system

Abstract

Provide a system. [Solution] A means for a user to photograph an object via a device; means for transmitting the captured image data to a server; means for the server to analyze the image data and identify an object; means for generating advice for the identified object based on user information by the server; means for displaying the generated advice to a user; a means for allowing a user to select a method of processing the object based on the displayed advice; and means for transmitting the selected processing method to a server and storing the same.

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] As unnecessary items continue to accumulate in the home, living space becomes smaller and quality of life declines. However, many people cannot easily dispose of things due to feelings of wastefulness or an inability to make good decisions. Furthermore, many people do not have appropriate criteria for determining whether or not something should be disposed of. For this reason, a system to support the disposal of items is needed. [Means for solving the problem]

[0005] The user takes a photo of an object using a device and sends the captured image data to a server. The server analyzes the image data to identify the object and generates advice for the object based on the user's body type, age, and other information about the user's belongings. The generated advice is displayed to the user, who then chooses how to dispose of the object based on the advice. The server saves the user's choice for future reference. The server also calculates the market value of the object and provides it to the user, reducing their resistance to throwing things away. The server also displays avatars that the user can choose from, increasing user motivation and providing a more user-friendly system.

[0006] "User" refers to an individual or group that uses the system, and is responsible for providing information about an object via a device, receiving advice, and deciding how to process the object.

[0007] "Device" refers to an information and communication device such as a smartphone, tablet, or PC, which a user uses to photograph an object and send the image data to a server.

[0008] "Object" refers to an item that a user is considering disposing of, saving, or requesting a trade-in, and that is the subject of identification and evaluation by the system.

[0009] "Photographing" refers to the act of taking a photograph of an object using a device, which provides basic information for the system to analyze the object.

[0010] "Image data" refers to photographic information of a photographed object, which is sent to a server in digital format and used for analysis.

[0011] The term "server" refers to a computer system that receives image data, analyzes it, and generates advice, and is responsible for communicating with users and devices.

[0012] "Analysis" refers to the series of processes in which the server processes image data to identify objects and evaluate their attributes and conditions.

[0013] "Identification" refers to the act of the server identifying the type and characteristics of objects contained in image data through analysis.

[0014] "User information" refers to data about the user's body type, age, and other possessions, including factors that the server considers when generating advice.

[0015] "Advice" refers to suggestions or recommendations generated by the server based on analysis and user information, including information that helps users choose how to handle an item (preserve, dispose of, or buy).

[0016] "Market value" refers to the monetary value for which an object can be sold in the current market, and indicates the economic value of the item to the user.

[0017] An "avatar" is a virtual character that a user selects and uses within the system, and serves as an interface to the system, enhancing familiarity and motivation. [Brief explanation of the drawings]

[0018] [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 illustrating 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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] The present invention provides a system that allows users to efficiently dispose of unnecessary items in their daily lives. This system operates mainly based on the user's device, a server, and data exchanged between them.

[0040] First, the user launches the application on their device, enters their account information on the login screen, and authenticates, at which point they are granted access to the system.

[0041] Next, the user selects from a selection of virtual characters (avatars) on a character selection screen within the application. The selected character guides the user through subsequent interactions and provides a sense of familiarity.

[0042] To identify an item a user wants to throw away, they take a photo of the item using the device's camera. The captured image data is then sent from the device to a server. The server then analyzes the image data and uses computer vision technology to identify the item. Information about the user's body type, age, and other items they own is also sent to the server.

[0043] The server generates advice about the item based on the results of image data analysis and user information. For example, it provides specific advice such as, "This coat does not suit your body type, age, or current trends." It also calculates the current market value and provides an economic assessment, such as, "This coat could potentially be sold for 3,000 yen."

[0044] The generated advice is sent from the server to the device and displayed to the user, who can then choose to keep, dispose of, or request a resale of the item.

[0045] Once the selection is complete, the device sends the selection information to the server, which stores it in a database and uses it as reference information for future use. This allows users to declutter efficiently and systematically.

[0046] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The server analyzes the image and identifies the coat. After that, taking into account the user's information, the server generates advice such as "This coat does not fit your body type and is out of fashion, so we recommend that you dispose of or sell it," and presents this to the user. It also displays the market value, such as "This coat may be able to be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved.

[0047] In this way, the system of the present invention provides support for users to declutter easily and efficiently.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] The user launches the "Danshell" app on a device such as a smartphone. The user enters their account information (username and password) on the login screen and presses the "Login" button.

[0051] Step 2:

[0052] The terminal sends the entered login information to the server. The server then authenticates the login information and returns the authentication result to the terminal. If the authentication is successful, the user can proceed to the next step.

[0053] Step 3:

[0054] The terminal displays a screen after successful login, and allows the user to select their preferred AI character (avatar) from multiple options. The user makes a selection and presses the confirm button.

[0055] Step 4:

[0056] The device sends the selected character information to the server, which then saves the user's character settings.

[0057] Step 5:

[0058] The user uses the app's camera to take a photo of the item they are considering disposing of (e.g., an old coat). Once the photo is taken, the user presses the "Send" button.

[0059] Step 6:

[0060] The device sends the captured image data and user information (body type, age, and information about other items held) to the server.

[0061] Step 7:

[0062] The server analyzes the received image data using computer vision technology to identify the object. For example, it may determine that the object is an "old coat" through image analysis.

[0063] Step 8:

[0064] The server generates advice for the identified object based on the user information. For example, it generates advice such as "This coat does not suit your body type or current fashion" by taking into account body type, age, and current fashion.

[0065] Step 9:

[0066] The server calculates the market value of the object, for example, generating a rating such as "This coat is worth 3,000 yen on the market."

[0067] Step 10:

[0068] The generated advice and market value are sent from the server to the terminal, which displays this information to the user.

[0069] Step 11:

[0070] The user refers to the advice and selects one of the options: "Keep," "Dispose," or "Request a Buyback." Once the selection is complete, the user presses the "OK" button.

[0071] Step 12:

[0072] The device sends the user's selection information to the server, which stores the selection information in a database and uses it as reference for the next time.

[0073] Step 13:

[0074] When the user quits the app, the device closes the application.

[0075] The above are the specific steps of the "Danshell" program processing.

[0076] Example 1

[0077] 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."

[0078] In modern society, many users are seeking an efficient way to dispose of items that are no longer needed in their daily lives. However, it is often difficult to decide whether to throw away, store, or sell these items, which results in delays in decluttering. There is also a lack of professional advice on these items and ways to understand their market value. Furthermore, tools and systems are often difficult to use, preventing users from actively using them. Therefore, a system is needed that allows users to easily dispose of unwanted items and provides appropriate advice and value assessments.

[0079] 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.

[0080] In this invention, the server includes means for a user to photograph an object via an information device, means for transmitting the photographed image data to the server, means for the server to analyze the image data and identify the object, means for generating advice for the identified object based on user information, means for displaying the generated advice to the user, means for the user to select a method of disposing of the object based on the displayed advice, means for transmitting the selected method of disposing of the object to the server and saving it, means for the user to select from a plurality of virtual characters, means for the virtual characters to guide the user through dialogue, means for using a camera function, and means for the server to simultaneously process related information. This allows users to easily and effortlessly photograph and analyze unwanted items, determine a method of disposing of them based on appropriate advice, and then perform optimal disposal after understanding their market value.

[0081] "User" refers to an individual who uses the system to dispose of unwanted items.

[0082] "Information devices" refers to digital devices such as smartphones, tablets, and personal computers.

[0083] The term "target item" refers to an item that the user has determined to be unnecessary.

[0084] "Means for photographing" refers to a method for obtaining an image of an object using the camera function built into an information device.

[0085] "Image data" refers to digital image information obtained when photographing an object.

[0086] "Server" refers to a central processing unit that analyzes image data, identifies objects, and generates advice.

[0087] "Means for analyzing" refers to the techniques and algorithms used to process image data and extract features of interest.

[0088] "Means for identifying" refers to a technique for identifying what an object is based on analyzed characteristics.

[0089] "User Information" refers to data about a user's characteristics and other possessions.

[0090] The "means for generating advice" refers to a function for proposing an appropriate processing method to the user based on the object identification result and user information.

[0091] The "display means" refers to a function for visually presenting the generated advice on the user's information device.

[0092] The "means for selecting a disposal method" refers to a method by which a user can select a disposal method, such as preserving, disposing of, or selling an object, based on the advice provided.

[0093] "Means for saving" refers to the technology for recording the processing method selected by the user within the system and reusing it as needed.

[0094] "Virtual character," also known as an avatar, refers to a digital character that interacts with the user and guides them through the system.

[0095] "Dialogue-based guidance" refers to a function that allows a virtual character to provide operating procedures and advice through communication with the user.

[0096] "Means for simultaneously processing related information" refers to a technique for processing image data together with user information and other necessary data.

[0097] "Market value" refers to an indicator used to assess the price at which an object may be traded in the market.

[0098] The system of the present invention supports users in efficiently disposing of unnecessary items in their daily lives. This system operates mainly based on the user's information device, a server, and the data exchanged between them.

[0099] First, the user installs and launches a dedicated application on an information device such as a smartphone or tablet. The user then enters their account information on the login screen and performs authentication. This authentication uses an arbitrary user ID and password, which the server verifies against a database.

[0100] Once a user has successfully logged in, they proceed to a character selection screen within the application and choose their preferred virtual character (avatar) from multiple options. Once character selection is complete, the selected virtual character will guide the user through subsequent interactions, ensuring smooth use of the system.

[0101] The user takes a photo of the item they want to throw away using the camera function of their information device. The camera function uses the built-in camera of a smartphone or tablet. At this time, the captured image data is sent from the information device to a server. The server analyzes the received image data and uses computer vision technology such as OpenCV or TENSORFLOW (registered trademark) to identify the item.

[0102] The server processes the identified item, along with information about the user's body type, age, and other items they own. This starts the process of generating advice about the item. For example, it might provide specific advice like, "This coat doesn't suit your body type, age, or current trends." The server also calculates its current market value and provides an economic assessment, such as, "This coat could potentially be sold for 3,000 yen."

[0103] The generated advice is sent from the server to the user's information device and displayed to the user. The user then refers to the displayed advice and selects from the options of "save," "dispose," or "request a resale." Once the selection is complete, the information is sent from the information device to the server, which then stores it in a database. This data is used as reference information for future use.

[0104] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. On the character selection screen, they select a female character in their 30s and then take a photo of an old coat. This image data is sent to the server, which analyzes the image and identifies the coat. The server then takes into account the user's information and generates advice such as, "This coat doesn't fit your body type and is out of fashion, so we recommend you dispose of or sell it," and presents this to the user. It also displays the market value, showing that "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved in a database.

[0105] Example prompt sentence:

[0106] "Please explain the steps to use the application to help users efficiently dispose of unwanted items."

[0107] "Please show us the specific process flow of a system for efficiently decluttering."

[0108] "Please explain in detail the process that will allow users to easily declutter their old coats."

[0109] The above is a specific embodiment for carrying out the present invention.

[0110] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0111] Step 1:

[0112] Launching the application and logging in

[0113] A user starts an application on an information device such as a smartphone or tablet. Next, the user enters their account information (user ID and password) on the login screen. Based on this input, the server compares it with the account information stored in the database and authenticates the user. If authentication is successful, a "Login successful" message is output to the user.

[0114] Input: User ID, Password

[0115] Data processing: database matching, fair comparison

[0116] Output: Authentication result message (success / failure)

[0117] Step 2:

[0118] Character Selection

[0119] After logging in, the user goes to the character selection screen within the application and chooses their favorite virtual character from several options. Once the selection is complete, the device sends the selected character information to the server, which records it and outputs instructions for proceeding to the next step.

[0120] Input: User's character selection

[0121] Data processing: Recording character ID

[0122] Output: Character selection confirmation message

[0123] Step 3:

[0124] Photographing items and sending data

[0125] Users use the camera function of their smartphone or tablet to take a photo of the item they want to throw away. The captured image data is sent from the device to the server. The server stores the received image data and outputs a notification to proceed to the next analysis step.

[0126] Input: Captured image data

[0127] Data processing: Sending and storing image data

[0128] Output: A confirmation message that the image was received

[0129] Step 4:

[0130] Analysis of product images

[0131] The server uses computer vision technologies such as OpenCV and TensorFlow to analyze the received image data. The analysis extracts features of the item and identifies it based on those features. The analysis results are then processed along with information about the user's body type, age, and other items they own.

[0132] Input: Image data, user information

[0133] Data processing: image analysis, feature extraction, item identification

[0134] Output: Analysis results (item identification)

[0135] Step 5:

[0136] Generating Advice

[0137] The server generates advice based on the image analysis results and user information. For example, it provides specific advice such as, "This coat does not suit your body type, age, or current trends." It also calculates the current market value and makes an assessment such as, "This coat could potentially be sold for 3,000 yen."

[0138] Input: Analysis results, user information

[0139] Data processing: advice generation, value calculation

[0140] Output: Advice content, market value

[0141] Step 6:

[0142] Viewing advice and selecting options

[0143] The server sends the generated advice to the terminal, which then displays it to the user, who can then select from the options of "save," "dispose," or "request a buyback."

[0144] Input: Advice content, market value

[0145] Data processing: Sending advice, displaying options

[0146] Output: User selection

[0147] Step 7:

[0148] Sending and storing your selections

[0149] The terminal sends the option information selected by the user to the server, which stores this information in a database. This data will be used as reference information for future use.

[0150] Input: User selection information

[0151] Data processing: sending and storing selected information

[0152] Output: Database update confirmation message

[0153] The above is a specific flow of processing in the system of the present invention.

[0154] (Application example 1)

[0155] 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."

[0156] There is a need to provide a means for users to efficiently dispose of items that are no longer needed in their daily lives. In particular, there is a need for a system that can identify items, evaluate their economic value, suggest disposal methods, and even link with online marketplace sites to enable smoother disposal or sale of items. Currently, many users find it time-consuming and laborious to dispose of items, and a system that can solve this problem is desirable.

[0157] 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.

[0158] In this invention, the server includes means for a user to photograph an object via a device, means for transmitting the photographed image data to the server, means for the server to analyze the image data and identify the object, means for the server to generate advice for the identified object based on user information, means for displaying the generated advice to the user, means for the user to select a method of disposing of the object based on the displayed advice, means for transmitting and storing the selected method of disposing of the object to the server, and means for linking to an online marketplace site and making a buyback request, thereby enabling users to efficiently dispose of unwanted items and maximize their economic value.

[0159] "User" refers to any individual or legal entity that uses the System.

[0160] "Device" refers to the hardware device, primarily a smartphone or tablet, that a user uses to interface with the system.

[0161] "Object" refers to an item that a user wishes to dispose of, save, or sell.

[0162] "Means for photographing" refers to the function of acquiring an image of an object using the camera function built into the device.

[0163] "Means for transmitting image data to a server" refers to a function for transmitting captured image data from a device via a network to a remote server.

[0164] "Server" refers to the back-end computer that processes and stores data at the heart of the system.

[0165] "Means for analyzing image data and identifying objects" refers to the function of the server or its related systems to identify the type and characteristics of objects using image processing technology.

[0166] "User information" refers to data such as a user's personal information, preferences, body type, age, and past behavioral history.

[0167] "Means for generating advice" refers to the function of the server to make specific suggestions and evaluations for the target object based on the analysis results and user information.

[0168] "Means for displaying advice to the user" refers to a function for displaying advice generated by the server on the screen of the user's device.

[0169] "Means for selecting a disposal method" refers to a function that allows a user to choose whether to preserve, dispose of, or sell an object by referring to the displayed advice.

[0170] The "means for transmitting the processing method to the server and storing it" refers to a function for transmitting the processing method selected by the user to the server and storing it in the database.

[0171] "Online Marketplace Site" means a web platform through which users can buy and sell goods.

[0172] The "means for making a purchase request" refers to a function for transmitting a purchase request for the selected object to the online market site.

[0173] The present invention provides a system for efficiently disposing of items that users no longer need in their daily lives. Specifically, the system operates based on the user's device, a server, and data exchanged between them.

[0174] System configuration

[0175] Users install an application on their devices, such as smartphones or tablets, which uses the camera function to take pictures of unwanted items and send the image data to a server.

[0176] 1. User Authentication

[0177] The user enters their account information on the login screen and sends it to the server, where it is authenticated, and if the authentication is successful, the user is allowed to access the system.

[0178] 2. Avatar selection

[0179] After authentication, the user selects from multiple virtual characters (avatars) within the application, and the selected avatar guides the user through subsequent operations.

[0180] 3. Photographing and analyzing the object

[0181] Users take a photo of the item they want to dispose of using their device's camera. The image data is sent to a server, which then analyzes the image. The technology used is based on computer vision technology.

[0182] 4. Generating and displaying advice

[0183] The server generates advice for the item based on the image analysis results and user information. This advice includes suggestions for preserving, disposing of, or selling the item. The advice is sent to the user's device and displayed on the screen.

[0184] 5. Calculating market value

[0185] The server also calculates the market value of the object and displays it to the user.

[0186] 6. Selection of processing method

[0187] The user can refer to the displayed advice and choose how to dispose of the item. There are three options: "Keep," "Dispose," or "Request a purchase."

[0188] 7. Submitting a purchase request

[0189] If the user selects "purchase request," the system will link to an online marketplace site and make a purchase request.

[0190] 8. Data Retention

[0191] The processing method selected by the user is stored in a database and used as reference information the next time the system is used.

[0192] Hardware and software used

[0193] The hardware used is a smartphone, tablet, and server, and the software used is Python, OpenCV, the Requests library, and PIL (Python Imaging Library).

[0194] 1. User Authentication

[0195] Use the Python Requests library to send the user's credentials to the server for authentication.

[0196] 2. Taking photos and sending images

[0197] OpenCV is used to control the device's camera function and take images, which are then sent to the server using the Requests library.

[0198] 3. Image analysis and advice generation

[0199] On the server, image data is analyzed using computer vision and generative AI models, and appropriate advice is generated based on the user information and analysis results.

[0200] 4. Advice and Market Value Calculation

[0201] Advice generated using PIL is displayed as an image on the user's device, and the generative AI model is also used to calculate market value.

[0202] 5. Selecting a disposal method and requesting a purchase

[0203] The user's selection of the treatment method is transmitted to the server and, if necessary, forwarded to the online marketplace site.

[0204] Examples of concrete examples and prompts

[0205] Examples:

[0206] For example, consider a scenario in which a user wants to get rid of an old coat. The user launches the application on their device and logs in. They select a female character (avatar) in her 30s and takes a photo of the old coat with the device's camera. The server analyzes the image and, taking into account the user's body type, age, and current trends, suggests advice such as "This coat doesn't suit your body type and is out of fashion, so we recommend you get rid of or sell it," along with a market value such as "This coat may sell for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and stored in a database.

[0207] Example prompt sentence:

[0208] "Write a Python program that authenticates users, photographs and identifies unwanted items, provides advice and economic evaluation, and submits the final disposal selection to the server."

[0209] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0210] Step 1:

[0211] A user starts an application using a device such as a smartphone or tablet. The user enters their account information (username, password) on the login screen. This information is sent from the device to the server, which then performs authentication. The server compares the entered information with its database, and if it matches, the authentication is successful. The user is then shown a message indicating successful login, and the process moves to the next step.

[0212] Input: Username, Password

[0213] Output: Authentication result (success / failure)

[0214] Step 2:

[0215] The user selects their preferred avatar from multiple virtual characters on the avatar selection screen. The selected avatar information is stored on the device and used for subsequent interactions. The server retains session information including the selected avatar information and reflects it in the next step.

[0216] Input: User avatar selection

[0217] Output: Add avatar information to session information

[0218] Step 3:

[0219] The user uses the device's camera to take a picture of the item they want to dispose of. The captured image data is sent from the device to the server, which uses computer vision technology to analyze the received image data and identify the object.

[0220] Input: Photographed image data

[0221] Output: Object identification information

[0222] Step 4:

[0223] The server generates advice for the identified object. Using a generative AI model, it creates specific advice based on user information (body type, age, fashion, etc.) and the results of image analysis. The generated advice is then sent to the device.

[0224] Input: Object identification information, user information

[0225] Output: Specific advice

[0226] Step 5:

[0227] The terminal receives the advice sent from the server and displays it to the user. In addition, the server simultaneously calculates the market value of the object and displays it to the user together with the advice.

[0228] Input: Specific advice, market value

[0229] Output: Advice and market value displayed on the terminal

[0230] Step 6:

[0231] The user refers to the advice and selects how to dispose of the object (preservation, disposal, purchase request). The selected method is sent from the terminal to the server and stored in the database.

[0232] Input: User-selected processing method

[0233] Output: Data on the selected processing method

[0234] Step 7:

[0235] If the user selects a buyback request, the system connects to the online marketplace site and sends the buyback request information, which the server then processes.

[0236] Input: Purchase request information

[0237] Output: Request information sent to online marketplace site

[0238] The above is the specific processing flow of the program for the system that realizes the application example. At each step, appropriate data processing and calculation are performed based on the input data, and the output for the next step is generated.

[0239] 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.

[0240] The present invention is a system that allows users to efficiently dispose of unnecessary items in their daily lives. This system operates mainly based on the user's device, a server, an emotion engine, and data exchanged among them.

[0241] First, a user launches an application on their device. They enter their account information on the login screen and authenticate. If authentication is successful, the user can proceed to the next step. Next, the user selects their preferred virtual character (avatar) from multiple options on the character selection screen within the application. The selected character guides the user through subsequent interactions, providing a sense of familiarity.

[0242] To identify the item the user wants to throw away, the user takes a photo of the item using the device's camera function. This image data is sent from the device to the server. At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize the user's emotions. The emotion engine detects the user's emotional state and also sends this data to the server.

[0243] The server analyzes the received image data and uses computer vision technology to identify the item. In addition, information about the user's body type, age, and other items they are holding, as well as emotion recognition results from the emotion engine, are also sent to the server.

[0244] The server generates advice about the item based on the results of image data analysis, user information, and emotion recognition. For example, it can provide specific advice such as "This coat doesn't suit your body type, age, or current trends," or emotion-based advice such as "You seem reluctant to throw away the item. Would you like to reconsider?" It also calculates the current market value and provides an economic assessment, such as "This coat could be sold for 3,000 yen."

[0245] The generated advice is sent from the server to the device and displayed to the user on the device. The user can refer to the displayed advice and select from the options of "keep," "dispose," or "request purchase" for the item. Once the selection is complete, the device sends the selection information to the server. The server saves the selection information in a database and uses it as reference information for future use.

[0246] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The emotion engine recognizes the user's emotions from their facial expression and determines that they are "a little reluctant to throw things away." The server analyzes the image, identifies the coat, and, taking into account the user information and the emotion recognition results, generates advice such as "This coat doesn't suit your body type or trends, but you seem to have trouble getting rid of things, so you might want to reconsider." It also displays the market value, saying, "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved.

[0247] In this way, the system of the present invention provides support to help users declutter easily and efficiently, and by incorporating emotion recognition technology, it generates more personalized advice and reduces users' psychological resistance.

[0248] The processing flow will be explained below.

[0249] Step 1:

[0250] The user launches an application on a device such as a smartphone. The user enters account information (username and password) on the login screen and presses the "Login" button.

[0251] Step 2:

[0252] The terminal sends the entered login information to the server. The server then authenticates the login information and returns the authentication result to the terminal. If the authentication is successful, the user can proceed to the next step.

[0253] Step 3:

[0254] The terminal displays a screen after successful login, and allows the user to select their preferred AI character (avatar) from multiple options. The user makes a selection and presses the confirm button.

[0255] Step 4:

[0256] The device sends the selected character information to the server, which then saves the user's character settings.

[0257] Step 5:

[0258] The user uses the app's camera to take a photo of the item they are considering disposing of (e.g., an old coat). Once the photo is taken, the user presses the "Send" button.

[0259] Step 6:

[0260] The device sends the captured image data and user information (body type, age, and information about other items held by the user) to the server. At the same time, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state.

[0261] Step 7:

[0262] The emotion engine sends the recognized emotion data to the server, which then analyzes the received image data using computer vision technology to identify the target object.

[0263] Step 8:

[0264] The server generates advice for the identified object based on the user's information and emotion data. For example, it takes into account body type, age, and current fashion trends to generate advice such as "This coat doesn't suit your body type or the current trends," or emotion-based advice such as "You seem reluctant to throw things away. Would you reconsider?"

[0265] Step 9:

[0266] The server calculates the market value of the object, for example, generating a rating such as "This coat is worth 3,000 yen on the market."

[0267] Step 10:

[0268] The server transmits the generated advice and market value to the terminal, which displays this information to the user.

[0269] Step 11:

[0270] The user refers to the advice and selects one of the options: "Keep," "Dispose," or "Request a Buyback." Once the selection is complete, the user presses the "OK" button.

[0271] Step 12:

[0272] The device sends the user's selection information to the server, which stores the selection information in a database and uses it as reference for the next time.

[0273] Step 13:

[0274] When the user quits the app, the device closes the application.

[0275] The above are the specific steps in the programming process of the "Danshell" system, which incorporates an emotion engine.

[0276] Example 2

[0277] 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."

[0278] In today's consumer society, people frequently purchase goods, resulting in an increasing number of unnecessary items. However, disposing of these items is a psychological burden for many people. Specifically, the main challenges are a reluctance to throw away items and an inability to properly evaluate their value. In addition, there is a lack of systems that provide users with appropriate advice when choosing how to dispose of items.

[0279] 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.

[0280] In this invention, the server includes a means for a user to photograph an object via an electronic device, a means for transmitting the photographed image data to a data center, a means for the data center to analyze the image data and identify the object, a means for the data center to generate advice for the identified object based on user information and emotion recognition results, a means for displaying the generated advice to the user, a means for the user to select a method of disposing of the object based on the displayed advice, and a means for transmitting and storing the selected method of disposing of the object to the data center. This reduces the user's psychological resistance to disposing of the item and enables them to correctly evaluate the value of the item. Furthermore, appropriate and personalized advice can be provided to the user.

[0281] "User" refers to an individual or organization that uses this system to dispose of items.

[0282] "Electronic devices" refer to devices that have computer functions, such as smartphones, tablets, and personal computers, and are equipped with input devices such as cameras and microphones.

[0283] "Target item" refers to an item that the user is considering disposing of.

[0284] "Photographing" refers to the act of a user acquiring image data of an object using the camera function of an electronic device.

[0285] "Image data" refers to digital image information of a photographed object.

[0286] "Data Center" means a centralized facility containing servers and other computing resources where data is stored and processed.

[0287] "Analysis" refers to the process of recognizing and identifying objects in the image data received by the data center using computer vision technology, etc.

[0288] "User information" refers to information such as the user's profile data (age, gender, body type, etc.), past usage history, and item ownership status.

[0289] "Emotion recognition results" refers to data indicating the user's emotional state obtained by the emotion engine by analyzing the user's facial expressions, voice, and input actions.

[0290] "Advice" refers to advice provided by the Data Center to the User regarding the disposal method and market value of the object based on the analyzed data.

[0291] "Saving" refers to the act of recording information or data selected by the user in storage such as a database, making it available for subsequent access.

[0292] "Market value" refers to information that indicates the value of an object in the current market as a number or evaluation.

[0293] "Virtual Character" refers to an anthropomorphic digital avatar that a user selects within the system and that guides the user through the interaction.

[0294] The present invention is a system that allows users to efficiently dispose of items that are no longer needed in their daily lives. This system operates mainly based on the user's electronic devices, a data center, an emotion engine, and data exchanged among them.

[0295] First, the user launches the application on their electronic device (smartphone, tablet, etc.) and enters their account information on the login screen to authenticate. If authentication is successful, the user is taken to the application's home screen.

[0296] Next, the user taps the "Select Character" button on the home screen and chooses from a selection of virtual characters (avatars), which guide the user through subsequent interactions and provide a sense of familiarity.

[0297] The user identifies the item they want to throw away and takes a photo of it using the camera function of their electronic device. The image data is then sent from the electronic device to a data center.

[0298] At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize their emotional state. The emotion engine uses facial recognition and voice analysis software to generate the user's emotional data (e.g., "joy," "sadness," "resistance," etc.), which is also sent to the data center.

[0299] The data center uses computer vision technology (e.g., TensorFlow) to identify the item based on the received image data. It also references the user's body type, age, information about other items they own, and emotion recognition results. Based on this information, the data center uses a generative AI model to generate advice. For example, it can provide advice such as "This coat doesn't suit your body type, age, or current trends," or emotion-based advice such as "You seem reluctant to throw it away. Would you like to reconsider?" It also calculates the current market value and makes an economic assessment, such as "This coat could potentially be sold for 3,000 yen."

[0300] The generated advice is sent from the data center to the electronic device and displayed to the user. The user can refer to the displayed advice and select from the options of "keep," "dispose," or "request purchase" for the item. Once the selection is complete, the selection information is sent from the electronic device to the data center, which stores it in a database. The stored information will be used as reference information the next time the service is used.

[0301] As a concrete example, consider the case of considering disposing of an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The emotion engine recognizes the user's emotions from their facial expression and determines that they are "a little reluctant to throw things away." The data center analyzes the image, identifies the coat, and, taking into account the user information and the emotion recognition results, generates advice such as "This coat doesn't suit your body type or trends, but since you seem reluctant to get rid of it, you may want to reconsider." It also displays the market value, indicating that "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the data center and stored.

[0302] Example prompts for generative AI models

[0303] "A female user in her 30s is reluctant to throw things away and has taken a photo of an old coat. Please provide advice and market value."

[0304] The system of the present invention allows users to dispose of items easily and efficiently, and by incorporating emotion recognition technology, it provides more personalized advice and reduces users' psychological resistance.

[0305] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0306] Step 1:

[0307] The user launches the application on an electronic device (smartphone, tablet, etc.) and enters account information (ID, password) on the login screen to authenticate.

[0308] Input: User account information

[0309] Output: Authentication result (success / failure)

[0310] Specific behavior:

[0311] The user taps the application to launch it.

[0312] Enter your ID and password on the login screen.

[0313] When you press the "Login" button, data is sent to the authentication server and authentication is performed.

[0314] If authentication is successful, the home screen will be displayed.

[0315] Step 2:

[0316] The user taps the "Character Selection" button on the home screen and chooses their preferred virtual character (avatar) from multiple options.

[0317] Input: Selection information of virtual character

[0318] Output: Selected characters

[0319] Specific behavior:

[0320] The user taps the "Character Selection" button.

[0321] A number of virtual characters are displayed.

[0322] The user taps on the character of their choice to select it.

[0323] The selected character will be reflected in the application.

[0324] Step 3:

[0325] Users take a photo of the item they want to throw away using the camera function of their electronic device, and the captured image data is sent from the electronic device to a data center.

[0326] Input: Image data of the item

[0327] Output: Image data transmission results to the data center

[0328] Specific behavior:

[0329] The user taps the camera launch button within the app.

[0330] The device's camera is activated and the user points the camera at the item they want to throw away and takes a picture.

[0331] After the image is taken, the image data is automatically uploaded to a data center.

[0332] Step 4:

[0333] The emotion engine analyzes the user's facial expressions, voice, and input actions to recognize their emotional state, and sends this data to a data center.

[0334] Input: facial expression data, voice data, input action data

[0335] Output: Emotion recognition result

[0336] Specific behavior:

[0337] The device's camera and microphone capture the user's facial expressions and voice in real time.

[0338] The emotion engine performs facial expression recognition and voice analysis to generate emotion data.

[0339] Emotion data is sent to a data center.

[0340] Step 5:

[0341] The data center uses computer vision technology (e.g., TensorFlow) to identify the item based on the image data received.

[0342] Input: Image data of the item

[0343] Output: Item identification result

[0344] Specific behavior:

[0345] The image data is received at a data center.

[0346] Computer vision technology is used to analyze the characteristics of an item and identify it.

[0347] Information about the identified items is generated.

[0348] Step 6:

[0349] The data center analyzes user information (body type, age, etc.) together with emotion recognition results, and generates advice using a generative AI model.

[0350] Input: Item identification results, user information, emotion recognition results

[0351] Output: Generated advice

[0352] Specific behavior:

[0353] The item identification results, user information, and emotion recognition results are imported into the data center.

[0354] A generative AI model generates advice sentences based on this data.

[0355] The generated advice is stored in a data center.

[0356] Step 7:

[0357] The advice generated by the data center is sent to the electronic device and displayed to the user, who can choose from the options of "keep," "dispose," or "request a resale."

[0358] Input: Generated advice

[0359] Output: User's choice

[0360] Specific behavior:

[0361] The data center transmits the advice data to the electronic device.

[0362] An advice message is displayed on the electronic device, and selection buttons are arranged.

[0363] The user taps the desired option (e.g., "Dispose").

[0364] Step 8:

[0365] The selected information is sent from the electronic device to a data center, which stores it in a database.

[0366] Input: User selection information

[0367] Output: Selections saved in the database

[0368] Specific behavior:

[0369] The user's selection information is transmitted from the electronic device to the data center.

[0370] The data center stores the selection information in a database and checks the integrity of the data.

[0371] (Application example 2)

[0372] 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."

[0373] Current methods for decluttering and disposing of items often fail to take into account users' psychological resistance, resulting in ineffective and efficient disposal. Furthermore, it is difficult for users to understand the appropriate disposal method and economic value of items, resulting in wasted time and effort. Furthermore, personalized advice that takes into account the user's emotional state is not provided, resulting in low user satisfaction. To solve these issues, a system that also takes into account the user's emotional information is needed.

[0374] 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.

[0375] In this invention, the server includes means for generating advice for the identified object based on user information and emotion information, means for displaying the generated advice to the user, and means for the user to select a method of processing the object based on the displayed advice, thereby providing personalized advice that takes into account the user's emotional state and enabling efficient and effective processing of items.

[0376] "User information" refers to personal information about the user, such as age, sex, body type, and past item processing history.

[0377] "Emotion information" is data on the user's emotional state analyzed from their facial expressions, voice, and input actions.

[0378] A "virtual character" is a user-selectable digital impersonation that provides a sense of familiarity through interaction.

[0379] "Photographing means" refers to the way in which a user photographs an object using the device's camera.

[0380] The "means for generating advice" is a method for generating advice about an item based on image data, user information, and emotion information received by the server.

[0381] The "means for displaying advice" is a method for displaying the generated advice on the screen of the user device.

[0382] The "means for selecting a disposal method" is a method by which the user selects from the options of "save," "dispose," and "request purchase" for the item based on the generated advice.

[0383] "Means for calculating market value" refers to the method by which the server evaluates the current market value of an item and presents it to the user.

[0384] This invention is a system that allows users to efficiently dispose of unwanted items, and operates mainly based on the user's terminal, a server, an emotion engine, and the data exchanged between them. A specific example of the entire system will be described below.

[0385] System Overview

[0386] The user launches a dedicated application on their device and enters their account information on the login screen to perform authentication. If authentication is successful, the user can proceed to the next step. The user then selects their preferred virtual character from multiple options on the virtual character selection screen within the application. The selected character guides the user through subsequent interactions, providing a sense of familiarity.

[0387] To dispose of an item, the user takes a picture of the item using the device's camera. This image data is sent from the device to the server. At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize the user's emotions. The emotion engine uses facial recognition software (e.g., EmotionRecognizer) to detect the user's emotional state, and this data is also sent to the server.

[0388] The server analyzes the received image data and identifies the item using computer vision technology (e.g., OpenCV). It also uses user information (e.g., age, gender, body type, past item handling history, etc.) and emotional information to generate more accurate advice. The generated advice is specific, such as "This jacket doesn't seem to fit in with current fashion" or "You could potentially sell it for 3,000 yen."

[0389] The generated advice is sent from the server to the device and displayed to the user on the device. Based on the displayed advice, the user selects from the options of "save," "dispose," or "request purchase." Once the selection is complete, the information is sent from the device to the server and saved in a database. The saved data will be used as reference information the next time the service is used.

[0390] Specific examples

[0391] For example, if a male user in his 40s wants to get rid of an old guitar, he can use this system to effectively handle the situation.

[0392] The user launches the Smart Danshari app, enters their account information and logs in.

[0393] A male character is selected from among a plurality of virtual characters.

[0394] By taking a photo of an old guitar, the emotion engine analyzes the user's facial expression and recognizes "nostalgia."

[0395] The server analyzes the image and generates advice such as, "This guitar is a little out of proportion to your age, but if you sell it, you could potentially sell it for 5,000 yen."

[0396] When the user selects "purchase request," the information is sent to the server and saved.

[0397] In this way, the invention can also take into account the user's emotional information, allowing for more personalized and efficient handling of items.

[0398] Prompt Sentence Examples

[0399] "Develop an application that allows users to take photos of items and provides advice on how to dispose of them based on the results of analysis by an emotion engine. The user selects a virtual character, sends the photo of the item and their own emotion data to the server, and then selects "keep," "dispose," or "request purchase" based on the advice generated."

[0400] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0401] Step 1:

[0402] A user starts a device and opens an application. Next, the user enters their account information on the login screen and authenticates. At this point, the input is the user's account information, and the output is the result of authentication success or failure. If authentication is successful, the user proceeds to the next step.

[0403] Step 2:

[0404] The user selects a preferred virtual character from multiple virtual characters on a virtual character selection screen within the application. The input is the virtual character selection information, and the output is the display of the selected character to the user.

[0405] Step 3:

[0406] The user takes a photo of the item they want to dispose of using the device's camera. At this time, the input is the image of the item, and the output is the image data stored in the device.

[0407] Step 4:

[0408] The emotion engine on the device recognizes the user's emotions. It analyzes the user's facial expressions, voice, and input actions, and outputs the user's emotional state as data. The input is information such as the user's facial expressions and voice, and the output is emotional information.

[0409] Step 5:

[0410] The device sends the captured image data and emotion information to the server. The input is the image data and emotion information, and the output is the data received by the server.

[0411] Step 6:

[0412] The server analyzes the image data and identifies the item using computer vision technology. The input is the transmitted image data, and the output is information about the identified object. OpenCV and other computer vision technologies are used.

[0413] Step 7:

[0414] The server generates advice for the identified object based on the user information and emotion information. The input is the item information, user information, and emotion information, and the output is the generated advice. For example, this advice might be, "This jacket doesn't seem to fit in with modern fashion" or "You could potentially sell it for 3,000 yen."

[0415] Step 8:

[0416] The server sends the generated advice to the terminal, which then displays the advice to the user. The input is the advice sent from the server, and the output is the advice displayed on the application.

[0417] Step 9:

[0418] The user selects from the options of "save," "dispose," or "request a resale" based on the displayed advice. The input is the user's selection information, and the output is the selected option.

[0419] Step 10:

[0420] The selection information is sent from the terminal to the server, which then stores it in a database. The input is the user's selection information, and the output is the processing history stored in the database. The stored data is also used as reference information for future use.

[0421] 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.

[0422] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0423] 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.

[0424] [Second embodiment]

[0425] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0426] 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.

[0427] 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).

[0428] 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.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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."

[0437] The present invention provides a system that allows users to efficiently dispose of unnecessary items in their daily lives. This system operates mainly based on the user's device, a server, and data exchanged between them.

[0438] First, the user launches the application on their device, enters their account information on the login screen, and authenticates, at which point they are granted access to the system.

[0439] Next, the user selects from a selection of virtual characters (avatars) on a character selection screen within the application. The selected character guides the user through subsequent interactions and provides a sense of familiarity.

[0440] To identify an item a user wants to throw away, they take a photo of the item using the device's camera. The captured image data is then sent from the device to a server. The server then analyzes the image data and uses computer vision technology to identify the item. Information about the user's body type, age, and other items they own is also sent to the server.

[0441] The server generates advice about the item based on the results of image data analysis and user information. For example, it provides specific advice such as, "This coat does not suit your body type, age, or current trends." It also calculates the current market value and provides an economic assessment, such as, "This coat could potentially be sold for 3,000 yen."

[0442] The generated advice is sent from the server to the device and displayed to the user, who can then choose to keep, dispose of, or request a resale of the item.

[0443] Once the selection is complete, the device sends the selection information to the server, which stores it in a database and uses it as reference information for future use. This allows users to declutter efficiently and systematically.

[0444] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The server analyzes the image and identifies the coat. After that, taking into account the user's information, the server generates advice such as "This coat does not fit your body type and is out of fashion, so we recommend that you dispose of or sell it," and presents this to the user. It also displays the market value, such as "This coat may be able to be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved.

[0445] In this way, the system of the present invention provides support for users to declutter easily and efficiently.

[0446] The processing flow will be explained below.

[0447] Step 1:

[0448] The user launches the "Danshell" app on a device such as a smartphone. The user enters their account information (username and password) on the login screen and presses the "Login" button.

[0449] Step 2:

[0450] The terminal sends the entered login information to the server. The server then authenticates the login information and returns the authentication result to the terminal. If the authentication is successful, the user can proceed to the next step.

[0451] Step 3:

[0452] The terminal displays a screen after successful login, and allows the user to select their preferred AI character (avatar) from multiple options. The user makes a selection and presses the confirm button.

[0453] Step 4:

[0454] The device sends the selected character information to the server, which then saves the user's character settings.

[0455] Step 5:

[0456] The user uses the app's camera to take a photo of the item they are considering disposing of (e.g., an old coat). Once the photo is taken, the user presses the "Send" button.

[0457] Step 6:

[0458] The device sends the captured image data and user information (body type, age, and information about other items held) to the server.

[0459] Step 7:

[0460] The server analyzes the received image data using computer vision technology to identify the object. For example, it may determine that the object is an "old coat" through image analysis.

[0461] Step 8:

[0462] The server generates advice for the identified object based on the user information. For example, it generates advice such as "This coat does not suit your body type or current fashion" by taking into account body type, age, and current fashion.

[0463] Step 9:

[0464] The server calculates the market value of the object, for example, generating a rating such as "This coat is worth 3,000 yen on the market."

[0465] Step 10:

[0466] The generated advice and market value are sent from the server to the terminal, which displays this information to the user.

[0467] Step 11:

[0468] The user refers to the advice and selects one of the options: "Keep," "Dispose," or "Request a Buyback." Once the selection is complete, the user presses the "OK" button.

[0469] Step 12:

[0470] The device sends the user's selection information to the server, which stores the selection information in a database and uses it as reference for the next time.

[0471] Step 13:

[0472] When the user quits the app, the device closes the application.

[0473] The above are the specific steps of the "Danshell" program processing.

[0474] Example 1

[0475] 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."

[0476] In modern society, many users are seeking an efficient way to dispose of items that are no longer needed in their daily lives. However, it is often difficult to decide whether to throw away, store, or sell these items, which results in delays in decluttering. There is also a lack of professional advice on these items and ways to understand their market value. Furthermore, tools and systems are often difficult to use, preventing users from actively using them. Therefore, a system is needed that allows users to easily dispose of unwanted items and provides appropriate advice and value assessments.

[0477] 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.

[0478] In this invention, the server includes means for a user to photograph an object via an information device, means for transmitting the photographed image data to the server, means for the server to analyze the image data and identify the object, means for generating advice for the identified object based on user information, means for displaying the generated advice to the user, means for the user to select a method of disposing of the object based on the displayed advice, means for transmitting the selected method of disposing of the object to the server and saving it, means for the user to select from a plurality of virtual characters, means for the virtual characters to guide the user through dialogue, means for using a camera function, and means for the server to simultaneously process related information. This allows users to easily and effortlessly photograph and analyze unwanted items, determine a method of disposing of them based on appropriate advice, and then perform optimal disposal after understanding their market value.

[0479] "User" refers to an individual who uses the system to dispose of unwanted items.

[0480] "Information devices" refers to digital devices such as smartphones, tablets, and personal computers.

[0481] The term "target item" refers to an item that the user has determined to be unnecessary.

[0482] "Means for photographing" refers to a method for obtaining an image of an object using the camera function built into an information device.

[0483] "Image data" refers to digital image information obtained when photographing an object.

[0484] "Server" refers to a central processing unit that analyzes image data, identifies objects, and generates advice.

[0485] "Means for analyzing" refers to the techniques and algorithms used to process image data and extract features of interest.

[0486] "Means for identifying" refers to a technique for identifying what an object is based on analyzed characteristics.

[0487] "User Information" refers to data about a user's characteristics and other possessions.

[0488] The "means for generating advice" refers to a function for proposing an appropriate processing method to the user based on the object identification result and user information.

[0489] The "display means" refers to a function for visually presenting the generated advice on the user's information device.

[0490] The "means for selecting a disposal method" refers to a method by which a user can select a disposal method, such as preserving, disposing of, or selling an object, based on the advice provided.

[0491] "Means for saving" refers to the technology for recording the processing method selected by the user within the system and reusing it as needed.

[0492] "Virtual character," also known as an avatar, refers to a digital character that interacts with the user and guides them through the system.

[0493] "Dialogue-based guidance" refers to a function that allows a virtual character to provide operating procedures and advice through communication with the user.

[0494] "Means for simultaneously processing related information" refers to a technique for processing image data together with user information and other necessary data.

[0495] "Market value" refers to an indicator used to assess the price at which an object may be traded in the market.

[0496] The system of the present invention supports users in efficiently disposing of unnecessary items in their daily lives. This system operates mainly based on the user's information device, a server, and the data exchanged between them.

[0497] First, the user installs and launches a dedicated application on an information device such as a smartphone or tablet. The user then enters their account information on the login screen and performs authentication. This authentication uses an arbitrary user ID and password, which the server verifies against a database.

[0498] Once a user has successfully logged in, they proceed to a character selection screen within the application and choose their preferred virtual character (avatar) from multiple options. Once character selection is complete, the selected virtual character will guide the user through subsequent interactions, ensuring smooth use of the system.

[0499] The user takes a photo of the item they want to throw away using the camera function of their information device. The camera function is implemented using the built-in camera of a smartphone or tablet. At this time, the captured image data is sent from the information device to a server. The server analyzes the received image data and uses computer vision technologies such as OpenCV and TensorFlow to identify the item.

[0500] The server processes the identified item, along with information about the user's body type, age, and other items they own. This starts the process of generating advice about the item. For example, it might provide specific advice like, "This coat doesn't suit your body type, age, or current trends." The server also calculates its current market value and provides an economic assessment, such as, "This coat could potentially be sold for 3,000 yen."

[0501] The generated advice is sent from the server to the user's information device and displayed to the user. The user then refers to the displayed advice and selects from the options of "save," "dispose," or "request a resale." Once the selection is complete, the information is sent from the information device to the server, which then stores it in a database. This data is used as reference information for future use.

[0502] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. On the character selection screen, they select a female character in their 30s and then take a photo of an old coat. This image data is sent to the server, which analyzes the image and identifies the coat. The server then takes into account the user's information and generates advice such as, "This coat doesn't fit your body type and is out of fashion, so we recommend you dispose of or sell it," and presents this to the user. It also displays the market value, showing that "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved in a database.

[0503] Example prompt sentence:

[0504] "Please explain the steps to use the application to help users efficiently dispose of unwanted items."

[0505] "Please show us the specific process flow of a system for efficiently decluttering."

[0506] "Please explain in detail the process that will allow users to easily declutter their old coats."

[0507] The above is a specific embodiment for carrying out the present invention.

[0508] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0509] Step 1:

[0510] Launching the application and logging in

[0511] A user starts an application on an information device such as a smartphone or tablet. Next, the user enters their account information (user ID and password) on the login screen. Based on this input, the server compares it with the account information stored in the database and authenticates the user. If authentication is successful, a "Login successful" message is output to the user.

[0512] Input: User ID, Password

[0513] Data processing: database matching, fair comparison

[0514] Output: Authentication result message (success / failure)

[0515] Step 2:

[0516] Character Selection

[0517] After logging in, the user goes to the character selection screen within the application and chooses their favorite virtual character from several options. Once the selection is complete, the device sends the selected character information to the server, which records it and outputs instructions for proceeding to the next step.

[0518] Input: User's character selection

[0519] Data processing: Recording character ID

[0520] Output: Character selection confirmation message

[0521] Step 3:

[0522] Photographing items and sending data

[0523] Users use the camera function of their smartphone or tablet to take a photo of the item they want to throw away. The captured image data is sent from the device to the server. The server stores the received image data and outputs a notification to proceed to the next analysis step.

[0524] Input: Captured image data

[0525] Data processing: Sending and storing image data

[0526] Output: A confirmation message that the image was received

[0527] Step 4:

[0528] Analysis of product images

[0529] The server uses computer vision technologies such as OpenCV and TensorFlow to analyze the received image data. The analysis extracts features of the item and identifies it based on those features. The analysis results are then processed along with information about the user's body type, age, and other items they own.

[0530] Input: Image data, user information

[0531] Data processing: image analysis, feature extraction, item identification

[0532] Output: Analysis results (item identification)

[0533] Step 5:

[0534] Generating Advice

[0535] The server generates advice based on the image analysis results and user information. For example, it provides specific advice such as, "This coat does not suit your body type, age, or current trends." It also calculates the current market value and makes an assessment such as, "This coat could potentially be sold for 3,000 yen."

[0536] Input: Analysis results, user information

[0537] Data processing: advice generation, value calculation

[0538] Output: Advice content, market value

[0539] Step 6:

[0540] Viewing advice and selecting options

[0541] The server sends the generated advice to the terminal, which then displays it to the user, who can then select from the options of "save," "dispose," or "request a buyback."

[0542] Input: Advice content, market value

[0543] Data processing: Sending advice, displaying options

[0544] Output: User selection

[0545] Step 7:

[0546] Sending and storing your selections

[0547] The terminal sends the option information selected by the user to the server, which stores this information in a database. This data will be used as reference information for future use.

[0548] Input: User selection information

[0549] Data processing: sending and storing selected information

[0550] Output: Database update confirmation message

[0551] The above is a specific flow of processing in the system of the present invention.

[0552] (Application example 1)

[0553] 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."

[0554] There is a need to provide a means for users to efficiently dispose of items that are no longer needed in their daily lives. In particular, there is a need for a system that can identify items, evaluate their economic value, suggest disposal methods, and even link with online marketplace sites to enable smoother disposal or sale of items. Currently, many users find it time-consuming and laborious to dispose of items, and a system that can solve this problem is desirable.

[0555] 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.

[0556] In this invention, the server includes means for a user to photograph an object via a device, means for transmitting the photographed image data to the server, means for the server to analyze the image data and identify the object, means for the server to generate advice for the identified object based on user information, means for displaying the generated advice to the user, means for the user to select a method of disposing of the object based on the displayed advice, means for transmitting and storing the selected method of disposing of the object to the server, and means for linking to an online marketplace site and making a buyback request, thereby enabling users to efficiently dispose of unwanted items and maximize their economic value.

[0557] "User" refers to any individual or legal entity that uses the System.

[0558] "Device" refers to the hardware device, primarily a smartphone or tablet, that a user uses to interface with the system.

[0559] "Object" refers to an item that a user wishes to dispose of, save, or sell.

[0560] "Means for photographing" refers to the function of acquiring an image of an object using the camera function built into the device.

[0561] "Means for transmitting image data to a server" refers to a function for transmitting captured image data from a device via a network to a remote server.

[0562] "Server" refers to the back-end computer that processes and stores data at the heart of the system.

[0563] "Means for analyzing image data and identifying objects" refers to the function of the server or its related systems to identify the type and characteristics of objects using image processing technology.

[0564] "User information" refers to data such as a user's personal information, preferences, body type, age, and past behavioral history.

[0565] "Means for generating advice" refers to the function of the server to make specific suggestions and evaluations for the target object based on the analysis results and user information.

[0566] "Means for displaying advice to the user" refers to a function for displaying advice generated by the server on the screen of the user's device.

[0567] "Means for selecting a disposal method" refers to a function that allows a user to choose whether to preserve, dispose of, or sell an object by referring to the displayed advice.

[0568] The "means for transmitting the processing method to the server and storing it" refers to a function for transmitting the processing method selected by the user to the server and storing it in the database.

[0569] "Online Marketplace Site" means a web platform through which users can buy and sell goods.

[0570] The "means for making a purchase request" refers to a function for transmitting a purchase request for the selected object to the online market site.

[0571] The present invention provides a system for efficiently disposing of items that users no longer need in their daily lives. Specifically, the system operates based on the user's device, a server, and data exchanged between them.

[0572] System configuration

[0573] Users install an application on their devices, such as smartphones or tablets, which uses the camera function to take pictures of unwanted items and send the image data to a server.

[0574] 1. User Authentication

[0575] The user enters their account information on the login screen and sends it to the server, where it is authenticated, and if the authentication is successful, the user is allowed to access the system.

[0576] 2. Avatar selection

[0577] After authentication, the user selects from multiple virtual characters (avatars) within the application, and the selected avatar guides the user through subsequent operations.

[0578] 3. Photographing and analyzing the object

[0579] Users take a photo of the item they want to dispose of using their device's camera. The image data is sent to a server, which then analyzes the image. The technology used is based on computer vision technology.

[0580] 4. Generating and displaying advice

[0581] The server generates advice for the item based on the image analysis results and user information. This advice includes suggestions for preserving, disposing of, or selling the item. The advice is sent to the user's device and displayed on the screen.

[0582] 5. Calculating market value

[0583] The server also calculates the market value of the object and displays it to the user.

[0584] 6. Selection of processing method

[0585] The user can refer to the displayed advice and choose how to dispose of the item. There are three options: "Keep," "Dispose," or "Request a purchase."

[0586] 7. Submitting a purchase request

[0587] If the user selects "purchase request," the system will link to an online marketplace site and make a purchase request.

[0588] 8. Data Retention

[0589] The processing method selected by the user is stored in a database and used as reference information the next time the system is used.

[0590] Hardware and software used

[0591] The hardware used is a smartphone, tablet, and server, and the software used is Python, OpenCV, the Requests library, and PIL (Python Imaging Library).

[0592] 1. User Authentication

[0593] Use the Python Requests library to send the user's credentials to the server for authentication.

[0594] 2. Taking photos and sending images

[0595] OpenCV is used to control the device's camera function and take images, which are then sent to the server using the Requests library.

[0596] 3. Image analysis and advice generation

[0597] On the server, image data is analyzed using computer vision and generative AI models, and appropriate advice is generated based on the user information and analysis results.

[0598] 4. Advice and Market Value Calculation

[0599] Advice generated using PIL is displayed as an image on the user's device, and the generative AI model is also used to calculate market value.

[0600] 5. Selecting a disposal method and requesting a purchase

[0601] The user's selection of the treatment method is transmitted to the server and, if necessary, forwarded to the online marketplace site.

[0602] Examples of concrete examples and prompts

[0603] Examples:

[0604] For example, consider a scenario in which a user wants to get rid of an old coat. The user launches the application on their device and logs in. They select a female character (avatar) in her 30s and takes a photo of the old coat with the device's camera. The server analyzes the image and, taking into account the user's body type, age, and current trends, suggests advice such as "This coat doesn't suit your body type and is out of fashion, so we recommend you get rid of or sell it," along with a market value such as "This coat may sell for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and stored in a database.

[0605] Example prompt sentence:

[0606] "Write a Python program that authenticates users, photographs and identifies unwanted items, provides advice and economic evaluation, and submits the final disposal selection to the server."

[0607] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0608] Step 1:

[0609] A user starts an application using a device such as a smartphone or tablet. The user enters their account information (username, password) on the login screen. This information is sent from the device to the server, which then performs authentication. The server compares the entered information with its database, and if it matches, the authentication is successful. The user is then shown a message indicating successful login, and the process moves to the next step.

[0610] Input: Username, Password

[0611] Output: Authentication result (success / failure)

[0612] Step 2:

[0613] The user selects their preferred avatar from multiple virtual characters on the avatar selection screen. The selected avatar information is stored on the device and used for subsequent interactions. The server retains session information including the selected avatar information and reflects it in the next step.

[0614] Input: User avatar selection

[0615] Output: Add avatar information to session information

[0616] Step 3:

[0617] The user uses the device's camera to take a picture of the item they want to dispose of. The captured image data is sent from the device to the server, which uses computer vision technology to analyze the received image data and identify the object.

[0618] Input: Photographed image data

[0619] Output: Object identification information

[0620] Step 4:

[0621] The server generates advice for the identified object. Using a generative AI model, it creates specific advice based on user information (body type, age, fashion, etc.) and the results of image analysis. The generated advice is then sent to the device.

[0622] Input: Object identification information, user information

[0623] Output: Specific advice

[0624] Step 5:

[0625] The terminal receives the advice sent from the server and displays it to the user. In addition, the server simultaneously calculates the market value of the object and displays it to the user together with the advice.

[0626] Input: Specific advice, market value

[0627] Output: Advice and market value displayed on the terminal

[0628] Step 6:

[0629] The user refers to the advice and selects how to dispose of the object (preservation, disposal, purchase request). The selected method is sent from the terminal to the server and stored in the database.

[0630] Input: User-selected processing method

[0631] Output: Data on the selected processing method

[0632] Step 7:

[0633] If the user selects a buyback request, the system connects to the online marketplace site and sends the buyback request information, which the server then processes.

[0634] Input: Purchase request information

[0635] Output: Request information sent to online marketplace site

[0636] The above is the specific processing flow of the program for the system that realizes the application example. At each step, appropriate data processing and calculation are performed based on the input data, and the output for the next step is generated.

[0637] 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.

[0638] The present invention is a system that allows users to efficiently dispose of unnecessary items in their daily lives. This system operates mainly based on the user's device, a server, an emotion engine, and data exchanged among them.

[0639] First, a user launches an application on their device. They enter their account information on the login screen and authenticate. If authentication is successful, the user can proceed to the next step. Next, the user selects their preferred virtual character (avatar) from multiple options on the character selection screen within the application. The selected character guides the user through subsequent interactions, providing a sense of familiarity.

[0640] To identify the item the user wants to throw away, the user takes a photo of the item using the device's camera function. This image data is sent from the device to the server. At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize the user's emotions. The emotion engine detects the user's emotional state and also sends this data to the server.

[0641] The server analyzes the received image data and uses computer vision technology to identify the item. In addition, information about the user's body type, age, and other items they are holding, as well as emotion recognition results from the emotion engine, are also sent to the server.

[0642] The server generates advice about the item based on the results of image data analysis, user information, and emotion recognition. For example, it can provide specific advice such as "This coat doesn't suit your body type, age, or current trends," or emotion-based advice such as "You seem reluctant to throw away the item. Would you like to reconsider?" It also calculates the current market value and provides an economic assessment, such as "This coat could be sold for 3,000 yen."

[0643] The generated advice is sent from the server to the device and displayed to the user on the device. The user can refer to the displayed advice and select from the options of "keep," "dispose," or "request purchase" for the item. Once the selection is complete, the device sends the selection information to the server. The server saves the selection information in a database and uses it as reference information for future use.

[0644] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The emotion engine recognizes the user's emotions from their facial expression and determines that they are "a little reluctant to throw things away." The server analyzes the image, identifies the coat, and, taking into account the user information and the emotion recognition results, generates advice such as "This coat doesn't suit your body type or trends, but you seem to have trouble getting rid of things, so you might want to reconsider." It also displays the market value, saying, "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved.

[0645] In this way, the system of the present invention provides support to help users declutter easily and efficiently, and by incorporating emotion recognition technology, it generates more personalized advice and reduces users' psychological resistance.

[0646] The processing flow will be explained below.

[0647] Step 1:

[0648] The user launches an application on a device such as a smartphone. The user enters account information (username and password) on the login screen and presses the "Login" button.

[0649] Step 2:

[0650] The terminal sends the entered login information to the server. The server then authenticates the login information and returns the authentication result to the terminal. If the authentication is successful, the user can proceed to the next step.

[0651] Step 3:

[0652] The terminal displays a screen after successful login, and allows the user to select their preferred AI character (avatar) from multiple options. The user makes a selection and presses the confirm button.

[0653] Step 4:

[0654] The device sends the selected character information to the server, which then saves the user's character settings.

[0655] Step 5:

[0656] The user uses the app's camera to take a photo of the item they are considering disposing of (e.g., an old coat). Once the photo is taken, the user presses the "Send" button.

[0657] Step 6:

[0658] The device sends the captured image data and user information (body type, age, and information about other items held by the user) to the server. At the same time, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state.

[0659] Step 7:

[0660] The emotion engine sends the recognized emotion data to the server, which then analyzes the received image data using computer vision technology to identify the target object.

[0661] Step 8:

[0662] The server generates advice for the identified object based on the user's information and emotion data. For example, it takes into account body type, age, and current fashion trends to generate advice such as "This coat doesn't suit your body type or the current trends," or emotion-based advice such as "You seem reluctant to throw things away. Would you reconsider?"

[0663] Step 9:

[0664] The server calculates the market value of the object, for example, generating a rating such as "This coat is worth 3,000 yen on the market."

[0665] Step 10:

[0666] The server transmits the generated advice and market value to the terminal, which displays this information to the user.

[0667] Step 11:

[0668] The user refers to the advice and selects one of the options: "Keep," "Dispose," or "Request a Buyback." Once the selection is complete, the user presses the "OK" button.

[0669] Step 12:

[0670] The device sends the user's selection information to the server, which stores the selection information in a database and uses it as reference for the next time.

[0671] Step 13:

[0672] When the user quits the app, the device closes the application.

[0673] The above are the specific steps in the programming process of the "Danshell" system, which incorporates an emotion engine.

[0674] Example 2

[0675] 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."

[0676] In today's consumer society, people frequently purchase goods, resulting in an increasing number of unnecessary items. However, disposing of these items is a psychological burden for many people. Specifically, the main challenges are a reluctance to throw away items and an inability to properly evaluate their value. In addition, there is a lack of systems that provide users with appropriate advice when choosing how to dispose of items.

[0677] 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.

[0678] In this invention, the server includes a means for a user to photograph an object via an electronic device, a means for transmitting the photographed image data to a data center, a means for the data center to analyze the image data and identify the object, a means for the data center to generate advice for the identified object based on user information and emotion recognition results, a means for displaying the generated advice to the user, a means for the user to select a method of disposing of the object based on the displayed advice, and a means for transmitting and storing the selected method of disposing of the object to the data center. This reduces the user's psychological resistance to disposing of the item and enables them to correctly evaluate the value of the item. Furthermore, appropriate and personalized advice can be provided to the user.

[0679] "User" refers to an individual or organization that uses this system to dispose of items.

[0680] "Electronic devices" refer to devices that have computer functions, such as smartphones, tablets, and personal computers, and are equipped with input devices such as cameras and microphones.

[0681] "Target item" refers to an item that the user is considering disposing of.

[0682] "Photographing" refers to the act of a user acquiring image data of an object using the camera function of an electronic device.

[0683] "Image data" refers to digital image information of a photographed object.

[0684] "Data Center" means a centralized facility containing servers and other computing resources where data is stored and processed.

[0685] "Analysis" refers to the process of recognizing and identifying objects in the image data received by the data center using computer vision technology, etc.

[0686] "User information" refers to information such as the user's profile data (age, gender, body type, etc.), past usage history, and item ownership status.

[0687] "Emotion recognition results" refers to data indicating the user's emotional state obtained by the emotion engine by analyzing the user's facial expressions, voice, and input actions.

[0688] "Advice" refers to advice provided by the Data Center to the User regarding the disposal method and market value of the object based on the analyzed data.

[0689] "Saving" refers to the act of recording information or data selected by the user in storage such as a database, making it available for subsequent access.

[0690] "Market value" refers to information that indicates the value of an object in the current market as a number or evaluation.

[0691] "Virtual Character" refers to an anthropomorphic digital avatar that a user selects within the system and that guides the user through the interaction.

[0692] The present invention is a system that allows users to efficiently dispose of items that are no longer needed in their daily lives. This system operates mainly based on the user's electronic devices, a data center, an emotion engine, and data exchanged among them.

[0693] First, the user launches the application on their electronic device (smartphone, tablet, etc.) and enters their account information on the login screen to authenticate. If authentication is successful, the user is taken to the application's home screen.

[0694] Next, the user taps the "Select Character" button on the home screen and chooses from a selection of virtual characters (avatars), which guide the user through subsequent interactions and provide a sense of familiarity.

[0695] The user identifies the item they want to throw away and takes a photo of it using the camera function of their electronic device. The image data is then sent from the electronic device to a data center.

[0696] At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize their emotional state. The emotion engine uses facial recognition and voice analysis software to generate the user's emotional data (e.g., "joy," "sadness," "resistance," etc.), which is also sent to the data center.

[0697] The data center uses computer vision technology (e.g., TensorFlow) to identify the item based on the received image data. It also references the user's body type, age, information about other items they own, and emotion recognition results. Based on this information, the data center uses a generative AI model to generate advice. For example, it can provide advice such as "This coat doesn't suit your body type, age, or current trends," or emotion-based advice such as "You seem reluctant to throw it away. Would you like to reconsider?" It also calculates the current market value and makes an economic assessment, such as "This coat could potentially be sold for 3,000 yen."

[0698] The generated advice is sent from the data center to the electronic device and displayed to the user. The user can refer to the displayed advice and select from the options of "keep," "dispose," or "request purchase" for the item. Once the selection is complete, the selection information is sent from the electronic device to the data center, which stores it in a database. The stored information will be used as reference information the next time the service is used.

[0699] As a concrete example, consider the case of considering disposing of an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The emotion engine recognizes the user's emotions from their facial expression and determines that they are "a little reluctant to throw things away." The data center analyzes the image, identifies the coat, and, taking into account the user information and the emotion recognition results, generates advice such as "This coat doesn't suit your body type or trends, but since you seem reluctant to get rid of it, you may want to reconsider." It also displays the market value, indicating that "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the data center and stored.

[0700] Example prompts for generative AI models

[0701] "A female user in her 30s is reluctant to throw things away and has taken a photo of an old coat. Please provide advice and market value."

[0702] The system of the present invention allows users to dispose of items easily and efficiently, and by incorporating emotion recognition technology, it provides more personalized advice and reduces users' psychological resistance.

[0703] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0704] Step 1:

[0705] The user launches the application on an electronic device (smartphone, tablet, etc.) and enters account information (ID, password) on the login screen to authenticate.

[0706] Input: User account information

[0707] Output: Authentication result (success / failure)

[0708] Specific behavior:

[0709] The user taps the application to launch it.

[0710] Enter your ID and password on the login screen.

[0711] When you press the "Login" button, data is sent to the authentication server and authentication is performed.

[0712] If authentication is successful, the home screen will be displayed.

[0713] Step 2:

[0714] The user taps the "Character Selection" button on the home screen and chooses their preferred virtual character (avatar) from multiple options.

[0715] Input: Selection information of virtual character

[0716] Output: Selected characters

[0717] Specific behavior:

[0718] The user taps the "Character Selection" button.

[0719] A number of virtual characters are displayed.

[0720] The user taps on the character of their choice to select it.

[0721] The selected character will be reflected in the application.

[0722] Step 3:

[0723] Users take a photo of the item they want to throw away using the camera function of their electronic device, and the captured image data is sent from the electronic device to a data center.

[0724] Input: Image data of the item

[0725] Output: Image data transmission results to the data center

[0726] Specific behavior:

[0727] The user taps the camera launch button within the app.

[0728] The device's camera is activated and the user points the camera at the item they want to throw away and takes a picture.

[0729] After the image is taken, the image data is automatically uploaded to a data center.

[0730] Step 4:

[0731] The emotion engine analyzes the user's facial expressions, voice, and input actions to recognize their emotional state, and sends this data to a data center.

[0732] Input: facial expression data, voice data, input action data

[0733] Output: Emotion recognition result

[0734] Specific behavior:

[0735] The device's camera and microphone capture the user's facial expressions and voice in real time.

[0736] The emotion engine performs facial expression recognition and voice analysis to generate emotion data.

[0737] Emotion data is sent to a data center.

[0738] Step 5:

[0739] The data center uses computer vision technology (e.g., TensorFlow) to identify the item based on the image data received.

[0740] Input: Image data of the item

[0741] Output: Item identification result

[0742] Specific behavior:

[0743] The image data is received at a data center.

[0744] Computer vision technology is used to analyze the characteristics of an item and identify it.

[0745] Information about the identified items is generated.

[0746] Step 6:

[0747] The data center analyzes user information (body type, age, etc.) together with emotion recognition results, and generates advice using a generative AI model.

[0748] Input: Item identification results, user information, emotion recognition results

[0749] Output: Generated advice

[0750] Specific behavior:

[0751] The item identification results, user information, and emotion recognition results are imported into the data center.

[0752] A generative AI model generates advice sentences based on this data.

[0753] The generated advice is stored in a data center.

[0754] Step 7:

[0755] The advice generated by the data center is sent to the electronic device and displayed to the user, who can choose from the options of "keep," "dispose," or "request a resale."

[0756] Input: Generated advice

[0757] Output: User's choice

[0758] Specific behavior:

[0759] The data center transmits the advice data to the electronic device.

[0760] An advice message is displayed on the electronic device, and selection buttons are arranged.

[0761] The user taps the desired option (e.g., "Dispose").

[0762] Step 8:

[0763] The selected information is sent from the electronic device to a data center, which stores it in a database.

[0764] Input: User selection information

[0765] Output: Selections saved in the database

[0766] Specific behavior:

[0767] The user's selection information is transmitted from the electronic device to the data center.

[0768] The data center stores the selection information in a database and checks the integrity of the data.

[0769] (Application example 2)

[0770] 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."

[0771] Current methods for decluttering and disposing of items often fail to take into account users' psychological resistance, resulting in ineffective and efficient disposal. Furthermore, it is difficult for users to understand the appropriate disposal method and economic value of items, resulting in wasted time and effort. Furthermore, personalized advice that takes into account the user's emotional state is not provided, resulting in low user satisfaction. To solve these issues, a system that also takes into account the user's emotional information is needed.

[0772] 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.

[0773] In this invention, the server includes means for generating advice for the identified object based on user information and emotion information, means for displaying the generated advice to the user, and means for the user to select a method of processing the object based on the displayed advice, thereby providing personalized advice that takes into account the user's emotional state and enabling efficient and effective processing of items.

[0774] "User information" refers to personal information about the user, such as age, sex, body type, and past item processing history.

[0775] "Emotion information" is data on the user's emotional state analyzed from their facial expressions, voice, and input actions.

[0776] A "virtual character" is a user-selectable digital impersonation that provides a sense of familiarity through interaction.

[0777] "Photographing means" refers to the way in which a user photographs an object using the device's camera.

[0778] The "means for generating advice" is a method for generating advice about an item based on image data, user information, and emotion information received by the server.

[0779] The "means for displaying advice" is a method for displaying the generated advice on the screen of the user device.

[0780] The "means for selecting a disposal method" is a method by which the user selects from the options of "save," "dispose," and "request purchase" for the item based on the generated advice.

[0781] "Means for calculating market value" refers to the method by which the server evaluates the current market value of an item and presents it to the user.

[0782] This invention is a system that allows users to efficiently dispose of unwanted items, and operates mainly based on the user's terminal, a server, an emotion engine, and the data exchanged between them. A specific example of the entire system will be described below.

[0783] System Overview

[0784] The user launches a dedicated application on their device and enters their account information on the login screen to perform authentication. If authentication is successful, the user can proceed to the next step. The user then selects their preferred virtual character from multiple options on the virtual character selection screen within the application. The selected character guides the user through subsequent interactions, providing a sense of familiarity.

[0785] To dispose of an item, the user takes a picture of the item using the device's camera. This image data is sent from the device to the server. At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize the user's emotions. The emotion engine uses facial recognition software (e.g., EmotionRecognizer) to detect the user's emotional state, and this data is also sent to the server.

[0786] The server analyzes the received image data and identifies the item using computer vision technology (e.g., OpenCV). It also uses user information (e.g., age, gender, body type, past item handling history, etc.) and emotional information to generate more accurate advice. The generated advice is specific, such as "This jacket doesn't seem to fit in with current fashion" or "You could potentially sell it for 3,000 yen."

[0787] The generated advice is sent from the server to the device and displayed to the user on the device. Based on the displayed advice, the user selects from the options of "save," "dispose," or "request purchase." Once the selection is complete, the information is sent from the device to the server and saved in a database. The saved data will be used as reference information the next time the service is used.

[0788] Specific examples

[0789] For example, if a male user in his 40s wants to get rid of an old guitar, he can use this system to effectively handle the situation.

[0790] The user launches the Smart Danshari app, enters their account information and logs in.

[0791] A male character is selected from among a plurality of virtual characters.

[0792] By taking a photo of an old guitar, the emotion engine analyzes the user's facial expression and recognizes "nostalgia."

[0793] The server analyzes the image and generates advice such as, "This guitar is a little out of proportion to your age, but if you sell it, you could potentially sell it for 5,000 yen."

[0794] When the user selects "purchase request," the information is sent to the server and saved.

[0795] In this way, the invention can also take into account the user's emotional information, allowing for more personalized and efficient handling of items.

[0796] Prompt Sentence Examples

[0797] "Develop an application that allows users to take photos of items and provides advice on how to dispose of them based on the results of analysis by an emotion engine. The user selects a virtual character, sends the photo of the item and their own emotion data to the server, and then selects "keep," "dispose," or "request purchase" based on the advice generated."

[0798] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0799] Step 1:

[0800] A user starts a device and opens an application. Next, the user enters their account information on the login screen and authenticates. At this point, the input is the user's account information, and the output is the result of authentication success or failure. If authentication is successful, the user proceeds to the next step.

[0801] Step 2:

[0802] The user selects a preferred virtual character from multiple virtual characters on a virtual character selection screen within the application. The input is the virtual character selection information, and the output is the display of the selected character to the user.

[0803] Step 3:

[0804] The user takes a photo of the item they want to dispose of using the device's camera. At this time, the input is the image of the item, and the output is the image data stored in the device.

[0805] Step 4:

[0806] The emotion engine on the device recognizes the user's emotions. It analyzes the user's facial expressions, voice, and input actions, and outputs the user's emotional state as data. The input is information such as the user's facial expressions and voice, and the output is emotional information.

[0807] Step 5:

[0808] The device sends the captured image data and emotion information to the server. The input is the image data and emotion information, and the output is the data received by the server.

[0809] Step 6:

[0810] The server analyzes the image data and identifies the item using computer vision technology. The input is the transmitted image data, and the output is information about the identified object. OpenCV and other computer vision technologies are used.

[0811] Step 7:

[0812] The server generates advice for the identified object based on the user information and emotion information. The input is the item information, user information, and emotion information, and the output is the generated advice. For example, this advice might be, "This jacket doesn't seem to fit in with modern fashion" or "You could potentially sell it for 3,000 yen."

[0813] Step 8:

[0814] The server sends the generated advice to the terminal, which then displays the advice to the user. The input is the advice sent from the server, and the output is the advice displayed on the application.

[0815] Step 9:

[0816] The user selects from the options of "save," "dispose," or "request a resale" based on the displayed advice. The input is the user's selection information, and the output is the selected option.

[0817] Step 10:

[0818] The selection information is sent from the terminal to the server, which then stores it in a database. The input is the user's selection information, and the output is the processing history stored in the database. The stored data is also used as reference information for future use.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] [Third embodiment]

[0823] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0824] 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.

[0825] 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).

[0826] 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.

[0827] 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.

[0828] 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).

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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."

[0835] The present invention provides a system that allows users to efficiently dispose of unnecessary items in their daily lives. This system operates mainly based on the user's device, a server, and data exchanged between them.

[0836] First, the user launches the application on their device, enters their account information on the login screen, and authenticates, at which point they are granted access to the system.

[0837] Next, the user selects from a selection of virtual characters (avatars) on a character selection screen within the application. The selected character guides the user through subsequent interactions and provides a sense of familiarity.

[0838] To identify an item a user wants to throw away, they take a photo of the item using the device's camera. The captured image data is then sent from the device to a server. The server then analyzes the image data and uses computer vision technology to identify the item. Information about the user's body type, age, and other items they own is also sent to the server.

[0839] The server generates advice about the item based on the results of image data analysis and user information. For example, it provides specific advice such as, "This coat does not suit your body type, age, or current trends." It also calculates the current market value and provides an economic assessment, such as, "This coat could potentially be sold for 3,000 yen."

[0840] The generated advice is sent from the server to the device and displayed to the user, who can then choose to keep, dispose of, or request a resale of the item.

[0841] Once the selection is complete, the device sends the selection information to the server, which stores it in a database and uses it as reference information for future use. This allows users to declutter efficiently and systematically.

[0842] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The server analyzes the image and identifies the coat. After that, taking into account the user's information, the server generates advice such as "This coat does not fit your body type and is out of fashion, so we recommend that you dispose of or sell it," and presents this to the user. It also displays the market value, such as "This coat may be able to be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved.

[0843] In this way, the system of the present invention provides support for users to declutter easily and efficiently.

[0844] The processing flow will be explained below.

[0845] Step 1:

[0846] The user launches the "Danshell" app on a device such as a smartphone. The user enters their account information (username and password) on the login screen and presses the "Login" button.

[0847] Step 2:

[0848] The terminal sends the entered login information to the server. The server then authenticates the login information and returns the authentication result to the terminal. If the authentication is successful, the user can proceed to the next step.

[0849] Step 3:

[0850] The terminal displays a screen after successful login, and allows the user to select their preferred AI character (avatar) from multiple options. The user makes a selection and presses the confirm button.

[0851] Step 4:

[0852] The device sends the selected character information to the server, which then saves the user's character settings.

[0853] Step 5:

[0854] The user uses the app's camera to take a photo of the item they are considering disposing of (e.g., an old coat). Once the photo is taken, the user presses the "Send" button.

[0855] Step 6:

[0856] The device sends the captured image data and user information (body type, age, and information about other items held) to the server.

[0857] Step 7:

[0858] The server analyzes the received image data using computer vision technology to identify the object. For example, it may determine that the object is an "old coat" through image analysis.

[0859] Step 8:

[0860] The server generates advice for the identified object based on the user information. For example, it generates advice such as "This coat does not suit your body type or current fashion" by taking into account body type, age, and current fashion.

[0861] Step 9:

[0862] The server calculates the market value of the object, for example, generating a rating such as "This coat is worth 3,000 yen on the market."

[0863] Step 10:

[0864] The generated advice and market value are sent from the server to the terminal, which displays this information to the user.

[0865] Step 11:

[0866] The user refers to the advice and selects one of the options: "Keep," "Dispose," or "Request a Buyback." Once the selection is complete, the user presses the "OK" button.

[0867] Step 12:

[0868] The device sends the user's selection information to the server, which stores the selection information in a database and uses it as reference for the next time.

[0869] Step 13:

[0870] When the user quits the app, the device closes the application.

[0871] The above are the specific steps of the "Danshell" program processing.

[0872] Example 1

[0873] 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."

[0874] In modern society, many users are seeking an efficient way to dispose of items that are no longer needed in their daily lives. However, it is often difficult to decide whether to throw away, store, or sell these items, which results in delays in decluttering. There is also a lack of professional advice on these items and ways to understand their market value. Furthermore, tools and systems are often difficult to use, preventing users from actively using them. Therefore, a system is needed that allows users to easily dispose of unwanted items and provides appropriate advice and value assessments.

[0875] 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.

[0876] In this invention, the server includes means for a user to photograph an object via an information device, means for transmitting the photographed image data to the server, means for the server to analyze the image data and identify the object, means for generating advice for the identified object based on user information, means for displaying the generated advice to the user, means for the user to select a method of disposing of the object based on the displayed advice, means for transmitting the selected method of disposing of the object to the server and saving it, means for the user to select from a plurality of virtual characters, means for the virtual characters to guide the user through dialogue, means for using a camera function, and means for the server to simultaneously process related information. This allows users to easily and effortlessly photograph and analyze unwanted items, determine a method of disposing of them based on appropriate advice, and then perform optimal disposal after understanding their market value.

[0877] "User" refers to an individual who uses the system to dispose of unwanted items.

[0878] "Information devices" refers to digital devices such as smartphones, tablets, and personal computers.

[0879] The term "target item" refers to an item that the user has determined to be unnecessary.

[0880] "Means for photographing" refers to a method for obtaining an image of an object using the camera function built into an information device.

[0881] "Image data" refers to digital image information obtained when photographing an object.

[0882] "Server" refers to a central processing unit that analyzes image data, identifies objects, and generates advice.

[0883] "Means for analyzing" refers to the techniques and algorithms used to process image data and extract features of interest.

[0884] "Means for identifying" refers to a technique for identifying what an object is based on analyzed characteristics.

[0885] "User Information" refers to data about a user's characteristics and other possessions.

[0886] The "means for generating advice" refers to a function for proposing an appropriate processing method to the user based on the object identification result and user information.

[0887] The "display means" refers to a function for visually presenting the generated advice on the user's information device.

[0888] The "means for selecting a disposal method" refers to a method by which a user can select a disposal method, such as preserving, disposing of, or selling an object, based on the advice provided.

[0889] "Means for saving" refers to the technology for recording the processing method selected by the user within the system and reusing it as needed.

[0890] "Virtual character," also known as an avatar, refers to a digital character that interacts with the user and guides them through the system.

[0891] "Dialogue-based guidance" refers to a function that allows a virtual character to provide operating procedures and advice through communication with the user.

[0892] "Means for simultaneously processing related information" refers to a technique for processing image data together with user information and other necessary data.

[0893] "Market value" refers to an indicator used to assess the price at which an object may be traded in the market.

[0894] The system of the present invention supports users in efficiently disposing of unnecessary items in their daily lives. This system operates mainly based on the user's information device, a server, and the data exchanged between them.

[0895] First, the user installs and launches a dedicated application on an information device such as a smartphone or tablet. The user then enters their account information on the login screen and performs authentication. This authentication uses an arbitrary user ID and password, which the server verifies against a database.

[0896] Once a user has successfully logged in, they proceed to a character selection screen within the application and choose their preferred virtual character (avatar) from multiple options. Once character selection is complete, the selected virtual character will guide the user through subsequent interactions, ensuring smooth use of the system.

[0897] The user takes a photo of the item they want to throw away using the camera function of their information device. The camera function is implemented using the built-in camera of a smartphone or tablet. At this time, the captured image data is sent from the information device to a server. The server analyzes the received image data and uses computer vision technologies such as OpenCV and TensorFlow to identify the item.

[0898] The server processes the identified item, along with information about the user's body type, age, and other items they own. This starts the process of generating advice about the item. For example, it might provide specific advice like, "This coat doesn't suit your body type, age, or current trends." The server also calculates its current market value and provides an economic assessment, such as, "This coat could potentially be sold for 3,000 yen."

[0899] The generated advice is sent from the server to the user's information device and displayed to the user. The user then refers to the displayed advice and selects from the options of "save," "dispose," or "request a resale." Once the selection is complete, the information is sent from the information device to the server, which then stores it in a database. This data is used as reference information for future use.

[0900] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. On the character selection screen, they select a female character in their 30s and then take a photo of an old coat. This image data is sent to the server, which analyzes the image and identifies the coat. The server then takes into account the user's information and generates advice such as, "This coat doesn't fit your body type and is out of fashion, so we recommend you dispose of or sell it," and presents this to the user. It also displays the market value, showing that "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved in a database.

[0901] Example prompt sentence:

[0902] "Please explain the steps to use the application to help users efficiently dispose of unwanted items."

[0903] "Please show us the specific process flow of a system for efficiently decluttering."

[0904] "Please explain in detail the process that will allow users to easily declutter their old coats."

[0905] The above is a specific embodiment for carrying out the present invention.

[0906] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0907] Step 1:

[0908] Launching the application and logging in

[0909] A user starts an application on an information device such as a smartphone or tablet. Next, the user enters their account information (user ID and password) on the login screen. Based on this input, the server compares it with the account information stored in the database and authenticates the user. If authentication is successful, a "Login successful" message is output to the user.

[0910] Input: User ID, Password

[0911] Data processing: database matching, fair comparison

[0912] Output: Authentication result message (success / failure)

[0913] Step 2:

[0914] Character Selection

[0915] After logging in, the user goes to the character selection screen within the application and chooses their favorite virtual character from several options. Once the selection is complete, the device sends the selected character information to the server, which records it and outputs instructions for proceeding to the next step.

[0916] Input: User's character selection

[0917] Data processing: Recording character ID

[0918] Output: Character selection confirmation message

[0919] Step 3:

[0920] Photographing items and sending data

[0921] Users use the camera function of their smartphone or tablet to take a photo of the item they want to throw away. The captured image data is sent from the device to the server. The server stores the received image data and outputs a notification to proceed to the next analysis step.

[0922] Input: Captured image data

[0923] Data processing: Sending and storing image data

[0924] Output: A confirmation message that the image was received

[0925] Step 4:

[0926] Analysis of product images

[0927] The server uses computer vision technologies such as OpenCV and TensorFlow to analyze the received image data. The analysis extracts features of the item and identifies it based on those features. The analysis results are then processed along with information about the user's body type, age, and other items they own.

[0928] Input: Image data, user information

[0929] Data processing: image analysis, feature extraction, item identification

[0930] Output: Analysis results (item identification)

[0931] Step 5:

[0932] Generating Advice

[0933] The server generates advice based on the image analysis results and user information. For example, it provides specific advice such as, "This coat does not suit your body type, age, or current trends." It also calculates the current market value and makes an assessment such as, "This coat could potentially be sold for 3,000 yen."

[0934] Input: Analysis results, user information

[0935] Data processing: advice generation, value calculation

[0936] Output: Advice content, market value

[0937] Step 6:

[0938] Viewing advice and selecting options

[0939] The server sends the generated advice to the terminal, which then displays it to the user, who can then select from the options of "save," "dispose," or "request a buyback."

[0940] Input: Advice content, market value

[0941] Data processing: Sending advice, displaying options

[0942] Output: User selection

[0943] Step 7:

[0944] Sending and storing your selections

[0945] The terminal sends the option information selected by the user to the server, which stores this information in a database. This data will be used as reference information for future use.

[0946] Input: User selection information

[0947] Data processing: sending and storing selected information

[0948] Output: Database update confirmation message

[0949] The above is a specific flow of processing in the system of the present invention.

[0950] (Application example 1)

[0951] 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."

[0952] There is a need to provide a means for users to efficiently dispose of items that are no longer needed in their daily lives. In particular, there is a need for a system that can identify items, evaluate their economic value, suggest disposal methods, and even link with online marketplace sites to enable smoother disposal or sale of items. Currently, many users find it time-consuming and laborious to dispose of items, and a system that can solve this problem is desirable.

[0953] 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.

[0954] In this invention, the server includes means for a user to photograph an object via a device, means for transmitting the photographed image data to the server, means for the server to analyze the image data and identify the object, means for the server to generate advice for the identified object based on user information, means for displaying the generated advice to the user, means for the user to select a method of disposing of the object based on the displayed advice, means for transmitting and storing the selected method of disposing of the object to the server, and means for linking to an online marketplace site and making a buyback request, thereby enabling users to efficiently dispose of unwanted items and maximize their economic value.

[0955] "User" refers to any individual or legal entity that uses the System.

[0956] "Device" refers to the hardware device, primarily a smartphone or tablet, that a user uses to interface with the system.

[0957] "Object" refers to an item that a user wishes to dispose of, save, or sell.

[0958] "Means for photographing" refers to the function of acquiring an image of an object using the camera function built into the device.

[0959] "Means for transmitting image data to a server" refers to a function for transmitting captured image data from a device via a network to a remote server.

[0960] "Server" refers to the back-end computer that processes and stores data at the heart of the system.

[0961] "Means for analyzing image data and identifying objects" refers to the function of the server or its related systems to identify the type and characteristics of objects using image processing technology.

[0962] "User information" refers to data such as a user's personal information, preferences, body type, age, and past behavioral history.

[0963] "Means for generating advice" refers to the function of the server to make specific suggestions and evaluations for the target object based on the analysis results and user information.

[0964] "Means for displaying advice to the user" refers to a function for displaying advice generated by the server on the screen of the user's device.

[0965] "Means for selecting a disposal method" refers to a function that allows a user to choose whether to preserve, dispose of, or sell an object by referring to the displayed advice.

[0966] The "means for transmitting the processing method to the server and storing it" refers to a function for transmitting the processing method selected by the user to the server and storing it in the database.

[0967] "Online Marketplace Site" means a web platform through which users can buy and sell goods.

[0968] The "means for making a purchase request" refers to a function for transmitting a purchase request for the selected object to the online market site.

[0969] The present invention provides a system for efficiently disposing of items that users no longer need in their daily lives. Specifically, the system operates based on the user's device, a server, and data exchanged between them.

[0970] System configuration

[0971] Users install an application on their devices, such as smartphones or tablets, which uses the camera function to take pictures of unwanted items and send the image data to a server.

[0972] 1. User Authentication

[0973] The user enters their account information on the login screen and sends it to the server, where it is authenticated, and if the authentication is successful, the user is allowed to access the system.

[0974] 2. Avatar selection

[0975] After authentication, the user selects from multiple virtual characters (avatars) within the application, and the selected avatar guides the user through subsequent operations.

[0976] 3. Photographing and analyzing the object

[0977] Users take a photo of the item they want to dispose of using their device's camera. The image data is sent to a server, which then analyzes the image. The technology used is based on computer vision technology.

[0978] 4. Generating and displaying advice

[0979] The server generates advice for the item based on the image analysis results and user information. This advice includes suggestions for preserving, disposing of, or selling the item. The advice is sent to the user's device and displayed on the screen.

[0980] 5. Calculating market value

[0981] The server also calculates the market value of the object and displays it to the user.

[0982] 6. Selection of processing method

[0983] The user can refer to the displayed advice and choose how to dispose of the item. There are three options: "Keep," "Dispose," or "Request a purchase."

[0984] 7. Submitting a purchase request

[0985] If the user selects "purchase request," the system will link to an online marketplace site and make a purchase request.

[0986] 8. Data Retention

[0987] The processing method selected by the user is stored in a database and used as reference information the next time the system is used.

[0988] Hardware and software used

[0989] The hardware used is a smartphone, tablet, and server, and the software used is Python, OpenCV, the Requests library, and PIL (Python Imaging Library).

[0990] 1. User Authentication

[0991] Use the Python Requests library to send the user's credentials to the server for authentication.

[0992] 2. Taking photos and sending images

[0993] OpenCV is used to control the device's camera function and take images, which are then sent to the server using the Requests library.

[0994] 3. Image analysis and advice generation

[0995] On the server, image data is analyzed using computer vision and generative AI models, and appropriate advice is generated based on the user information and analysis results.

[0996] 4. Advice and Market Value Calculation

[0997] Advice generated using PIL is displayed as an image on the user's device, and the generative AI model is also used to calculate market value.

[0998] 5. Selecting a disposal method and requesting a purchase

[0999] The user's selection of the treatment method is transmitted to the server and, if necessary, forwarded to the online marketplace site.

[1000] Examples of concrete examples and prompts

[1001] Examples:

[1002] For example, consider a scenario in which a user wants to get rid of an old coat. The user launches the application on their device and logs in. They select a female character (avatar) in her 30s and takes a photo of the old coat with the device's camera. The server analyzes the image and, taking into account the user's body type, age, and current trends, suggests advice such as "This coat doesn't suit your body type and is out of fashion, so we recommend you get rid of or sell it," along with a market value such as "This coat may sell for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and stored in a database.

[1003] Example prompt sentence:

[1004] "Write a Python program that authenticates users, photographs and identifies unwanted items, provides advice and economic evaluation, and submits the final disposal selection to the server."

[1005] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1006] Step 1:

[1007] A user starts an application using a device such as a smartphone or tablet. The user enters their account information (username, password) on the login screen. This information is sent from the device to the server, which then performs authentication. The server compares the entered information with its database, and if it matches, the authentication is successful. The user is then shown a message indicating successful login, and the process moves to the next step.

[1008] Input: Username, Password

[1009] Output: Authentication result (success / failure)

[1010] Step 2:

[1011] The user selects their preferred avatar from multiple virtual characters on the avatar selection screen. The selected avatar information is stored on the device and used for subsequent interactions. The server retains session information including the selected avatar information and reflects it in the next step.

[1012] Input: User avatar selection

[1013] Output: Add avatar information to session information

[1014] Step 3:

[1015] The user uses the device's camera to take a picture of the item they want to dispose of. The captured image data is sent from the device to the server, which uses computer vision technology to analyze the received image data and identify the object.

[1016] Input: Photographed image data

[1017] Output: Object identification information

[1018] Step 4:

[1019] The server generates advice for the identified object. Using a generative AI model, it creates specific advice based on user information (body type, age, fashion, etc.) and the results of image analysis. The generated advice is then sent to the device.

[1020] Input: Object identification information, user information

[1021] Output: Specific advice

[1022] Step 5:

[1023] The terminal receives the advice sent from the server and displays it to the user. In addition, the server simultaneously calculates the market value of the object and displays it to the user together with the advice.

[1024] Input: Specific advice, market value

[1025] Output: Advice and market value displayed on the terminal

[1026] Step 6:

[1027] The user refers to the advice and selects how to dispose of the object (preservation, disposal, purchase request). The selected method is sent from the terminal to the server and stored in the database.

[1028] Input: User-selected processing method

[1029] Output: Data on the selected processing method

[1030] Step 7:

[1031] If the user selects a buyback request, the system connects to the online marketplace site and sends the buyback request information, which the server then processes.

[1032] Input: Purchase request information

[1033] Output: Request information sent to online marketplace site

[1034] The above is the specific processing flow of the program for the system that realizes the application example. At each step, appropriate data processing and calculation are performed based on the input data, and the output for the next step is generated.

[1035] 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.

[1036] The present invention is a system that allows users to efficiently dispose of unnecessary items in their daily lives. This system operates mainly based on the user's device, a server, an emotion engine, and data exchanged among them.

[1037] First, a user launches an application on their device. They enter their account information on the login screen and authenticate. If authentication is successful, the user can proceed to the next step. Next, the user selects their preferred virtual character (avatar) from multiple options on the character selection screen within the application. The selected character guides the user through subsequent interactions, providing a sense of familiarity.

[1038] To identify the item the user wants to throw away, the user takes a photo of the item using the device's camera function. This image data is sent from the device to the server. At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize the user's emotions. The emotion engine detects the user's emotional state and also sends this data to the server.

[1039] The server analyzes the received image data and uses computer vision technology to identify the item. In addition, information about the user's body type, age, and other items they are holding, as well as emotion recognition results from the emotion engine, are also sent to the server.

[1040] The server generates advice about the item based on the results of image data analysis, user information, and emotion recognition. For example, it can provide specific advice such as "This coat doesn't suit your body type, age, or current trends," or emotion-based advice such as "You seem reluctant to throw away the item. Would you like to reconsider?" It also calculates the current market value and provides an economic assessment, such as "This coat could be sold for 3,000 yen."

[1041] The generated advice is sent from the server to the device and displayed to the user on the device. The user can refer to the displayed advice and select from the options of "keep," "dispose," or "request purchase" for the item. Once the selection is complete, the device sends the selection information to the server. The server saves the selection information in a database and uses it as reference information for future use.

[1042] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The emotion engine recognizes the user's emotions from their facial expression and determines that they are "a little reluctant to throw things away." The server analyzes the image, identifies the coat, and, taking into account the user information and the emotion recognition results, generates advice such as "This coat doesn't suit your body type or trends, but you seem to have trouble getting rid of things, so you might want to reconsider." It also displays the market value, saying, "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved.

[1043] In this way, the system of the present invention provides support to help users declutter easily and efficiently, and by incorporating emotion recognition technology, it generates more personalized advice and reduces users' psychological resistance.

[1044] The processing flow will be explained below.

[1045] Step 1:

[1046] The user launches an application on a device such as a smartphone. The user enters account information (username and password) on the login screen and presses the "Login" button.

[1047] Step 2:

[1048] The terminal sends the entered login information to the server. The server then authenticates the login information and returns the authentication result to the terminal. If the authentication is successful, the user can proceed to the next step.

[1049] Step 3:

[1050] The terminal displays a screen after successful login, and allows the user to select their preferred AI character (avatar) from multiple options. The user makes a selection and presses the confirm button.

[1051] Step 4:

[1052] The device sends the selected character information to the server, which then saves the user's character settings.

[1053] Step 5:

[1054] The user uses the app's camera to take a photo of the item they are considering disposing of (e.g., an old coat). Once the photo is taken, the user presses the "Send" button.

[1055] Step 6:

[1056] The device sends the captured image data and user information (body type, age, and information about other items held by the user) to the server. At the same time, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state.

[1057] Step 7:

[1058] The emotion engine sends the recognized emotion data to the server, which then analyzes the received image data using computer vision technology to identify the target object.

[1059] Step 8:

[1060] The server generates advice for the identified object based on the user's information and emotion data. For example, it takes into account body type, age, and current fashion trends to generate advice such as "This coat doesn't suit your body type or the current trends," or emotion-based advice such as "You seem reluctant to throw things away. Would you reconsider?"

[1061] Step 9:

[1062] The server calculates the market value of the object, for example, generating a rating such as "This coat is worth 3,000 yen on the market."

[1063] Step 10:

[1064] The server transmits the generated advice and market value to the terminal, which displays this information to the user.

[1065] Step 11:

[1066] The user refers to the advice and selects one of the options: "Keep," "Dispose," or "Request a Buyback." Once the selection is complete, the user presses the "OK" button.

[1067] Step 12:

[1068] The device sends the user's selection information to the server, which stores the selection information in a database and uses it as reference for the next time.

[1069] Step 13:

[1070] When the user quits the app, the device closes the application.

[1071] The above are the specific steps in the programming process of the "Danshell" system, which incorporates an emotion engine.

[1072] Example 2

[1073] 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."

[1074] In today's consumer society, people frequently purchase goods, resulting in an increasing number of unnecessary items. However, disposing of these items is a psychological burden for many people. Specifically, the main challenges are a reluctance to throw away items and an inability to properly evaluate their value. In addition, there is a lack of systems that provide users with appropriate advice when choosing how to dispose of items.

[1075] 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.

[1076] In this invention, the server includes a means for a user to photograph an object via an electronic device, a means for transmitting the photographed image data to a data center, a means for the data center to analyze the image data and identify the object, a means for the data center to generate advice for the identified object based on user information and emotion recognition results, a means for displaying the generated advice to the user, a means for the user to select a method of disposing of the object based on the displayed advice, and a means for transmitting and storing the selected method of disposing of the object to the data center. This reduces the user's psychological resistance to disposing of the item and enables them to correctly evaluate the value of the item. Furthermore, appropriate and personalized advice can be provided to the user.

[1077] "User" refers to an individual or organization that uses this system to dispose of items.

[1078] "Electronic devices" refer to devices that have computer functions, such as smartphones, tablets, and personal computers, and are equipped with input devices such as cameras and microphones.

[1079] "Target item" refers to an item that the user is considering disposing of.

[1080] "Photographing" refers to the act of a user acquiring image data of an object using the camera function of an electronic device.

[1081] "Image data" refers to digital image information of a photographed object.

[1082] "Data Center" means a centralized facility containing servers and other computing resources where data is stored and processed.

[1083] "Analysis" refers to the process of recognizing and identifying objects in the image data received by the data center using computer vision technology, etc.

[1084] "User information" refers to information such as the user's profile data (age, gender, body type, etc.), past usage history, and item ownership status.

[1085] "Emotion recognition results" refers to data indicating the user's emotional state obtained by the emotion engine by analyzing the user's facial expressions, voice, and input actions.

[1086] "Advice" refers to advice provided by the Data Center to the User regarding the disposal method and market value of the object based on the analyzed data.

[1087] "Saving" refers to the act of recording information or data selected by the user in storage such as a database, making it available for subsequent access.

[1088] "Market value" refers to information that indicates the value of an object in the current market as a number or evaluation.

[1089] "Virtual Character" refers to an anthropomorphic digital avatar that a user selects within the system and that guides the user through the interaction.

[1090] The present invention is a system that allows users to efficiently dispose of items that are no longer needed in their daily lives. This system operates mainly based on the user's electronic devices, a data center, an emotion engine, and data exchanged among them.

[1091] First, the user launches the application on their electronic device (smartphone, tablet, etc.) and enters their account information on the login screen to authenticate. If authentication is successful, the user is taken to the application's home screen.

[1092] Next, the user taps the "Select Character" button on the home screen and chooses from a selection of virtual characters (avatars), which guide the user through subsequent interactions and provide a sense of familiarity.

[1093] The user identifies the item they want to throw away and takes a photo of it using the camera function of their electronic device. The image data is then sent from the electronic device to a data center.

[1094] At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize their emotional state. The emotion engine uses facial recognition and voice analysis software to generate the user's emotional data (e.g., "joy," "sadness," "resistance," etc.), which is also sent to the data center.

[1095] The data center uses computer vision technology (e.g., TensorFlow) to identify the item based on the received image data. It also references the user's body type, age, information about other items they own, and emotion recognition results. Based on this information, the data center uses a generative AI model to generate advice. For example, it can provide advice such as "This coat doesn't suit your body type, age, or current trends," or emotion-based advice such as "You seem reluctant to throw it away. Would you like to reconsider?" It also calculates the current market value and makes an economic assessment, such as "This coat could potentially be sold for 3,000 yen."

[1096] The generated advice is sent from the data center to the electronic device and displayed to the user. The user can refer to the displayed advice and select from the options of "keep," "dispose," or "request purchase" for the item. Once the selection is complete, the selection information is sent from the electronic device to the data center, which stores it in a database. The stored information will be used as reference information the next time the service is used.

[1097] As a concrete example, consider the case of considering disposing of an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The emotion engine recognizes the user's emotions from their facial expression and determines that they are "a little reluctant to throw things away." The data center analyzes the image, identifies the coat, and, taking into account the user information and the emotion recognition results, generates advice such as "This coat doesn't suit your body type or trends, but since you seem reluctant to get rid of it, you may want to reconsider." It also displays the market value, indicating that "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the data center and stored.

[1098] Example prompts for generative AI models

[1099] "A female user in her 30s is reluctant to throw things away and has taken a photo of an old coat. Please provide advice and market value."

[1100] The system of the present invention allows users to dispose of items easily and efficiently, and by incorporating emotion recognition technology, it provides more personalized advice and reduces users' psychological resistance.

[1101] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1102] Step 1:

[1103] The user launches the application on an electronic device (smartphone, tablet, etc.) and enters account information (ID, password) on the login screen to authenticate.

[1104] Input: User account information

[1105] Output: Authentication result (success / failure)

[1106] Specific behavior:

[1107] The user taps the application to launch it.

[1108] Enter your ID and password on the login screen.

[1109] When you press the "Login" button, data is sent to the authentication server and authentication is performed.

[1110] If authentication is successful, the home screen will be displayed.

[1111] Step 2:

[1112] The user taps the "Character Selection" button on the home screen and chooses their preferred virtual character (avatar) from multiple options.

[1113] Input: Selection information of virtual character

[1114] Output: Selected characters

[1115] Specific behavior:

[1116] The user taps the "Character Selection" button.

[1117] A number of virtual characters are displayed.

[1118] The user taps on the character of their choice to select it.

[1119] The selected character will be reflected in the application.

[1120] Step 3:

[1121] Users take a photo of the item they want to throw away using the camera function of their electronic device, and the captured image data is sent from the electronic device to a data center.

[1122] Input: Image data of the item

[1123] Output: Image data transmission results to the data center

[1124] Specific behavior:

[1125] The user taps the camera launch button within the app.

[1126] The device's camera is activated and the user points the camera at the item they want to throw away and takes a picture.

[1127] After the image is taken, the image data is automatically uploaded to a data center.

[1128] Step 4:

[1129] The emotion engine analyzes the user's facial expressions, voice, and input actions to recognize their emotional state, and sends this data to a data center.

[1130] Input: facial expression data, voice data, input action data

[1131] Output: Emotion recognition result

[1132] Specific behavior:

[1133] The device's camera and microphone capture the user's facial expressions and voice in real time.

[1134] The emotion engine performs facial expression recognition and voice analysis to generate emotion data.

[1135] Emotion data is sent to a data center.

[1136] Step 5:

[1137] The data center uses computer vision technology (e.g., TensorFlow) to identify the item based on the image data received.

[1138] Input: Image data of the item

[1139] Output: Item identification result

[1140] Specific behavior:

[1141] The image data is received at a data center.

[1142] Computer vision technology is used to analyze the characteristics of an item and identify it.

[1143] Information about the identified items is generated.

[1144] Step 6:

[1145] The data center analyzes user information (body type, age, etc.) together with emotion recognition results, and generates advice using a generative AI model.

[1146] Input: Item identification results, user information, emotion recognition results

[1147] Output: Generated advice

[1148] Specific behavior:

[1149] The item identification results, user information, and emotion recognition results are imported into the data center.

[1150] A generative AI model generates advice sentences based on this data.

[1151] The generated advice is stored in a data center.

[1152] Step 7:

[1153] The advice generated by the data center is sent to the electronic device and displayed to the user, who can choose from the options of "keep," "dispose," or "request a resale."

[1154] Input: Generated advice

[1155] Output: User's choice

[1156] Specific behavior:

[1157] The data center transmits the advice data to the electronic device.

[1158] An advice message is displayed on the electronic device, and selection buttons are arranged.

[1159] The user taps the desired option (e.g., "Dispose").

[1160] Step 8:

[1161] The selected information is sent from the electronic device to a data center, which stores it in a database.

[1162] Input: User selection information

[1163] Output: Selections saved in the database

[1164] Specific behavior:

[1165] The user's selection information is transmitted from the electronic device to the data center.

[1166] The data center stores the selection information in a database and checks the integrity of the data.

[1167] (Application example 2)

[1168] 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."

[1169] Current methods for decluttering and disposing of items often fail to take into account users' psychological resistance, resulting in ineffective and efficient disposal. Furthermore, it is difficult for users to understand the appropriate disposal method and economic value of items, resulting in wasted time and effort. Furthermore, personalized advice that takes into account the user's emotional state is not provided, resulting in low user satisfaction. To solve these issues, a system that also takes into account the user's emotional information is needed.

[1170] 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.

[1171] In this invention, the server includes means for generating advice for the identified object based on user information and emotion information, means for displaying the generated advice to the user, and means for the user to select a method of processing the object based on the displayed advice, thereby providing personalized advice that takes into account the user's emotional state and enabling efficient and effective processing of items.

[1172] "User information" refers to personal information about the user, such as age, sex, body type, and past item processing history.

[1173] "Emotion information" is data on the user's emotional state analyzed from their facial expressions, voice, and input actions.

[1174] A "virtual character" is a user-selectable digital impersonation that provides a sense of familiarity through interaction.

[1175] "Photographing means" refers to the way in which a user photographs an object using the device's camera.

[1176] The "means for generating advice" is a method for generating advice about an item based on image data, user information, and emotion information received by the server.

[1177] The "means for displaying advice" is a method for displaying the generated advice on the screen of the user device.

[1178] The "means for selecting a disposal method" is a method by which the user selects from the options of "save," "dispose," and "request purchase" for the item based on the generated advice.

[1179] "Means for calculating market value" refers to the method by which the server evaluates the current market value of an item and presents it to the user.

[1180] This invention is a system that allows users to efficiently dispose of unwanted items, and operates mainly based on the user's terminal, a server, an emotion engine, and the data exchanged between them. A specific example of the entire system will be described below.

[1181] System Overview

[1182] The user launches a dedicated application on their device and enters their account information on the login screen to perform authentication. If authentication is successful, the user can proceed to the next step. The user then selects their preferred virtual character from multiple options on the virtual character selection screen within the application. The selected character guides the user through subsequent interactions, providing a sense of familiarity.

[1183] To dispose of an item, the user takes a picture of the item using the device's camera. This image data is sent from the device to the server. At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize the user's emotions. The emotion engine uses facial recognition software (e.g., EmotionRecognizer) to detect the user's emotional state, and this data is also sent to the server.

[1184] The server analyzes the received image data and identifies the item using computer vision technology (e.g., OpenCV). It also uses user information (e.g., age, gender, body type, past item handling history, etc.) and emotional information to generate more accurate advice. The generated advice is specific, such as "This jacket doesn't seem to fit in with current fashion" or "You could potentially sell it for 3,000 yen."

[1185] The generated advice is sent from the server to the device and displayed to the user on the device. Based on the displayed advice, the user selects from the options of "save," "dispose," or "request purchase." Once the selection is complete, the information is sent from the device to the server and saved in a database. The saved data will be used as reference information the next time the service is used.

[1186] Specific examples

[1187] For example, if a male user in his 40s wants to get rid of an old guitar, he can use this system to effectively handle the situation.

[1188] The user launches the Smart Danshari app, enters their account information and logs in.

[1189] A male character is selected from among a plurality of virtual characters.

[1190] By taking a photo of an old guitar, the emotion engine analyzes the user's facial expression and recognizes "nostalgia."

[1191] The server analyzes the image and generates advice such as, "This guitar is a little out of proportion to your age, but if you sell it, you could potentially sell it for 5,000 yen."

[1192] When the user selects "purchase request," the information is sent to the server and saved.

[1193] In this way, the invention can also take into account the user's emotional information, allowing for more personalized and efficient handling of items.

[1194] Prompt Sentence Examples

[1195] "Develop an application that allows users to take photos of items and provides advice on how to dispose of them based on the results of analysis by an emotion engine. The user selects a virtual character, sends the photo of the item and their own emotion data to the server, and then selects "keep," "dispose," or "request purchase" based on the advice generated."

[1196] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1197] Step 1:

[1198] A user starts a device and opens an application. Next, the user enters their account information on the login screen and authenticates. At this point, the input is the user's account information, and the output is the result of authentication success or failure. If authentication is successful, the user proceeds to the next step.

[1199] Step 2:

[1200] The user selects a preferred virtual character from multiple virtual characters on a virtual character selection screen within the application. The input is the virtual character selection information, and the output is the display of the selected character to the user.

[1201] Step 3:

[1202] The user takes a photo of the item they want to dispose of using the device's camera. At this time, the input is the image of the item, and the output is the image data stored in the device.

[1203] Step 4:

[1204] The emotion engine on the device recognizes the user's emotions. It analyzes the user's facial expressions, voice, and input actions, and outputs the user's emotional state as data. The input is information such as the user's facial expressions and voice, and the output is emotional information.

[1205] Step 5:

[1206] The device sends the captured image data and emotion information to the server. The input is the image data and emotion information, and the output is the data received by the server.

[1207] Step 6:

[1208] The server analyzes the image data and identifies the item using computer vision technology. The input is the transmitted image data, and the output is information about the identified object. OpenCV and other computer vision technologies are used.

[1209] Step 7:

[1210] The server generates advice for the identified object based on the user information and emotion information. The input is the item information, user information, and emotion information, and the output is the generated advice. For example, this advice might be, "This jacket doesn't seem to fit in with modern fashion" or "You could potentially sell it for 3,000 yen."

[1211] Step 8:

[1212] The server sends the generated advice to the terminal, which then displays the advice to the user. The input is the advice sent from the server, and the output is the advice displayed on the application.

[1213] Step 9:

[1214] The user selects from the options of "save," "dispose," or "request a resale" based on the displayed advice. The input is the user's selection information, and the output is the selected option.

[1215] Step 10:

[1216] The selection information is sent from the terminal to the server, which then stores it in a database. The input is the user's selection information, and the output is the processing history stored in the database. The stored data is also used as reference information for future use.

[1217] 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.

[1218] 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.

[1219] 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.

[1220] [Fourth embodiment]

[1221] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1222] 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.

[1223] 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).

[1224] 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.

[1225] 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.

[1226] 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).

[1227] 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.

[1228] 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.

[1229] 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.

[1230] 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.

[1231] 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.

[1232] 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.

[1233] 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."

[1234] The present invention provides a system that allows users to efficiently dispose of unnecessary items in their daily lives. This system operates mainly based on the user's device, a server, and data exchanged between them.

[1235] First, the user launches the application on their device, enters their account information on the login screen, and authenticates, at which point they are granted access to the system.

[1236] Next, the user selects from a selection of virtual characters (avatars) on a character selection screen within the application. The selected character guides the user through subsequent interactions and provides a sense of familiarity.

[1237] To identify an item a user wants to throw away, they take a photo of the item using the device's camera. The captured image data is then sent from the device to a server. The server then analyzes the image data and uses computer vision technology to identify the item. Information about the user's body type, age, and other items they own is also sent to the server.

[1238] The server generates advice about the item based on the results of image data analysis and user information. For example, it provides specific advice such as, "This coat does not suit your body type, age, or current trends." It also calculates the current market value and provides an economic assessment, such as, "This coat could potentially be sold for 3,000 yen."

[1239] The generated advice is sent from the server to the device and displayed to the user, who can then choose to keep, dispose of, or request a resale of the item.

[1240] Once the selection is complete, the device sends the selection information to the server, which stores it in a database and uses it as reference information for future use. This allows users to declutter efficiently and systematically.

[1241] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The server analyzes the image and identifies the coat. After that, taking into account the user's information, the server generates advice such as "This coat does not fit your body type and is out of fashion, so we recommend that you dispose of or sell it," and presents this to the user. It also displays the market value, such as "This coat may be able to be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved.

[1242] In this way, the system of the present invention provides support for users to declutter easily and efficiently.

[1243] The processing flow will be explained below.

[1244] Step 1:

[1245] The user launches the "Danshell" app on a device such as a smartphone. The user enters their account information (username and password) on the login screen and presses the "Login" button.

[1246] Step 2:

[1247] The terminal sends the entered login information to the server. The server then authenticates the login information and returns the authentication result to the terminal. If the authentication is successful, the user can proceed to the next step.

[1248] Step 3:

[1249] The terminal displays a screen after successful login, and allows the user to select their preferred AI character (avatar) from multiple options. The user makes a selection and presses the confirm button.

[1250] Step 4:

[1251] The device sends the selected character information to the server, which then saves the user's character settings.

[1252] Step 5:

[1253] The user uses the app's camera to take a photo of the item they are considering disposing of (e.g., an old coat). Once the photo is taken, the user presses the "Send" button.

[1254] Step 6:

[1255] The device sends the captured image data and user information (body type, age, and information about other items held) to the server.

[1256] Step 7:

[1257] The server analyzes the received image data using computer vision technology to identify the object. For example, it may determine that the object is an "old coat" through image analysis.

[1258] Step 8:

[1259] The server generates advice for the identified object based on the user information. For example, it generates advice such as "This coat does not suit your body type or current fashion" by taking into account body type, age, and current fashion.

[1260] Step 9:

[1261] The server calculates the market value of the object, for example, generating a rating such as "This coat is worth 3,000 yen on the market."

[1262] Step 10:

[1263] The generated advice and market value are sent from the server to the terminal, which displays this information to the user.

[1264] Step 11:

[1265] The user refers to the advice and selects one of the options: "Keep," "Dispose," or "Request a Buyback." Once the selection is complete, the user presses the "OK" button.

[1266] Step 12:

[1267] The device sends the user's selection information to the server, which stores the selection information in a database and uses it as reference for the next time.

[1268] Step 13:

[1269] When the user quits the app, the device closes the application.

[1270] The above are the specific steps of the "Danshell" program processing.

[1271] Example 1

[1272] 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."

[1273] In modern society, many users are seeking an efficient way to dispose of items that are no longer needed in their daily lives. However, it is often difficult to decide whether to throw away, store, or sell these items, which results in delays in decluttering. There is also a lack of professional advice on these items and ways to understand their market value. Furthermore, tools and systems are often difficult to use, preventing users from actively using them. Therefore, a system is needed that allows users to easily dispose of unwanted items and provides appropriate advice and value assessments.

[1274] 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.

[1275] In this invention, the server includes means for a user to photograph an object via an information device, means for transmitting the photographed image data to the server, means for the server to analyze the image data and identify the object, means for generating advice for the identified object based on user information, means for displaying the generated advice to the user, means for the user to select a method of disposing of the object based on the displayed advice, means for transmitting the selected method of disposing of the object to the server and saving it, means for the user to select from a plurality of virtual characters, means for the virtual characters to guide the user through dialogue, means for using a camera function, and means for the server to simultaneously process related information. This allows users to easily and effortlessly photograph and analyze unwanted items, determine a method of disposing of them based on appropriate advice, and then perform optimal disposal after understanding their market value.

[1276] "User" refers to an individual who uses the system to dispose of unwanted items.

[1277] "Information devices" refers to digital devices such as smartphones, tablets, and personal computers.

[1278] The term "target item" refers to an item that the user has determined to be unnecessary.

[1279] "Means for photographing" refers to a method for obtaining an image of an object using the camera function built into an information device.

[1280] "Image data" refers to digital image information obtained when photographing an object.

[1281] "Server" refers to a central processing unit that analyzes image data, identifies objects, and generates advice.

[1282] "Means for analyzing" refers to the techniques and algorithms used to process image data and extract features of interest.

[1283] "Means for identifying" refers to a technique for identifying what an object is based on analyzed characteristics.

[1284] "User Information" refers to data about a user's characteristics and other possessions.

[1285] The "means for generating advice" refers to a function for proposing an appropriate processing method to the user based on the object identification result and user information.

[1286] The "display means" refers to a function for visually presenting the generated advice on the user's information device.

[1287] The "means for selecting a disposal method" refers to a method by which a user can select a disposal method, such as preserving, disposing of, or selling an object, based on the advice provided.

[1288] "Means for saving" refers to the technology for recording the processing method selected by the user within the system and reusing it as needed.

[1289] "Virtual character," also known as an avatar, refers to a digital character that interacts with the user and guides them through the system.

[1290] "Dialogue-based guidance" refers to a function that allows a virtual character to provide operating procedures and advice through communication with the user.

[1291] "Means for simultaneously processing related information" refers to a technique for processing image data together with user information and other necessary data.

[1292] "Market value" refers to an indicator used to assess the price at which an object may be traded in the market.

[1293] The system of the present invention supports users in efficiently disposing of unnecessary items in their daily lives. This system operates mainly based on the user's information device, a server, and the data exchanged between them.

[1294] First, the user installs and launches a dedicated application on an information device such as a smartphone or tablet. The user then enters their account information on the login screen and performs authentication. This authentication uses an arbitrary user ID and password, which the server verifies against a database.

[1295] Once a user has successfully logged in, they proceed to a character selection screen within the application and choose their preferred virtual character (avatar) from multiple options. Once character selection is complete, the selected virtual character will guide the user through subsequent interactions, ensuring smooth use of the system.

[1296] The user takes a photo of the item they want to throw away using the camera function of their information device. The camera function is implemented using the built-in camera of a smartphone or tablet. At this time, the captured image data is sent from the information device to a server. The server analyzes the received image data and uses computer vision technologies such as OpenCV and TensorFlow to identify the item.

[1297] The server processes the identified item, along with information about the user's body type, age, and other items they own. This starts the process of generating advice about the item. For example, it might provide specific advice like, "This coat doesn't suit your body type, age, or current trends." The server also calculates its current market value and provides an economic assessment, such as, "This coat could potentially be sold for 3,000 yen."

[1298] The generated advice is sent from the server to the user's information device and displayed to the user. The user then refers to the displayed advice and selects from the options of "save," "dispose," or "request a resale." Once the selection is complete, the information is sent from the information device to the server, which then stores it in a database. This data is used as reference information for future use.

[1299] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. On the character selection screen, they select a female character in their 30s and then take a photo of an old coat. This image data is sent to the server, which analyzes the image and identifies the coat. The server then takes into account the user's information and generates advice such as, "This coat doesn't fit your body type and is out of fashion, so we recommend you dispose of or sell it," and presents this to the user. It also displays the market value, showing that "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved in a database.

[1300] Example prompt sentence:

[1301] "Please explain the steps to use the application to help users efficiently dispose of unwanted items."

[1302] "Please show us the specific process flow of a system for efficiently decluttering."

[1303] "Please explain in detail the process that will allow users to easily declutter their old coats."

[1304] The above is a specific embodiment for carrying out the present invention.

[1305] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1306] Step 1:

[1307] Launching the application and logging in

[1308] A user starts an application on an information device such as a smartphone or tablet. Next, the user enters their account information (user ID and password) on the login screen. Based on this input, the server compares it with the account information stored in the database and authenticates the user. If authentication is successful, a "Login successful" message is output to the user.

[1309] Input: User ID, Password

[1310] Data processing: database matching, fair comparison

[1311] Output: Authentication result message (success / failure)

[1312] Step 2:

[1313] Character Selection

[1314] After logging in, the user goes to the character selection screen within the application and chooses their favorite virtual character from several options. Once the selection is complete, the device sends the selected character information to the server, which records it and outputs instructions for proceeding to the next step.

[1315] Input: User's character selection

[1316] Data processing: Recording character ID

[1317] Output: Character selection confirmation message

[1318] Step 3:

[1319] Photographing items and sending data

[1320] Users use the camera function of their smartphone or tablet to take a photo of the item they want to throw away. The captured image data is sent from the device to the server. The server stores the received image data and outputs a notification to proceed to the next analysis step.

[1321] Input: Captured image data

[1322] Data processing: Sending and storing image data

[1323] Output: A confirmation message that the image was received

[1324] Step 4:

[1325] Analysis of product images

[1326] The server uses computer vision technologies such as OpenCV and TensorFlow to analyze the received image data. The analysis extracts features of the item and identifies it based on those features. The analysis results are then processed along with information about the user's body type, age, and other items they own.

[1327] Input: Image data, user information

[1328] Data processing: image analysis, feature extraction, item identification

[1329] Output: Analysis results (item identification)

[1330] Step 5:

[1331] Generating Advice

[1332] The server generates advice based on the image analysis results and user information. For example, it provides specific advice such as, "This coat does not suit your body type, age, or current trends." It also calculates the current market value and makes an assessment such as, "This coat could potentially be sold for 3,000 yen."

[1333] Input: Analysis results, user information

[1334] Data processing: advice generation, value calculation

[1335] Output: Advice content, market value

[1336] Step 6:

[1337] Viewing advice and selecting options

[1338] The server sends the generated advice to the terminal, which then displays it to the user, who can then select from the options of "save," "dispose," or "request a buyback."

[1339] Input: Advice content, market value

[1340] Data processing: Sending advice, displaying options

[1341] Output: User selection

[1342] Step 7:

[1343] Sending and storing your selections

[1344] The terminal sends the option information selected by the user to the server, which stores this information in a database. This data will be used as reference information for future use.

[1345] Input: User selection information

[1346] Data processing: sending and storing selected information

[1347] Output: Database update confirmation message

[1348] The above is a specific flow of processing in the system of the present invention.

[1349] (Application example 1)

[1350] 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."

[1351] There is a need to provide a means for users to efficiently dispose of items that are no longer needed in their daily lives. In particular, there is a need for a system that can identify items, evaluate their economic value, suggest disposal methods, and even link with online marketplace sites to enable smoother disposal or sale of items. Currently, many users find it time-consuming and laborious to dispose of items, and a system that can solve this problem is desirable.

[1352] 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.

[1353] In this invention, the server includes means for a user to photograph an object via a device, means for transmitting the photographed image data to the server, means for the server to analyze the image data and identify the object, means for the server to generate advice for the identified object based on user information, means for displaying the generated advice to the user, means for the user to select a method of disposing of the object based on the displayed advice, means for transmitting and storing the selected method of disposing of the object to the server, and means for linking to an online marketplace site and making a buyback request, thereby enabling users to efficiently dispose of unwanted items and maximize their economic value.

[1354] "User" refers to any individual or legal entity that uses the System.

[1355] "Device" refers to the hardware device, primarily a smartphone or tablet, that a user uses to interface with the system.

[1356] "Object" refers to an item that a user wishes to dispose of, save, or sell.

[1357] "Means for photographing" refers to the function of acquiring an image of an object using the camera function built into the device.

[1358] "Means for transmitting image data to a server" refers to a function for transmitting captured image data from a device via a network to a remote server.

[1359] "Server" refers to the back-end computer that processes and stores data at the heart of the system.

[1360] "Means for analyzing image data and identifying objects" refers to the function of the server or its related systems to identify the type and characteristics of objects using image processing technology.

[1361] "User information" refers to data such as a user's personal information, preferences, body type, age, and past behavioral history.

[1362] "Means for generating advice" refers to the function of the server to make specific suggestions and evaluations for the target object based on the analysis results and user information.

[1363] "Means for displaying advice to the user" refers to a function for displaying advice generated by the server on the screen of the user's device.

[1364] "Means for selecting a disposal method" refers to a function that allows a user to choose whether to preserve, dispose of, or sell an object by referring to the displayed advice.

[1365] The "means for transmitting the processing method to the server and storing it" refers to a function for transmitting the processing method selected by the user to the server and storing it in the database.

[1366] "Online Marketplace Site" means a web platform through which users can buy and sell goods.

[1367] The "means for making a purchase request" refers to a function for transmitting a purchase request for the selected object to the online market site.

[1368] The present invention provides a system for efficiently disposing of items that users no longer need in their daily lives. Specifically, the system operates based on the user's device, a server, and data exchanged between them.

[1369] System configuration

[1370] Users install an application on their devices, such as smartphones or tablets, which uses the camera function to take pictures of unwanted items and send the image data to a server.

[1371] 1. User Authentication

[1372] The user enters their account information on the login screen and sends it to the server, where it is authenticated, and if the authentication is successful, the user is allowed to access the system.

[1373] 2. Avatar selection

[1374] After authentication, the user selects from multiple virtual characters (avatars) within the application, and the selected avatar guides the user through subsequent operations.

[1375] 3. Photographing and analyzing the object

[1376] Users take a photo of the item they want to dispose of using their device's camera. The image data is sent to a server, which then analyzes the image. The technology used is based on computer vision technology.

[1377] 4. Generating and displaying advice

[1378] The server generates advice for the item based on the image analysis results and user information. This advice includes suggestions for preserving, disposing of, or selling the item. The advice is sent to the user's device and displayed on the screen.

[1379] 5. Calculating market value

[1380] The server also calculates the market value of the object and displays it to the user.

[1381] 6. Selection of processing method

[1382] The user can refer to the displayed advice and choose how to dispose of the item. There are three options: "Keep," "Dispose," or "Request a purchase."

[1383] 7. Submitting a purchase request

[1384] If the user selects "purchase request," the system will link to an online marketplace site and make a purchase request.

[1385] 8. Data Retention

[1386] The processing method selected by the user is stored in a database and used as reference information the next time the system is used.

[1387] Hardware and software used

[1388] The hardware used is a smartphone, tablet, and server, and the software used is Python, OpenCV, the Requests library, and PIL (Python Imaging Library).

[1389] 1. User Authentication

[1390] Use the Python Requests library to send the user's credentials to the server for authentication.

[1391] 2. Taking photos and sending images

[1392] OpenCV is used to control the device's camera function and take images, which are then sent to the server using the Requests library.

[1393] 3. Image analysis and advice generation

[1394] On the server, image data is analyzed using computer vision and generative AI models, and appropriate advice is generated based on the user information and analysis results.

[1395] 4. Advice and Market Value Calculation

[1396] Advice generated using PIL is displayed as an image on the user's device, and the generative AI model is also used to calculate market value.

[1397] 5. Selecting a disposal method and requesting a purchase

[1398] The user's selection of the treatment method is transmitted to the server and, if necessary, forwarded to the online marketplace site.

[1399] Examples of concrete examples and prompts

[1400] Examples:

[1401] For example, consider a scenario in which a user wants to get rid of an old coat. The user launches the application on their device and logs in. They select a female character (avatar) in her 30s and takes a photo of the old coat with the device's camera. The server analyzes the image and, taking into account the user's body type, age, and current trends, suggests advice such as "This coat doesn't suit your body type and is out of fashion, so we recommend you get rid of or sell it," along with a market value such as "This coat may sell for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and stored in a database.

[1402] Example prompt sentence:

[1403] "Write a Python program that authenticates users, photographs and identifies unwanted items, provides advice and economic evaluation, and submits the final disposal selection to the server."

[1404] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1405] Step 1:

[1406] A user starts an application using a device such as a smartphone or tablet. The user enters their account information (username, password) on the login screen. This information is sent from the device to the server, which then performs authentication. The server compares the entered information with its database, and if it matches, the authentication is successful. The user is then shown a message indicating successful login, and the process moves to the next step.

[1407] Input: Username, Password

[1408] Output: Authentication result (success / failure)

[1409] Step 2:

[1410] The user selects their preferred avatar from multiple virtual characters on the avatar selection screen. The selected avatar information is stored on the device and used for subsequent interactions. The server retains session information including the selected avatar information and reflects it in the next step.

[1411] Input: User avatar selection

[1412] Output: Add avatar information to session information

[1413] Step 3:

[1414] The user uses the device's camera to take a picture of the item they want to dispose of. The captured image data is sent from the device to the server, which uses computer vision technology to analyze the received image data and identify the object.

[1415] Input: Photographed image data

[1416] Output: Object identification information

[1417] Step 4:

[1418] The server generates advice for the identified object. Using a generative AI model, it creates specific advice based on user information (body type, age, fashion, etc.) and the results of image analysis. The generated advice is then sent to the device.

[1419] Input: Object identification information, user information

[1420] Output: Specific advice

[1421] Step 5:

[1422] The terminal receives the advice sent from the server and displays it to the user. In addition, the server simultaneously calculates the market value of the object and displays it to the user together with the advice.

[1423] Input: Specific advice, market value

[1424] Output: Advice and market value displayed on the terminal

[1425] Step 6:

[1426] The user refers to the advice and selects how to dispose of the object (preservation, disposal, purchase request). The selected method is sent from the terminal to the server and stored in the database.

[1427] Input: User-selected processing method

[1428] Output: Data on the selected processing method

[1429] Step 7:

[1430] If the user selects a buyback request, the system connects to the online marketplace site and sends the buyback request information, which the server then processes.

[1431] Input: Purchase request information

[1432] Output: Request information sent to online marketplace site

[1433] The above is the specific processing flow of the program for the system that realizes the application example. At each step, appropriate data processing and calculation are performed based on the input data, and the output for the next step is generated.

[1434] 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.

[1435] The present invention is a system that allows users to efficiently dispose of unnecessary items in their daily lives. This system operates mainly based on the user's device, a server, an emotion engine, and data exchanged among them.

[1436] First, a user launches an application on their device. They enter their account information on the login screen and authenticate. If authentication is successful, the user can proceed to the next step. Next, the user selects their preferred virtual character (avatar) from multiple options on the character selection screen within the application. The selected character guides the user through subsequent interactions, providing a sense of familiarity.

[1437] To identify the item the user wants to throw away, the user takes a photo of the item using the device's camera function. This image data is sent from the device to the server. At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize the user's emotions. The emotion engine detects the user's emotional state and also sends this data to the server.

[1438] The server analyzes the received image data and uses computer vision technology to identify the item. In addition, information about the user's body type, age, and other items they are holding, as well as emotion recognition results from the emotion engine, are also sent to the server.

[1439] The server generates advice about the item based on the results of image data analysis, user information, and emotion recognition. For example, it can provide specific advice such as "This coat doesn't suit your body type, age, or current trends," or emotion-based advice such as "You seem reluctant to throw away the item. Would you like to reconsider?" It also calculates the current market value and provides an economic assessment, such as "This coat could be sold for 3,000 yen."

[1440] The generated advice is sent from the server to the device and displayed to the user on the device. The user can refer to the displayed advice and select from the options of "keep," "dispose," or "request purchase" for the item. Once the selection is complete, the device sends the selection information to the server. The server saves the selection information in a database and uses it as reference information for future use.

[1441] As a concrete example, consider decluttering an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The emotion engine recognizes the user's emotions from their facial expression and determines that they are "a little reluctant to throw things away." The server analyzes the image, identifies the coat, and, taking into account the user information and the emotion recognition results, generates advice such as "This coat doesn't suit your body type or trends, but you seem to have trouble getting rid of things, so you might want to reconsider." It also displays the market value, saying, "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the server and saved.

[1442] In this way, the system of the present invention provides support to help users declutter easily and efficiently, and by incorporating emotion recognition technology, it generates more personalized advice and reduces users' psychological resistance.

[1443] The processing flow will be explained below.

[1444] Step 1:

[1445] The user launches an application on a device such as a smartphone. The user enters account information (username and password) on the login screen and presses the "Login" button.

[1446] Step 2:

[1447] The terminal sends the entered login information to the server. The server then authenticates the login information and returns the authentication result to the terminal. If the authentication is successful, the user can proceed to the next step.

[1448] Step 3:

[1449] The terminal displays a screen after successful login, and allows the user to select their preferred AI character (avatar) from multiple options. The user makes a selection and presses the confirm button.

[1450] Step 4:

[1451] The device sends the selected character information to the server, which then saves the user's character settings.

[1452] Step 5:

[1453] The user uses the app's camera to take a photo of the item they are considering disposing of (e.g., an old coat). Once the photo is taken, the user presses the "Send" button.

[1454] Step 6:

[1455] The device sends the captured image data and user information (body type, age, and information about other items held by the user) to the server. At the same time, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state.

[1456] Step 7:

[1457] The emotion engine sends the recognized emotion data to the server, which then analyzes the received image data using computer vision technology to identify the target object.

[1458] Step 8:

[1459] The server generates advice for the identified object based on the user's information and emotion data. For example, it takes into account body type, age, and current fashion trends to generate advice such as "This coat doesn't suit your body type or the current trends," or emotion-based advice such as "You seem reluctant to throw things away. Would you reconsider?"

[1460] Step 9:

[1461] The server calculates the market value of the object, for example, generating a rating such as "This coat is worth 3,000 yen on the market."

[1462] Step 10:

[1463] The server transmits the generated advice and market value to the terminal, which displays this information to the user.

[1464] Step 11:

[1465] The user refers to the advice and selects one of the options: "Keep," "Dispose," or "Request a Buyback." Once the selection is complete, the user presses the "OK" button.

[1466] Step 12:

[1467] The device sends the user's selection information to the server, which stores the selection information in a database and uses it as reference for the next time.

[1468] Step 13:

[1469] When the user quits the app, the device closes the application.

[1470] The above are the specific steps in the programming process of the "Danshell" system, which incorporates an emotion engine.

[1471] Example 2

[1472] 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."

[1473] In today's consumer society, people frequently purchase goods, resulting in an increasing number of unnecessary items. However, disposing of these items is a psychological burden for many people. Specifically, the main challenges are a reluctance to throw away items and an inability to properly evaluate their value. In addition, there is a lack of systems that provide users with appropriate advice when choosing how to dispose of items.

[1474] 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.

[1475] In this invention, the server includes a means for a user to photograph an object via an electronic device, a means for transmitting the photographed image data to a data center, a means for the data center to analyze the image data and identify the object, a means for the data center to generate advice for the identified object based on user information and emotion recognition results, a means for displaying the generated advice to the user, a means for the user to select a method of disposing of the object based on the displayed advice, and a means for transmitting and storing the selected method of disposing of the object to the data center. This reduces the user's psychological resistance to disposing of the item and enables them to correctly evaluate the value of the item. Furthermore, appropriate and personalized advice can be provided to the user.

[1476] "User" refers to an individual or organization that uses this system to dispose of items.

[1477] "Electronic devices" refer to devices that have computer functions, such as smartphones, tablets, and personal computers, and are equipped with input devices such as cameras and microphones.

[1478] "Target item" refers to an item that the user is considering disposing of.

[1479] "Photographing" refers to the act of a user acquiring image data of an object using the camera function of an electronic device.

[1480] "Image data" refers to digital image information of a photographed object.

[1481] "Data Center" means a centralized facility containing servers and other computing resources where data is stored and processed.

[1482] "Analysis" refers to the process of recognizing and identifying objects in the image data received by the data center using computer vision technology, etc.

[1483] "User information" refers to information such as the user's profile data (age, gender, body type, etc.), past usage history, and item ownership status.

[1484] "Emotion recognition results" refers to data indicating the user's emotional state obtained by the emotion engine by analyzing the user's facial expressions, voice, and input actions.

[1485] "Advice" refers to advice provided by the Data Center to the User regarding the disposal method and market value of the object based on the analyzed data.

[1486] "Saving" refers to the act of recording information or data selected by the user in storage such as a database, making it available for subsequent access.

[1487] "Market value" refers to information that indicates the value of an object in the current market as a number or evaluation.

[1488] "Virtual Character" refers to an anthropomorphic digital avatar that a user selects within the system and that guides the user through the interaction.

[1489] The present invention is a system that allows users to efficiently dispose of items that are no longer needed in their daily lives. This system operates mainly based on the user's electronic devices, a data center, an emotion engine, and data exchanged among them.

[1490] First, the user launches the application on their electronic device (smartphone, tablet, etc.) and enters their account information on the login screen to authenticate. If authentication is successful, the user is taken to the application's home screen.

[1491] Next, the user taps the "Select Character" button on the home screen and chooses from a selection of virtual characters (avatars), which guide the user through subsequent interactions and provide a sense of familiarity.

[1492] The user identifies the item they want to throw away and takes a photo of it using the camera function of their electronic device. The image data is then sent from the electronic device to a data center.

[1493] At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize their emotional state. The emotion engine uses facial recognition and voice analysis software to generate the user's emotional data (e.g., "joy," "sadness," "resistance," etc.), which is also sent to the data center.

[1494] The data center uses computer vision technology (e.g., TensorFlow) to identify the item based on the received image data. It also references the user's body type, age, information about other items they own, and emotion recognition results. Based on this information, the data center uses a generative AI model to generate advice. For example, it can provide advice such as "This coat doesn't suit your body type, age, or current trends," or emotion-based advice such as "You seem reluctant to throw it away. Would you like to reconsider?" It also calculates the current market value and makes an economic assessment, such as "This coat could potentially be sold for 3,000 yen."

[1495] The generated advice is sent from the data center to the electronic device and displayed to the user. The user can refer to the displayed advice and select from the options of "keep," "dispose," or "request purchase" for the item. Once the selection is complete, the selection information is sent from the electronic device to the data center, which stores it in a database. The stored information will be used as reference information the next time the service is used.

[1496] As a concrete example, consider the case of considering disposing of an old coat. The user launches the app and logs in. They select a female character in her 30s and take a photo of the old coat. The emotion engine recognizes the user's emotions from their facial expression and determines that they are "a little reluctant to throw things away." The data center analyzes the image, identifies the coat, and, taking into account the user information and the emotion recognition results, generates advice such as "This coat doesn't suit your body type or trends, but since you seem reluctant to get rid of it, you may want to reconsider." It also displays the market value, indicating that "This coat can potentially be sold for 3,000 yen." When the user selects "Request a purchase," the information is sent to the data center and stored.

[1497] Example prompts for generative AI models

[1498] "A female user in her 30s is reluctant to throw things away and has taken a photo of an old coat. Please provide advice and market value."

[1499] The system of the present invention allows users to dispose of items easily and efficiently, and by incorporating emotion recognition technology, it provides more personalized advice and reduces users' psychological resistance.

[1500] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1501] Step 1:

[1502] The user launches the application on an electronic device (smartphone, tablet, etc.) and enters account information (ID, password) on the login screen to authenticate.

[1503] Input: User account information

[1504] Output: Authentication result (success / failure)

[1505] Specific behavior:

[1506] The user taps the application to launch it.

[1507] Enter your ID and password on the login screen.

[1508] When you press the "Login" button, data is sent to the authentication server and authentication is performed.

[1509] If authentication is successful, the home screen will be displayed.

[1510] Step 2:

[1511] The user taps the "Character Selection" button on the home screen and chooses their preferred virtual character (avatar) from multiple options.

[1512] Input: Selection information of virtual character

[1513] Output: Selected characters

[1514] Specific behavior:

[1515] The user taps the "Character Selection" button.

[1516] A number of virtual characters are displayed.

[1517] The user taps on the character of their choice to select it.

[1518] The selected character will be reflected in the application.

[1519] Step 3:

[1520] Users take a photo of the item they want to throw away using the camera function of their electronic device, and the captured image data is sent from the electronic device to a data center.

[1521] Input: Image data of the item

[1522] Output: Image data transmission results to the data center

[1523] Specific behavior:

[1524] The user taps the camera launch button within the app.

[1525] The device's camera is activated and the user points the camera at the item they want to throw away and takes a picture.

[1526] After the image is taken, the image data is automatically uploaded to a data center.

[1527] Step 4:

[1528] The emotion engine analyzes the user's facial expressions, voice, and input actions to recognize their emotional state, and sends this data to a data center.

[1529] Input: facial expression data, voice data, input action data

[1530] Output: Emotion recognition result

[1531] Specific behavior:

[1532] The device's camera and microphone capture the user's facial expressions and voice in real time.

[1533] The emotion engine performs facial expression recognition and voice analysis to generate emotion data.

[1534] Emotion data is sent to a data center.

[1535] Step 5:

[1536] The data center uses computer vision technology (e.g., TensorFlow) to identify the item based on the image data received.

[1537] Input: Image data of the item

[1538] Output: Item identification result

[1539] Specific behavior:

[1540] The image data is received at a data center.

[1541] Computer vision technology is used to analyze the characteristics of an item and identify it.

[1542] Information about the identified items is generated.

[1543] Step 6:

[1544] The data center analyzes user information (body type, age, etc.) together with emotion recognition results, and generates advice using a generative AI model.

[1545] Input: Item identification results, user information, emotion recognition results

[1546] Output: Generated advice

[1547] Specific behavior:

[1548] The item identification results, user information, and emotion recognition results are imported into the data center.

[1549] A generative AI model generates advice sentences based on this data.

[1550] The generated advice is stored in a data center.

[1551] Step 7:

[1552] The advice generated by the data center is sent to the electronic device and displayed to the user, who can choose from the options of "keep," "dispose," or "request a resale."

[1553] Input: Generated advice

[1554] Output: User's choice

[1555] Specific behavior:

[1556] The data center transmits the advice data to the electronic device.

[1557] An advice message is displayed on the electronic device, and selection buttons are arranged.

[1558] The user taps the desired option (e.g., "Dispose").

[1559] Step 8:

[1560] The selected information is sent from the electronic device to a data center, which stores it in a database.

[1561] Input: User selection information

[1562] Output: Selections saved in the database

[1563] Specific behavior:

[1564] The user's selection information is transmitted from the electronic device to the data center.

[1565] The data center stores the selection information in a database and checks the integrity of the data.

[1566] (Application example 2)

[1567] 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."

[1568] Current methods for decluttering and disposing of items often fail to take into account users' psychological resistance, resulting in ineffective and efficient disposal. Furthermore, it is difficult for users to understand the appropriate disposal method and economic value of items, resulting in wasted time and effort. Furthermore, personalized advice that takes into account the user's emotional state is not provided, resulting in low user satisfaction. To solve these issues, a system that also takes into account the user's emotional information is needed.

[1569] 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.

[1570] In this invention, the server includes means for generating advice for the identified object based on user information and emotion information, means for displaying the generated advice to the user, and means for the user to select a method of processing the object based on the displayed advice, thereby providing personalized advice that takes into account the user's emotional state and enabling efficient and effective processing of items.

[1571] "User information" refers to personal information about the user, such as age, sex, body type, and past item processing history.

[1572] "Emotion information" is data on the user's emotional state analyzed from their facial expressions, voice, and input actions.

[1573] A "virtual character" is a user-selectable digital impersonation that provides a sense of familiarity through interaction.

[1574] "Photographing means" refers to the way in which a user photographs an object using the device's camera.

[1575] The "means for generating advice" is a method for generating advice about an item based on image data, user information, and emotion information received by the server.

[1576] The "means for displaying advice" is a method for displaying the generated advice on the screen of the user device.

[1577] The "means for selecting a disposal method" is a method by which the user selects from the options of "save," "dispose," and "request purchase" for the item based on the generated advice.

[1578] "Means for calculating market value" refers to the method by which the server evaluates the current market value of an item and presents it to the user.

[1579] This invention is a system that allows users to efficiently dispose of unwanted items, and operates mainly based on the user's terminal, a server, an emotion engine, and the data exchanged between them. A specific example of the entire system will be described below.

[1580] System Overview

[1581] The user launches a dedicated application on their device and enters their account information on the login screen to perform authentication. If authentication is successful, the user can proceed to the next step. The user then selects their preferred virtual character from multiple options on the virtual character selection screen within the application. The selected character guides the user through subsequent interactions, providing a sense of familiarity.

[1582] To dispose of an item, the user takes a picture of the item using the device's camera. This image data is sent from the device to the server. At the same time, the emotion engine analyzes the user's facial expressions, voice, and input actions to recognize the user's emotions. The emotion engine uses facial recognition software (e.g., EmotionRecognizer) to detect the user's emotional state, and this data is also sent to the server.

[1583] The server analyzes the received image data and identifies the item using computer vision technology (e.g., OpenCV). It also uses user information (e.g., age, gender, body type, past item handling history, etc.) and emotional information to generate more accurate advice. The generated advice is specific, such as "This jacket doesn't seem to fit in with current fashion" or "You could potentially sell it for 3,000 yen."

[1584] The generated advice is sent from the server to the device and displayed to the user on the device. Based on the displayed advice, the user selects from the options of "save," "dispose," or "request purchase." Once the selection is complete, the information is sent from the device to the server and saved in a database. The saved data will be used as reference information the next time the service is used.

[1585] Specific examples

[1586] For example, if a male user in his 40s wants to get rid of an old guitar, he can use this system to effectively handle the situation.

[1587] The user launches the Smart Danshari app, enters their account information and logs in.

[1588] A male character is selected from among a plurality of virtual characters.

[1589] By taking a photo of an old guitar, the emotion engine analyzes the user's facial expression and recognizes "nostalgia."

[1590] The server analyzes the image and generates advice such as, "This guitar is a little out of proportion to your age, but if you sell it, you could potentially sell it for 5,000 yen."

[1591] When the user selects "purchase request," the information is sent to the server and saved.

[1592] In this way, the invention can also take into account the user's emotional information, allowing for more personalized and efficient handling of items.

[1593] Prompt Sentence Examples

[1594] "Develop an application that allows users to take photos of items and provides advice on how to dispose of them based on the results of analysis by an emotion engine. The user selects a virtual character, sends the photo of the item and their own emotion data to the server, and then selects "keep," "dispose," or "request purchase" based on the advice generated."

[1595] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1596] Step 1:

[1597] A user starts a device and opens an application. Next, the user enters their account information on the login screen and authenticates. At this point, the input is the user's account information, and the output is the result of authentication success or failure. If authentication is successful, the user proceeds to the next step.

[1598] Step 2:

[1599] The user selects a preferred virtual character from multiple virtual characters on a virtual character selection screen within the application. The input is the virtual character selection information, and the output is the display of the selected character to the user.

[1600] Step 3:

[1601] The user takes a photo of the item they want to dispose of using the device's camera. At this time, the input is the image of the item, and the output is the image data stored in the device.

[1602] Step 4:

[1603] The emotion engine on the device recognizes the user's emotions. It analyzes the user's facial expressions, voice, and input actions, and outputs the user's emotional state as data. The input is information such as the user's facial expressions and voice, and the output is emotional information.

[1604] Step 5:

[1605] The device sends the captured image data and emotion information to the server. The input is the image data and emotion information, and the output is the data received by the server.

[1606] Step 6:

[1607] The server analyzes the image data and identifies the item using computer vision technology. The input is the transmitted image data, and the output is information about the identified object. OpenCV and other computer vision technologies are used.

[1608] Step 7:

[1609] The server generates advice for the identified object based on the user information and emotion information. The input is the item information, user information, and emotion information, and the output is the generated advice. For example, this advice might be, "This jacket doesn't seem to fit in with modern fashion" or "You could potentially sell it for 3,000 yen."

[1610] Step 8:

[1611] The server sends the generated advice to the terminal, which then displays the advice to the user. The input is the advice sent from the server, and the output is the advice displayed on the application.

[1612] Step 9:

[1613] The user selects from the options of "save," "dispose," or "request a resale" based on the displayed advice. The input is the user's selection information, and the output is the selected option.

[1614] Step 10:

[1615] The selection information is sent from the terminal to the server, which then stores it in a database. The input is the user's selection information, and the output is the processing history stored in the database. The stored data is also used as reference information for future use.

[1616] 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.

[1617] 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.

[1618] 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.

[1619] 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.

[1620] 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 of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1621] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1622] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1623] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1624] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1625] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1626] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1627] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1628] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1629] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1630] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1631] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1632] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1633] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1634] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1635] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1636] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1637] The following is further disclosed regarding the above embodiment.

[1638] (Claim 1)

[1639] A means for a user to photograph an object via a device;

[1640] means for transmitting the captured image data to a server;

[1641] means for the server to analyze the image data and identify an object;

[1642] means for generating advice for the identified object based on user information by the server;

[1643] means for displaying the generated advice to a user;

[1644] a means for allowing a user to select a method of processing the object based on the displayed advice;

[1645] The system further includes means for transmitting the selected processing method to a server and storing the same therein.

[1646] (Claim 2)

[1647] 10. The system according to claim 1, further comprising means for calculating a market value of the object and displaying it to a user.

[1648] (Claim 3)

[1649] 2. The system according to claim 1, further comprising means for displaying a plurality of avatars selectable by the user based on the user information.

[1650] "Example 1"

[1651] (Claim 1)

[1652] A means for a user to photograph an object via an information device;

[1653] means for transmitting the captured image data to a server;

[1654] means for the server to analyze the image data and identify an object;

[1655] means for generating advice for the identified object based on user information by the server;

[1656] means for displaying the generated advice to a user;

[1657] a means for allowing a user to select a method of processing the object based on the displayed advice;

[1658] means for transmitting the selected processing method to a server and storing the same;

[1659] means for a user to select from a plurality of virtual characters;

[1660] means for the virtual character to guide the user through dialogue;

[1661] means for using the camera function;

[1662] A system in which the server includes means for concurrently processing related information.

[1663] (Claim 2)

[1664] 10. The system of claim 1, further comprising means for calculating and displaying to the user the market value of the object.

[1665] (Claim 3)

[1666] 10. The system of claim 1, further comprising: means for displaying a plurality of virtual characters selectable by the user based on the user information.

[1667] "Application Example 1"

[1668] (Claim 1)

[1669] A means for a user to photograph an object via a device;

[1670] means for transmitting the captured image data to a server;

[1671] means for the server to analyze the image data and identify an object;

[1672] means for generating advice for the identified object based on user information by the server;

[1673] means for displaying the generated advice to a user;

[1674] a means for allowing a user to select a method of processing the object based on the displayed advice;

[1675] means for transmitting the selected processing method to a server and storing the same;

[1676] A means to link to online market sites and make purchase requests,

[1677] A system including:

[1678] (Claim 2)

[1679] 10. The system according to claim 1, further comprising means for calculating a market value of the object and displaying it to a user.

[1680] (Claim 3)

[1681] 2. The system according to claim 1, further comprising means for displaying a plurality of avatars selectable by the user based on the user information.

[1682] "Example 2: Combining Emotion Engines"

[1683] (Claim 1)

[1684] A means for a user to photograph an object via an electronic device;

[1685] means for transmitting the captured image data to a data center;

[1686] means for the data center to analyze the image data and identify an object;

[1687] a means for generating advice for the identified object based on user information and emotion recognition results, in the data center;

[1688] means for displaying the generated advice to a user;

[1689] a means for allowing a user to select a method of processing the object based on the displayed advice;

[1690] The system includes means for transmitting and storing the selected processing method in a data center.

[1691] (Claim 2)

[1692] 10. The system according to claim 1, further comprising means for calculating a market value of the object and displaying it to a user.

[1693] (Claim 3)

[1694] 2. The system according to claim 1, further comprising means for displaying a plurality of virtual characters selectable by the user based on the user information and the emotion recognition result.

[1695] "Application example 2 when combining emotion engines"

[1696] (Claim 1)

[1697] A means for a user to photograph an object via a device;

[1698] means for transmitting the captured image data to a server;

[1699] means for the server to analyze the image data and identify an object;

[1700] a means for generating advice for the identified object based on user information and emotion information by the server;

[1701] means for displaying the generated advice to a user;

[1702] a means for allowing a user to select a method of processing the object based on the displayed advice;

[1703] The system further includes means for transmitting the selected processing method to a server and storing the same therein.

[1704] (Claim 2)

[1705] 10. The system according to claim 1, further comprising means for calculating a market value of the object and displaying it to a user.

[1706] (Claim 3)

[1707] 10. The system of claim 1, further comprising: means for displaying a plurality of virtual characters selectable by the user based on the user information.

[1708] Explanation of changes

[1709] We added a section based on "emotional information."

[1710] I used the expression "virtual character."

[1711] These changes are intended to clarify the technical scope of the invention and ensure novelty by including the characteristic parts of the invention within the scope of the claims. [Explanation of symbols]

[1712] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for a user to photograph an object via a device; means for transmitting the captured image data to a server; means for the server to analyze the image data and identify an object; means for generating advice for the identified object based on user information by the server; means for displaying the generated advice to a user; a means for allowing a user to select a method of processing the object based on the displayed advice; and means for transmitting the selected processing method to a server and storing the same.

2. 2. The system according to claim 1, further comprising means for calculating a market value of the object and displaying it to a user.

3. The system of claim 1 , further comprising: means for displaying a plurality of avatars selectable by the user based on the user information.

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