AI model and prompts.

[0278] Server Roles

[0279] The server is the core of the system and performs the following functions:

[0280] 1. Weather data collection: The server connects to an external weather data API (e.g., Weatherstack) to collect the latest weather information (temperature, weather, humidity, wind speed, etc.), allowing users to understand the weather conditions at their current location or a specified location in real time.

[0281] 2. User Data Management: The server manages a database of the user's clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[0282] 3. Coordination suggestion generation: The server uses a generative AI model to generate optimal outfits based on weather data, user data, and destination information, eliminating the need for users to worry about choosing their daily outfits.

[0283] 4. Saving the outfit: The server saves the outfit selected by the user in a database and uses it as learning data to help with future suggestions.

[0284] 5. Providing rental and purchase options: The server works with partner external brands to provide users with the option to rent or purchase the latest fashion items of their choice.

[0285] 6. Sending order data: The server sends the order information for the items selected by the user to the partner brand or retailer to initiate the purchase or rental process.

[0286] 7. Proposing a new outfit: After new items arrive, the server again uses the generative AI model to propose a new outfit.

[0287] Device Role

[0288] The terminal operated by the user has the following functions:

[0289] 1. User authentication: The device provides an authentication process for the user to log in to their account. The authentication information is sent to the server and verified there.

[0290] 2. Data input and transmission: The terminal prompts the user to input the day's temperature, weather, destination, etc., and transmits this information to the server, which then obtains the data needed to generate the optimal coordinates.

[0291] 3. Display of outfits: The device visually displays the outfits sent from the server, helping the user make a selection by displaying the suggestions in an easy-to-read format.

[0292] 4. Order Processing: If the user selects the rental or purchase option, the device sends the order data to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[0293] User Roles

[0294] Users operate the system and fulfill the following roles:

[0295] 1. Initial setup and registration: When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits.

[0296] 2. Daily information input and confirmation: The user inputs the daily weather conditions and destinations in the prompts and checks the coordinates returned by the server. If the generated coordinates are satisfactory, the user sends the decision to the server via the terminal.

[0297] 3. Rent and Buy: Users select the option to rent or buy a new fashion item and complete the necessary steps.

[0298] Example: A day in the life of User A

[0299] morning

[0300] User A wakes up in the morning, launches the app, and the login screen appears. User A enters their user ID and password and taps the login button. The device sends the authentication information to the server, and the server authenticates the login. If the login is successful, the home screen appears on the device.

[0301] Entering information

[0302] User A inputs the information "sunny," "25 degrees," and "office" using prompts from the home screen. The device sends this information to the server, which then collects the latest weather information from an external weather data API and compares it with User A's information.

[0303] Coordination suggestions

[0304] The server references User A's registration database, and the generative AI model generates the optimal outfit. For example, it suggests a combination of a T-shirt, jacket, pants, and shoes. The generated outfit is sent to the device, where User A checks it. If User A likes it, he or she selects the outfit, and the device sends the selected outfit to the server and saves it.

[0305] Use of subscription services

[0306] If User A wants to rent the suggested new jacket through the subscription service, the device sends a rental order to the server, which then sends the order data to the partner brand and initiates the delivery process.

[0307] Example prompt:

[0308] "It's sunny and 25 degrees today, so I'm heading to the office. Could you recommend an outfit for me? I'd also like to rent the denim jacket you suggested."

[0309] In this way, User A can efficiently choose their daily outfits and always maintain the best fashion. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[0310] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0311] Step 1:

[0312] The server calls an external weather data API to collect current weather data (temperature, weather, humidity, wind speed, etc.) and stores it in a database. The input is the weather data obtained from the API, and the output is a database containing the latest weather data.

[0313] Step 2:

[0314] A user launches a smartphone app and logs in by entering their user ID and password on the login screen. The input is the user's authentication information (user ID and password), and the output is transitioning to the app's home screen. The device sends this authentication information to the server and authenticates the login.

[0315] Step 3:

[0316] The user inputs information such as "sunny," "25 degrees," and "office" using prompts on the home screen. The input is the weather conditions and destination information entered by the user, and the output is to send this information to the server.

[0317] Step 4:

[0318] The server parses the prompt and extracts the input information from the user. The input is the text information of the prompt, and the output is the parsed weather conditions and destination information. The server then compares this with the latest weather data obtained from an external weather data API.

[0319] Step 5:

[0320] The server references the user's registered database and generates the optimal outfit using a generative AI model. The input is the collated weather conditions, destination information, and the user's registered data, and the output is the generated outfit plan.

[0321] Step 6:

[0322] The server sends the generated coordinates to the terminal. The input is the data of the generated coordinates, and the output is the display of the proposed coordinates on the terminal.

[0323] Step 7:

[0324] The user checks the proposed outfits and selects them if they like them. The input is the user's confirmation and selection actions, and the output is the transmission of the selected outfit information from the terminal to the server.

[0325] Step 8:

[0326] The server saves the selected outfit in a database for future suggestions. In this step, the input is the outfit information selected by the user, and the output is the saved outfit data.

[0327] Step 9:

[0328] The user selects to rent or purchase a new item from the proposed items through the subscription service. The input is the user's selection action of renting or purchasing, and the output is the transmission of order information for the selected item from the terminal to the server.

[0329] Step 10:

[0330] The server sends the order data to the partner external brand and starts the delivery procedure. The input is the user's order data, and the output is the transmission of the order data to the external brand and the start of the delivery procedure.

[0331] Step 11:

[0332] After receiving new items, the server uses the generative AI model again to propose new outfits and sends the results to the device. The input is the new item information and existing user data, and the output is the new outfit proposal data.

[0333] 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.

[0334] MODE FOR CARRYING OUT THE INVENTION

[0335] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day, and then provides coordination that takes the user's emotions into consideration. The system works in cooperation with a server, a terminal, and an emotion engine, and each component plays a specific role.

[0336] Server Roles

[0337] The server is the core of the system and performs the following functions:

[0338] 1. Weather data collection: Integrate with external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.). The collected data is used as a basis for learning from past trends and patterns.

[0339] 2. User Data Management: Manages a database of users' clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[0340] 3. Emotion data management: Manage user emotion data sent from the emotion engine and learn past emotion trends.

[0341] 4. Coordination suggestion generation: Using AI algorithms, the system generates optimal outfits based on weather data, user data, destination information, and emotional data, eliminating the need for users to worry about choosing their daily outfits.

[0342] 5. Saving outfits: The outfits selected by the user are saved in a database and used as learning data for future suggestions.

[0343] 6. Offering rental and purchase options: We partner with third-party brands to offer users the option to rent or purchase selected latest fashion items.

[0344] Device Role

[0345] The terminal operated by the user has the following functions:

[0346] 1. User Authentication: Provides an authentication process for users to log in to their accounts. The authentication information is sent to the server and verified there.

[0347] 2. Sending input information: The user inputs the day's temperature, weather, destination, etc. and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[0348] 3. Acquiring emotional data: The emotion engine generates emotional data based on the user's facial expressions and input information, and sends it to the server via the device.

[0349] 4. Display of outfits: The outfits sent from the server are visually displayed. The suggestions are displayed in a format that is easy for the user to check, helping them make a selection.

[0350] 5. Order Processing: If you select the rental or purchase option, the order data is sent to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[0351] User Roles

[0352] Users operate the system and fulfill the following roles:

[0353] 1. Initial setup and registration: When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits. The emotion engine also initially registers the user's emotional data.

[0354] 2. Daily input and confirmation: Enter the daily weather conditions, destination, and emotional data, and check the outfits sent back from the server. If you like the outfit, you can send your decision to the server via your device.

[0355] 3. Rent and Buy: Choose your option to rent or buy a new fashion item and follow the necessary steps.

[0356] Specific examples

[0357] A day in the life of User A

[0358] 1. Morning

[0359] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[0360] User: User A enters his / her user ID and password and taps the login button.

[0361] Device: Sends authentication information to the server.

[0362] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[0363] Device: Displays login success and displays the home screen.

[0364] User: User A inputs the temperature, weather, destination, and emotions for that day. For example, "Sunny," "25 degrees," "Office," and "Feeling a little tired."

[0365] 2. Transmission of information

[0366] Terminal: Sends the entered information to the server.

[0367] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[0368] 3. Coordination suggestions

[0369] Server: Referencing User A's registration database and emotional data, the AI ​​algorithm generates optimal outfits based on past data. For example, it suggests a combination of a shirt, pants, jacket, and shoes made of a relaxed material.

[0370] Server: Sends the generated coordinates to the terminal.

[0371] Device: Display suggested outfits.

[0372] User: User A reviews the suggestions and selects the outfit if they like it.

[0373] Terminal: Sends the selected coordinates to the server and stores them.

[0374] 4. Use of Subscription Services

[0375] User: User A rents the suggested new jacket through a subscription service.

[0376] Terminal: Sends rental orders to the server.

[0377] Server: Sends order data to partner brands and initiates shipping procedures.

[0378] In this way, User A can streamline their daily clothing selection and enjoy optimal fashion that takes their emotions into consideration. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[0379] The processing flow will be explained below.

[0380] Step 1:

[0381] On the device: The user opens the application and the login screen appears. The user enters their user ID and password and taps the login button.

[0382] Step 2:

[0383] Terminal: Sends the entered user ID and password to the server.

[0384] Step 3:

[0385] Server: Compares the received user ID and password with the database. If the login is successful, it sends the user data to the terminal, and if not, it sends an error message to the terminal.

[0386] Step 4:

[0387] Device: If login is successful, display the home screen.

[0388] Step 5:

[0389] User: Enters the weather, temperature, destination (e.g., office, casual outing, formal event), and emotional state (e.g., "slightly tired," "energetic," etc.) for the day.

[0390] Step 6:

[0391] Terminal: Sends the entered information to the server.

[0392] Step 7:

[0393] Server: Accesses external weather data API to collect the latest weather information (temperature, weather conditions), and compares this information with user input.

[0394] Step 8:

[0395] Server: Manages user emotion data sent from the emotion engine and learns past emotion trends.

[0396] Step 9:

[0397] Server: Refers to the user's clothing database and uses AI algorithms to generate optimal outfits based on past weather data and fashion information. For example, it suggests shirts, pants, jackets, and shoes made from relaxing materials.

[0398] Step 10:

[0399] Server: Sends the generated coordinates to the terminal.

[0400] Step 11:

[0401] Device: Visually displays the received outfits, showing a list of combinations of shirts, jackets, pants, shoes, etc.

[0402] Step 12:

[0403] User: Select the outfit they like from the ones presented. Once they have made their selection, they tap the confirm button.

[0404] Step 13:

[0405] Terminal: Sends the selected coordinate information to the server.

[0406] Step 14:

[0407] Server: The selected coordinates are saved in a database and used as learning data for future suggestions.

[0408] Step 15:

[0409] User: Selects a subscription option to rent or purchase new fashion items included in the suggested outfits.

[0410] Step 16:

[0411] Terminal: Sends rental or purchase order data to the server.

[0412] Step 17:

[0413] Server: Sends order data to partner external brands and initiates shipping procedures.

[0414] Step 18:

[0415] User: After receiving new items, the user uses the application again to receive new outfit suggestions based on the new items.

[0416] In this way, a system is realized that allows users to efficiently choose their daily outfits and enjoy optimal fashion that takes their emotions into consideration.

[0417] Example 2

[0418] 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."

[0419] Conventional coordination systems were limited to making suggestions based on the user's weather conditions and the clothing they owned, and were unable to make coordination suggestions that took into account the user's emotions or current mood. Furthermore, when users wanted to try out the latest fashion items, the process was cumbersome and burdensome for users. This resulted in a decrease in satisfaction and efficiency with fashion.

[0420] 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.

[0421] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for acquiring and managing the user's emotional data, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing options to rent or purchase fashion items, means for transmitting order data to affiliated external brands, and means for proposing new outfits after new items arrive. This makes it possible to propose outfits that reflect the user's emotions and current mood in addition to weather conditions and data on the clothing they own, and also allows them to smoothly try on and purchase the latest fashion items.

[0422] "Latest weather data" refers to environmental information such as current and near-future temperature, weather, humidity, and wind speed.

[0423] "User clothing data" refers to information about the clothing items owned by the user, including the type, color, material, style, and size of the item.

[0424] "User emotional data" refers to data that indicates the user's current emotions and moods as inferred from their facial expressions, input information, and past data.

[0425] "Means for generating outfits" refers to algorithms or systems that suggest optimal outfit combinations based on collected weather data, data on the user's clothing, and emotional data.

[0426] "Means for displaying coordination" refers to a device or application for visually presenting the generated outfit combinations to the user.

[0427] "Means for saving outfits" refers to a system that records the outfit combinations selected by the user in a database for future reference or as learning data.

[0428] "Means for providing rental or purchase options" refers to systems or applications that suggest options for users to rent or purchase their favorite latest fashion items and assist them in the process.

[0429] "Means for transmitting order data to partnering third-party brands" refers to a system that transmits order information to third-party fashion brands and retailers based on the rental or purchase option selected by the user.

[0430] "Means to suggest new outfits after new items arrive" refers to algorithms or systems that incorporate the user's newly acquired fashion items and suggest optimal outfit combinations again.

[0431] "Historical weather data" refers to information about temperature and weather conditions over a specific period in the past.

[0432] "Past emotion data" refers to data records regarding emotions and moods that a user has felt in the past.

[0433] "Fashion information" refers to data about the latest trends, styles, and fashions.

[0434] "User input means" refers to an interface or device that allows a user to manually input information such as temperature, weather, destination, and emotion.

[0435] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day, and then provides coordination that takes the user's emotions into consideration. The system works in cooperation with a server, a terminal, and an emotion engine, and each component plays a specific role.

[0436] Server Roles

[0437] The server is the core of the system and performs the following functions:

[0438] 1. Meteorological data collection:

[0439] The server connects to an external weather data API (e.g., OpenWeatherMap API) to collect the latest weather information (temperature, weather, humidity, wind speed, etc.), which allows it to always provide suggestions based on the latest weather data.

[0440] 2. Managing your data:

[0441] The server manages a database of the user's clothing and style preferences, allowing the user to keep an up-to-date inventory of the clothing items they own.

[0442] 3. Emotional Data Management:

[0443] The server manages the user's emotional data sent from the emotion engine and learns past emotional trends. This information is reflected in the outfit suggestions.

[0444] 4. Coordination proposal generation:

[0445] The server uses AI algorithms (e.g., models using TensorFlow or PyTorch) to generate optimal outfits based on weather data, user data, destination information, and emotional data. This process allows users to receive more accurate outfit suggestions.

[0446] 5. Save your outfit:

[0447] The server stores the user's selected outfits in a database and uses them as learning data to help with future suggestions.

[0448] 6. Offering Rental and Purchase Options:

[0449] The server works with partner external brands to provide users with the option to rent or purchase the latest fashion items of their choice, allowing them to easily try out the latest fashions.

[0450] Device Role

[0451] The terminal operated by the user has the following functions:

[0452] 1. User authentication:

[0453] The device provides an authentication process for the user to log into their account, and the authentication information is sent to the server where it is verified.

[0454] 2. Submitting input information:

[0455] The user inputs the day's temperature, weather, destination, etc. into the device, and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[0456] 3. Acquiring emotion data:

[0457] The device's emotion engine generates emotion data based on the user's facial expressions and input information, and sends it to a server via the device. The emotion engine uses facial recognition technology and natural language processing (NLP) technology.

[0458] 4. Show your outfit:

[0459] The terminal visually displays the coordinates sent from the server, allowing the user to easily check and select the suggestions.

[0460] 5. Order Processing:

[0461] If the user selects the rental or purchase option, the device sends the order data to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[0462] User Roles

[0463] The user operates the system and performs the following roles:

[0464] 1. Initial Setup and Registration:

[0465] When using the app for the first time, users register their clothing and preferred styles. The server then manages this data and uses it to suggest outfits. The emotion engine also initially registers the user's emotional data.

[0466] 2. Daily input and confirmation:

[0467] Users input their daily weather conditions, destination, and emotions, and then check the outfits sent back from the server. If they like the outfit, they can send their decision to the server via their device.

[0468] 3. Rental and Purchase:

[0469] Users select the option to rent or purchase a new fashion item and complete the necessary steps.

[0470] Specific examples

[0471] A day in the life of User A

[0472] 1. Morning

[0473] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[0474] User: User A enters his / her user ID and password and taps the login button.

[0475] Device: Sends authentication information to the server.

[0476] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[0477] Device: Displays login success and displays the home screen.

[0478] User: User A inputs the temperature, weather, destination, and emotions for that day. For example, "Sunny," "25 degrees," "Office," and "Feeling a little tired."

[0479] 2. Transmission of information

[0480] Terminal: Sends the entered information to the server.

[0481] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[0482] 3. Coordination suggestions

[0483] Server: Referencing User A's registration database and emotional data, the AI ​​algorithm generates optimal outfits based on past data. For example, it suggests a combination of a shirt, pants, jacket, and shoes made of a relaxed material.

[0484] Server: Sends the generated coordinates to the terminal.

[0485] Device: Display suggested outfits.

[0486] User: User A reviews the suggestions and selects the outfit if they like it.

[0487] Terminal: Sends the selected coordinates to the server and stores them.

[0488] 4. Use of Subscription Services

[0489] User: User A rents the suggested new jacket through a subscription service.

[0490] Terminal: Sends rental orders to the server.

[0491] Server: Sends order data to partner brands and initiates shipping procedures.

[0492] In this way, User A can streamline their daily clothing selection and enjoy optimal fashion that takes their emotions into consideration. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[0493] Prompt Sentence Examples

[0494] "25 degrees, sunny, office, feeling a bit tired"

[0495] Based on this information, the system provides input data for a generative AI model, allowing the device to receive optimal outfit suggestions.

[0496] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0497] Step 1: User authentication

[0498] Input: User ID and Password

[0499] Output: Home screen

[0500] Device: Launch the app and the login screen will appear.

[0501] User: Enter your user ID and password and tap the login button.

[0502] Device: Sends authentication information to the server.

[0503] Server: Checks the received authentication information against a database and returns a success or failure result to the terminal.

[0504] Terminal: If login is successful, the home screen is displayed and user data is sent to the terminal.

[0505] Step 2: Initial data entry

[0506] Input: User's clothing, preferred style, and emotional data

[0507] Output: Registration complete confirmation message

[0508] User: Register your clothes and preferred style on the home screen. Also, register your initial emotional data.

[0509] Terminal: Sends data entered by the user to the server.

[0510] Server: Stores the received data in a database and sends a confirmation message to the terminal that registration is complete.

[0511] Step 3: Meteorological data collection

[0512] Input: Weather information for the day, destination entered by the user

[0513] Output: Latest weather data

[0514] User: Enter the weather conditions for the day (e.g., "sunny" and "25 degrees") and destination.

[0515] Terminal: Sends the entered information to the server.

[0516] Server: Uses an external weather data API (e.g., OpenWeatherMap API) to collect the latest weather information.

[0517] Server: Compares the collected weather data with the information entered by the user and stores it in a database.

[0518] Step 4: Acquire emotion data

[0519] Input: User's facial expression, input information

[0520] Output: Emotion data

[0521] Device: The emotion engine captures the user's facial expressions with a camera, analyzes the data, and generates emotion data.

[0522] Terminal: Sends the generated emotion data to the server.

[0523] Server: Stores the emotion data in a database for future analysis.

[0524] Step 5: Coordinate generation

[0525] Input: Weather data, user data, emotion data, destination information

[0526] Output: Optimal Coordination

[0527] Server: Based on the received weather data, user data, emotion data, and destination information, an AI algorithm is used to generate the optimal coordinates. At this stage, a generative AI model (e.g., TensorFlow or PyTorch) is used.

[0528] Server: Sends the generated coordinate data to the terminal.

[0529] Step 6: Coordination presentation and selection

[0530] Input: Best outfit

[0531] Output: Selected coordinates

[0532] Terminal: Visually displays the outfit received from the server (e.g., a relaxed shirt, pants, jacket, and shoes).

[0533] User: Check the presented outfits and select if you like them.

[0534] Terminal: Sends the selected coordinate information to the server.

[0535] Step 7: Save your outfit

[0536] Input: Selected coordinates

[0537] Output: Save complete confirmation message

[0538] Server: The selected coordinates are stored in a database and used as learning data for future suggestions.

[0539] Server: Sends a confirmation message to the terminal that the save is complete.

[0540] Step 8: Rental / Purchase Process

[0541] Input: The rental or purchase option selected by the user

[0542] Output: Order completed confirmation message

[0543] User: Selects an option to rent or buy a fashion item, such as a new jacket.

[0544] Terminal: Sends the user's order information to the server.

[0545] Server: Sends order data to partner external brands and initiates shipping procedures.

[0546] Server: Sends a confirmation message to the terminal that the order has been completed.

[0547] (Application example 2)

[0548] 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."

[0549] Conventional outfit suggestion systems can suggest outfits based on the user's weather conditions and preferences, but they cannot consider the user's emotions. It is also difficult to suggest appropriate outfits based on the driver's emotions inside an autonomous vehicle. This makes it difficult to suggest optimal outfits to reduce fatigue and stress, especially during long driving trips.

[0550] 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.

[0551] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing options for renting or purchasing clothing items, means for sending order data to affiliated external brands, means for suggesting new outfits after new items arrive, means for acquiring facial images using a camera attached to the information entertainment system in the autonomous vehicle and analyzing emotional data, means for suggesting outfits that suit the driver based on the analyzed emotional data, and means for displaying the suggested outfits on an in-vehicle display. This enables optimal outfit suggestions based on the driver's emotions and weather conditions, improving driving comfort and safety.

[0552] "Weather data" is information about weather conditions such as temperature, weather, humidity, and wind speed.

[0553] "Clothing data" refers to information about the type, design, material, color, size, etc. of clothing owned by the user.

[0554] "Outfit" refers to the coordination suggested based on weather conditions and emotions.

[0555] An "information entertainment system" is a system installed in an autonomous vehicle for providing information and displaying entertainment content.

[0556] "Camera" refers to a device that captures images, especially one installed in an autonomous vehicle.

[0557] "Emotional data" is information about the user's emotional state analyzed based on images captured by a camera.

[0558] "External brands" refer to companies or brands that partner with the system to rent or sell clothing items to users.

[0559] "Coordination" refers to the optimal combination of clothing suggested to the user.

[0560] "Rental" refers to a service that allows you to borrow clothing items for a certain period of time.

[0561] "Purchase" refers to purchasing an item of clothing to own it.

[0562] System Overview:

[0563] This invention is a system that proposes optimal outfits based on the user's weather conditions, destination, and emotion data for the day. The system operates in cooperation with a server, a terminal, and an emotion engine.

[0564] Server Role:

[0565] The server is the center of the system and has the following responsibilities:

[0566] 1. Weather data collection: The server uses an external weather data API to collect the latest weather data and then suggests appropriate outfits to the user based on that data.

[0567] 2. Managing clothing data: The server manages the clothing data registered by the user.

[0568] 3. Emotion data management: The server analyzes the emotion data acquired by the camera inside the autonomous vehicle and uses it to propose appropriate coordination.

[0569] 4. Coordination generation: The server uses AI algorithms to generate optimal coordination based on weather data, clothing data, and emotional data.

[0570] 5. Sending proposal: The server sends the generated coordinates to the terminal, which then displays them on the in-car display.

[0571] Device role:

[0572] The user-operated device has the following features:

[0573] 1. User Authentication: Provides an authentication process for users to log in to their accounts.

[0574] 2. Data input: The user inputs the weather conditions, destination, and emotions for the day and sends this to the server.

[0575] 3. Emotion data acquisition: Using a camera installed inside the vehicle, an image of the user's face is acquired and sent to the emotion engine.

[0576] 4. Coordination display: Displays the coordination proposals sent from the server.

[0577] User role:

[0578] The user interfaces with the system to:

[0579] 1. Initial setup and registration: By registering your clothing and preferred styles in the system, you will be prepared to receive optimal outfit suggestions.

[0580] 2. Daily data input: By inputting daily weather conditions, destinations, and emotions, the server will suggest the best outfits for you.

[0581] 3. Review and select the suggestions: Review the outfits sent by the server and select them if you like them.

[0582] Hardware and software used:

[0583] Hardware:

[0584] Information and entertainment systems in autonomous vehicles

[0585] In-car camera

[0586] software:

[0587] requests library (weather data acquisition)

[0588] OpenCV (emotion analysis)

[0589] TensorFlow (AI algorithm)

[0590] Examples:

[0591] Example 1: Morning preparation

[0592] Before getting into a self-driving vehicle, users input "sunny," "25 degrees," "office," and "feeling a bit tired" into a smartphone app. The system then uses weather data to suggest outfits for light shirts and pants. It also analyzes facial images to recommend comfortable clothing.

[0593] Example prompt for a generative AI model:

[0594] "Weather data: Tokyo, Temperature: 28°C, Emotion data: Happy: 0.7, Sad: 0.1, Destination: Office. What is the best outfit?"

[0595] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0596] Step 1:

[0597] User authentication

[0598] Input: User ID and Password

[0599] What happens: A user logs into an app using a device, which sends their credentials to a server, which checks them against a database for authentication.

[0600] Output: If authentication is successful, send user data to the device. Login is successful and the home screen is displayed.

[0601] Step 2:

[0602] Data Entry

[0603] Input: Weather conditions, destination information, emotional state

[0604] Processing: The user inputs the weather conditions, destination, and emotions for the day into the device, which then sends this information to the server.

[0605] Output: The submitted data is stored on the server and used to generate coordinates.

[0606] Step 3:

[0607] Weather data collection

[0608] Input: User's destination information

[0609] Processing: The server uses an external weather data API to gather the latest weather information for the user's destination, sending an API request to get information such as temperature, weather, humidity, and wind speed.

[0610] Output: The acquired weather data is saved and used to generate coordinates.

[0611] Step 4:

[0612] Emotional Data Analysis

[0613] Input: Facial image captured by the in-car camera

[0614] Processing: The device captures the user's facial expressions using the in-car camera and sends the image data to the emotion engine, which uses OpenCV to preprocess the images and TensorFlow AI models to analyze emotions.

[0615] Output: The emotion analysis results are sent to the server and stored as user emotion data.

[0616] Step 5:

[0617] Coordinate generation

[0618] Input: Weather data, clothing data, emotion data

[0619] Processing: The server uses AI algorithms to generate the optimal outfit based on collected weather data, accumulated clothing data, and emotion analysis results. The generation process involves selecting materials based on temperature and suggesting colors and styles based on emotional state.

[0620] Output: The generated coordinates are sent from the server to the device.

[0621] Step 6:

[0622] Displaying outfits

[0623] Input: Generated coordinates

[0624] Processing: The terminal receives the coordinates sent from the server and displays them on the in-car display. The user confirms the displayed coordinates.

[0625] Output: The coordinates are visually presented for user confirmation.

[0626] Step 7:

[0627] Select and save outfits

[0628] Input: User's choice

[0629] Process: The user selects their favorite outfit and sends the selection to the server via their device. The server stores the selected outfit in a database for future suggestions.

[0630] Output: The selected coordinates are saved.

[0631] Step 8:

[0632] Rental and purchase procedures

[0633] Input: User's rental or purchase intent

[0634] Processing: If the user decides to rent or purchase a new clothing item, they submit the order via their device to the server, which then sends the order data to the partnering external brand and initiates the delivery process.

[0635] Output: The order is placed and the item is delivered.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] [Second embodiment]

[0640] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0641] 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.

[0642] 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).

[0643] 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.

[0644] 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.

[0645] 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).

[0646] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0647] 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.

[0648] 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.

[0649] 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.

[0650] 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.

[0651] 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."

[0652] MODE FOR CARRYING OUT THE INVENTION

[0653] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day. This system is made up of three components: a server, a terminal, and a user, who exchange information with each other, and each component plays a specific role.

[0654] Server Roles

[0655] The server is the core of the system and performs the following functions:

[0656] 1. Weather data collection: Integrate with external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.). The collected data is used as a basis for learning from past trends and patterns.

[0657] 2. User Data Management: Manages a database of users' clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[0658] 3. Generating outfit suggestions: Using AI algorithms, the system generates optimal outfit suggestions based on weather data, user data, and destination information, eliminating the need for users to worry about choosing their daily outfits.

[0659] 4. Saving outfits: The outfits selected by the user are saved in a database and used as learning data for future suggestions.

[0660] 5. Offering rental and purchase options: We partner with third-party brands to offer users the option to rent or purchase the latest fashion items of their choice.

[0661] Device Role

[0662] The terminal operated by the user has the following functions:

[0663] 1. User Authentication: Provides an authentication process for users to log in to their accounts. The authentication information is sent to the server and verified there.

[0664] 2. Sending input information: The user inputs the day's temperature, weather, destination, etc. and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[0665] 3. Display of outfits: The outfits sent from the server are visually displayed. The suggestions are displayed in a format that is easy for the user to check, helping them make a selection.

[0666] 4. Order Processing: If you select the rental or purchase option, the order data is sent to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[0667] User Roles

[0668] Users operate the system and fulfill the following roles:

[0669] 1. Initial setup and registration: When using the app for the first time, you will need to register your clothing and preferred style. This data will be managed on the server and used to suggest outfits.

[0670] 2. Daily input and confirmation: Enter the daily weather conditions and destination, and check the coordinates returned by the server. If you like it, send your decision to the server via your device.

[0671] 3. Rent and Buy: Choose your option to rent or buy a new fashion item and follow the necessary steps.

[0672] Specific examples

[0673] A day in the life of User A

[0674] 1. Morning

[0675] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[0676] User: User A enters his / her user ID and password and taps the login button.

[0677] Device: Sends authentication information to the server.

[0678] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[0679] Device: Displays login success and displays the home screen.

[0680] 2. Enter your information

[0681] User: User A enters the information "sunny," "25 degrees," and "office" on the home screen.

[0682] Terminal: Sends this information to the server.

[0683] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[0684] 3. Coordination suggestions

[0685] Server: Referencing User A's registered database, the AI ​​algorithm generates the optimal outfit based on past data, suggesting combinations of T-shirt, jacket, pants, and shoes.

[0686] Server: Sends the generated coordinates to the terminal.

[0687] Device: Display suggested outfits.

[0688] User: User A reviews the suggestions and selects the outfit if they like it.

[0689] Terminal: Sends the selected coordinates to the server and stores them.

[0690] 4. Use of Subscription Services

[0691] User: User A rents the suggested new jacket through a subscription service.

[0692] Terminal: Sends rental orders to the server.

[0693] Server: Sends order data to partner brands and initiates shipping procedures.

[0694] In this way, User A can streamline their daily clothing selection and always maintain the best fashion. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[0695] The processing flow will be explained below.

[0696] Step 1:

[0697] On the device: The user opens the application and the login screen appears. The user enters their user ID and password and taps the login button.

[0698] Step 2:

[0699] Terminal: Sends the entered user ID and password to the server.

[0700] Step 3:

[0701] Server: Compares the received user ID and password with the database. If the login is successful, sends the user data to the terminal. If not successful, sends an error message to the terminal.

[0702] Step 4:

[0703] Device: If login is successful, display the home screen.

[0704] Step 5:

[0705] User: Enters the weather for the day, temperature, and destination (e.g., office, casual outing, formal event).

[0706] Step 6:

[0707] Terminal: Sends the entered information to the server.

[0708] Step 7:

[0709] Server: Accesses external weather data API to collect the latest weather information (temperature, weather conditions), and compares this information with user input.

[0710] Step 8:

[0711] Server: Refers to the database of the user's clothing and uses AI algorithms to generate optimal outfits based on past weather data and fashion information. For example, it suggests shirts, jackets, pants, shoes, etc.

[0712] Step 9:

[0713] Server: Sends the generated coordinates to the terminal.

[0714] Step 10:

[0715] Device: Visually displays the received outfits, showing a list of combinations of shirts, jackets, pants, shoes, etc.

[0716] Step 11:

[0717] User: Select the outfit they like from the ones presented. Once they have made their selection, they tap the confirm button.

[0718] Step 12:

[0719] Terminal: Sends the selected coordinate information to the server.

[0720] Step 13:

[0721] Server: The selected coordinates are saved in a database and used as learning data for future suggestions.

[0722] Step 14:

[0723] User: Selects a subscription option to rent or purchase new fashion items included in the suggested outfits.

[0724] Step 15:

[0725] Terminal: Sends rental or purchase order data to the server.

[0726] Step 16:

[0727] Server: Sends order data to partner external brands and initiates shipping procedures.

[0728] Step 17:

[0729] User: After receiving new items, the user uses the application again to receive new outfit suggestions based on the new items.

[0730] In this way, a system is realized that allows users to efficiently choose their daily outfits and always enjoy the most appropriate fashion.

[0731] Example 1

[0732] 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."

[0733] In modern society, choosing the best outfit for each day based on weather conditions and schedules is a tedious task for many users. Managing existing clothing and renting or purchasing new fashion items can also be time-consuming. There is a need for a way to efficiently solve these issues, simplify daily outfit selection, and ensure optimal fashion at all times.

[0734] 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.

[0735] In this invention, the server includes means for collecting the latest weather data, means for managing the user's clothing data, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing the option to rent or purchase fashion items, means for transmitting order data to affiliated external suppliers, means for proposing new outfits after new items arrive, means for transmitting daily temperature, weather, and destination information entered by the user, means for comparing the weather data with the user's clothing data, and means for generating outfits using an AI algorithm. This allows users to easily select optimal outfits based on daily weather conditions and plans, and enables efficient clothing management and the rental or purchase of new items.

[0736] "Weather data" is information about weather conditions such as temperature, weather, humidity, and wind speed.

[0737] "User's clothing data" refers to data including details of clothing owned by the user, such as style, size, and color.

[0738] The "coordination generation means" is a system that automatically suggests optimal outfit combinations based on weather data and the user's clothing data.

[0739] The "means for displaying generated coordinated outfits" is an interface for visually displaying to the user the outfit combinations proposed by the server or terminal.

[0740] The "coordinate storage means" is a system that stores the outfit combinations selected by the user in a database.

[0741] "Rental or purchase option providing means" refers to a system that provides a user with the option to rent or purchase a suggested fashion item.

[0742] "Order data transmission means" refers to a means for transmitting a user's rental or purchase order to an affiliated external supplier.

[0743] The "new coordination suggestion method" is a system that suggests new outfit combinations that include new items after the user receives them.

[0744] The "means for transmitting daily temperature, weather, and destination information" is a system that transmits information about the temperature, weather, and destination of the day entered by the user to the server.

[0745] The "means for comparing weather data with user's clothing data" is a means for comparing collected weather data with the user's clothing data to select the optimal outfit.

[0746] "A means for generating coordination using an AI algorithm" is a system that uses an artificial intelligence algorithm to generate optimal clothing combinations.

[0747] The present invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day. This system is made up of three components: a server, a terminal, and a user, who exchange information with each other, and each component plays a specific role.

[0748] Server Roles

[0749] Weather data collection

[0750] The server connects to external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.) using software such as the OpenWeatherMap API or WeatherStack API. The collected data is stored in a database and used as a basis for learning from past trends and patterns.

[0751] Managing User Data

[0752] The server manages a database of the user's clothing and style preferences, which is used to keep the user's inventory of clothing items up to date.

[0753] Generating outfit suggestions

[0754] The server uses AI algorithms to generate optimal trips based on weather data, user data, and destination information, using machine learning frameworks such as TensorFlow and PyTorch.

[0755] Save your outfit

[0756] The coordination selected by the user is stored in a database and used as learning data to help with future suggestions.

[0757] Offering rental and purchase options

[0758] The server works with affiliated external suppliers, such as general online fashion stores, to provide users with the option to rent or purchase selected latest fashion items.

[0759] Device Role

[0760] User authentication

[0761] The device provides an authentication process for the user to log into their account, and the authentication information is sent to the server where it is verified.

[0762] Sending input information

[0763] The user inputs the temperature, weather, destination, and other information for that day, and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[0764] Displaying outfits

[0765] The terminal visually displays the coordinates sent from the server, and displays the suggestions in a format that is easy for the user to check.

[0766] Order Processing

[0767] If the user selects the rental or purchase option, the terminal sends the order data to the server, which then sends the order to the partner external supplier and initiates the delivery process.

[0768] User Roles

[0769] Initial Setup and Registration

[0770] When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits.

[0771] Daily input and confirmation

[0772] Users input the daily weather conditions and destinations, check the outfits sent back from the server, and if they like the outfit, they send their decision to the server via their device.

[0773] Rental and Purchase

[0774] Users select the option to rent or purchase a new fashion item and complete the necessary steps.

[0775] Examples of specific examples and prompt usage

[0776] As an example of actual use, we will explain specific situations in which users use the app.

[0777] A day in the life of User A

[0778] morning

[0779] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[0780] User: Enter your user ID and password and tap the login button.

[0781] Device: Sends authentication information to the server.

[0782] Server: Checks the authentication information against a database and sends the user data to the device if the login is successful.

[0783] Terminal: Displays login success and displays the home screen.

[0784] Entering information

[0785] User: User A enters the information "Sunny", "25 degrees", and "Office" on the home screen.

[0786] Device: Sends this information to the server.

[0787] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[0788] Coordination suggestions

[0789] Server: Referencing User A's registered database, the AI ​​algorithm generates the optimal outfit based on past data, suggesting combinations of T-shirt, jacket, pants, and shoes.

[0790] Server: Sends the generated coordinates to the device.

[0791] Device: Display suggested outfits.

[0792] User: User A reviews the suggestions and selects the outfit if they like it.

[0793] Device: Sends the selected coordinates to the server and saves them.

[0794] Use of subscription services

[0795] User: User A rents a suggested new jacket through a subscription service.

[0796] Terminal: Sends rental orders to the server.

[0797] Server: Sends order data to partner brands and initiates the shipping process.

[0798] Examples of prompt statements

[0799] An example of a prompt that a user might enter into the system is:

[0800] "Tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and humidity of 70%. Please suggest some business casual attire."

[0801] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0802] Step 1:

[0803] User authentication

[0804] Device: The user launches the app and sees the login screen.

[0805] Input: User ID and password

[0806] Output: Sends login information to the server

[0807] User: Enter your user ID and password and tap the login button.

[0808] Device: Sends authentication information to the server.

[0809] Input: User ID and password

[0810] Output: Sending authentication information

[0811] Server: Checks the authentication information against the database, and if the login is successful, sends the user data to the terminal.

[0812] Input: Credentials

[0813] Data calculation: User ID and password verification

[0814] Output: Login success or failure information

[0815] Device: Displays login success and displays the home screen.

[0816] Input: Login success information

[0817] Output: Login success screen displayed

[0818] Step 2:

[0819] Entering information

[0820] User: The user enters the information "sunny," "25 degrees," and "office" from the home screen.

[0821] Input: Temperature, weather, destination information

[0822] Output: Preparing input information for transmission

[0823] Terminal: Sends this information to the server.

[0824] Input: User input information

[0825] Data calculation: Format conversion of input information

[0826] Output: Send to server

[0827] Step 3:

[0828] Meteorological data collection and collation

[0829] Server: Collects the latest weather information from an external weather data API.

[0830] Input: Request to external weather API

[0831] Output: Latest weather data

[0832] Server: Stores the collected weather data in a database.

[0833] Input: Collected weather data

[0834] Data processing: saving to database

[0835] Output: Save completion information

[0836] Server: Matches the information entered by the user with the collected weather data.

[0837] Input: User input information, latest weather data

[0838] Data calculation: Check whether the input information matches the weather data

[0839] Output: Matching result

[0840] Step 4:

[0841] Generating outfit suggestions

[0842] Server: Refers to the user's clothing database to obtain the user's clothing and preferred styles.

[0843] Input: User database query

[0844] Output: Clothing data

[0845] Server: Using AI algorithms, it generates optimal coordination based on weather data, user data, and destination information.

[0846] Input: Weather data, clothing data, destination information

[0847] Data calculation: Coordination suggestions based on AI models

[0848] Output: Generated coordinates

[0849] Server: Sends the generated coordinates to the terminal.

[0850] Input: Generated coordinates

[0851] Output: Send to terminal

[0852] Step 5:

[0853] View and select suggestions

[0854] Terminal: Visually displays the proposed coordination.

[0855] Input: Generated coordinate information

[0856] Output: Display of proposal

[0857] User: Check the suggestions and select the outfit they like.

[0858] Input: Proposal

[0859] Output: Selection information

[0860] Terminal: Sends the selected coordinates to the server.

[0861] Input: User selection information

[0862] Output: Send to server

[0863] Server: Saves the selected coordinates in the user database.

[0864] Input: Selected coordinate information

[0865] Data processing: saving to database

[0866] Output: Save completion information

[0867] Step 6:

[0868] Use of subscription service (optional)

[0869] User: Select the option to rent or buy the suggested new item.

[0870] Input: Rental or purchase selection information

[0871] Output: Order information ready to send

[0872] Terminal: Sends rental or purchase orders to the server.

[0873] Input: User's order information

[0874] Output: Send to server

[0875] Server: Sends order information to affiliated external suppliers and initiates delivery procedures.

[0876] Input: Order Information

[0877] Output: Sending order information to partner suppliers, information on starting delivery procedures

[0878] (Application example 1)

[0879] 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."

[0880] Conventional clothing suggestion systems have not been able to provide sufficient support for users in choosing the most appropriate outfit based on the day's weather conditions and destination. Furthermore, the process of suggesting, renting, and purchasing the latest fashion items is cumbersome, reducing user convenience. Therefore, there was a need for a system that could suggest optimal outfits based on weather conditions and destination, and easily rent or purchase fashion items.

[0881] 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.

[0882] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing an option to rent or purchase fashion items, means for transmitting order data to affiliated external brands, means for proposing new outfits after new items arrive, means for generating outfits using a generative AI model, and means for collecting user input via prompt text. This allows the user to receive optimal outfit suggestions based on weather conditions and destination, and further allows the user to easily rent or purchase the suggested fashion items.

[0883] "Means for collecting weather data" refers to a system for obtaining the latest information such as temperature, weather, humidity, and wind speed from external weather data providers.

[0884] "A means of managing clothing data" is a system for registering and storing the types of clothing owned by users, their attributes, and preferred styles in a database.

[0885] The "means for generating coordination" is an algorithm or program that suggests optimal clothing combinations based on collected weather data and managed clothing data.

[0886] The "means for displaying coordinates" refers to a display device or application for visually presenting the generated coordinates to the user.

[0887] The "means for saving outfits" refers to a system that records the outfits selected by the user in a database for use in future suggestions and analysis.

[0888] "Means for providing rental or purchase options" refers to an interface and system that allows users to choose between renting or purchasing suggested fashion items.

[0889] "Means for sending order data to external brands" refers to a system that sends order information for the items selected by the user to partner brands or retailers and initiates the purchase or rental process.

[0890] The "means for suggesting new coordination" is an algorithm or program for regenerating the latest coordination including newly arrived items and suggesting it to the user.

[0891] A "generative AI model" is an artificial intelligence algorithm that learns from large amounts of data and generates outfits.

[0892] A "means for collecting user input via prompt sentences" is a system for analyzing information entered by a user in natural language and obtaining and processing the required data.

[0893] This invention is a system that allows users to choose the best outfit based on the day's weather conditions and destination. The system is made up of three components: a server, a device, and a user, each of which plays a specific role. It is particularly notable for collecting user input via a generative AI model and prompts.

[0894] Server Roles

[0895] The server is the core of the system and performs the following functions:

[0896] 1. Weather data collection: The server connects to an external weather data API (e.g., Weatherstack) to collect the latest weather information (temperature, weather, humidity, wind speed, etc.), allowing users to understand the weather conditions at their current location or a specified location in real time.

[0897] 2. User Data Management: The server manages a database of the user's clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[0898] 3. Coordination suggestion generation: The server uses a generative AI model to generate optimal outfits based on weather data, user data, and destination information, eliminating the need for users to worry about choosing their daily outfits.

[0899] 4. Saving the outfit: The server saves the outfit selected by the user in a database and uses it as learning data to help with future suggestions.

[0900] 5. Providing rental and purchase options: The server works with partner external brands to provide users with the option to rent or purchase the latest fashion items of their choice.

[0901] 6. Sending order data: The server sends the order information for the items selected by the user to the partner brand or retailer to initiate the purchase or rental process.

[0902] 7. Proposing a new outfit: After new items arrive, the server again uses the generative AI model to propose a new outfit.

[0903] Device Role

[0904] The terminal operated by the user has the following functions:

[0905] 1. User authentication: The device provides an authentication process for the user to log in to their account. The authentication information is sent to the server and verified there.

[0906] 2. Data input and transmission: The terminal prompts the user to input the day's temperature, weather, destination, etc., and transmits this information to the server, which then obtains the data needed to generate the optimal coordinates.

[0907] 3. Display of outfits: The device visually displays the outfits sent from the server, helping the user make a selection by displaying the suggestions in an easy-to-read format.

[0908] 4. Order Processing: If the user selects the rental or purchase option, the device sends the order data to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[0909] User Roles

[0910] Users operate the system and fulfill the following roles:

[0911] 1. Initial setup and registration: When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits.

[0912] 2. Daily information input and confirmation: The user inputs the daily weather conditions and destinations in the prompts and checks the coordinates returned by the server. If the generated coordinates are satisfactory, the user sends the decision to the server via the terminal.

[0913] 3. Rent and Buy: Users select the option to rent or buy a new fashion item and complete the necessary steps.

[0914] Example: A day in the life of User A

[0915] morning

[0916] User A wakes up in the morning, launches the app, and the login screen appears. User A enters their user ID and password and taps the login button. The device sends the authentication information to the server, and the server authenticates the login. If the login is successful, the home screen appears on the device.

[0917] Entering information

[0918] User A inputs the information "sunny," "25 degrees," and "office" using prompts from the home screen. The device sends this information to the server, which then collects the latest weather information from an external weather data API and compares it with User A's information.

[0919] Coordination suggestions

[0920] The server references User A's registration database, and the generative AI model generates the optimal outfit. For example, it suggests a combination of a T-shirt, jacket, pants, and shoes. The generated outfit is sent to the device, where User A checks it. If User A likes it, he or she selects the outfit, and the device sends the selected outfit to the server and saves it.

[0921] Use of subscription services

[0922] If User A wants to rent the suggested new jacket through the subscription service, the device sends a rental order to the server, which then sends the order data to the partner brand and initiates the delivery process.

[0923] Example prompt:

[0924] "It's sunny and 25 degrees today, so I'm heading to the office. Could you recommend an outfit for me? I'd also like to rent the denim jacket you suggested."

[0925] In this way, User A can efficiently choose their daily outfits and always maintain the best fashion. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[0926] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0927] Step 1:

[0928] The server calls an external weather data API to collect current weather data (temperature, weather, humidity, wind speed, etc.) and stores it in a database. The input is the weather data obtained from the API, and the output is a database containing the latest weather data.

[0929] Step 2:

[0930] A user launches a smartphone app and logs in by entering their user ID and password on the login screen. The input is the user's authentication information (user ID and password), and the output is transitioning to the app's home screen. The device sends this authentication information to the server and authenticates the login.

[0931] Step 3:

[0932] The user inputs information such as "sunny," "25 degrees," and "office" using prompts on the home screen. The input is the weather conditions and destination information entered by the user, and the output is to send this information to the server.

[0933] Step 4:

[0934] The server parses the prompt and extracts the input information from the user. The input is the text information of the prompt, and the output is the parsed weather conditions and destination information. The server then compares this with the latest weather data obtained from an external weather data API.

[0935] Step 5:

[0936] The server references the user's registered database and generates the optimal outfit using a generative AI model. The input is the collated weather conditions, destination information, and the user's registered data, and the output is the generated outfit plan.

[0937] Step 6:

[0938] The server sends the generated coordinates to the terminal. The input is the data of the generated coordinates, and the output is the display of the proposed coordinates on the terminal.

[0939] Step 7:

[0940] The user checks the proposed outfits and selects them if they like them. The input is the user's confirmation and selection actions, and the output is the transmission of the selected outfit information from the terminal to the server.

[0941] Step 8:

[0942] The server saves the selected outfit in a database for future suggestions. In this step, the input is the outfit information selected by the user, and the output is the saved outfit data.

[0943] Step 9:

[0944] The user selects to rent or purchase a new item from the proposed items through the subscription service. The input is the user's selection action of renting or purchasing, and the output is the transmission of order information for the selected item from the terminal to the server.

[0945] Step 10:

[0946] The server sends the order data to the partner external brand and starts the delivery procedure. The input is the user's order data, and the output is the transmission of the order data to the external brand and the start of the delivery procedure.

[0947] Step 11:

[0948] After receiving new items, the server uses the generative AI model again to propose new outfits and sends the results to the device. The input is the new item information and existing user data, and the output is the new outfit proposal data.

[0949] 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.

[0950] MODE FOR CARRYING OUT THE INVENTION

[0951] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day, and then provides coordination that takes the user's emotions into consideration. The system works in cooperation with a server, a terminal, and an emotion engine, and each component plays a specific role.

[0952] Server Roles

[0953] The server is the core of the system and performs the following functions:

[0954] 1. Weather data collection: Integrate with external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.). The collected data is used as a basis for learning from past trends and patterns.

[0955] 2. User Data Management: Manages a database of users' clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[0956] 3. Emotion data management: Manage user emotion data sent from the emotion engine and learn past emotion trends.

[0957] 4. Coordination suggestion generation: Using AI algorithms, the system generates optimal outfits based on weather data, user data, destination information, and emotional data, eliminating the need for users to worry about choosing their daily outfits.

[0958] 5. Saving outfits: The outfits selected by the user are saved in a database and used as learning data for future suggestions.

[0959] 6. Offering rental and purchase options: We partner with third-party brands to offer users the option to rent or purchase selected latest fashion items.

[0960] Device Role

[0961] The terminal operated by the user has the following functions:

[0962] 1. User Authentication: Provides an authentication process for users to log in to their accounts. The authentication information is sent to the server and verified there.

[0963] 2. Sending input information: The user inputs the day's temperature, weather, destination, etc. and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[0964] 3. Acquiring emotional data: The emotion engine generates emotional data based on the user's facial expressions and input information, and sends it to the server via the device.

[0965] 4. Display of outfits: The outfits sent from the server are visually displayed. The suggestions are displayed in a format that is easy for the user to check, helping them make a selection.

[0966] 5. Order Processing: If you select the rental or purchase option, the order data is sent to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[0967] User Roles

[0968] Users operate the system and fulfill the following roles:

[0969] 1. Initial setup and registration: When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits. The emotion engine also initially registers the user's emotional data.

[0970] 2. Daily input and confirmation: Enter the daily weather conditions, destination, and emotional data, and check the outfits sent back from the server. If you like the outfit, you can send your decision to the server via your device.

[0971] 3. Rent and Buy: Choose your option to rent or buy a new fashion item and follow the necessary steps.

[0972] Specific examples

[0973] A day in the life of User A

[0974] 1. Morning

[0975] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[0976] User: User A enters his / her user ID and password and taps the login button.

[0977] Device: Sends authentication information to the server.

[0978] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[0979] Device: Displays login success and displays the home screen.

[0980] User: User A inputs the temperature, weather, destination, and emotions for that day. For example, "Sunny," "25 degrees," "Office," and "Feeling a little tired."

[0981] 2. Transmission of information

[0982] Terminal: Sends the entered information to the server.

[0983] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[0984] 3. Coordination suggestions

[0985] Server: Referencing User A's registration database and emotional data, the AI ​​algorithm generates optimal outfits based on past data. For example, it suggests a combination of a shirt, pants, jacket, and shoes made of a relaxed material.

[0986] Server: Sends the generated coordinates to the terminal.

[0987] Device: Display suggested outfits.

[0988] User: User A reviews the suggestions and selects the outfit if they like it.

[0989] Terminal: Sends the selected coordinates to the server and stores them.

[0990] 4. Use of Subscription Services

[0991] User: User A rents the suggested new jacket through a subscription service.

[0992] Terminal: Sends rental orders to the server.

[0993] Server: Sends order data to partner brands and initiates shipping procedures.

[0994] In this way, User A can streamline their daily clothing selection and enjoy optimal fashion that takes their emotions into consideration. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[0995] The processing flow will be explained below.

[0996] Step 1:

[0997] On the device: The user opens the application and the login screen appears. The user enters their user ID and password and taps the login button.

[0998] Step 2:

[0999] Terminal: Sends the entered user ID and password to the server.

[1000] Step 3:

[1001] Server: Compares the received user ID and password with the database. If the login is successful, it sends the user data to the terminal, and if not, it sends an error message to the terminal.

[1002] Step 4:

[1003] Device: If login is successful, display the home screen.

[1004] Step 5:

[1005] User: Enters the weather, temperature, destination (e.g., office, casual outing, formal event), and emotional state (e.g., "slightly tired," "energetic," etc.) for the day.

[1006] Step 6:

[1007] Terminal: Sends the entered information to the server.

[1008] Step 7:

[1009] Server: Accesses external weather data API to collect the latest weather information (temperature, weather conditions), and compares this information with user input.

[1010] Step 8:

[1011] Server: Manages user emotion data sent from the emotion engine and learns past emotion trends.

[1012] Step 9:

[1013] Server: Refers to the user's clothing database and uses AI algorithms to generate optimal outfits based on past weather data and fashion information. For example, it suggests shirts, pants, jackets, and shoes made from relaxing materials.

[1014] Step 10:

[1015] Server: Sends the generated coordinates to the terminal.

[1016] Step 11:

[1017] Device: Visually displays the received outfits, showing a list of combinations of shirts, jackets, pants, shoes, etc.

[1018] Step 12:

[1019] User: Select the outfit they like from the ones presented. Once they have made their selection, they tap the confirm button.

[1020] Step 13:

[1021] Terminal: Sends the selected coordinate information to the server.

[1022] Step 14:

[1023] Server: The selected coordinates are saved in a database and used as learning data for future suggestions.

[1024] Step 15:

[1025] User: Selects a subscription option to rent or purchase new fashion items included in the suggested outfits.

[1026] Step 16:

[1027] Terminal: Sends rental or purchase order data to the server.

[1028] Step 17:

[1029] Server: Sends order data to partner external brands and initiates shipping procedures.

[1030] Step 18:

[1031] User: After receiving new items, the user uses the application again to receive new outfit suggestions based on the new items.

[1032] In this way, a system is realized that allows users to efficiently choose their daily outfits and enjoy optimal fashion that takes their emotions into consideration.

[1033] Example 2

[1034] 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."

[1035] Conventional coordination systems were limited to making suggestions based on the user's weather conditions and the clothing they owned, and were unable to make coordination suggestions that took into account the user's emotions or current mood. Furthermore, when users wanted to try out the latest fashion items, the process was cumbersome and burdensome for users. This resulted in a decrease in satisfaction and efficiency with fashion.

[1036] 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.

[1037] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for acquiring and managing the user's emotional data, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing options to rent or purchase fashion items, means for transmitting order data to affiliated external brands, and means for proposing new outfits after new items arrive. This makes it possible to propose outfits that reflect the user's emotions and current mood in addition to weather conditions and data on the clothing they own, and also allows them to smoothly try on and purchase the latest fashion items.

[1038] "Latest weather data" refers to environmental information such as current and near-future temperature, weather, humidity, and wind speed.

[1039] "User clothing data" refers to information about the clothing items owned by the user, including the type, color, material, style, and size of the item.

[1040] "User emotional data" refers to data that indicates the user's current emotions and moods as inferred from their facial expressions, input information, and past data.

[1041] "Means for generating outfits" refers to algorithms or systems that suggest optimal outfit combinations based on collected weather data, data on the user's clothing, and emotional data.

[1042] "Means for displaying coordination" refers to a device or application for visually presenting the generated outfit combinations to the user.

[1043] "Means for saving outfits" refers to a system that records the outfit combinations selected by the user in a database for future reference or as learning data.

[1044] "Means for providing rental or purchase options" refers to systems or applications that suggest options for users to rent or purchase their favorite latest fashion items and assist them in the process.

[1045] "Means for transmitting order data to partnering third-party brands" refers to a system that transmits order information to third-party fashion brands and retailers based on the rental or purchase option selected by the user.

[1046] "Means to suggest new outfits after new items arrive" refers to algorithms or systems that incorporate the user's newly acquired fashion items and suggest optimal outfit combinations again.

[1047] "Historical weather data" refers to information about temperature and weather conditions over a specific period in the past.

[1048] "Past emotion data" refers to data records regarding emotions and moods that a user has felt in the past.

[1049] "Fashion information" refers to data about the latest trends, styles, and fashions.

[1050] "User input means" refers to an interface or device that allows a user to manually input information such as temperature, weather, destination, and emotion.

[1051] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day, and then provides coordination that takes the user's emotions into consideration. The system works in cooperation with a server, a terminal, and an emotion engine, and each component plays a specific role.

[1052] Server Roles

[1053] The server is the core of the system and performs the following functions:

[1054] 1. Meteorological data collection:

[1055] The server connects to an external weather data API (e.g., OpenWeatherMap API) to collect the latest weather information (temperature, weather, humidity, wind speed, etc.), which allows it to always provide suggestions based on the latest weather data.

[1056] 2. Managing your data:

[1057] The server manages a database of the user's clothing and style preferences, allowing the user to keep an up-to-date inventory of the clothing items they own.

[1058] 3. Emotional Data Management:

[1059] The server manages the user's emotional data sent from the emotion engine and learns past emotional trends. This information is reflected in the outfit suggestions.

[1060] 4. Coordination proposal generation:

[1061] The server uses AI algorithms (e.g., models using TensorFlow or PyTorch) to generate optimal outfits based on weather data, user data, destination information, and emotional data. This process allows users to receive more accurate outfit suggestions.

[1062] 5. Save your outfit:

[1063] The server stores the user's selected outfits in a database and uses them as learning data to help with future suggestions.

[1064] 6. Offering Rental and Purchase Options:

[1065] The server works with partner external brands to provide users with the option to rent or purchase the latest fashion items of their choice, allowing them to easily try out the latest fashions.

[1066] Device Role

[1067] The terminal operated by the user has the following functions:

[1068] 1. User authentication:

[1069] The device provides an authentication process for the user to log into their account, and the authentication information is sent to the server where it is verified.

[1070] 2. Submitting input information:

[1071] The user inputs the day's temperature, weather, destination, etc. into the device, and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[1072] 3. Acquiring emotion data:

[1073] The device's emotion engine generates emotion data based on the user's facial expressions and input information, and sends it to a server via the device. The emotion engine uses facial recognition technology and natural language processing (NLP) technology.

[1074] 4. Show your outfit:

[1075] The terminal visually displays the coordinates sent from the server, allowing the user to easily check and select the suggestions.

[1076] 5. Order Processing:

[1077] If the user selects the rental or purchase option, the device sends the order data to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[1078] User Roles

[1079] The user operates the system and performs the following roles:

[1080] 1. Initial Setup and Registration:

[1081] When using the app for the first time, users register their clothing and preferred styles. The server then manages this data and uses it to suggest outfits. The emotion engine also initially registers the user's emotional data.

[1082] 2. Daily input and confirmation:

[1083] Users input their daily weather conditions, destination, and emotions, and then check the outfits sent back from the server. If they like the outfit, they can send their decision to the server via their device.

[1084] 3. Rental and Purchase:

[1085] Users select the option to rent or purchase a new fashion item and complete the necessary steps.

[1086] Specific examples

[1087] A day in the life of User A

[1088] 1. Morning

[1089] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[1090] User: User A enters his / her user ID and password and taps the login button.

[1091] Device: Sends authentication information to the server.

[1092] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[1093] Device: Displays login success and displays the home screen.

[1094] User: User A inputs the temperature, weather, destination, and emotions for that day. For example, "Sunny," "25 degrees," "Office," and "Feeling a little tired."

[1095] 2. Transmission of information

[1096] Terminal: Sends the entered information to the server.

[1097] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[1098] 3. Coordination suggestions

[1099] Server: Referencing User A's registration database and emotional data, the AI ​​algorithm generates optimal outfits based on past data. For example, it suggests a combination of a shirt, pants, jacket, and shoes made of a relaxed material.

[1100] Server: Sends the generated coordinates to the terminal.

[1101] Device: Display suggested outfits.

[1102] User: User A reviews the suggestions and selects the outfit if they like it.

[1103] Terminal: Sends the selected coordinates to the server and stores them.

[1104] 4. Use of Subscription Services

[1105] User: User A rents the suggested new jacket through a subscription service.

[1106] Terminal: Sends rental orders to the server.

[1107] Server: Sends order data to partner brands and initiates shipping procedures.

[1108] In this way, User A can streamline their daily clothing selection and enjoy optimal fashion that takes their emotions into consideration. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[1109] Prompt Sentence Examples

[1110] "25 degrees, sunny, office, feeling a bit tired"

[1111] Based on this information, the system provides input data for a generative AI model, allowing the device to receive optimal outfit suggestions.

[1112] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1113] Step 1: User authentication

[1114] Input: User ID and Password

[1115] Output: Home screen

[1116] Device: Launch the app and the login screen will appear.

[1117] User: Enter your user ID and password and tap the login button.

[1118] Device: Sends authentication information to the server.

[1119] Server: Checks the received authentication information against a database and returns a success or failure result to the terminal.

[1120] Terminal: If login is successful, the home screen is displayed and user data is sent to the terminal.

[1121] Step 2: Initial data entry

[1122] Input: User's clothing, preferred style, and emotional data

[1123] Output: Registration complete confirmation message

[1124] User: Register your clothes and preferred style on the home screen. Also, register your initial emotional data.

[1125] Terminal: Sends data entered by the user to the server.

[1126] Server: Stores the received data in a database and sends a confirmation message to the terminal that registration is complete.

[1127] Step 3: Meteorological data collection

[1128] Input: Weather information for the day, destination entered by the user

[1129] Output: Latest weather data

[1130] User: Enter the weather conditions for the day (e.g., "sunny" and "25 degrees") and destination.

[1131] Terminal: Sends the entered information to the server.

[1132] Server: Uses an external weather data API (e.g., OpenWeatherMap API) to collect the latest weather information.

[1133] Server: Compares the collected weather data with the information entered by the user and stores it in a database.

[1134] Step 4: Acquire emotion data

[1135] Input: User's facial expression, input information

[1136] Output: Emotion data

[1137] Device: The emotion engine captures the user's facial expressions with a camera, analyzes the data, and generates emotion data.

[1138] Terminal: Sends the generated emotion data to the server.

[1139] Server: Stores the emotion data in a database for future analysis.

[1140] Step 5: Coordinate generation

[1141] Input: Weather data, user data, emotion data, destination information

[1142] Output: Optimal Coordination

[1143] Server: Based on the received weather data, user data, emotion data, and destination information, an AI algorithm is used to generate the optimal coordinates. At this stage, a generative AI model (e.g., TensorFlow or PyTorch) is used.

[1144] Server: Sends the generated coordinate data to the terminal.

[1145] Step 6: Coordination presentation and selection

[1146] Input: Best outfit

[1147] Output: Selected coordinates

[1148] Terminal: Visually displays the outfit received from the server (e.g., a relaxed shirt, pants, jacket, and shoes).

[1149] User: Check the presented outfits and select if you like them.

[1150] Terminal: Sends the selected coordinate information to the server.

[1151] Step 7: Save your outfit

[1152] Input: Selected coordinates

[1153] Output: Save complete confirmation message

[1154] Server: The selected coordinates are stored in a database and used as learning data for future suggestions.

[1155] Server: Sends a confirmation message to the terminal that the save is complete.

[1156] Step 8: Rental / Purchase Process

[1157] Input: The rental or purchase option selected by the user

[1158] Output: Order completed confirmation message

[1159] User: Selects an option to rent or buy a fashion item, such as a new jacket.

[1160] Terminal: Sends the user's order information to the server.

[1161] Server: Sends order data to partner external brands and initiates shipping procedures.

[1162] Server: Sends a confirmation message to the terminal that the order has been completed.

[1163] (Application example 2)

[1164] 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."

[1165] Conventional outfit suggestion systems can suggest outfits based on the user's weather conditions and preferences, but they cannot consider the user's emotions. It is also difficult to suggest appropriate outfits based on the driver's emotions inside an autonomous vehicle. This makes it difficult to suggest optimal outfits to reduce fatigue and stress, especially during long driving trips.

[1166] 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.

[1167] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing options for renting or purchasing clothing items, means for sending order data to affiliated external brands, means for suggesting new outfits after new items arrive, means for acquiring facial images using a camera attached to the information entertainment system in the autonomous vehicle and analyzing emotional data, means for suggesting outfits that suit the driver based on the analyzed emotional data, and means for displaying the suggested outfits on an in-vehicle display. This enables optimal outfit suggestions based on the driver's emotions and weather conditions, improving driving comfort and safety.

[1168] "Weather data" is information about weather conditions such as temperature, weather, humidity, and wind speed.

[1169] "Clothing data" refers to information about the type, design, material, color, size, etc. of clothing owned by the user.

[1170] "Outfit" refers to the coordination suggested based on weather conditions and emotions.

[1171] An "information entertainment system" is a system installed in an autonomous vehicle for providing information and displaying entertainment content.

[1172] "Camera" refers to a device that captures images, especially one installed in an autonomous vehicle.

[1173] "Emotional data" is information about the user's emotional state analyzed based on images captured by a camera.

[1174] "External brands" refer to companies or brands that partner with the system to rent or sell clothing items to users.

[1175] "Coordination" refers to the optimal combination of clothing suggested to the user.

[1176] "Rental" refers to a service that allows you to borrow clothing items for a certain period of time.

[1177] "Purchase" refers to purchasing an item of clothing to own it.

[1178] System Overview:

[1179] This invention is a system that proposes optimal outfits based on the user's weather conditions, destination, and emotion data for the day. The system operates in cooperation with a server, a terminal, and an emotion engine.

[1180] Server Role:

[1181] The server is the center of the system and has the following responsibilities:

[1182] 1. Weather data collection: The server uses an external weather data API to collect the latest weather data and then suggests appropriate outfits to the user based on that data.

[1183] 2. Managing clothing data: The server manages the clothing data registered by the user.

[1184] 3. Emotion data management: The server analyzes the emotion data acquired by the camera inside the autonomous vehicle and uses it to propose appropriate coordination.

[1185] 4. Coordination generation: The server uses AI algorithms to generate optimal coordination based on weather data, clothing data, and emotional data.

[1186] 5. Sending proposal: The server sends the generated coordinates to the terminal, which then displays them on the in-car display.

[1187] Device role:

[1188] The user-operated device has the following features:

[1189] 1. User Authentication: Provides an authentication process for users to log in to their accounts.

[1190] 2. Data input: The user inputs the weather conditions, destination, and emotions for the day and sends this to the server.

[1191] 3. Emotion data acquisition: Using a camera installed inside the vehicle, an image of the user's face is acquired and sent to the emotion engine.

[1192] 4. Coordination display: Displays the coordination proposals sent from the server.

[1193] User role:

[1194] The user interfaces with the system to:

[1195] 1. Initial setup and registration: By registering your clothing and preferred styles in the system, you will be prepared to receive optimal outfit suggestions.

[1196] 2. Daily data input: By inputting daily weather conditions, destinations, and emotions, the server will suggest the best outfits for you.

[1197] 3. Review and select the suggestions: Review the outfits sent by the server and select them if you like them.

[1198] Hardware and software used:

[1199] Hardware:

[1200] Information and entertainment systems in autonomous vehicles

[1201] In-car camera

[1202] software:

[1203] requests library (weather data acquisition)

[1204] OpenCV (emotion analysis)

[1205] TensorFlow (AI algorithm)

[1206] Examples:

[1207] Example 1: Morning preparation

[1208] Before getting into a self-driving vehicle, users input "sunny," "25 degrees," "office," and "feeling a bit tired" into a smartphone app. The system then uses weather data to suggest outfits for light shirts and pants. It also analyzes facial images to recommend comfortable clothing.

[1209] Example prompt for a generative AI model:

[1210] "Weather data: Tokyo, Temperature: 28°C, Emotion data: Happy: 0.7, Sad: 0.1, Destination: Office. What is the best outfit?"

[1211] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1212] Step 1:

[1213] User authentication

[1214] Input: User ID and Password

[1215] What happens: A user logs into an app using a device, which sends their credentials to a server, which checks them against a database for authentication.

[1216] Output: If authentication is successful, send user data to the device. Login is successful and the home screen is displayed.

[1217] Step 2:

[1218] Data Entry

[1219] Input: Weather conditions, destination information, emotional state

[1220] Processing: The user inputs the weather conditions, destination, and emotions for the day into the device, which then sends this information to the server.

[1221] Output: The submitted data is stored on the server and used to generate coordinates.

[1222] Step 3:

[1223] Weather data collection

[1224] Input: User's destination information

[1225] Processing: The server uses an external weather data API to gather the latest weather information for the user's destination, sending an API request to get information such as temperature, weather, humidity, and wind speed.

[1226] Output: The acquired weather data is saved and used to generate coordinates.

[1227] Step 4:

[1228] Emotional Data Analysis

[1229] Input: Facial image captured by the in-car camera

[1230] Processing: The device captures the user's facial expressions using the in-car camera and sends the image data to the emotion engine, which uses OpenCV to preprocess the images and TensorFlow AI models to analyze emotions.

[1231] Output: The emotion analysis results are sent to the server and stored as user emotion data.

[1232] Step 5:

[1233] Coordinate generation

[1234] Input: Weather data, clothing data, emotion data

[1235] Processing: The server uses AI algorithms to generate the optimal outfit based on collected weather data, accumulated clothing data, and emotion analysis results. The generation process involves selecting materials based on temperature and suggesting colors and styles based on emotional state.

[1236] Output: The generated coordinates are sent from the server to the device.

[1237] Step 6:

[1238] Displaying outfits

[1239] Input: Generated coordinates

[1240] Processing: The terminal receives the coordinates sent from the server and displays them on the in-car display. The user confirms the displayed coordinates.

[1241] Output: The coordinates are visually presented for user confirmation.

[1242] Step 7:

[1243] Select and save outfits

[1244] Input: User's choice

[1245] Process: The user selects their favorite outfit and sends the selection to the server via their device. The server stores the selected outfit in a database for future suggestions.

[1246] Output: The selected coordinates are saved.

[1247] Step 8:

[1248] Rental and purchase procedures

[1249] Input: User's rental or purchase intent

[1250] Processing: If the user decides to rent or purchase a new clothing item, they submit the order via their device to the server, which then sends the order data to the partnering external brand and initiates the delivery process.

[1251] Output: The order is placed and the item is delivered.

[1252] 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.

[1253] 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.

[1254] 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.

[1255] [Third embodiment]

[1256] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1257] 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.

[1258] 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).

[1259] 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.

[1260] 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.

[1261] 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).

[1262] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1263] 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.

[1264] 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.

[1265] 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.

[1266] 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.

[1267] 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."

[1268] MODE FOR CARRYING OUT THE INVENTION

[1269] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day. This system is made up of three components: a server, a terminal, and a user, who exchange information with each other, and each component plays a specific role.

[1270] Server Roles

[1271] The server is the core of the system and performs the following functions:

[1272] 1. Weather data collection: Integrate with external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.). The collected data is used as a basis for learning from past trends and patterns.

[1273] 2. User Data Management: Manages a database of users' clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[1274] 3. Generating outfit suggestions: Using AI algorithms, the system generates optimal outfit suggestions based on weather data, user data, and destination information, eliminating the need for users to worry about choosing their daily outfits.

[1275] 4. Saving outfits: The outfits selected by the user are saved in a database and used as learning data for future suggestions.

[1276] 5. Offering rental and purchase options: We partner with third-party brands to offer users the option to rent or purchase the latest fashion items of their choice.

[1277] Device Role

[1278] The terminal operated by the user has the following functions:

[1279] 1. User Authentication: Provides an authentication process for users to log in to their accounts. The authentication information is sent to the server and verified there.

[1280] 2. Sending input information: The user inputs the day's temperature, weather, destination, etc. and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[1281] 3. Display of outfits: The outfits sent from the server are visually displayed. The suggestions are displayed in a format that is easy for the user to check, helping them make a selection.

[1282] 4. Order Processing: If you select the rental or purchase option, the order data is sent to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[1283] User Roles

[1284] Users operate the system and fulfill the following roles:

[1285] 1. Initial setup and registration: When using the app for the first time, you will need to register your clothing and preferred style. This data will be managed on the server and used to suggest outfits.

[1286] 2. Daily input and confirmation: Enter the daily weather conditions and destination, and check the coordinates returned by the server. If you like it, send your decision to the server via your device.

[1287] 3. Rent and Buy: Choose your option to rent or buy a new fashion item and follow the necessary steps.

[1288] Specific examples

[1289] A day in the life of User A

[1290] 1. Morning

[1291] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[1292] User: User A enters his / her user ID and password and taps the login button.

[1293] Device: Sends authentication information to the server.

[1294] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[1295] Device: Displays login success and displays the home screen.

[1296] 2. Enter your information

[1297] User: User A enters the information "sunny," "25 degrees," and "office" on the home screen.

[1298] Terminal: Sends this information to the server.

[1299] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[1300] 3. Coordination suggestions

[1301] Server: Referencing User A's registered database, the AI ​​algorithm generates the optimal outfit based on past data, suggesting combinations of T-shirt, jacket, pants, and shoes.

[1302] Server: Sends the generated coordinates to the terminal.

[1303] Device: Display suggested outfits.

[1304] User: User A reviews the suggestions and selects the outfit if they like it.

[1305] Terminal: Sends the selected coordinates to the server and stores them.

[1306] 4. Use of Subscription Services

[1307] User: User A rents the suggested new jacket through a subscription service.

[1308] Terminal: Sends rental orders to the server.

[1309] Server: Sends order data to partner brands and initiates shipping procedures.

[1310] In this way, User A can streamline their daily clothing selection and always maintain the best fashion. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[1311] The processing flow will be explained below.

[1312] Step 1:

[1313] On the device: The user opens the application and the login screen appears. The user enters their user ID and password and taps the login button.

[1314] Step 2:

[1315] Terminal: Sends the entered user ID and password to the server.

[1316] Step 3:

[1317] Server: Compares the received user ID and password with the database. If the login is successful, sends the user data to the terminal. If not successful, sends an error message to the terminal.

[1318] Step 4:

[1319] Device: If login is successful, display the home screen.

[1320] Step 5:

[1321] User: Enters the weather for the day, temperature, and destination (e.g., office, casual outing, formal event).

[1322] Step 6:

[1323] Terminal: Sends the entered information to the server.

[1324] Step 7:

[1325] Server: Accesses external weather data API to collect the latest weather information (temperature, weather conditions), and compares this information with user input.

[1326] Step 8:

[1327] Server: Refers to the database of the user's clothing and uses AI algorithms to generate optimal outfits based on past weather data and fashion information. For example, it suggests shirts, jackets, pants, shoes, etc.

[1328] Step 9:

[1329] Server: Sends the generated coordinates to the terminal.

[1330] Step 10:

[1331] Device: Visually displays the received outfits, showing a list of combinations of shirts, jackets, pants, shoes, etc.

[1332] Step 11:

[1333] User: Select the outfit they like from the ones presented. Once they have made their selection, they tap the confirm button.

[1334] Step 12:

[1335] Terminal: Sends the selected coordinate information to the server.

[1336] Step 13:

[1337] Server: The selected coordinates are saved in a database and used as learning data for future suggestions.

[1338] Step 14:

[1339] User: Selects a subscription option to rent or purchase new fashion items included in the suggested outfits.

[1340] Step 15:

[1341] Terminal: Sends rental or purchase order data to the server.

[1342] Step 16:

[1343] Server: Sends order data to partner external brands and initiates shipping procedures.

[1344] Step 17:

[1345] User: After receiving new items, the user uses the application again to receive new outfit suggestions based on the new items.

[1346] In this way, a system is realized that allows users to efficiently choose their daily outfits and always enjoy the most appropriate fashion.

[1347] Example 1

[1348] 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."

[1349] In modern society, choosing the best outfit for each day based on weather conditions and schedules is a tedious task for many users. Managing existing clothing and renting or purchasing new fashion items can also be time-consuming. There is a need for a way to efficiently solve these issues, simplify daily outfit selection, and ensure optimal fashion at all times.

[1350] 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.

[1351] In this invention, the server includes means for collecting the latest weather data, means for managing the user's clothing data, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing the option to rent or purchase fashion items, means for transmitting order data to affiliated external suppliers, means for proposing new outfits after new items arrive, means for transmitting daily temperature, weather, and destination information entered by the user, means for comparing the weather data with the user's clothing data, and means for generating outfits using an AI algorithm. This allows users to easily select optimal outfits based on daily weather conditions and plans, and enables efficient clothing management and the rental or purchase of new items.

[1352] "Weather data" is information about weather conditions such as temperature, weather, humidity, and wind speed.

[1353] "User's clothing data" refers to data including details of clothing owned by the user, such as style, size, and color.

[1354] The "coordination generation means" is a system that automatically suggests optimal outfit combinations based on weather data and the user's clothing data.

[1355] The "means for displaying generated coordinated outfits" is an interface for visually displaying to the user the outfit combinations proposed by the server or terminal.

[1356] The "coordinate storage means" is a system that stores the outfit combinations selected by the user in a database.

[1357] "Rental or purchase option providing means" refers to a system that provides a user with the option to rent or purchase a suggested fashion item.

[1358] "Order data transmission means" refers to a means for transmitting a user's rental or purchase order to an affiliated external supplier.

[1359] The "new coordination suggestion method" is a system that suggests new outfit combinations that include new items after the user receives them.

[1360] The "means for transmitting daily temperature, weather, and destination information" is a system that transmits information about the temperature, weather, and destination of the day entered by the user to the server.

[1361] The "means for comparing weather data with user's clothing data" is a means for comparing collected weather data with the user's clothing data to select the optimal outfit.

[1362] "A means for generating coordination using an AI algorithm" is a system that uses an artificial intelligence algorithm to generate optimal clothing combinations.

[1363] The present invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day. This system is made up of three components: a server, a terminal, and a user, who exchange information with each other, and each component plays a specific role.

[1364] Server Roles

[1365] Weather data collection

[1366] The server connects to external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.) using software such as the OpenWeatherMap API or WeatherStack API. The collected data is stored in a database and used as a basis for learning from past trends and patterns.

[1367] Managing User Data

[1368] The server manages a database of the user's clothing and style preferences, which is used to keep the user's inventory of clothing items up to date.

[1369] Generating outfit suggestions

[1370] The server uses AI algorithms to generate optimal trips based on weather data, user data, and destination information, using machine learning frameworks such as TensorFlow and PyTorch.

[1371] Save your outfit

[1372] The coordination selected by the user is stored in a database and used as learning data to help with future suggestions.

[1373] Offering rental and purchase options

[1374] The server works with affiliated external suppliers, such as general online fashion stores, to provide users with the option to rent or purchase selected latest fashion items.

[1375] Device Role

[1376] User authentication

[1377] The device provides an authentication process for the user to log into their account, and the authentication information is sent to the server where it is verified.

[1378] Sending input information

[1379] The user inputs the temperature, weather, destination, and other information for that day, and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[1380] Displaying outfits

[1381] The terminal visually displays the coordinates sent from the server, and displays the suggestions in a format that is easy for the user to check.

[1382] Order Processing

[1383] If the user selects the rental or purchase option, the terminal sends the order data to the server, which then sends the order to the partner external supplier and initiates the delivery process.

[1384] User Roles

[1385] Initial Setup and Registration

[1386] When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits.

[1387] Daily input and confirmation

[1388] Users input the daily weather conditions and destinations, check the outfits sent back from the server, and if they like the outfit, they send their decision to the server via their device.

[1389] Rental and Purchase

[1390] Users select the option to rent or purchase a new fashion item and complete the necessary steps.

[1391] Examples of specific examples and prompt usage

[1392] As an example of actual use, we will explain specific situations in which users use the app.

[1393] A day in the life of User A

[1394] morning

[1395] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[1396] User: Enter your user ID and password and tap the login button.

[1397] Device: Sends authentication information to the server.

[1398] Server: Checks the authentication information against a database and sends the user data to the device if the login is successful.

[1399] Terminal: Displays login success and displays the home screen.

[1400] Entering information

[1401] User: User A enters the information "Sunny", "25 degrees", and "Office" on the home screen.

[1402] Device: Sends this information to the server.

[1403] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[1404] Coordination suggestions

[1405] Server: Referencing User A's registered database, the AI ​​algorithm generates the optimal outfit based on past data, suggesting combinations of T-shirt, jacket, pants, and shoes.

[1406] Server: Sends the generated coordinates to the device.

[1407] Device: Display suggested outfits.

[1408] User: User A reviews the suggestions and selects the outfit if they like it.

[1409] Device: Sends the selected coordinates to the server and saves them.

[1410] Use of subscription services

[1411] User: User A rents a suggested new jacket through a subscription service.

[1412] Terminal: Sends rental orders to the server.

[1413] Server: Sends order data to partner brands and initiates the shipping process.

[1414] Examples of prompt statements

[1415] An example of a prompt that a user might enter into the system is:

[1416] "Tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and humidity of 70%. Please suggest some business casual attire."

[1417] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1418] Step 1:

[1419] User authentication

[1420] Device: The user launches the app and sees the login screen.

[1421] Input: User ID and password

[1422] Output: Sends login information to the server

[1423] User: Enter your user ID and password and tap the login button.

[1424] Device: Sends authentication information to the server.

[1425] Input: User ID and password

[1426] Output: Sending authentication information

[1427] Server: Checks the authentication information against the database, and if the login is successful, sends the user data to the terminal.

[1428] Input: Credentials

[1429] Data calculation: User ID and password verification

[1430] Output: Login success or failure information

[1431] Device: Displays login success and displays the home screen.

[1432] Input: Login success information

[1433] Output: Login success screen displayed

[1434] Step 2:

[1435] Entering information

[1436] User: The user enters the information "sunny," "25 degrees," and "office" from the home screen.

[1437] Input: Temperature, weather, destination information

[1438] Output: Preparing input information for transmission

[1439] Terminal: Sends this information to the server.

[1440] Input: User input information

[1441] Data calculation: Format conversion of input information

[1442] Output: Send to server

[1443] Step 3:

[1444] Meteorological data collection and collation

[1445] Server: Collects the latest weather information from an external weather data API.

[1446] Input: Request to external weather API

[1447] Output: Latest weather data

[1448] Server: Stores the collected weather data in a database.

[1449] Input: Collected weather data

[1450] Data processing: saving to database

[1451] Output: Save completion information

[1452] Server: Matches the information entered by the user with the collected weather data.

[1453] Input: User input information, latest weather data

[1454] Data calculation: Check whether the input information matches the weather data

[1455] Output: Matching result

[1456] Step 4:

[1457] Generating outfit suggestions

[1458] Server: Refers to the user's clothing database to obtain the user's clothing and preferred styles.

[1459] Input: User database query

[1460] Output: Clothing data

[1461] Server: Using AI algorithms, it generates optimal coordination based on weather data, user data, and destination information.

[1462] Input: Weather data, clothing data, destination information

[1463] Data calculation: Coordination suggestions based on AI models

[1464] Output: Generated coordinates

[1465] Server: Sends the generated coordinates to the terminal.

[1466] Input: Generated coordinates

[1467] Output: Send to terminal

[1468] Step 5:

[1469] View and select suggestions

[1470] Terminal: Visually displays the proposed coordination.

[1471] Input: Generated coordinate information

[1472] Output: Display of proposal

[1473] User: Check the suggestions and select the outfit they like.

[1474] Input: Proposal

[1475] Output: Selection information

[1476] Terminal: Sends the selected coordinates to the server.

[1477] Input: User selection information

[1478] Output: Send to server

[1479] Server: Saves the selected coordinates in the user database.

[1480] Input: Selected coordinate information

[1481] Data processing: saving to database

[1482] Output: Save completion information

[1483] Step 6:

[1484] Use of subscription service (optional)

[1485] User: Select the option to rent or buy the suggested new item.

[1486] Input: Rental or purchase selection information

[1487] Output: Order information ready to send

[1488] Terminal: Sends rental or purchase orders to the server.

[1489] Input: User's order information

[1490] Output: Send to server

[1491] Server: Sends order information to affiliated external suppliers and initiates delivery procedures.

[1492] Input: Order Information

[1493] Output: Sending order information to partner suppliers, information on starting delivery procedures

[1494] (Application example 1)

[1495] 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."

[1496] Conventional clothing suggestion systems have not been able to provide sufficient support for users in choosing the most appropriate outfit based on the day's weather conditions and destination. Furthermore, the process of suggesting, renting, and purchasing the latest fashion items is cumbersome, reducing user convenience. Therefore, there was a need for a system that could suggest optimal outfits based on weather conditions and destination, and easily rent or purchase fashion items.

[1497] 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.

[1498] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing an option to rent or purchase fashion items, means for transmitting order data to affiliated external brands, means for proposing new outfits after new items arrive, means for generating outfits using a generative AI model, and means for collecting user input via prompt text. This allows the user to receive optimal outfit suggestions based on weather conditions and destination, and further allows the user to easily rent or purchase the suggested fashion items.

[1499] "Means for collecting weather data" refers to a system for obtaining the latest information such as temperature, weather, humidity, and wind speed from external weather data providers.

[1500] "A means of managing clothing data" is a system for registering and storing the types of clothing owned by users, their attributes, and preferred styles in a database.

[1501] The "means for generating coordination" is an algorithm or program that suggests optimal clothing combinations based on collected weather data and managed clothing data.

[1502] The "means for displaying coordinates" refers to a display device or application for visually presenting the generated coordinates to the user.

[1503] The "means for saving outfits" refers to a system that records the outfits selected by the user in a database for use in future suggestions and analysis.

[1504] "Means for providing rental or purchase options" refers to an interface and system that allows users to choose between renting or purchasing suggested fashion items.

[1505] "Means for sending order data to external brands" refers to a system that sends order information for the items selected by the user to partner brands or retailers and initiates the purchase or rental process.

[1506] The "means for suggesting new coordination" is an algorithm or program for regenerating the latest coordination including newly arrived items and suggesting it to the user.

[1507] A "generative AI model" is an artificial intelligence algorithm that learns from large amounts of data and generates outfits.

[1508] A "means for collecting user input via prompt sentences" is a system for analyzing information entered by a user in natural language and obtaining and processing the required data.

[1509] This invention is a system that allows users to choose the best outfit based on the day's weather conditions and destination. The system is made up of three components: a server, a device, and a user, each of which plays a specific role. It is particularly notable for collecting user input via a generative AI model and prompts.

[1510] Server Roles

[1511] The server is the core of the system and performs the following functions:

[1512] 1. Weather data collection: The server connects to an external weather data API (e.g., Weatherstack) to collect the latest weather information (temperature, weather, humidity, wind speed, etc.), allowing users to understand the weather conditions at their current location or a specified location in real time.

[1513] 2. User Data Management: The server manages a database of the user's clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[1514] 3. Coordination suggestion generation: The server uses a generative AI model to generate optimal outfits based on weather data, user data, and destination information, eliminating the need for users to worry about choosing their daily outfits.

[1515] 4. Saving the outfit: The server saves the outfit selected by the user in a database and uses it as learning data to help with future suggestions.

[1516] 5. Providing rental and purchase options: The server works with partner external brands to provide users with the option to rent or purchase the latest fashion items of their choice.

[1517] 6. Sending order data: The server sends the order information for the items selected by the user to the partner brand or retailer to initiate the purchase or rental process.

[1518] 7. Proposing a new outfit: After new items arrive, the server again uses the generative AI model to propose a new outfit.

[1519] Device Role

[1520] The terminal operated by the user has the following functions:

[1521] 1. User authentication: The device provides an authentication process for the user to log in to their account. The authentication information is sent to the server and verified there.

[1522] 2. Data input and transmission: The terminal prompts the user to input the day's temperature, weather, destination, etc., and transmits this information to the server, which then obtains the data needed to generate the optimal coordinates.

[1523] 3. Display of outfits: The device visually displays the outfits sent from the server, helping the user make a selection by displaying the suggestions in an easy-to-read format.

[1524] 4. Order Processing: If the user selects the rental or purchase option, the device sends the order data to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[1525] User Roles

[1526] Users operate the system and fulfill the following roles:

[1527] 1. Initial setup and registration: When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits.

[1528] 2. Daily information input and confirmation: The user inputs the daily weather conditions and destinations in the prompts and checks the coordinates returned by the server. If the generated coordinates are satisfactory, the user sends the decision to the server via the terminal.

[1529] 3. Rent and Buy: Users select the option to rent or buy a new fashion item and complete the necessary steps.

[1530] Example: A day in the life of User A

[1531] morning

[1532] User A wakes up in the morning, launches the app, and the login screen appears. User A enters their user ID and password and taps the login button. The device sends the authentication information to the server, and the server authenticates the login. If the login is successful, the home screen appears on the device.

[1533] Entering information

[1534] User A inputs the information "sunny," "25 degrees," and "office" using prompts from the home screen. The device sends this information to the server, which then collects the latest weather information from an external weather data API and compares it with User A's information.

[1535] Coordination suggestions

[1536] The server references User A's registration database, and the generative AI model generates the optimal outfit. For example, it suggests a combination of a T-shirt, jacket, pants, and shoes. The generated outfit is sent to the device, where User A checks it. If User A likes it, he or she selects the outfit, and the device sends the selected outfit to the server and saves it.

[1537] Use of subscription services

[1538] If User A wants to rent the suggested new jacket through the subscription service, the device sends a rental order to the server, which then sends the order data to the partner brand and initiates the delivery process.

[1539] Example prompt:

[1540] "It's sunny and 25 degrees today, so I'm heading to the office. Could you recommend an outfit for me? I'd also like to rent the denim jacket you suggested."

[1541] In this way, User A can efficiently choose their daily outfits and always maintain the best fashion. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[1542] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1543] Step 1:

[1544] The server calls an external weather data API to collect current weather data (temperature, weather, humidity, wind speed, etc.) and stores it in a database. The input is the weather data obtained from the API, and the output is a database containing the latest weather data.

[1545] Step 2:

[1546] A user launches a smartphone app and logs in by entering their user ID and password on the login screen. The input is the user's authentication information (user ID and password), and the output is transitioning to the app's home screen. The device sends this authentication information to the server and authenticates the login.

[1547] Step 3:

[1548] The user inputs information such as "sunny," "25 degrees," and "office" using prompts on the home screen. The input is the weather conditions and destination information entered by the user, and the output is to send this information to the server.

[1549] Step 4:

[1550] The server parses the prompt and extracts the input information from the user. The input is the text information of the prompt, and the output is the parsed weather conditions and destination information. The server then compares this with the latest weather data obtained from an external weather data API.

[1551] Step 5:

[1552] The server references the user's registered database and generates the optimal outfit using a generative AI model. The input is the collated weather conditions, destination information, and the user's registered data, and the output is the generated outfit plan.

[1553] Step 6:

[1554] The server sends the generated coordinates to the terminal. The input is the data of the generated coordinates, and the output is the display of the proposed coordinates on the terminal.

[1555] Step 7:

[1556] The user checks the proposed outfits and selects them if they like them. The input is the user's confirmation and selection actions, and the output is the transmission of the selected outfit information from the terminal to the server.

[1557] Step 8:

[1558] The server saves the selected outfit in a database for future suggestions. In this step, the input is the outfit information selected by the user, and the output is the saved outfit data.

[1559] Step 9:

[1560] The user selects to rent or purchase a new item from the proposed items through the subscription service. The input is the user's selection action of renting or purchasing, and the output is the transmission of order information for the selected item from the terminal to the server.

[1561] Step 10:

[1562] The server sends the order data to the partner external brand and starts the delivery procedure. The input is the user's order data, and the output is the transmission of the order data to the external brand and the start of the delivery procedure.

[1563] Step 11:

[1564] After receiving new items, the server uses the generative AI model again to propose new outfits and sends the results to the device. The input is the new item information and existing user data, and the output is the new outfit proposal data.

[1565] 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.

[1566] MODE FOR CARRYING OUT THE INVENTION

[1567] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day, and then provides coordination that takes the user's emotions into consideration. The system works in cooperation with a server, a terminal, and an emotion engine, and each component plays a specific role.

[1568] Server Roles

[1569] The server is the core of the system and performs the following functions:

[1570] 1. Weather data collection: Integrate with external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.). The collected data is used as a basis for learning from past trends and patterns.

[1571] 2. User Data Management: Manages a database of users' clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[1572] 3. Emotion data management: Manage user emotion data sent from the emotion engine and learn past emotion trends.

[1573] 4. Coordination suggestion generation: Using AI algorithms, the system generates optimal outfits based on weather data, user data, destination information, and emotional data, eliminating the need for users to worry about choosing their daily outfits.

[1574] 5. Saving outfits: The outfits selected by the user are saved in a database and used as learning data for future suggestions.

[1575] 6. Offering rental and purchase options: We partner with third-party brands to offer users the option to rent or purchase selected latest fashion items.

[1576] Device Role

[1577] The terminal operated by the user has the following functions:

[1578] 1. User Authentication: Provides an authentication process for users to log in to their accounts. The authentication information is sent to the server and verified there.

[1579] 2. Sending input information: The user inputs the day's temperature, weather, destination, etc. and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[1580] 3. Acquiring emotional data: The emotion engine generates emotional data based on the user's facial expressions and input information, and sends it to the server via the device.

[1581] 4. Display of outfits: The outfits sent from the server are visually displayed. The suggestions are displayed in a format that is easy for the user to check, helping them make a selection.

[1582] 5. Order Processing: If you select the rental or purchase option, the order data is sent to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[1583] User Roles

[1584] Users operate the system and fulfill the following roles:

[1585] 1. Initial setup and registration: When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits. The emotion engine also initially registers the user's emotional data.

[1586] 2. Daily input and confirmation: Enter the daily weather conditions, destination, and emotional data, and check the outfits sent back from the server. If you like the outfit, you can send your decision to the server via your device.

[1587] 3. Rent and Buy: Choose your option to rent or buy a new fashion item and follow the necessary steps.

[1588] Specific examples

[1589] A day in the life of User A

[1590] 1. Morning

[1591] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[1592] User: User A enters his / her user ID and password and taps the login button.

[1593] Device: Sends authentication information to the server.

[1594] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[1595] Device: Displays login success and displays the home screen.

[1596] User: User A inputs the temperature, weather, destination, and emotions for that day. For example, "Sunny," "25 degrees," "Office," and "Feeling a little tired."

[1597] 2. Transmission of information

[1598] Terminal: Sends the entered information to the server.

[1599] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[1600] 3. Coordination suggestions

[1601] Server: Referencing User A's registration database and emotional data, the AI ​​algorithm generates optimal outfits based on past data. For example, it suggests a combination of a shirt, pants, jacket, and shoes made of a relaxed material.

[1602] Server: Sends the generated coordinates to the terminal.

[1603] Device: Display suggested outfits.

[1604] User: User A reviews the suggestions and selects the outfit if they like it.

[1605] Terminal: Sends the selected coordinates to the server and stores them.

[1606] 4. Use of Subscription Services

[1607] User: User A rents the suggested new jacket through a subscription service.

[1608] Terminal: Sends rental orders to the server.

[1609] Server: Sends order data to partner brands and initiates shipping procedures.

[1610] In this way, User A can streamline their daily clothing selection and enjoy optimal fashion that takes their emotions into consideration. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[1611] The processing flow will be explained below.

[1612] Step 1:

[1613] On the device: The user opens the application and the login screen appears. The user enters their user ID and password and taps the login button.

[1614] Step 2:

[1615] Terminal: Sends the entered user ID and password to the server.

[1616] Step 3:

[1617] Server: Compares the received user ID and password with the database. If the login is successful, it sends the user data to the terminal, and if not, it sends an error message to the terminal.

[1618] Step 4:

[1619] Device: If login is successful, display the home screen.

[1620] Step 5:

[1621] User: Enters the weather, temperature, destination (e.g., office, casual outing, formal event), and emotional state (e.g., "slightly tired," "energetic," etc.) for the day.

[1622] Step 6:

[1623] Terminal: Sends the entered information to the server.

[1624] Step 7:

[1625] Server: Accesses external weather data API to collect the latest weather information (temperature, weather conditions), and compares this information with user input.

[1626] Step 8:

[1627] Server: Manages user emotion data sent from the emotion engine and learns past emotion trends.

[1628] Step 9:

[1629] Server: Refers to the user's clothing database and uses AI algorithms to generate optimal outfits based on past weather data and fashion information. For example, it suggests shirts, pants, jackets, and shoes made from relaxing materials.

[1630] Step 10:

[1631] Server: Sends the generated coordinates to the terminal.

[1632] Step 11:

[1633] Device: Visually displays the received outfits, showing a list of combinations of shirts, jackets, pants, shoes, etc.

[1634] Step 12:

[1635] User: Select the outfit they like from the ones presented. Once they have made their selection, they tap the confirm button.

[1636] Step 13:

[1637] Terminal: Sends the selected coordinate information to the server.

[1638] Step 14:

[1639] Server: The selected coordinates are saved in a database and used as learning data for future suggestions.

[1640] Step 15:

[1641] User: Selects a subscription option to rent or purchase new fashion items included in the suggested outfits.

[1642] Step 16:

[1643] Terminal: Sends rental or purchase order data to the server.

[1644] Step 17:

[1645] Server: Sends order data to partner external brands and initiates shipping procedures.

[1646] Step 18:

[1647] User: After receiving new items, the user uses the application again to receive new outfit suggestions based on the new items.

[1648] In this way, a system is realized that allows users to efficiently choose their daily outfits and enjoy optimal fashion that takes their emotions into consideration.

[1649] Example 2

[1650] 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."

[1651] Conventional coordination systems were limited to making suggestions based on the user's weather conditions and the clothing they owned, and were unable to make coordination suggestions that took into account the user's emotions or current mood. Furthermore, when users wanted to try out the latest fashion items, the process was cumbersome and burdensome for users. This resulted in a decrease in satisfaction and efficiency with fashion.

[1652] 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.

[1653] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for acquiring and managing the user's emotional data, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing options to rent or purchase fashion items, means for transmitting order data to affiliated external brands, and means for proposing new outfits after new items arrive. This makes it possible to propose outfits that reflect the user's emotions and current mood in addition to weather conditions and data on the clothing they own, and also allows them to smoothly try on and purchase the latest fashion items.

[1654] "Latest weather data" refers to environmental information such as current and near-future temperature, weather, humidity, and wind speed.

[1655] "User clothing data" refers to information about the clothing items owned by the user, including the type, color, material, style, and size of the item.

[1656] "User emotional data" refers to data that indicates the user's current emotions and moods as inferred from their facial expressions, input information, and past data.

[1657] "Means for generating outfits" refers to algorithms or systems that suggest optimal outfit combinations based on collected weather data, data on the user's clothing, and emotional data.

[1658] "Means for displaying coordination" refers to a device or application for visually presenting the generated outfit combinations to the user.

[1659] "Means for saving outfits" refers to a system that records the outfit combinations selected by the user in a database for future reference or as learning data.

[1660] "Means for providing rental or purchase options" refers to systems or applications that suggest options for users to rent or purchase their favorite latest fashion items and assist them in the process.

[1661] "Means for transmitting order data to partnering third-party brands" refers to a system that transmits order information to third-party fashion brands and retailers based on the rental or purchase option selected by the user.

[1662] "Means to suggest new outfits after new items arrive" refers to algorithms or systems that incorporate the user's newly acquired fashion items and suggest optimal outfit combinations again.

[1663] "Historical weather data" refers to information about temperature and weather conditions over a specific period in the past.

[1664] "Past emotion data" refers to data records regarding emotions and moods that a user has felt in the past.

[1665] "Fashion information" refers to data about the latest trends, styles, and fashions.

[1666] "User input means" refers to an interface or device that allows a user to manually input information such as temperature, weather, destination, and emotion.

[1667] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day, and then provides coordination that takes the user's emotions into consideration. The system works in cooperation with a server, a terminal, and an emotion engine, and each component plays a specific role.

[1668] Server Roles

[1669] The server is the core of the system and performs the following functions:

[1670] 1. Meteorological data collection:

[1671] The server connects to an external weather data API (e.g., OpenWeatherMap API) to collect the latest weather information (temperature, weather, humidity, wind speed, etc.), which allows it to always provide suggestions based on the latest weather data.

[1672] 2. Managing your data:

[1673] The server manages a database of the user's clothing and style preferences, allowing the user to keep an up-to-date inventory of the clothing items they own.

[1674] 3. Emotional Data Management:

[1675] The server manages the user's emotional data sent from the emotion engine and learns past emotional trends. This information is reflected in the outfit suggestions.

[1676] 4. Coordination proposal generation:

[1677] The server uses AI algorithms (e.g., models using TensorFlow or PyTorch) to generate optimal outfits based on weather data, user data, destination information, and emotional data. This process allows users to receive more accurate outfit suggestions.

[1678] 5. Save your outfit:

[1679] The server stores the user's selected outfits in a database and uses them as learning data to help with future suggestions.

[1680] 6. Offering Rental and Purchase Options:

[1681] The server works with partner external brands to provide users with the option to rent or purchase the latest fashion items of their choice, allowing them to easily try out the latest fashions.

[1682] Device Role

[1683] The terminal operated by the user has the following functions:

[1684] 1. User authentication:

[1685] The device provides an authentication process for the user to log into their account, and the authentication information is sent to the server where it is verified.

[1686] 2. Submitting input information:

[1687] The user inputs the day's temperature, weather, destination, etc. into the device, and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[1688] 3. Acquiring emotion data:

[1689] The device's emotion engine generates emotion data based on the user's facial expressions and input information, and sends it to a server via the device. The emotion engine uses facial recognition technology and natural language processing (NLP) technology.

[1690] 4. Show your outfit:

[1691] The terminal visually displays the coordinates sent from the server, allowing the user to easily check and select the suggestions.

[1692] 5. Order Processing:

[1693] If the user selects the rental or purchase option, the device sends the order data to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[1694] User Roles

[1695] The user operates the system and performs the following roles:

[1696] 1. Initial Setup and Registration:

[1697] When using the app for the first time, users register their clothing and preferred styles. The server then manages this data and uses it to suggest outfits. The emotion engine also initially registers the user's emotional data.

[1698] 2. Daily input and confirmation:

[1699] Users input their daily weather conditions, destination, and emotions, and then check the outfits sent back from the server. If they like the outfit, they can send their decision to the server via their device.

[1700] 3. Rental and Purchase:

[1701] Users select the option to rent or purchase a new fashion item and complete the necessary steps.

[1702] Specific examples

[1703] A day in the life of User A

[1704] 1. Morning

[1705] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[1706] User: User A enters his / her user ID and password and taps the login button.

[1707] Device: Sends authentication information to the server.

[1708] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[1709] Device: Displays login success and displays the home screen.

[1710] User: User A inputs the temperature, weather, destination, and emotions for that day. For example, "Sunny," "25 degrees," "Office," and "Feeling a little tired."

[1711] 2. Transmission of information

[1712] Terminal: Sends the entered information to the server.

[1713] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[1714] 3. Coordination suggestions

[1715] Server: Referencing User A's registration database and emotional data, the AI ​​algorithm generates optimal outfits based on past data. For example, it suggests a combination of a shirt, pants, jacket, and shoes made of a relaxed material.

[1716] Server: Sends the generated coordinates to the terminal.

[1717] Device: Display suggested outfits.

[1718] User: User A reviews the suggestions and selects the outfit if they like it.

[1719] Terminal: Sends the selected coordinates to the server and stores them.

[1720] 4. Use of Subscription Services

[1721] User: User A rents the suggested new jacket through a subscription service.

[1722] Terminal: Sends rental orders to the server.

[1723] Server: Sends order data to partner brands and initiates shipping procedures.

[1724] In this way, User A can streamline their daily clothing selection and enjoy optimal fashion that takes their emotions into consideration. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[1725] Prompt Sentence Examples

[1726] "25 degrees, sunny, office, feeling a bit tired"

[1727] Based on this information, the system provides input data for a generative AI model, allowing the device to receive optimal outfit suggestions.

[1728] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1729] Step 1: User authentication

[1730] Input: User ID and Password

[1731] Output: Home screen

[1732] Device: Launch the app and the login screen will appear.

[1733] User: Enter your user ID and password and tap the login button.

[1734] Device: Sends authentication information to the server.

[1735] Server: Checks the received authentication information against a database and returns a success or failure result to the terminal.

[1736] Terminal: If login is successful, the home screen is displayed and user data is sent to the terminal.

[1737] Step 2: Initial data entry

[1738] Input: User's clothing, preferred style, and emotional data

[1739] Output: Registration complete confirmation message

[1740] User: Register your clothes and preferred style on the home screen. Also, register your initial emotional data.

[1741] Terminal: Sends data entered by the user to the server.

[1742] Server: Stores the received data in a database and sends a confirmation message to the terminal that registration is complete.

[1743] Step 3: Meteorological data collection

[1744] Input: Weather information for the day, destination entered by the user

[1745] Output: Latest weather data

[1746] User: Enter the weather conditions for the day (e.g., "sunny" and "25 degrees") and destination.

[1747] Terminal: Sends the entered information to the server.

[1748] Server: Uses an external weather data API (e.g., OpenWeatherMap API) to collect the latest weather information.

[1749] Server: Compares the collected weather data with the information entered by the user and stores it in a database.

[1750] Step 4: Acquire emotion data

[1751] Input: User's facial expression, input information

[1752] Output: Emotion data

[1753] Device: The emotion engine captures the user's facial expressions with a camera, analyzes the data, and generates emotion data.

[1754] Terminal: Sends the generated emotion data to the server.

[1755] Server: Stores the emotion data in a database for future analysis.

[1756] Step 5: Coordinate generation

[1757] Input: Weather data, user data, emotion data, destination information

[1758] Output: Optimal Coordination

[1759] Server: Based on the received weather data, user data, emotion data, and destination information, an AI algorithm is used to generate the optimal coordinates. At this stage, a generative AI model (e.g., TensorFlow or PyTorch) is used.

[1760] Server: Sends the generated coordinate data to the terminal.

[1761] Step 6: Coordination presentation and selection

[1762] Input: Best outfit

[1763] Output: Selected coordinates

[1764] Terminal: Visually displays the outfit received from the server (e.g., a relaxed shirt, pants, jacket, and shoes).

[1765] User: Check the presented outfits and select if you like them.

[1766] Terminal: Sends the selected coordinate information to the server.

[1767] Step 7: Save your outfit

[1768] Input: Selected coordinates

[1769] Output: Save complete confirmation message

[1770] Server: The selected coordinates are stored in a database and used as learning data for future suggestions.

[1771] Server: Sends a confirmation message to the terminal that the save is complete.

[1772] Step 8: Rental / Purchase Process

[1773] Input: The rental or purchase option selected by the user

[1774] Output: Order completed confirmation message

[1775] User: Selects an option to rent or buy a fashion item, such as a new jacket.

[1776] Terminal: Sends the user's order information to the server.

[1777] Server: Sends order data to partner external brands and initiates shipping procedures.

[1778] Server: Sends a confirmation message to the terminal that the order has been completed.

[1779] (Application example 2)

[1780] 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."

[1781] Conventional outfit suggestion systems can suggest outfits based on the user's weather conditions and preferences, but they cannot consider the user's emotions. It is also difficult to suggest appropriate outfits based on the driver's emotions inside an autonomous vehicle. This makes it difficult to suggest optimal outfits to reduce fatigue and stress, especially during long driving trips.

[1782] 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.

[1783] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing options for renting or purchasing clothing items, means for sending order data to affiliated external brands, means for suggesting new outfits after new items arrive, means for acquiring facial images using a camera attached to the information entertainment system in the autonomous vehicle and analyzing emotional data, means for suggesting outfits that suit the driver based on the analyzed emotional data, and means for displaying the suggested outfits on an in-vehicle display. This enables optimal outfit suggestions based on the driver's emotions and weather conditions, improving driving comfort and safety.

[1784] "Weather data" is information about weather conditions such as temperature, weather, humidity, and wind speed.

[1785] "Clothing data" refers to information about the type, design, material, color, size, etc. of clothing owned by the user.

[1786] "Outfit" refers to the coordination suggested based on weather conditions and emotions.

[1787] An "information entertainment system" is a system installed in an autonomous vehicle for providing information and displaying entertainment content.

[1788] "Camera" refers to a device that captures images, especially one installed in an autonomous vehicle.

[1789] "Emotional data" is information about the user's emotional state analyzed based on images captured by a camera.

[1790] "External brands" refer to companies or brands that partner with the system to rent or sell clothing items to users.

[1791] "Coordination" refers to the optimal combination of clothing suggested to the user.

[1792] "Rental" refers to a service that allows you to borrow clothing items for a certain period of time.

[1793] "Purchase" refers to purchasing an item of clothing to own it.

[1794] System Overview:

[1795] This invention is a system that proposes optimal outfits based on the user's weather conditions, destination, and emotion data for the day. The system operates in cooperation with a server, a terminal, and an emotion engine.

[1796] Server Role:

[1797] The server is the center of the system and has the following responsibilities:

[1798] 1. Weather data collection: The server uses an external weather data API to collect the latest weather data and then suggests appropriate outfits to the user based on that data.

[1799] 2. Managing clothing data: The server manages the clothing data registered by the user.

[1800] 3. Emotion data management: The server analyzes the emotion data acquired by the camera inside the autonomous vehicle and uses it to propose appropriate coordination.

[1801] 4. Coordination generation: The server uses AI algorithms to generate optimal coordination based on weather data, clothing data, and emotional data.

[1802] 5. Sending proposal: The server sends the generated coordinates to the terminal, which then displays them on the in-car display.

[1803] Device role:

[1804] The user-operated device has the following features:

[1805] 1. User Authentication: Provides an authentication process for users to log in to their accounts.

[1806] 2. Data input: The user inputs the weather conditions, destination, and emotions for the day and sends this to the server.

[1807] 3. Emotion data acquisition: Using a camera installed inside the vehicle, an image of the user's face is acquired and sent to the emotion engine.

[1808] 4. Coordination display: Displays the coordination proposals sent from the server.

[1809] User role:

[1810] The user interfaces with the system to:

[1811] 1. Initial setup and registration: By registering your clothing and preferred styles in the system, you will be prepared to receive optimal outfit suggestions.

[1812] 2. Daily data input: By inputting daily weather conditions, destinations, and emotions, the server will suggest the best outfits for you.

[1813] 3. Review and select the suggestions: Review the outfits sent by the server and select them if you like them.

[1814] Hardware and software used:

[1815] Hardware:

[1816] Information and entertainment systems in autonomous vehicles

[1817] In-car camera

[1818] software:

[1819] requests library (weather data acquisition)

[1820] OpenCV (emotion analysis)

[1821] TensorFlow (AI algorithm)

[1822] Examples:

[1823] Example 1: Morning preparation

[1824] Before getting into a self-driving vehicle, users input "sunny," "25 degrees," "office," and "feeling a bit tired" into a smartphone app. The system then uses weather data to suggest outfits for light shirts and pants. It also analyzes facial images to recommend comfortable clothing.

[1825] Example prompt for a generative AI model:

[1826] "Weather data: Tokyo, Temperature: 28°C, Emotion data: Happy: 0.7, Sad: 0.1, Destination: Office. What is the best outfit?"

[1827] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1828] Step 1:

[1829] User authentication

[1830] Input: User ID and Password

[1831] What happens: A user logs into an app using a device, which sends their credentials to a server, which checks them against a database for authentication.

[1832] Output: If authentication is successful, send user data to the device. Login is successful and the home screen is displayed.

[1833] Step 2:

[1834] Data Entry

[1835] Input: Weather conditions, destination information, emotional state

[1836] Processing: The user inputs the weather conditions, destination, and emotions for the day into the device, which then sends this information to the server.

[1837] Output: The submitted data is stored on the server and used to generate coordinates.

[1838] Step 3:

[1839] Weather data collection

[1840] Input: User's destination information

[1841] Processing: The server uses an external weather data API to gather the latest weather information for the user's destination, sending an API request to get information such as temperature, weather, humidity, and wind speed.

[1842] Output: The acquired weather data is saved and used to generate coordinates.

[1843] Step 4:

[1844] Emotional Data Analysis

[1845] Input: Facial image captured by the in-car camera

[1846] Processing: The device captures the user's facial expressions using the in-car camera and sends the image data to the emotion engine, which uses OpenCV to preprocess the images and TensorFlow AI models to analyze emotions.

[1847] Output: The emotion analysis results are sent to the server and stored as user emotion data.

[1848] Step 5:

[1849] Coordinate generation

[1850] Input: Weather data, clothing data, emotion data

[1851] Processing: The server uses AI algorithms to generate the optimal outfit based on collected weather data, accumulated clothing data, and emotion analysis results. The generation process involves selecting materials based on temperature and suggesting colors and styles based on emotional state.

[1852] Output: The generated coordinates are sent from the server to the device.

[1853] Step 6:

[1854] Displaying outfits

[1855] Input: Generated coordinates

[1856] Processing: The terminal receives the coordinates sent from the server and displays them on the in-car display. The user confirms the displayed coordinates.

[1857] Output: The coordinates are visually presented for user confirmation.

[1858] Step 7:

[1859] Select and save outfits

[1860] Input: User's choice

[1861] Process: The user selects their favorite outfit and sends the selection to the server via their device. The server stores the selected outfit in a database for future suggestions.

[1862] Output: The selected coordinates are saved.

[1863] Step 8:

[1864] Rental and purchase procedures

[1865] Input: User's rental or purchase intent

[1866] Processing: If the user decides to rent or purchase a new clothing item, they submit the order via their device to the server, which then sends the order data to the partnering external brand and initiates the delivery process.

[1867] Output: The order is placed and the item is delivered.

[1868] 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.

[1869] 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.

[1870] 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.

[1871] [Fourth embodiment]

[1872] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1873] 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.

[1874] 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).

[1875] 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.

[1876] 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.

[1877] 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).

[1878] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1879] 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.

[1880] 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.

[1881] 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.

[1882] 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.

[1883] 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.

[1884] 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."

[1885] MODE FOR CARRYING OUT THE INVENTION

[1886] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day. This system is made up of three components: a server, a terminal, and a user, who exchange information with each other, and each component plays a specific role.

[1887] Server Roles

[1888] The server is the core of the system and performs the following functions:

[1889] 1. Weather data collection: Integrate with external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.). The collected data is used as a basis for learning from past trends and patterns.

[1890] 2. User Data Management: Manages a database of users' clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[1891] 3. Generating outfit suggestions: Using AI algorithms, the system generates optimal outfit suggestions based on weather data, user data, and destination information, eliminating the need for users to worry about choosing their daily outfits.

[1892] 4. Saving outfits: The outfits selected by the user are saved in a database and used as learning data for future suggestions.

[1893] 5. Offering rental and purchase options: We partner with third-party brands to offer users the option to rent or purchase the latest fashion items of their choice.

[1894] Device Role

[1895] The terminal operated by the user has the following functions:

[1896] 1. User Authentication: Provides an authentication process for users to log in to their accounts. The authentication information is sent to the server and verified there.

[1897] 2. Sending input information: The user inputs the day's temperature, weather, destination, etc. and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[1898] 3. Display of outfits: The outfits sent from the server are visually displayed. The suggestions are displayed in a format that is easy for the user to check, helping them make a selection.

[1899] 4. Order Processing: If you select the rental or purchase option, the order data is sent to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[1900] User Roles

[1901] Users operate the system and fulfill the following roles:

[1902] 1. Initial setup and registration: When using the app for the first time, you will need to register your clothing and preferred style. This data will be managed on the server and used to suggest outfits.

[1903] 2. Daily input and confirmation: Enter the daily weather conditions and destination, and check the coordinates returned by the server. If you like it, send your decision to the server via your device.

[1904] 3. Rent and Buy: Choose your option to rent or buy a new fashion item and follow the necessary steps.

[1905] Specific examples

[1906] A day in the life of User A

[1907] 1. Morning

[1908] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[1909] User: User A enters his / her user ID and password and taps the login button.

[1910] Device: Sends authentication information to the server.

[1911] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[1912] Device: Displays login success and displays the home screen.

[1913] 2. Enter your information

[1914] User: User A enters the information "sunny," "25 degrees," and "office" on the home screen.

[1915] Terminal: Sends this information to the server.

[1916] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[1917] 3. Coordination suggestions

[1918] Server: Referencing User A's registered database, the AI ​​algorithm generates the optimal outfit based on past data, suggesting combinations of T-shirt, jacket, pants, and shoes.

[1919] Server: Sends the generated coordinates to the terminal.

[1920] Device: Display suggested outfits.

[1921] User: User A reviews the suggestions and selects the outfit if they like it.

[1922] Terminal: Sends the selected coordinates to the server and stores them.

[1923] 4. Use of Subscription Services

[1924] User: User A rents the suggested new jacket through a subscription service.

[1925] Terminal: Sends rental orders to the server.

[1926] Server: Sends order data to partner brands and initiates shipping procedures.

[1927] In this way, User A can streamline their daily clothing selection and always maintain the best fashion. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[1928] The processing flow will be explained below.

[1929] Step 1:

[1930] On the device: The user opens the application and the login screen appears. The user enters their user ID and password and taps the login button.

[1931] Step 2:

[1932] Terminal: Sends the entered user ID and password to the server.

[1933] Step 3:

[1934] Server: Compares the received user ID and password with the database. If the login is successful, sends the user data to the terminal. If not successful, sends an error message to the terminal.

[1935] Step 4:

[1936] Device: If login is successful, display the home screen.

[1937] Step 5:

[1938] User: Enters the weather for the day, temperature, and destination (e.g., office, casual outing, formal event).

[1939] Step 6:

[1940] Terminal: Sends the entered information to the server.

[1941] Step 7:

[1942] Server: Accesses external weather data API to collect the latest weather information (temperature, weather conditions), and compares this information with user input.

[1943] Step 8:

[1944] Server: Refers to the database of the user's clothing and uses AI algorithms to generate optimal outfits based on past weather data and fashion information. For example, it suggests shirts, jackets, pants, shoes, etc.

[1945] Step 9:

[1946] Server: Sends the generated coordinates to the terminal.

[1947] Step 10:

[1948] Device: Visually displays the received outfits, showing a list of combinations of shirts, jackets, pants, shoes, etc.

[1949] Step 11:

[1950] User: Select the outfit they like from the ones presented. Once they have made their selection, they tap the confirm button.

[1951] Step 12:

[1952] Terminal: Sends the selected coordinate information to the server.

[1953] Step 13:

[1954] Server: The selected coordinates are saved in a database and used as learning data for future suggestions.

[1955] Step 14:

[1956] User: Selects a subscription option to rent or purchase new fashion items included in the suggested outfits.

[1957] Step 15:

[1958] Terminal: Sends rental or purchase order data to the server.

[1959] Step 16:

[1960] Server: Sends order data to partner external brands and initiates shipping procedures.

[1961] Step 17:

[1962] User: After receiving new items, the user uses the application again to receive new outfit suggestions based on the new items.

[1963] In this way, a system is realized that allows users to efficiently choose their daily outfits and always enjoy the most appropriate fashion.

[1964] Example 1

[1965] 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."

[1966] In modern society, choosing the best outfit for each day based on weather conditions and schedules is a tedious task for many users. Managing existing clothing and renting or purchasing new fashion items can also be time-consuming. There is a need for a way to efficiently solve these issues, simplify daily outfit selection, and ensure optimal fashion at all times.

[1967] 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.

[1968] In this invention, the server includes means for collecting the latest weather data, means for managing the user's clothing data, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing the option to rent or purchase fashion items, means for transmitting order data to affiliated external suppliers, means for proposing new outfits after new items arrive, means for transmitting daily temperature, weather, and destination information entered by the user, means for comparing the weather data with the user's clothing data, and means for generating outfits using an AI algorithm. This allows users to easily select optimal outfits based on daily weather conditions and plans, and enables efficient clothing management and the rental or purchase of new items.

[1969] "Weather data" is information about weather conditions such as temperature, weather, humidity, and wind speed.

[1970] "User's clothing data" refers to data including details of clothing owned by the user, such as style, size, and color.

[1971] The "coordination generation means" is a system that automatically suggests optimal outfit combinations based on weather data and the user's clothing data.

[1972] The "means for displaying generated coordinated outfits" is an interface for visually displaying to the user the outfit combinations proposed by the server or terminal.

[1973] The "coordinate storage means" is a system that stores the outfit combinations selected by the user in a database.

[1974] "Rental or purchase option providing means" refers to a system that provides a user with the option to rent or purchase a suggested fashion item.

[1975] "Order data transmission means" refers to a means for transmitting a user's rental or purchase order to an affiliated external supplier.

[1976] The "new coordination suggestion method" is a system that suggests new outfit combinations that include new items after the user receives them.

[1977] The "means for transmitting daily temperature, weather, and destination information" is a system that transmits information about the temperature, weather, and destination of the day entered by the user to the server.

[1978] The "means for comparing weather data with user's clothing data" is a means for comparing collected weather data with the user's clothing data to select the optimal outfit.

[1979] "A means for generating coordination using an AI algorithm" is a system that uses an artificial intelligence algorithm to generate optimal clothing combinations.

[1980] The present invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day. This system is made up of three components: a server, a terminal, and a user, who exchange information with each other, and each component plays a specific role.

[1981] Server Roles

[1982] Weather data collection

[1983] The server connects to external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.) using software such as the OpenWeatherMap API or WeatherStack API. The collected data is stored in a database and used as a basis for learning from past trends and patterns.

[1984] Managing User Data

[1985] The server manages a database of the user's clothing and style preferences, which is used to keep the user's inventory of clothing items up to date.

[1986] Generating outfit suggestions

[1987] The server uses AI algorithms to generate optimal trips based on weather data, user data, and destination information, using machine learning frameworks such as TensorFlow and PyTorch.

[1988] Save your outfit

[1989] The coordination selected by the user is stored in a database and used as learning data to help with future suggestions.

[1990] Offering rental and purchase options

[1991] The server works with affiliated external suppliers, such as general online fashion stores, to provide users with the option to rent or purchase selected latest fashion items.

[1992] Device Role

[1993] User authentication

[1994] The device provides an authentication process for the user to log into their account, and the authentication information is sent to the server where it is verified.

[1995] Sending input information

[1996] The user inputs the temperature, weather, destination, and other information for that day, and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[1997] Displaying outfits

[1998] The terminal visually displays the coordinates sent from the server, and displays the suggestions in a format that is easy for the user to check.

[1999] Order Processing

[2000] If the user selects the rental or purchase option, the terminal sends the order data to the server, which then sends the order to the partner external supplier and initiates the delivery process.

[2001] User Roles

[2002] Initial Setup and Registration

[2003] When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits.

[2004] Daily input and confirmation

[2005] Users input the daily weather conditions and destinations, check the outfits sent back from the server, and if they like the outfit, they send their decision to the server via their device.

[2006] Rental and Purchase

[2007] Users select the option to rent or purchase a new fashion item and complete the necessary steps.

[2008] Examples of specific examples and prompt usage

[2009] As an example of actual use, we will explain specific situations in which users use the app.

[2010] A day in the life of User A

[2011] morning

[2012] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[2013] User: Enter your user ID and password and tap the login button.

[2014] Device: Sends authentication information to the server.

[2015] Server: Checks the authentication information against a database and sends the user data to the device if the login is successful.

[2016] Terminal: Displays login success and displays the home screen.

[2017] Entering information

[2018] User: User A enters the information "Sunny", "25 degrees", and "Office" on the home screen.

[2019] Device: Sends this information to the server.

[2020] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[2021] Coordination suggestions

[2022] Server: Referencing User A's registered database, the AI ​​algorithm generates the optimal outfit based on past data, suggesting combinations of T-shirt, jacket, pants, and shoes.

[2023] Server: Sends the generated coordinates to the device.

[2024] Device: Display suggested outfits.

[2025] User: User A reviews the suggestions and selects the outfit if they like it.

[2026] Device: Sends the selected coordinates to the server and saves them.

[2027] Use of subscription services

[2028] User: User A rents a suggested new jacket through a subscription service.

[2029] Terminal: Sends rental orders to the server.

[2030] Server: Sends order data to partner brands and initiates the shipping process.

[2031] Examples of prompt statements

[2032] An example of a prompt that a user might enter into the system is:

[2033] "Tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and humidity of 70%. Please suggest some business casual attire."

[2034] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2035] Step 1:

[2036] User authentication

[2037] Device: The user launches the app and sees the login screen.

[2038] Input: User ID and password

[2039] Output: Sends login information to the server

[2040] User: Enter your user ID and password and tap the login button.

[2041] Device: Sends authentication information to the server.

[2042] Input: User ID and password

[2043] Output: Sending authentication information

[2044] Server: Checks the authentication information against the database, and if the login is successful, sends the user data to the terminal.

[2045] Input: Credentials

[2046] Data calculation: User ID and password verification

[2047] Output: Login success or failure information

[2048] Device: Displays login success and displays the home screen.

[2049] Input: Login success information

[2050] Output: Login success screen displayed

[2051] Step 2:

[2052] Entering information

[2053] User: The user enters the information "sunny," "25 degrees," and "office" from the home screen.

[2054] Input: Temperature, weather, destination information

[2055] Output: Preparing input information for transmission

[2056] Terminal: Sends this information to the server.

[2057] Input: User input information

[2058] Data calculation: Format conversion of input information

[2059] Output: Send to server

[2060] Step 3:

[2061] Meteorological data collection and collation

[2062] Server: Collects the latest weather information from an external weather data API.

[2063] Input: Request to external weather API

[2064] Output: Latest weather data

[2065] Server: Stores the collected weather data in a database.

[2066] Input: Collected weather data

[2067] Data processing: saving to database

[2068] Output: Save completion information

[2069] Server: Matches the information entered by the user with the collected weather data.

[2070] Input: User input information, latest weather data

[2071] Data calculation: Check whether the input information matches the weather data

[2072] Output: Matching result

[2073] Step 4:

[2074] Generating outfit suggestions

[2075] Server: Refers to the user's clothing database to obtain the user's clothing and preferred styles.

[2076] Input: User database query

[2077] Output: Clothing data

[2078] Server: Using AI algorithms, it generates optimal coordination based on weather data, user data, and destination information.

[2079] Input: Weather data, clothing data, destination information

[2080] Data calculation: Coordination suggestions based on AI models

[2081] Output: Generated coordinates

[2082] Server: Sends the generated coordinates to the terminal.

[2083] Input: Generated coordinates

[2084] Output: Send to terminal

[2085] Step 5:

[2086] View and select suggestions

[2087] Terminal: Visually displays the proposed coordination.

[2088] Input: Generated coordinate information

[2089] Output: Display of proposal

[2090] User: Check the suggestions and select the outfit they like.

[2091] Input: Proposal

[2092] Output: Selection information

[2093] Terminal: Sends the selected coordinates to the server.

[2094] Input: User selection information

[2095] Output: Send to server

[2096] Server: Saves the selected coordinates in the user database.

[2097] Input: Selected coordinate information

[2098] Data processing: saving to database

[2099] Output: Save completion information

[2100] Step 6:

[2101] Use of subscription service (optional)

[2102] User: Select the option to rent or buy the suggested new item.

[2103] Input: Rental or purchase selection information

[2104] Output: Order information ready to send

[2105] Terminal: Sends rental or purchase orders to the server.

[2106] Input: User's order information

[2107] Output: Send to server

[2108] Server: Sends order information to affiliated external suppliers and initiates delivery procedures.

[2109] Input: Order Information

[2110] Output: Sending order information to partner suppliers, information on starting delivery procedures

[2111] (Application example 1)

[2112] 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."

[2113] Conventional clothing suggestion systems have not been able to provide sufficient support for users in choosing the most appropriate outfit based on the day's weather conditions and destination. Furthermore, the process of suggesting, renting, and purchasing the latest fashion items is cumbersome, reducing user convenience. Therefore, there was a need for a system that could suggest optimal outfits based on weather conditions and destination, and easily rent or purchase fashion items.

[2114] 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.

[2115] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing an option to rent or purchase fashion items, means for transmitting order data to affiliated external brands, means for proposing new outfits after new items arrive, means for generating outfits using a generative AI model, and means for collecting user input via prompt text. This allows the user to receive optimal outfit suggestions based on weather conditions and destination, and further allows the user to easily rent or purchase the suggested fashion items.

[2116] "Means for collecting weather data" refers to a system for obtaining the latest information such as temperature, weather, humidity, and wind speed from external weather data providers.

[2117] "A means of managing clothing data" is a system for registering and storing the types of clothing owned by users, their attributes, and preferred styles in a database.

[2118] The "means for generating coordination" is an algorithm or program that suggests optimal clothing combinations based on collected weather data and managed clothing data.

[2119] The "means for displaying coordinates" refers to a display device or application for visually presenting the generated coordinates to the user.

[2120] The "means for saving outfits" refers to a system that records the outfits selected by the user in a database for use in future suggestions and analysis.

[2121] "Means for providing rental or purchase options" refers to an interface and system that allows users to choose between renting or purchasing suggested fashion items.

[2122] "Means for sending order data to external brands" refers to a system that sends order information for the items selected by the user to partner brands or retailers and initiates the purchase or rental process.

[2123] The "means for suggesting new coordination" is an algorithm or program for regenerating the latest coordination including newly arrived items and suggesting it to the user.

[2124] A "generative AI model" is an artificial intelligence algorithm that learns from large amounts of data and generates outfits.

[2125] A "means for collecting user input via prompt sentences" is a system for analyzing information entered by a user in natural language and obtaining and processing the required data.

[2126] This invention is a system that allows users to choose the best outfit based on the day's weather conditions and destination. The system is made up of three components: a server, a device, and a user, each of which plays a specific role. It is particularly notable for collecting user input via a generative AI model and prompts.

[2127] Server Roles

[2128] The server is the core of the system and performs the following functions:

[2129] 1. Weather data collection: The server connects to an external weather data API (e.g., Weatherstack) to collect the latest weather information (temperature, weather, humidity, wind speed, etc.), allowing users to understand the weather conditions at their current location or a specified location in real time.

[2130] 2. User Data Management: The server manages a database of the user's clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[2131] 3. Coordination suggestion generation: The server uses a generative AI model to generate optimal outfits based on weather data, user data, and destination information, eliminating the need for users to worry about choosing their daily outfits.

[2132] 4. Saving the outfit: The server saves the outfit selected by the user in a database and uses it as learning data to help with future suggestions.

[2133] 5. Providing rental and purchase options: The server works with partner external brands to provide users with the option to rent or purchase the latest fashion items of their choice.

[2134] 6. Sending order data: The server sends the order information for the items selected by the user to the partner brand or retailer to initiate the purchase or rental process.

[2135] 7. Proposing a new outfit: After new items arrive, the server again uses the generative AI model to propose a new outfit.

[2136] Device Role

[2137] The terminal operated by the user has the following functions:

[2138] 1. User authentication: The device provides an authentication process for the user to log in to their account. The authentication information is sent to the server and verified there.

[2139] 2. Data input and transmission: The terminal prompts the user to input the day's temperature, weather, destination, etc., and transmits this information to the server, which then obtains the data needed to generate the optimal coordinates.

[2140] 3. Display of outfits: The device visually displays the outfits sent from the server, helping the user make a selection by displaying the suggestions in an easy-to-read format.

[2141] 4. Order Processing: If the user selects the rental or purchase option, the device sends the order data to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[2142] User Roles

[2143] Users operate the system and fulfill the following roles:

[2144] 1. Initial setup and registration: When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits.

[2145] 2. Daily information input and confirmation: The user inputs the daily weather conditions and destinations in the prompts and checks the coordinates returned by the server. If the generated coordinates are satisfactory, the user sends the decision to the server via the terminal.

[2146] 3. Rent and Buy: Users select the option to rent or buy a new fashion item and complete the necessary steps.

[2147] Example: A day in the life of User A

[2148] morning

[2149] User A wakes up in the morning, launches the app, and the login screen appears. User A enters their user ID and password and taps the login button. The device sends the authentication information to the server, and the server authenticates the login. If the login is successful, the home screen appears on the device.

[2150] Entering information

[2151] User A inputs the information "sunny," "25 degrees," and "office" using prompts from the home screen. The device sends this information to the server, which then collects the latest weather information from an external weather data API and compares it with User A's information.

[2152] Coordination suggestions

[2153] The server references User A's registration database, and the generative AI model generates the optimal outfit. For example, it suggests a combination of a T-shirt, jacket, pants, and shoes. The generated outfit is sent to the device, where User A checks it. If User A likes it, he or she selects the outfit, and the device sends the selected outfit to the server and saves it.

[2154] Use of subscription services

[2155] If User A wants to rent the suggested new jacket through the subscription service, the device sends a rental order to the server, which then sends the order data to the partner brand and initiates the delivery process.

[2156] Example prompt:

[2157] "It's sunny and 25 degrees today, so I'm heading to the office. Could you recommend an outfit for me? I'd also like to rent the denim jacket you suggested."

[2158] In this way, User A can efficiently choose their daily outfits and always maintain the best fashion. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[2159] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2160] Step 1:

[2161] The server calls an external weather data API to collect current weather data (temperature, weather, humidity, wind speed, etc.) and stores it in a database. The input is the weather data obtained from the API, and the output is a database containing the latest weather data.

[2162] Step 2:

[2163] A user launches a smartphone app and logs in by entering their user ID and password on the login screen. The input is the user's authentication information (user ID and password), and the output is transitioning to the app's home screen. The device sends this authentication information to the server and authenticates the login.

[2164] Step 3:

[2165] The user inputs information such as "sunny," "25 degrees," and "office" using prompts on the home screen. The input is the weather conditions and destination information entered by the user, and the output is to send this information to the server.

[2166] Step 4:

[2167] The server parses the prompt and extracts the input information from the user. The input is the text information of the prompt, and the output is the parsed weather conditions and destination information. The server then compares this with the latest weather data obtained from an external weather data API.

[2168] Step 5:

[2169] The server references the user's registered database and generates the optimal outfit using a generative AI model. The input is the collated weather conditions, destination information, and the user's registered data, and the output is the generated outfit plan.

[2170] Step 6:

[2171] The server sends the generated coordinates to the terminal. The input is the data of the generated coordinates, and the output is the display of the proposed coordinates on the terminal.

[2172] Step 7:

[2173] The user checks the proposed outfits and selects them if they like them. The input is the user's confirmation and selection actions, and the output is the transmission of the selected outfit information from the terminal to the server.

[2174] Step 8:

[2175] The server saves the selected outfit in a database for future suggestions. In this step, the input is the outfit information selected by the user, and the output is the saved outfit data.

[2176] Step 9:

[2177] The user selects to rent or purchase a new item from the proposed items through the subscription service. The input is the user's selection action of renting or purchasing, and the output is the transmission of order information for the selected item from the terminal to the server.

[2178] Step 10:

[2179] The server sends the order data to the partner external brand and starts the delivery procedure. The input is the user's order data, and the output is the transmission of the order data to the external brand and the start of the delivery procedure.

[2180] Step 11:

[2181] After receiving new items, the server uses the generative AI model again to propose new outfits and sends the results to the device. The input is the new item information and existing user data, and the output is the new outfit proposal data.

[2182] 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.

[2183] MODE FOR CARRYING OUT THE INVENTION

[2184] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day, and then provides coordination that takes the user's emotions into consideration. The system works in cooperation with a server, a terminal, and an emotion engine, and each component plays a specific role.

[2185] Server Roles

[2186] The server is the core of the system and performs the following functions:

[2187] 1. Weather data collection: Integrate with external weather data APIs to collect the latest weather information (temperature, weather, humidity, wind speed, etc.). The collected data is used as a basis for learning from past trends and patterns.

[2188] 2. User Data Management: Manages a database of users' clothing and preferred styles, allowing the list of available clothing items to be kept up to date.

[2189] 3. Emotion data management: Manage user emotion data sent from the emotion engine and learn past emotion trends.

[2190] 4. Coordination suggestion generation: Using AI algorithms, the system generates optimal outfits based on weather data, user data, destination information, and emotional data, eliminating the need for users to worry about choosing their daily outfits.

[2191] 5. Saving outfits: The outfits selected by the user are saved in a database and used as learning data for future suggestions.

[2192] 6. Offering rental and purchase options: We partner with third-party brands to offer users the option to rent or purchase selected latest fashion items.

[2193] Device Role

[2194] The terminal operated by the user has the following functions:

[2195] 1. User Authentication: Provides an authentication process for users to log in to their accounts. The authentication information is sent to the server and verified there.

[2196] 2. Sending input information: The user inputs the day's temperature, weather, destination, etc. and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[2197] 3. Acquiring emotional data: The emotion engine generates emotional data based on the user's facial expressions and input information, and sends it to the server via the device.

[2198] 4. Display of outfits: The outfits sent from the server are visually displayed. The suggestions are displayed in a format that is easy for the user to check, helping them make a selection.

[2199] 5. Order Processing: If you select the rental or purchase option, the order data is sent to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[2200] User Roles

[2201] Users operate the system and fulfill the following roles:

[2202] 1. Initial setup and registration: When using the app for the first time, users register their clothing and preferred styles. This data is managed on the server and used to suggest outfits. The emotion engine also initially registers the user's emotional data.

[2203] 2. Daily input and confirmation: Enter the daily weather conditions, destination, and emotional data, and check the outfits sent back from the server. If you like the outfit, you can send your decision to the server via your device.

[2204] 3. Rent and Buy: Choose your option to rent or buy a new fashion item and follow the necessary steps.

[2205] Specific examples

[2206] A day in the life of User A

[2207] 1. Morning

[2208] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[2209] User: User A enters his / her user ID and password and taps the login button.

[2210] Device: Sends authentication information to the server.

[2211] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[2212] Device: Displays login success and displays the home screen.

[2213] User: User A inputs the temperature, weather, destination, and emotions for that day. For example, "Sunny," "25 degrees," "Office," and "Feeling a little tired."

[2214] 2. Transmission of information

[2215] Terminal: Sends the entered information to the server.

[2216] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[2217] 3. Coordination suggestions

[2218] Server: Referencing User A's registration database and emotional data, the AI ​​algorithm generates optimal outfits based on past data. For example, it suggests a combination of a shirt, pants, jacket, and shoes made of a relaxed material.

[2219] Server: Sends the generated coordinates to the terminal.

[2220] Device: Display suggested outfits.

[2221] User: User A reviews the suggestions and selects the outfit if they like it.

[2222] Terminal: Sends the selected coordinates to the server and stores them.

[2223] 4. Use of Subscription Services

[2224] User: User A rents the suggested new jacket through a subscription service.

[2225] Terminal: Sends rental orders to the server.

[2226] Server: Sends order data to partner brands and initiates shipping procedures.

[2227] In this way, User A can streamline their daily clothing selection and enjoy optimal fashion that takes their emotions into consideration. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[2228] The processing flow will be explained below.

[2229] Step 1:

[2230] On the device: The user opens the application and the login screen appears. The user enters their user ID and password and taps the login button.

[2231] Step 2:

[2232] Terminal: Sends the entered user ID and password to the server.

[2233] Step 3:

[2234] Server: Compares the received user ID and password with the database. If the login is successful, it sends the user data to the terminal, and if not, it sends an error message to the terminal.

[2235] Step 4:

[2236] Device: If login is successful, display the home screen.

[2237] Step 5:

[2238] User: Enters the weather, temperature, destination (e.g., office, casual outing, formal event), and emotional state (e.g., "slightly tired," "energetic," etc.) for the day.

[2239] Step 6:

[2240] Terminal: Sends the entered information to the server.

[2241] Step 7:

[2242] Server: Accesses external weather data API to collect the latest weather information (temperature, weather conditions), and compares this information with user input.

[2243] Step 8:

[2244] Server: Manages user emotion data sent from the emotion engine and learns past emotion trends.

[2245] Step 9:

[2246] Server: Refers to the user's clothing database and uses AI algorithms to generate optimal outfits based on past weather data and fashion information. For example, it suggests shirts, pants, jackets, and shoes made from relaxing materials.

[2247] Step 10:

[2248] Server: Sends the generated coordinates to the terminal.

[2249] Step 11:

[2250] Device: Visually displays the received outfits, showing a list of combinations of shirts, jackets, pants, shoes, etc.

[2251] Step 12:

[2252] User: Select the outfit they like from the ones presented. Once they have made their selection, they tap the confirm button.

[2253] Step 13:

[2254] Terminal: Sends the selected coordinate information to the server.

[2255] Step 14:

[2256] Server: The selected coordinates are saved in a database and used as learning data for future suggestions.

[2257] Step 15:

[2258] User: Selects a subscription option to rent or purchase new fashion items included in the suggested outfits.

[2259] Step 16:

[2260] Terminal: Sends rental or purchase order data to the server.

[2261] Step 17:

[2262] Server: Sends order data to partner external brands and initiates shipping procedures.

[2263] Step 18:

[2264] User: After receiving new items, the user uses the application again to receive new outfit suggestions based on the new items.

[2265] In this way, a system is realized that allows users to efficiently choose their daily outfits and enjoy optimal fashion that takes their emotions into consideration.

[2266] Example 2

[2267] 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."

[2268] Conventional coordination systems were limited to making suggestions based on the user's weather conditions and the clothing they owned, and were unable to make coordination suggestions that took into account the user's emotions or current mood. Furthermore, when users wanted to try out the latest fashion items, the process was cumbersome and burdensome for users. This resulted in a decrease in satisfaction and efficiency with fashion.

[2269] 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.

[2270] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for acquiring and managing the user's emotional data, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing options to rent or purchase fashion items, means for transmitting order data to affiliated external brands, and means for proposing new outfits after new items arrive. This makes it possible to propose outfits that reflect the user's emotions and current mood in addition to weather conditions and data on the clothing they own, and also allows them to smoothly try on and purchase the latest fashion items.

[2271] "Latest weather data" refers to environmental information such as current and near-future temperature, weather, humidity, and wind speed.

[2272] "User clothing data" refers to information about the clothing items owned by the user, including the type, color, material, style, and size of the item.

[2273] "User emotional data" refers to data that indicates the user's current emotions and moods as inferred from their facial expressions, input information, and past data.

[2274] "Means for generating outfits" refers to algorithms or systems that suggest optimal outfit combinations based on collected weather data, data on the user's clothing, and emotional data.

[2275] "Means for displaying coordination" refers to a device or application for visually presenting the generated outfit combinations to the user.

[2276] "Means for saving outfits" refers to a system that records the outfit combinations selected by the user in a database for future reference or as learning data.

[2277] "Means for providing rental or purchase options" refers to systems or applications that suggest options for users to rent or purchase their favorite latest fashion items and assist them in the process.

[2278] "Means for transmitting order data to partnering third-party brands" refers to a system that transmits order information to third-party fashion brands and retailers based on the rental or purchase option selected by the user.

[2279] "Means to suggest new outfits after new items arrive" refers to algorithms or systems that incorporate the user's newly acquired fashion items and suggest optimal outfit combinations again.

[2280] "Historical weather data" refers to information about temperature and weather conditions over a specific period in the past.

[2281] "Past emotion data" refers to data records regarding emotions and moods that a user has felt in the past.

[2282] "Fashion information" refers to data about the latest trends, styles, and fashions.

[2283] "User input means" refers to an interface or device that allows a user to manually input information such as temperature, weather, destination, and emotion.

[2284] This invention is a system that allows users to select the most suitable outfit based on the weather conditions and destination of the day, and then provides coordination that takes the user's emotions into consideration. The system works in cooperation with a server, a terminal, and an emotion engine, and each component plays a specific role.

[2285] Server Roles

[2286] The server is the core of the system and performs the following functions:

[2287] 1. Meteorological data collection:

[2288] The server connects to an external weather data API (e.g., OpenWeatherMap API) to collect the latest weather information (temperature, weather, humidity, wind speed, etc.), which allows it to always provide suggestions based on the latest weather data.

[2289] 2. Managing your data:

[2290] The server manages a database of the user's clothing and style preferences, allowing the user to keep an up-to-date inventory of the clothing items they own.

[2291] 3. Emotional Data Management:

[2292] The server manages the user's emotional data sent from the emotion engine and learns past emotional trends. This information is reflected in the outfit suggestions.

[2293] 4. Coordination proposal generation:

[2294] The server uses AI algorithms (e.g., models using TensorFlow or PyTorch) to generate optimal outfits based on weather data, user data, destination information, and emotional data. This process allows users to receive more accurate outfit suggestions.

[2295] 5. Save your outfit:

[2296] The server stores the user's selected outfits in a database and uses them as learning data to help with future suggestions.

[2297] 6. Offering Rental and Purchase Options:

[2298] The server works with partner external brands to provide users with the option to rent or purchase the latest fashion items of their choice, allowing them to easily try out the latest fashions.

[2299] Device Role

[2300] The terminal operated by the user has the following functions:

[2301] 1. User authentication:

[2302] The device provides an authentication process for the user to log into their account, and the authentication information is sent to the server where it is verified.

[2303] 2. Submitting input information:

[2304] The user inputs the day's temperature, weather, destination, etc. into the device, and sends this information to the server, which then obtains the data needed to generate the optimal outfit.

[2305] 3. Acquiring emotion data:

[2306] The device's emotion engine generates emotion data based on the user's facial expressions and input information, and sends it to a server via the device. The emotion engine uses facial recognition technology and natural language processing (NLP) technology.

[2307] 4. Show your outfit:

[2308] The terminal visually displays the coordinates sent from the server, allowing the user to easily check and select the suggestions.

[2309] 5. Order Processing:

[2310] If the user selects the rental or purchase option, the device sends the order data to the server, which then sends the order to the partnering external brand and initiates the delivery process.

[2311] User Roles

[2312] The user operates the system and performs the following roles:

[2313] 1. Initial Setup and Registration:

[2314] When using the app for the first time, users register their clothing and preferred styles. The server then manages this data and uses it to suggest outfits. The emotion engine also initially registers the user's emotional data.

[2315] 2. Daily input and confirmation:

[2316] Users input their daily weather conditions, destination, and emotions, and then check the outfits sent back from the server. If they like the outfit, they can send their decision to the server via their device.

[2317] 3. Rental and Purchase:

[2318] Users select the option to rent or purchase a new fashion item and complete the necessary steps.

[2319] Specific examples

[2320] A day in the life of User A

[2321] 1. Morning

[2322] Device: User A wakes up in the morning, launches the app, and the login screen appears.

[2323] User: User A enters his / her user ID and password and taps the login button.

[2324] Device: Sends authentication information to the server.

[2325] Server: Checks the authentication information against a database and sends the user data to the terminal if the login is successful.

[2326] Device: Displays login success and displays the home screen.

[2327] User: User A inputs the temperature, weather, destination, and emotions for that day. For example, "Sunny," "25 degrees," "Office," and "Feeling a little tired."

[2328] 2. Transmission of information

[2329] Terminal: Sends the entered information to the server.

[2330] Server: Collects the latest weather information from an external weather data API and compares it with User A's information.

[2331] 3. Coordination suggestions

[2332] Server: Referencing User A's registration database and emotional data, the AI ​​algorithm generates optimal outfits based on past data. For example, it suggests a combination of a shirt, pants, jacket, and shoes made of a relaxed material.

[2333] Server: Sends the generated coordinates to the terminal.

[2334] Device: Display suggested outfits.

[2335] User: User A reviews the suggestions and selects the outfit if they like it.

[2336] Terminal: Sends the selected coordinates to the server and stores them.

[2337] 4. Use of Subscription Services

[2338] User: User A rents the suggested new jacket through a subscription service.

[2339] Terminal: Sends rental orders to the server.

[2340] Server: Sends order data to partner brands and initiates shipping procedures.

[2341] In this way, User A can streamline their daily clothing selection and enjoy optimal fashion that takes their emotions into consideration. This system also allows users to easily try out the latest fashion items, thereby improving their quality of life.

[2342] Prompt Sentence Examples

[2343] "25 degrees, sunny, office, feeling a bit tired"

[2344] Based on this information, the system provides input data for a generative AI model, allowing the device to receive optimal outfit suggestions.

[2345] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2346] Step 1: User authentication

[2347] Input: User ID and Password

[2348] Output: Home screen

[2349] Device: Launch the app and the login screen will appear.

[2350] User: Enter your user ID and password and tap the login button.

[2351] Device: Sends authentication information to the server.

[2352] Server: Checks the received authentication information against a database and returns a success or failure result to the terminal.

[2353] Terminal: If login is successful, the home screen is displayed and user data is sent to the terminal.

[2354] Step 2: Initial data entry

[2355] Input: User's clothing, preferred style, and emotional data

[2356] Output: Registration complete confirmation message

[2357] User: Register your clothes and preferred style on the home screen. Also, register your initial emotional data.

[2358] Terminal: Sends data entered by the user to the server.

[2359] Server: Stores the received data in a database and sends a confirmation message to the terminal that registration is complete.

[2360] Step 3: Meteorological data collection

[2361] Input: Weather information for the day, destination entered by the user

[2362] Output: Latest weather data

[2363] User: Enter the weather conditions for the day (e.g., "sunny" and "25 degrees") and destination.

[2364] Terminal: Sends the entered information to the server.

[2365] Server: Uses an external weather data API (e.g., OpenWeatherMap API) to collect the latest weather information.

[2366] Server: Compares the collected weather data with the information entered by the user and stores it in a database.

[2367] Step 4: Acquire emotion data

[2368] Input: User's facial expression, input information

[2369] Output: Emotion data

[2370] Device: The emotion engine captures the user's facial expressions with a camera, analyzes the data, and generates emotion data.

[2371] Terminal: Sends the generated emotion data to the server.

[2372] Server: Stores the emotion data in a database for future analysis.

[2373] Step 5: Coordinate generation

[2374] Input: Weather data, user data, emotion data, destination information

[2375] Output: Optimal Coordination

[2376] Server: Based on the received weather data, user data, emotion data, and destination information, an AI algorithm is used to generate the optimal coordinates. At this stage, a generative AI model (e.g., TensorFlow or PyTorch) is used.

[2377] Server: Sends the generated coordinate data to the terminal.

[2378] Step 6: Coordination presentation and selection

[2379] Input: Best outfit

[2380] Output: Selected coordinates

[2381] Terminal: Visually displays the outfit received from the server (e.g., a relaxed shirt, pants, jacket, and shoes).

[2382] User: Check the presented outfits and select if you like them.

[2383] Terminal: Sends the selected coordinate information to the server.

[2384] Step 7: Save your outfit

[2385] Input: Selected coordinates

[2386] Output: Save complete confirmation message

[2387] Server: The selected coordinates are stored in a database and used as learning data for future suggestions.

[2388] Server: Sends a confirmation message to the terminal that the save is complete.

[2389] Step 8: Rental / Purchase Process

[2390] Input: The rental or purchase option selected by the user

[2391] Output: Order completed confirmation message

[2392] User: Selects an option to rent or buy a fashion item, such as a new jacket.

[2393] Terminal: Sends the user's order information to the server.

[2394] Server: Sends order data to partner external brands and initiates shipping procedures.

[2395] Server: Sends a confirmation message to the terminal that the order has been completed.

[2396] (Application example 2)

[2397] 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."

[2398] Conventional outfit suggestion systems can suggest outfits based on the user's weather conditions and preferences, but they cannot consider the user's emotions. It is also difficult to suggest appropriate outfits based on the driver's emotions inside an autonomous vehicle. This makes it difficult to suggest optimal outfits to reduce fatigue and stress, especially during long driving trips.

[2399] 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.

[2400] In this invention, the server includes means for collecting the latest weather data, means for managing data on the user's clothing, means for generating optimal outfits based on this data, means for displaying the generated outfits, means for saving the outfits selected by the user, means for providing options for renting or purchasing clothing items, means for sending order data to affiliated external brands, means for suggesting new outfits after new items arrive, means for acquiring facial images using a camera attached to the information entertainment system in the autonomous vehicle and analyzing emotional data, means for suggesting outfits that suit the driver based on the analyzed emotional data, and means for displaying the suggested outfits on an in-vehicle display. This enables optimal outfit suggestions based on the driver's emotions and weather conditions, improving driving comfort and safety.

[2401] "Weather data" is information about weather conditions such as temperature, weather, humidity, and wind speed.

[2402] "Clothing data" refers to information about the type, design, material, color, size, etc. of clothing owned by the user.

[2403] "Outfit" refers to the coordination suggested based on weather conditions and emotions.

[2404] An "information entertainment system" is a system installed in an autonomous vehicle for providing information and displaying entertainment content.

[2405] "Camera" refers to a device that captures images, especially one installed in an autonomous vehicle.

[2406] "Emotional data" is information about the user's emotional state analyzed based on images captured by a camera.

[2407] "External brands" refer to companies or brands that partner with the system to rent or sell clothing items to users.

[2408] "Coordination" refers to the optimal combination of clothing suggested to the user.

[2409] "Rental" refers to a service that allows you to borrow clothing items for a certain period of time.

[2410] "Purchase" refers to purchasing an item of clothing to own it.

[2411] System Overview:

[2412] This invention is a system that proposes optimal outfits based on the user's weather conditions, destination, and emotion data for the day. The system operates in cooperation with a server, a terminal, and an emotion engine.

[2413] Server Role:

[2414] The server is the center of the system and has the following responsibilities:

[2415] 1. Weather data collection: The server uses an external weather data API to collect the latest weather data and then suggests appropriate outfits to the user based on that data.

[2416] 2. Managing clothing data: The server manages the clothing data registered by the user.

[2417] 3. Emotion data management: The server analyzes the emotion data acquired by the camera inside the autonomous vehicle and uses it to propose appropriate coordination.

[2418] 4. Coordination generation: The server uses AI algorithms to generate optimal coordination based on weather data, clothing data, and emotional data.

[2419] 5. Sending proposal: The server sends the generated coordinates to the terminal, which then displays them on the in-car display.

[2420] Device role:

[2421] The user-operated device has the following features:

[2422] 1. User Authentication: Provides an authentication process for users to log in to their accounts.

[2423] 2. Data input: The user inputs the weather conditions, destination, and emotions for the day and sends this to the server.

[2424] 3. Emotion data acquisition: Using a camera installed inside the vehicle, an image of the user's face is acquired and sent to the emotion engine.

[2425] 4. Coordination display: Displays the coordination proposals sent from the server.

[2426] User role:

[2427] The user interfaces with the system to:

[2428] 1. Initial setup and registration: By registering your clothing and preferred styles in the system, you will be prepared to receive optimal outfit suggestions.

[2429] 2. Daily data input: By inputting daily weather conditions, destinations, and emotions, the server will suggest the best outfits for you.

[2430] 3. Review and select the suggestions: Review the outfits sent by the server and select them if you like them.

[2431] Hardware and software used:

[2432] Hardware:

[2433] Information and entertainment systems in autonomous vehicles

[2434] In-car camera

[2435] software:

[2436] requests library (weather data acquisition)

[2437] OpenCV (emotion analysis)

[2438] TensorFlow (AI algorithm)

[2439] Examples:

[2440] Example 1: Morning preparation

[2441] Before getting into a self-driving vehicle, users input "sunny," "25 degrees," "office," and "feeling a bit tired" into a smartphone app. The system then uses weather data to suggest outfits for light shirts and pants. It also analyzes facial images to recommend comfortable clothing.

[2442] Example prompt for a generative AI model:

[2443] "Weather data: Tokyo, Temperature: 28°C, Emotion data: Happy: 0.7, Sad: 0.1, Destination: Office. What is the best outfit?"

[2444] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2445] Step 1:

[2446] User authentication

[2447] Input: User ID and Password

[2448] What happens: A user logs into an app using a device, which sends their credentials to a server, which checks them against a database for authentication.

[2449] Output: If authentication is successful, send user data to the device. Login is successful and the home screen is displayed.

[2450] Step 2:

[2451] Data Entry

[2452] Input: Weather conditions, destination information, emotional state

[2453] Processing: The user inputs the weather conditions, destination, and emotions for the day into the device, which then sends this information to the server.

[2454] Output: The submitted data is stored on the server and used to generate coordinates.

[2455] Step 3:

[2456] Weather data collection

[2457] Input: User's destination information

[2458] Processing: The server uses an external weather data API to gather the latest weather information for the user's destination, sending an API request to get information such as temperature, weather, humidity, and wind speed.

[2459] Output: The acquired weather data is saved and used to generate coordinates.

[2460] Step 4:

[2461] Emotional Data Analysis

[2462] Input: Facial image captured by the in-car camera

[2463] Processing: The device captures the user's facial expressions using the in-car camera and sends the image data to the emotion engine, which uses OpenCV to preprocess the images and TensorFlow AI models to analyze emotions.

[2464] Output: The emotion analysis results are sent to the server and stored as user emotion data.

[2465] Step 5:

[2466] Coordinate generation

[2467] Input: Weather data, clothing data, emotion data

[2468] Processing: The server uses AI algorithms to generate the optimal outfit based on collected weather data, accumulated clothing data, and emotion analysis results. The generation process involves selecting materials based on temperature and suggesting colors and styles based on emotional state.

[2469] Output: The generated coordinates are sent from the server to the device.

[2470] Step 6:

[2471] Displaying outfits

[2472] Input: Generated coordinates

[2473] Processing: The terminal receives the coordinates sent from the server and displays them on the in-car display. The user confirms the displayed coordinates.

[2474] Output: The coordinates are visually presented for user confirmation.

[2475] Step 7:

[2476] Select and save outfits

[2477] Input: User's choice

[2478] Process: The user selects their favorite outfit and sends the selection to the server via their device. The server stores the selected outfit in a database for future suggestions.

[2479] Output: The selected coordinates are saved.

[2480] Step 8:

[2481] Rental and purchase procedures

[2482] Input: User's rental or purchase intent

[2483] Processing: If the user decides to rent or purchase a new clothing item, they submit the order via their device to the server, which then sends the order data to the partnering external brand and initiates the delivery process.

[2484] Output: The order is placed and the item is delivered.

[2485] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[2486] 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.

[2487] 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 robot 414.

[2488] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2489] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side o...

Claims

1. a means of collecting up-to-date weather data; A way to manage the data of the user's clothes, A means for generating optimal outfits based on this data; A means for displaying the generated coordinates; A means for saving the user's selected outfits; A means of providing options for renting or purchasing fashion items; A means of transmitting order data to partnering external brands; A system that includes a means to suggest new outfits after new items arrive.

2. 10. The system of claim 1, further comprising means for learning past weather data and fashion information.

3. 10. The system of claim 1 further comprising means for a user to input daily temperatures, weather conditions, and destinations.

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