system

Abstract

We provide the system. [Solution] A means of automatically registering ownership information, A means of suggesting the most suitable reading schedule to the user based on their ownership information, Means for efficiently reusing or redistributing unwanted personal information, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, when an individual owns many items, there is a lack of means to efficiently manage their information, and the methods for reuse or redistribution are also limited. As a result, there are problems such as duplicate purchases, insufficient storage space, and waste of resources. Furthermore, since there is no mechanism to receive appropriate proposals regarding the utilization methods of possessions, there is also a problem that the effective use of possessions is hindered.

Means for Solving the Problems

[0005] This invention provides a means for automatically registering ownership information, thereby enabling users to quickly and accurately grasp information about the items they own. Furthermore, by using a means to propose an optimal usage plan to the user based on this information, it promotes the effective utilization of possessions. In addition, by constructing a system that includes means for efficiently reusing or recirculating unwanted possessions, it realizes the effective utilization of goods.

[0006] "Ownership information" refers to all information about items owned by an individual, including the name, type, registration number, or identification code of the item.

[0007] "Means of automatic registration" refers to technical means of mechanically or electronically collecting and recording item information without manual operation.

[0008] "User" refers to an individual or legal entity that uses this system and wishes to register ownership information, receive information suggestions, and redistribute goods.

[0009] "Methods for suggesting optimal reading schedules" refer to technologies that provide users with the most suitable reading plan based on their past history and current circumstances.

[0010] "Means of reuse or redistribution" refers to the means necessary to transfer, sell, or recycle unwanted items to others, and includes technologies or services that specifically establish or mediate distribution channels for items. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and used as a work memory by the processor.

[0016] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0017] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. 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), or Bluetooth (registered trademark).

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] As shown in Figure 1, the 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.

[0022] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0023] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0024] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0025] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0026] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] As shown in Figure 2, in the data processing device 12, specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0029] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0030] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0031] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0032] Embodiments of the present invention provide a system and method for efficiently managing ownership information and promoting reuse or redistribution. Users utilize the present invention by installing a dedicated application on their terminal. First, the user obtains information about an item they own by taking a picture of the item using the terminal's camera or by scanning a QR code (registered trademark). The terminal analyzes this obtained information to generate identification information and transmits it to a server.

[0033] The server registers item information in a database based on the received identification information. This database is responsible for aggregating and managing information on all items owned by the user. The registered information is used as basic data to provide the user with various usage suggestions. The server uses AI technology to analyze the user's usage history and preferences based on the registered ownership information. This generates an optimal usage plan for the user, which is then proposed to the user via email or app notifications.

[0034] Furthermore, users can specify items they deem unnecessary. Based on this information, the server presents the user with market buy prices and resale options. This allows users to route unwanted items to appropriate resale channels, promoting the effective use of goods.

[0035] As a concrete example, when a user registers a book, registration is completed by taking a picture of the book's cover with the device's camera. The server analyzes the genres of books the user has read in the past and uses AI to predict and suggest books that the user might enjoy reading next. If a book is unwanted, its resale value or potential exchange partners are suggested, enabling further circulation. In this way, the present invention provides a form that comprehensively supports the management and use of a user's possessions.

[0036] The following describes the processing flow.

[0037] Step 1:

[0038] The user launches a dedicated application and either takes a picture of their belongings with the device's camera or scans a QR code.

[0039] Step 2:

[0040] The device either analyzes object information from an image using optical character recognition (OCR) technology, or obtains information directly from a code.

[0041] Step 3:

[0042] The terminal sends the analyzed or acquired item information to the server and requests its registration in the database.

[0043] Step 4:

[0044] The server registers the received item information in the database and checks for duplicates by comparing it with existing ownership information.

[0045] Step 5:

[0046] The server uses AI to analyze the user's past usage history and external factors, and generates an optimal usage plan based on their possessions.

[0047] Step 6:

[0048] The server generates a usage plan and notifies the terminal, presenting the suggested plan to the user.

[0049] Step 7:

[0050] Users can designate unwanted items on the app on their device and initiate the process of redistributing or reusing them.

[0051] Step 8:

[0052] The server calculates the market purchase price and resale options for the specified item and presents them to the user.

[0053] Step 9:

[0054] The user selects their preferred method from the presented resale options and confirms the procedure via the terminal.

[0055] In this way, the entire system functions, enabling the management and effective use of users' possessions.

[0056] (Example 1)

[0057] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0058] The challenge lies in addressing the difficulty in providing users with optimal usage plans while simultaneously promoting the effective use of goods by enabling owners to efficiently manage their possessions and facilitate their reuse and redistribution. In particular, there is a need to reduce the burden of manually managing information about possessions and to provide advanced usage suggestions using AI technology.

[0059] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0060] In this invention, the server includes a terminal device that automatically registers ownership information, a computing device that proposes an optimal usage plan to the user based on that ownership information, and means for recirculating unwanted possessions. This streamlines the management of ownership information and enables appropriate usage suggestions to the user and the recirculation of unwanted items.

[0061] "Ownership information" refers to detailed data about items owned by individual users, including item identification information and attribute information.

[0062] A "terminal device" is a device operated by the user, equipped with a camera, display, etc., to acquire and display information about items.

[0063] A "computational device" is a device that analyzes data based on owned information and plays a role in generating an optimal usage plan using AI technology.

[0064] A "generative AI model" refers to artificial intelligence technology used to analyze ownership information and usage history, and to make data-driven predictions and suggestions.

[0065] An "image processing device" refers to a device or software that analyzes image data of an object and extracts necessary information.

[0066] A "code analysis device" is a device or software used to read coded information such as QR codes and barcodes and convert it into data.

[0067] The system of the present invention is designed to efficiently manage ownership information, provide optimal usage plans, and facilitate the redistribution of goods. Specific embodiments thereof are described below.

[0068] The user installs a dedicated application on their device. This device is a standard smartphone or tablet equipped with a camera and a QR code reader. The application provides an interface for the user to manage items and analyzes images and codes that are captured.

[0069] When a user photographs an item, the device uses image processing software to extract the necessary information from the image. Similarly, when a QR code is scanned, code analysis software accurately reads the data. This generates identification information for the item.

[0070] The device sends the generated identification information to the server. This server uses an advanced database management system to efficiently register and manage item information. Based on this information, the server utilizes a generative AI model to analyze the user's past usage history and preferences. This generates an optimal usage plan for the user, which is then suggested via app notifications and email.

[0071] As a concrete example, when a user manages the books they own at home, they take a picture of the book's cover with the device's camera. The device reads the corresponding ISBN code and other information and sends it to the server. The server generates suggestions for the next book to read based on the user's past reading history. An example of a prompt to the generating AI model in this case would be, "Please provide information to make the best next purchase suggestion based on the user's past purchase history."

[0072] Furthermore, when a user selects unwanted items from their management list, the server provides market price data and information on available exchange channels. Based on this information, the user can efficiently redistribute the items. This comprehensively supports the effective use and management of possessions.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The user installs a dedicated application on their device and begins acquiring information about an item. Specifically, the user either takes a picture of the item (e.g., a book) with their camera or scans a QR code. The input at this time is the camera image or QR code data, and the output is the initial data necessary for identifying the item.

[0076] Step 2:

[0077] The terminal analyzes the acquired image or code data. Using image processing software, it extracts text information and barcode information from the image. Through this analysis process, the raw image data as input is converted into item identification information as output. Specifically, it performs ISBN code reading using optical character recognition technology.

[0078] Step 3:

[0079] The terminal sends the generated identification information to the server. This communication is conducted securely over the internet. The input is the identification information, and the output is the status of the completion of data transfer to the server. Specifically, this operation includes data transmission using the HTTPS protocol.

[0080] Step 4:

[0081] The server registers the received identification information in the database. This registration process stores the item information within the server. The input is the identification information sent from the terminal, and the output is the database update status indicating that the item has been registered. Specifically, an insertion operation is performed in the database using an SQL statement.

[0082] Step 5:

[0083] The server uses a generative AI model to analyze the user's usage history and preferences based on information in the database. The input for this analysis is the user's past database information, and the output is a suggestion of the optimal usage plan for the user. Specifically, it analyzes past reading history and suggests relevant new books.

[0084] Step 6:

[0085] The server notifies the user of the usage plan generated based on the analysis results. The input is the suggested data generated by the AI ​​model, and the output is the notification information sent to the user. Specifically, the suggested information is sent via the app's notification function or email service.

[0086] Step 7:

[0087] The user selects unwanted items within the application and sends that information to the server. The input is the selected items, and the output is the update status of the unwanted item information sent to the server. Specifically, the unwanted items are tagged using the UI.

[0088] Step 8:

[0089] The server analyzes information on unwanted items and presents the user with the market value and resale options for those items. The input is information on unwanted items submitted by the user, and the output is market value data and resale suggestions. Specifically, it collects, analyzes, and provides real-time market data.

[0090] (Application Example 1)

[0091] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0092] Consumers own many items in their daily lives, but there is a lack of efficient means to manage and recycle them. In particular, finding ways to dispose of unwanted items or options for reuse is difficult and time-consuming when done individually. There is a need to provide a system that solves this problem and promotes the effective use of possessions.

[0093] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0094] In this invention, the server includes means for automatically registering ownership information, means for suggesting the most suitable usage plan to the user based on that ownership information, means for efficiently reusing or redistributing ownership information that is no longer needed, and means for analyzing the market value of registered items and suggesting the most suitable disposal method. This enables users to efficiently manage and redistribute their possessions.

[0095] "Possession information" refers to identifiable information about all items owned by the user, including a record of the characteristics and condition of those items.

[0096] "Methods for automatic registration" refers to technologies that include a process of registering information about an item into a system without human intervention by photographing or scanning the item.

[0097] "Means of suggesting usage plans" refers to a function within the system that presents users with the most suitable plan for using items based on registered ownership information.

[0098] "Means of reuse or redistribution" refers to a function that embodies the process of making unwanted personal information usable again or circulating it in the market.

[0099] "Methods for analyzing market value" refer to techniques that utilize information about an item to evaluate and calculate how much value that item has in the market.

[0100] "Means of proposing the optimal disposal method" refers to the function of a system that presents the most effective and economical disposal method for an item, based on its condition and market value.

[0101] This invention is a system that efficiently manages users' possessions and promotes reuse and redistribution. Users automatically register their ownership information by taking a picture of their items with their smartphone's camera or scanning a QR code. The registered information is sent to a server, which processes this information in various ways. Specifically, the server analyzes the identification information of the items and evaluates their market value.

[0102] The server suggests the optimal disposal method for unwanted items based on their market value. This suggestion is implemented using AI technology, taking into account the user's past usage history and market trends. Users receive suggestions through application notifications, enabling efficient resale.

[0103] The server's judgment process utilizes machine learning algorithms, and the open-source computer vision library OpenCV is used for image analysis of objects. The user's terminal processes object information using a Python program and sends it to the server.

[0104] As a concrete example, consider a case where a user photographs and registers an unwanted electronic device. In this case, the server analyzes the current market value of the electronic device and suggests the most suitable online marketplace for sale. Furthermore, by utilizing the capabilities of a generative AI model, it is possible to recommend alternative products tailored to the user's interests.

[0105] An example of a prompt for a generative AI model is, "Analyze the value of a smartphone that is not currently in use and suggest the most suitable sales channel."

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The user takes a picture of their belongings using their device and inputs information about the items into the device through an application. The input image data is processed as visual data necessary for identifying the items.

[0109] Step 2:

[0110] The device analyzes the captured image data using OpenCV to extract characteristic information about the item. This characteristic information includes the item's shape, brand logo, label information, etc., and serves as basic data for identification. The output is the analyzed item identification information.

[0111] Step 3:

[0112] The analyzed identification information is sent from the terminal to the server. The server registers the received identification information in a database and uses a generative AI model to evaluate its market value. This model calculates the value based on the item's past transaction data and market trends. The output is the item's market value and its detailed information.

[0113] Step 4:

[0114] The server generates notifications to suggest the optimal disposal method to the user based on the calculated market value. Specifically, it uses AI to analyze information on reusable online marketplaces and exchangeable items, and sends this information to the user as a push notification. The output is a specific disposal suggestion sent to the user.

[0115] Step 5:

[0116] The user receives server suggestions via their terminal and selects the most suitable disposal method according to their preferences. The selected information is sent back from the terminal to the server, and processing to initiate redistribution is performed as needed. The output is a notification to the user of the selected redistribution method and the commencement of the associated operations.

[0117] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0118] Embodiments of the present invention provide a system and method that promotes the effective use of possessions by efficiently managing user ownership information and combining it with an emotion engine that recognizes the user's emotional state. This system enables automatic registration of ownership information, proposal of an optimal usage plan for the user, and reuse and redistribution of items.

[0119] Users install a dedicated application on their device and obtain ownership information by taking a picture of an item using the camera or scanning a QR code. The device analyzes this information and sends it to the server. The server registers the received information in a database and manages the items. This eliminates the need for manual registration.

[0120] Furthermore, the server utilizes an emotion engine to recognize the user's emotional state. It analyzes voice and facial expression data in real time to understand the user's emotions. Based on this emotional information, AI technology dynamically generates optimal reading schedules and suggestions for using items for the user, and notifies the device.

[0121] For example, after a user registers a book, if the emotion engine detects the user's calm emotional state, it will suggest books in relaxing genres. Similarly, if the user is feeling stressed, it will suggest books with uplifting content. Furthermore, for items that the user deems unnecessary, it will offer resale options and buyback prices in the market to promote efficient reuse.

[0122] In this way, the present invention provides an embodiment that, by working in conjunction with an emotion engine, further enhances the management and use of possessions and realizes meaningful suggestions for the user.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The user launches a dedicated application and obtains ownership information by taking a picture of the item with the device's camera or scanning a QR code.

[0126] Step 2:

[0127] The device analyzes the image or code data it acquires and extracts the item name and related information. This information is then sent to the server.

[0128] Step 3:

[0129] The server registers the received item information in the database and updates the user's ownership list.

[0130] Step 4:

[0131] The emotion engine collects data from the device to analyze the user's voice and facial expressions. This data is collected in real time with the user's consent.

[0132] Step 5:

[0133] The device performs sentiment analysis to identify the user's emotional state (e.g., relaxed, stressed, etc.). The results are then sent to the server.

[0134] Step 6:

[0135] The server uses AI technology to generate optimal item usage suggestions for the user based on emotional and ownership information. This also takes into account past usage history and external factors.

[0136] Step 7:

[0137] The server generates suggestions and sends them to the terminal, notifying the user. The terminal then provides suggestions such as the use of items or rereading schedules tailored to the user's emotions.

[0138] Step 8:

[0139] When a user specifies unwanted items on their device and initiates the resale process, the server displays market prices and resale options.

[0140] Step 9:

[0141] When a user selects an option, the server proceeds with the redistribution process based on that selection. This process is carried out in conjunction with other distribution services.

[0142] Through this series of steps, the system makes suggestions that respond to the user's emotions and supports the management and effective use of their possessions.

[0143] (Example 2)

[0144] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0145] In recent years, there has been a growing demand for systems that efficiently manage and effectively utilize personal belongings and information. However, conventional systems have faced challenges such as the cumbersome process of registering personal information and the difficulty in proposing plans that take into account the user's emotional state. Furthermore, methods for efficiently reusing unwanted items are still insufficient.

[0146] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0147] In this invention, the server includes means for automatically registering ownership information, means for proposing an optimal activity plan to the user based on the user's emotional state, and means for analyzing emotional data in real time and recognizing the user's emotional state. This not only streamlines the management of possessions but also enables personalized suggestions tailored to the user and effectively promotes the reuse of unwanted items.

[0148] "Ownership information" refers to detailed information about items and related data owned by the user.

[0149] "Automatic registration methods" refer to technologies for registering information about items within a system without requiring manual operation by the user.

[0150] "Means of proposing the optimal activity plan for the user" refers to technology that presents the most appropriate actions and options based on the user's information and circumstances.

[0151] "Emotional data" refers to data that can be obtained from audio and video, indicating the user's emotional state.

[0152] "Real-time analysis" refers to technologies that process data simultaneously with its collection, making the results immediately available for use.

[0153] "Means for recognizing emotional states" refers to technologies for identifying a user's emotions and specifying their state.

[0154] "Means of reuse or redistribution" refers to technologies that efficiently re-evaluate unwanted items based on ownership information, find new use value in them, and then distribute them.

[0155] As an embodiment of this invention, a system is described in which a user, a terminal, and a server cooperate to manage ownership information and realize emotion-based suggestions.

[0156] Users obtain information about their possessions using a device with a dedicated application installed. Specifically, users can obtain detailed information about items by taking a picture of the item using the device's camera or by scanning a QR code. This information includes data that can be accurately read using image analysis technology and identification code parsers.

[0157] The terminal analyzes the acquired information, converts the data into an appropriate format, and sends it to the server. Advanced image recognition algorithms and code analysis libraries are used for the analysis. The server registers the received data in a database, handling the registration and management of owned items. This entire process eliminates the need for users to manually register information.

[0158] Furthermore, the server uses an emotion engine to analyze voice and facial expression data acquired from the user in real time. This makes it possible to accurately recognize the user's emotional state. Based on this emotional information, the server uses a generative AI model to generate prompt sentences and create suggestions based on them.

[0159] For example, if the emotion engine determines that the user is in a calm emotional state and needs to relax, the server generates a prompt in the form of "Please suggest books that will help me relax" and sends it to the AI ​​model. The AI ​​model then generates a list of the most suitable books based on that prompt and presents the results to the user.

[0160] Furthermore, for items owned by the user that the user deems unnecessary, the server presents options for resale in the market or offers a purchase price, thereby promoting the reuse of the items. In this way, the present invention enables efficient management and effective utilization of possessions, and can provide users with a comprehensive range of suggestions.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The user launches a dedicated application installed on their device. With the application open, they use the device's camera to take a picture of an item or scan a QR code. The input is image data or QR code data of the item. This data is analyzed by the device using image analysis or code analysis to extract ownership information of the item. The output is the analyzed item information.

[0164] Step 2:

[0165] The terminal sends analyzed item information to the server. This information includes details such as item name, purchase date, and price. The input is ownership information obtained through image analysis or code analysis. The terminal converts this information into an appropriate format and transfers it to the server via the network. The output is the transferred ownership information data.

[0166] Step 3:

[0167] The server registers ownership information received from the terminal into the database. The input is ownership information data transferred from the terminal. The server checks the data format and registers it in the database while performing data conversion as necessary. The output is the updated database.

[0168] Step 4:

[0169] The server uses an emotion engine to recognize the user's emotional state. Voice data and facial expression data acquired from the user are input. The emotion engine analyzes this data in real time to identify the user's emotional state. The output is the recognized emotional state data.

[0170] Step 5:

[0171] The server uses a generative AI model to create suggestions based on emotional state data and ownership information. The input consists of emotional state data and ownership information. The server sends this data to the AI ​​model as a prompt (e.g., "Please suggest relaxing books"), generating the most suitable suggestions. The output is the generated suggestions.

[0172] Step 6:

[0173] The server notifies the terminal of the generated suggestions. The input is the suggestions obtained from the AI ​​model. The server converts the suggestions into a format that is easy for the user to understand and sends it to the terminal. The output is the displayed suggestions.

[0174] Step 7:

[0175] Users utilize items or reuse unwanted items based on the suggested options. Depending on the user's choices, reuse options or buyback prices for items may be presented. The input is the suggested content notified by the server. The user selects an action based on this. The output is the result of the user's effective use or reuse of the items.

[0176] (Application Example 2)

[0177] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0178] Traditional brick-and-mortar retail systems often struggle to provide personalized service based on individual customer emotional states, relying instead on uniform marketing strategies. This makes it difficult to improve customer satisfaction and maximize purchasing intent. Furthermore, there is a challenge in the insufficient promotion of the redistribution and reuse of owned goods, resulting in inefficient utilization of materials.

[0179] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0180] In this invention, the server includes means for automatically registering ownership information and the emotional state of users, means for determining the emotional state of buyers based on the information and providing appropriate product information in real time, and means for efficiently redistributing unwanted items and promoting reuse. This enables personalized sales strategies for individual customers and promotes the effective use of goods.

[0181] "Ownership information" refers to data about items owned by the user, such as information about the item's name, type, value, and usage status.

[0182] "User's emotional state" refers to the user's emotional tendencies at that particular moment, including states such as comfort, relaxation, and stress.

[0183] "Image analysis" is a technology that uses digital video data to extract the characteristics of an object and analyze that information.

[0184] "Code recognition" is a technology that reads codes such as QR codes and barcodes and retrieves related information.

[0185] A "buyer" refers to an individual or legal entity that intends to purchase goods or services.

[0186] "Intelligent technology" refers to technology that uses artificial intelligence to analyze things and make appropriate judgments and suggestions.

[0187] "Redistribution" refers to the process of bringing goods that have already been put on the market back into circulation, making them ready for sale again.

[0188] "Reuse" refers to the act of using unwanted items again in a different form, and is an act of making efficient use of resources without waste.

[0189] The central element of this system is a program that automatically registers and manages ownership information and the emotional state of users. This system is implemented using smartphones, smart glasses, and servers.

[0190] First, the user takes a picture of their belongings with the camera on their smartphone or smart glasses, and the system performs image analysis or code recognition. This utilizes image recognition software such as Google® Cloud Vision API. The recognized information is sent from the device to the server. The server registers this data in a database and manages it as ownership information.

[0191] Next, to assess the user's emotional state, real-time facial and audio data is collected from the device. This utilizes a camera and microphone to capture the user's facial expressions. The collected data is then analyzed using emotion analysis tools such as Azure® Emotion API to determine the user's emotional state.

[0192] Based on this data, the server understands the buyer's emotional state and uses artificial intelligence to generate product information tailored to the user. By utilizing intelligent technology, it's possible to provide products and special offers that match a specific buyer's historical usage patterns and current emotional state. For example, if a buyer is determined to be relaxed, they will be offered product information and special sale announcements appropriate for that state. In this way, the individual buyer's experience is personalized, improving satisfaction.

[0193] As a concrete example, if facial analysis reveals that a customer is relaxed while in a store, special discount information will be immediately displayed to that customer through smart glasses. This is expected to attract the customer's attention and increase their willingness to purchase. An example of a prompt message provided by the generating AI model is, "Immediately recommend special discount information to the relaxed customer."

[0194] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0195] Step 1:

[0196] The user takes a picture of an item using a smartphone or smart glasses. The device receives the captured image data as input and performs image analysis using the Google Cloud Vision API. As a result, ownership information such as the item's name and category is output.

[0197] Step 2:

[0198] Ownership information is sent from the terminal to the server. The server registers and manages the ownership information received as input in its database. This information is also used to update the user's list of owned items.

[0199] Step 3:

[0200] The device captures the user's facial expressions and voice in real time. The data collected using the camera and microphone is analyzed using the Azure Emotion API. The input for this analysis is real-time facial expression and voice data, and the output is the user's emotional state.

[0201] Step 4:

[0202] The server generates appropriate product information and suggestions based on the user's emotional state and ownership information. Utilizing intelligent technology, it analyzes data based on the input emotional state and historical usage trends, and uses prompts to generate appropriate product information. This output becomes personalized product information and special offers for each individual user.

[0203] Step 5:

[0204] The generated product information is sent from the server to the terminal. Users receive this information in real time via smart glasses or smartphones. This output functions as marketing information to increase the user's purchasing intent.

[0205] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0206] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0207] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0208] [Second Embodiment]

[0209] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0210] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0211] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0212] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0213] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0214] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0215] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0216] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0217] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0218] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0219] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0220] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0221] Embodiments of the present invention provide a system and method for efficiently managing ownership information and promoting reuse or redistribution. Users utilize the present invention by installing a dedicated application on their terminal. First, the user obtains information about an item they own by taking a picture of the item using the terminal's camera or by scanning a QR code. The terminal analyzes this obtained information to generate identification information and transmits it to a server.

[0222] The server registers item information in a database based on the received identification information. This database is responsible for aggregating and managing information on all items owned by the user. The registered information is used as basic data to provide the user with various usage suggestions. The server uses AI technology to analyze the user's usage history and preferences based on the registered ownership information. This generates an optimal usage plan for the user, which is then proposed to the user via email or app notifications.

[0223] Furthermore, users can specify items they deem unnecessary. Based on this information, the server presents the user with market buy prices and resale options. This allows users to route unwanted items to appropriate resale channels, promoting the effective use of goods.

[0224] As a concrete example, when a user registers a book, registration is completed by taking a picture of the book's cover with the device's camera. The server analyzes the genres of books the user has read in the past and uses AI to predict and suggest books that the user might enjoy reading next. If a book is unwanted, its resale value or potential exchange partners are suggested, enabling further circulation. In this way, the present invention provides a form that comprehensively supports the management and use of a user's possessions.

[0225] The following describes the processing flow.

[0226] Step 1:

[0227] The user launches a dedicated application and either takes a picture of their belongings with the device's camera or scans a QR code.

[0228] Step 2:

[0229] The device either analyzes object information from an image using optical character recognition (OCR) technology, or obtains information directly from a code.

[0230] Step 3:

[0231] The terminal sends the analyzed or acquired item information to the server and requests its registration in the database.

[0232] Step 4:

[0233] The server registers the received item information in the database and checks for duplicates by comparing it with existing ownership information.

[0234] Step 5:

[0235] The server uses AI to analyze the user's past usage history and external factors, and generates an optimal usage plan based on their possessions.

[0236] Step 6:

[0237] The server generates a usage plan and notifies the terminal, presenting the suggested plan to the user.

[0238] Step 7:

[0239] Users can designate unwanted items on the app on their device and initiate the process of redistributing or reusing them.

[0240] Step 8:

[0241] The server calculates the market purchase price and resale options for the specified item and presents them to the user.

[0242] Step 9:

[0243] The user selects their preferred method from the presented resale options and confirms the procedure via the terminal.

[0244] In this way, the entire system functions, enabling the management and effective use of users' possessions.

[0245] (Example 1)

[0246] Next, we will describe Example 1. 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."

[0247] The challenge lies in addressing the difficulty in providing users with optimal usage plans while simultaneously promoting the effective use of goods by enabling owners to efficiently manage their possessions and facilitate their reuse and redistribution. In particular, there is a need to reduce the burden of manually managing information about possessions and to provide advanced usage suggestions using AI technology.

[0248] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0249] In this invention, the server includes a terminal device that automatically registers ownership information, a computing device that proposes an optimal usage plan to the user based on that ownership information, and means for recirculating unwanted possessions. This streamlines the management of ownership information and enables appropriate usage suggestions to the user and the recirculation of unwanted items.

[0250] "Ownership information" refers to detailed data about items owned by individual users, including item identification information and attribute information.

[0251] A "terminal device" is a device operated by the user, equipped with a camera, display, etc., to acquire and display information about items.

[0252] A "computational device" is a device that analyzes data based on owned information and plays a role in generating an optimal usage plan using AI technology.

[0253] A "generative AI model" refers to artificial intelligence technology used to analyze ownership information and usage history, and to make data-driven predictions and suggestions.

[0254] An "image processing device" refers to a device or software that analyzes image data of an object and extracts necessary information.

[0255] A "code analysis device" is a device or software used to read coded information such as QR codes and barcodes and convert it into data.

[0256] The system of the present invention is designed to efficiently manage ownership information, provide optimal usage plans, and facilitate the redistribution of goods. Specific embodiments thereof are described below.

[0257] The user installs a dedicated application on their device. This device is a standard smartphone or tablet equipped with a camera and a QR code reader. The application provides an interface for the user to manage items and analyzes images and codes that are captured.

[0258] When a user photographs an item, the device uses image processing software to extract the necessary information from the image. Similarly, when a QR code is scanned, code analysis software accurately reads the data. This generates identification information for the item.

[0259] The device sends the generated identification information to the server. This server uses an advanced database management system to efficiently register and manage item information. Based on this information, the server utilizes a generative AI model to analyze the user's past usage history and preferences. This generates an optimal usage plan for the user, which is then suggested via app notifications and email.

[0260] As a concrete example, when a user manages the books they own at home, they take a picture of the book's cover with the device's camera. The device reads the corresponding ISBN code and other information and sends it to the server. The server generates suggestions for the next book to read based on the user's past reading history. An example of a prompt to the generating AI model in this case would be, "Please provide information to make the best next purchase suggestion based on the user's past purchase history."

[0261] Furthermore, when a user selects unwanted items from their management list, the server provides market price data and information on available exchange channels. Based on this information, the user can efficiently redistribute the items. This comprehensively supports the effective use and management of possessions.

[0262] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0263] Step 1:

[0264] The user installs a dedicated application on their device and begins acquiring information about an item. Specifically, the user either takes a picture of the item (e.g., a book) with their camera or scans a QR code. The input at this time is the camera image or QR code data, and the output is the initial data necessary for identifying the item.

[0265] Step 2:

[0266] The terminal analyzes the acquired image or code data. Using image processing software, it extracts text information and barcode information from the image. Through this analysis process, the raw image data as input is converted into item identification information as output. Specifically, it performs ISBN code reading using optical character recognition technology.

[0267] Step 3:

[0268] The terminal sends the generated identification information to the server. This communication is conducted securely over the internet. The input is the identification information, and the output is the status of the completion of data transfer to the server. Specifically, this operation includes data transmission using the HTTPS protocol.

[0269] Step 4:

[0270] The server registers the received identification information in the database. This registration process stores the item information within the server. The input is the identification information sent from the terminal, and the output is the database update status indicating that the item has been registered. Specifically, an insertion operation is performed in the database using an SQL statement.

[0271] Step 5:

[0272] The server uses a generative AI model to analyze the user's usage history and preferences based on information in the database. The input for this analysis is the user's past database information, and the output is a suggestion of the optimal usage plan for the user. Specifically, it analyzes past reading history and suggests relevant new books.

[0273] Step 6:

[0274] The server notifies the user of the usage plan generated based on the analysis results. The input is the suggested data generated by the AI ​​model, and the output is the notification information sent to the user. Specifically, the suggested information is sent via the app's notification function or email service.

[0275] Step 7:

[0276] The user selects unwanted items within the application and sends that information to the server. The input is the selected items, and the output is the update status of the unwanted item information sent to the server. Specifically, the unwanted items are tagged using the UI.

[0277] Step 8:

[0278] The server analyzes information on unwanted items and presents the user with the market value and resale options for those items. The input is information on unwanted items submitted by the user, and the output is market value data and resale suggestions. Specifically, it collects, analyzes, and provides real-time market data.

[0279] (Application Example 1)

[0280] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0281] Consumers own many items in their daily lives, but lack means to efficiently manage and recycle them. In particular, it is difficult and laborious for individuals to find ways to dispose of unwanted items or explore options for reuse. There is a need to provide a system that solves this problem and promotes the effective utilization of possessions.

[0282] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0283] In this invention, the server includes means for automatically registering ownership information, means for proposing an optimal usage plan to the user based on the ownership information, means for efficiently recycling or redistributing unwanted ownership information, and means for analyzing the market value of registered items and proposing an optimal disposal method. As a result, the user can efficiently manage and recycle their possessions.

[0284] "Ownership information" refers to identifiable information regarding all items held by the user, which records the characteristics and status of the items.

[0285] "Means for automatically registering" refers to a technology that includes a process of automatically registering the information of an item into the system by photographing or scanning the item without human intervention.

[0286] "Means for proposing a usage plan" refers to a function within the system that presents an optimal item usage plan to the user based on the registered ownership information.

[0287] "Means for recycling or redistributing" refers to a function that embodies a process of making unwanted ownership information reusable or circulating it in the market based on the unwanted ownership information.

[0288] "Methods for analyzing market value" refer to techniques that utilize information about an item to evaluate and calculate how much value that item has in the market.

[0289] "Means of proposing the optimal disposal method" refers to the function of a system that presents the most effective and economical disposal method for an item, based on its condition and market value.

[0290] This invention is a system that efficiently manages users' possessions and promotes reuse and redistribution. Users automatically register their ownership information by taking a picture of their items with their smartphone's camera or scanning a QR code. The registered information is sent to a server, which processes this information in various ways. Specifically, the server analyzes the identification information of the items and evaluates their market value.

[0291] The server suggests the optimal disposal method for unwanted items based on their market value. This suggestion is implemented using AI technology, taking into account the user's past usage history and market trends. Users receive suggestions through application notifications, enabling efficient resale.

[0292] The server's judgment process utilizes machine learning algorithms, and the open-source computer vision library OpenCV is used for image analysis of objects. The user's terminal processes object information using a Python program and sends it to the server.

[0293] As a concrete example, consider a case where a user photographs and registers an unwanted electronic device. In this case, the server analyzes the current market value of the electronic device and suggests the most suitable online marketplace for sale. Furthermore, by utilizing the capabilities of a generative AI model, it is possible to recommend alternative products tailored to the user's interests.

[0294] An example of a prompt for a generative AI model is, "Analyze the value of a smartphone that is not currently in use and suggest the most suitable sales channel."

[0295] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0296] Step 1:

[0297] The user takes a picture of their belongings using their device and inputs information about the items into the device through an application. The input image data is processed as visual data necessary for identifying the items.

[0298] Step 2:

[0299] The device analyzes the captured image data using OpenCV to extract characteristic information about the item. This characteristic information includes the item's shape, brand logo, label information, etc., and serves as basic data for identification. The output is the analyzed item identification information.

[0300] Step 3:

[0301] The analyzed identification information is sent from the terminal to the server. The server registers the received identification information in a database and uses a generative AI model to evaluate its market value. This model calculates the value based on the item's past transaction data and market trends. The output is the item's market value and its detailed information.

[0302] Step 4:

[0303] The server generates notifications to suggest the optimal disposal method to the user based on the calculated market value. Specifically, it uses AI to analyze information on reusable online marketplaces and exchangeable items, and sends this information to the user as a push notification. The output is a specific disposal suggestion sent to the user.

[0304] Step 5:

[0305] The user receives the server's proposal through the terminal and selects the optimal disposal method that meets their own wishes from among them. The selected information is sent from the terminal to the server again, and a process to start redistribution is executed as necessary. The output is a notification of the start of the redistribution method and related operations selected by the user.

[0306] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions.

[0307] Embodiments of the present invention provide a system and method for promoting the effective utilization of possessions by efficiently managing the user's ownership information and combining an emotion engine that recognizes the user's emotional state. This system enables automatic registration of ownership information, proposal of an optimal usage plan for the user, and reuse and redistribution of articles.

[0308] The user installs a dedicated application on the terminal, takes a picture of an article using the camera, or scans a QR code to obtain ownership information. The terminal analyzes this information and sends it to the server. The server registers the received information in the database and manages the articles. This eliminates the need for manual registration work.

[0309] Furthermore, the server utilizes an emotion engine to recognize the user's emotional state. It analyzes voice data and facial expression data in real time to grasp the user's emotions. Based on this emotion information, AI technology dynamically generates an optimal reading schedule and usage proposal for the user and notifies the terminal.

[0310] For example, after a user registers a book, if the emotion engine detects the user's calm emotional state, it will suggest books in relaxing genres. Similarly, if the user is feeling stressed, it will suggest books with uplifting content. Furthermore, for items that the user deems unnecessary, it will offer resale options and buyback prices in the market to promote efficient reuse.

[0311] In this way, the present invention provides an embodiment that, by working in conjunction with an emotion engine, further enhances the management and use of possessions and realizes meaningful suggestions for the user.

[0312] The following describes the processing flow.

[0313] Step 1:

[0314] The user launches a dedicated application and obtains ownership information by taking a picture of the item with the device's camera or scanning a QR code.

[0315] Step 2:

[0316] The device analyzes the image or code data it acquires and extracts the item name and related information. This information is then sent to the server.

[0317] Step 3:

[0318] The server registers the received item information in the database and updates the user's ownership list.

[0319] Step 4:

[0320] The emotion engine collects data from the device to analyze the user's voice and facial expressions. This data is collected in real time with the user's consent.

[0321] Step 5:

[0322] The device performs sentiment analysis to identify the user's emotional state (e.g., relaxed, stressed, etc.). The results are then sent to the server.

[0323] Step 6:

[0324] The server uses AI technology to generate optimal item usage suggestions for the user based on emotional and ownership information. This also takes into account past usage history and external factors.

[0325] Step 7:

[0326] The server generates suggestions and sends them to the terminal, notifying the user. The terminal then provides suggestions such as the use of items or rereading schedules tailored to the user's emotions.

[0327] Step 8:

[0328] When a user specifies unwanted items on their device and initiates the resale process, the server displays market prices and resale options.

[0329] Step 9:

[0330] When a user selects an option, the server proceeds with the redistribution process based on that selection. This process is carried out in conjunction with other distribution services.

[0331] Through this series of steps, the system makes suggestions that respond to the user's emotions and supports the management and effective use of their possessions.

[0332] (Example 2)

[0333] Next, we will describe Example 2. 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".

[0334] In recent years, there has been a growing demand for systems that efficiently manage and effectively utilize personal belongings and information. However, conventional systems have faced challenges such as the cumbersome process of registering personal information and the difficulty in proposing plans that take into account the user's emotional state. Furthermore, methods for efficiently reusing unwanted items are still insufficient.

[0335] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0336] In this invention, the server includes means for automatically registering ownership information, means for proposing an optimal activity plan to the user based on the user's emotional state, and means for analyzing emotional data in real time and recognizing the user's emotional state. This not only streamlines the management of possessions but also enables personalized suggestions tailored to the user and effectively promotes the reuse of unwanted items.

[0337] "Ownership information" refers to detailed information about items and related data owned by the user.

[0338] "Automatic registration methods" refer to technologies for registering information about items within a system without requiring manual operation by the user.

[0339] "Means of proposing the optimal activity plan for the user" refers to technology that presents the most appropriate actions and options based on the user's information and circumstances.

[0340] "Emotional data" refers to data that can be obtained from audio and video, indicating the user's emotional state.

[0341] "Real-time analysis" refers to technologies that process data simultaneously with its collection, making the results immediately available for use.

[0342] "Means for recognizing emotional states" refers to technologies for identifying a user's emotions and specifying their state.

[0343] "Means of reuse or redistribution" refers to technologies that efficiently re-evaluate unwanted items based on ownership information, find new use value in them, and then distribute them.

[0344] As an embodiment of this invention, a system is described in which a user, a terminal, and a server cooperate to manage ownership information and realize emotion-based suggestions.

[0345] Users obtain information about their possessions using a device with a dedicated application installed. Specifically, users can obtain detailed information about items by taking a picture of the item using the device's camera or by scanning a QR code. This information includes data that can be accurately read using image analysis technology and identification code parsers.

[0346] The terminal analyzes the acquired information, converts the data into an appropriate format, and sends it to the server. Advanced image recognition algorithms and code analysis libraries are used for the analysis. The server registers the received data in a database, handling the registration and management of owned items. This entire process eliminates the need for users to manually register information.

[0347] Furthermore, the server uses an emotion engine to analyze voice and facial expression data acquired from the user in real time. This makes it possible to accurately recognize the user's emotional state. Based on this emotional information, the server uses a generative AI model to generate prompt sentences and create suggestions based on them.

[0348] For example, if the emotion engine determines that the user is in a calm emotional state and needs to relax, the server generates a prompt in the form of "Please suggest books that will help me relax" and sends it to the AI ​​model. The AI ​​model then generates a list of the most suitable books based on that prompt and presents the results to the user.

[0349] Furthermore, for items owned by the user that the user deems unnecessary, the server presents options for resale in the market or offers a purchase price, thereby promoting the reuse of the items. In this way, the present invention enables efficient management and effective utilization of possessions, and can provide users with a comprehensive range of suggestions.

[0350] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0351] Step 1:

[0352] The user launches a dedicated application installed on their device. With the application open, they use the device's camera to take a picture of an item or scan a QR code. The input is image data or QR code data of the item. This data is analyzed by the device using image analysis or code analysis to extract ownership information of the item. The output is the analyzed item information.

[0353] Step 2:

[0354] The terminal sends analyzed item information to the server. This information includes details such as item name, purchase date, and price. The input is ownership information obtained through image analysis or code analysis. The terminal converts this information into an appropriate format and transfers it to the server via the network. The output is the transferred ownership information data.

[0355] Step 3:

[0356] The server registers ownership information received from the terminal into the database. The input is ownership information data transferred from the terminal. The server checks the data format and registers it in the database while performing data conversion as necessary. The output is the updated database.

[0357] Step 4:

[0358] The server uses an emotion engine to recognize the user's emotional state. Voice data and facial expression data acquired from the user are input. The emotion engine analyzes this data in real time to identify the user's emotional state. The output is the recognized emotional state data.

[0359] Step 5:

[0360] The server uses a generative AI model to create suggestions based on emotional state data and ownership information. The input consists of emotional state data and ownership information. The server sends this data to the AI ​​model as a prompt (e.g., "Please suggest relaxing books"), generating the most suitable suggestions. The output is the generated suggestions.

[0361] Step 6:

[0362] The server notifies the terminal of the generated suggestions. The input is the suggestions obtained from the AI ​​model. The server converts the suggestions into a format that is easy for the user to understand and sends it to the terminal. The output is the displayed suggestions.

[0363] Step 7:

[0364] Users utilize items or reuse unwanted items based on the suggested options. Depending on the user's choices, reuse options or buyback prices for items may be presented. The input is the suggested content notified by the server. The user selects an action based on this. The output is the result of the user's effective use or reuse of the items.

[0365] (Application Example 2)

[0366] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0367] Traditional brick-and-mortar retail systems often struggle to provide personalized service based on individual customer emotional states, relying instead on uniform marketing strategies. This makes it difficult to improve customer satisfaction and maximize purchasing intent. Furthermore, there is a challenge in the insufficient promotion of the redistribution and reuse of owned goods, resulting in inefficient utilization of materials.

[0368] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0369] In this invention, the server includes means for automatically registering ownership information and the emotional state of users, means for determining the emotional state of buyers based on the information and providing appropriate product information in real time, and means for efficiently redistributing unwanted items and promoting reuse. This enables personalized sales strategies for individual customers and promotes the effective use of goods.

[0370] "Ownership information" refers to data about items owned by the user, such as information about the item's name, type, value, and usage status.

[0371] "User's emotional state" refers to the user's emotional tendencies at that particular moment, including states such as comfort, relaxation, and stress.

[0372] "Image analysis" is a technology that uses digital video data to extract the characteristics of an object and analyze that information.

[0373] "Code recognition" is a technology that reads codes such as QR codes and barcodes and retrieves related information.

[0374] A "buyer" refers to an individual or legal entity that intends to purchase goods or services.

[0375] "Intelligent technology" refers to technology that uses artificial intelligence to analyze things and make appropriate judgments and suggestions.

[0376] "Redistribution" refers to the process of bringing goods that have already been put on the market back into circulation, making them ready for sale again.

[0377] "Reuse" refers to the act of using unwanted items again in a different form, and is an act of making efficient use of resources without waste.

[0378] The central element of this system is a program that automatically registers and manages ownership information and the emotional state of users. This system is implemented using smartphones, smart glasses, and servers.

[0379] First, the user takes a picture of their belongings with the camera on their smartphone or smart glasses, and the system performs image analysis or code recognition. This utilizes image recognition software such as the Google Cloud Vision API. The recognized information is sent from the device to the server. The server registers this data in a database and manages it as ownership information.

[0380] Next, to assess the user's emotional state, real-time facial and audio data is collected from the device. This utilizes a camera and microphone to capture the user's facial expressions. The collected data is then analyzed using emotion analysis tools such as the Azure Emotion API to determine the user's emotional state.

[0381] Based on this data, the server understands the buyer's emotional state and uses artificial intelligence to generate product information tailored to the user. By utilizing intelligent technology, it's possible to provide products and special offers that match a specific buyer's historical usage patterns and current emotional state. For example, if a buyer is determined to be relaxed, they will be offered product information and special sale announcements appropriate for that state. In this way, the individual buyer's experience is personalized, improving satisfaction.

[0382] As a concrete example, if facial analysis reveals that a customer is relaxed while in a store, special discount information will be immediately displayed to that customer through smart glasses. This is expected to attract the customer's attention and increase their willingness to purchase. An example of a prompt message provided by the generating AI model is, "Immediately recommend special discount information to the relaxed customer."

[0383] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0384] Step 1:

[0385] The user takes a picture of an item using a smartphone or smart glasses. The device receives the captured image data as input and performs image analysis using the Google Cloud Vision API. As a result, ownership information such as the item's name and category is output.

[0386] Step 2:

[0387] Ownership information is sent from the terminal to the server. The server registers and manages the ownership information received as input in its database. This information is also used to update the user's list of owned items.

[0388] Step 3:

[0389] The device captures the user's facial expressions and voice in real time. The data collected using the camera and microphone is analyzed using the Azure Emotion API. The input for this analysis is real-time facial expression and voice data, and the output is the user's emotional state.

[0390] Step 4:

[0391] The server generates appropriate product information and suggestions based on the user's emotional state and ownership information. Utilizing intelligent technology, it analyzes data based on the input emotional state and historical usage trends, and uses prompts to generate appropriate product information. This output becomes personalized product information and special offers for each individual user.

[0392] Step 5:

[0393] The generated product information is sent from the server to the terminal. Users receive this information in real time via smart glasses or smartphones. This output functions as marketing information to increase the user's purchasing intent.

[0394] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0395] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0396] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0397] [Third Embodiment]

[0398] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0399] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0400] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0401] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0402] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0403] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0404] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0405] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0406] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0407] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0408] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0409] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0410] Embodiments of the present invention provide a system and method for efficiently managing ownership information and promoting reuse or redistribution. Users utilize the present invention by installing a dedicated application on their terminal. First, the user obtains information about an item they own by taking a picture of the item using the terminal's camera or by scanning a QR code. The terminal analyzes this obtained information to generate identification information and transmits it to a server.

[0411] The server registers item information in a database based on the received identification information. This database is responsible for aggregating and managing information on all items owned by the user. The registered information is used as basic data to provide the user with various usage suggestions. The server uses AI technology to analyze the user's usage history and preferences based on the registered ownership information. This generates an optimal usage plan for the user, which is then proposed to the user via email or app notifications.

[0412] Furthermore, users can specify items they deem unnecessary. Based on this information, the server presents the user with market buy prices and resale options. This allows users to route unwanted items to appropriate resale channels, promoting the effective use of goods.

[0413] As a concrete example, when a user registers a book, registration is completed by taking a picture of the book's cover with the device's camera. The server analyzes the genres of books the user has read in the past and uses AI to predict and suggest books that the user might enjoy reading next. If a book is unwanted, its resale value or potential exchange partners are suggested, enabling further circulation. In this way, the present invention provides a form that comprehensively supports the management and use of a user's possessions.

[0414] The following describes the processing flow.

[0415] Step 1:

[0416] The user launches a dedicated application and either takes a picture of their belongings with the device's camera or scans a QR code.

[0417] Step 2:

[0418] The device either analyzes object information from an image using optical character recognition (OCR) technology, or obtains information directly from a code.

[0419] Step 3:

[0420] The terminal sends the analyzed or acquired item information to the server and requests its registration in the database.

[0421] Step 4:

[0422] The server registers the received item information in the database and checks for duplicates by comparing it with existing ownership information.

[0423] Step 5:

[0424] The server uses AI to analyze the user's past usage history and external factors, and generates an optimal usage plan based on their possessions.

[0425] Step 6:

[0426] The server generates a usage plan and notifies the terminal, presenting the suggested plan to the user.

[0427] Step 7:

[0428] Users can designate unwanted items on the app on their device and initiate the process of redistributing or reusing them.

[0429] Step 8:

[0430] The server calculates the market purchase price and resale options for the specified item and presents them to the user.

[0431] Step 9:

[0432] The user selects their preferred method from the presented resale options and confirms the procedure via the terminal.

[0433] In this way, the entire system functions, enabling the management and effective use of users' possessions.

[0434] (Example 1)

[0435] Next, we will describe Example 1. 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."

[0436] The challenge lies in addressing the difficulty in providing users with optimal usage plans while simultaneously promoting the effective use of goods by enabling owners to efficiently manage their possessions and facilitate their reuse and redistribution. In particular, there is a need to reduce the burden of manually managing information about possessions and to provide advanced usage suggestions using AI technology.

[0437] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0438] In this invention, the server includes a terminal device that automatically registers ownership information, a computing device that proposes an optimal usage plan to the user based on that ownership information, and means for recirculating unwanted possessions. This streamlines the management of ownership information and enables appropriate usage suggestions to the user and the recirculation of unwanted items.

[0439] "Ownership information" refers to detailed data about items owned by individual users, including item identification information and attribute information.

[0440] A "terminal device" is a device operated by the user, equipped with a camera, display, etc., to acquire and display information about items.

[0441] A "computational device" is a device that analyzes data based on owned information and plays a role in generating an optimal usage plan using AI technology.

[0442] A "generative AI model" refers to artificial intelligence technology used to analyze ownership information and usage history, and to make data-driven predictions and suggestions.

[0443] An "image processing device" refers to a device or software that analyzes image data of an object and extracts necessary information.

[0444] A "code analysis device" is a device or software used to read coded information such as QR codes and barcodes and convert it into data.

[0445] The system of the present invention is designed to efficiently manage ownership information, provide optimal usage plans, and facilitate the redistribution of goods. Specific embodiments thereof are described below.

[0446] The user installs a dedicated application on their device. This device is a standard smartphone or tablet equipped with a camera and a QR code reader. The application provides an interface for the user to manage items and analyzes images and codes that are captured.

[0447] When a user photographs an item, the device uses image processing software to extract the necessary information from the image. Similarly, when a QR code is scanned, code analysis software accurately reads the data. This generates identification information for the item.

[0448] The device sends the generated identification information to the server. This server uses an advanced database management system to efficiently register and manage item information. Based on this information, the server utilizes a generative AI model to analyze the user's past usage history and preferences. This generates an optimal usage plan for the user, which is then suggested via app notifications and email.

[0449] As a concrete example, when a user manages the books they own at home, they take a picture of the book's cover with the device's camera. The device reads the corresponding ISBN code and other information and sends it to the server. The server generates suggestions for the next book to read based on the user's past reading history. An example of a prompt to the generating AI model in this case would be, "Please provide information to make the best next purchase suggestion based on the user's past purchase history."

[0450] Furthermore, when a user selects unwanted items from their management list, the server provides market price data and information on available exchange channels. Based on this information, the user can efficiently redistribute the items. This comprehensively supports the effective use and management of possessions.

[0451] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0452] Step 1:

[0453] The user installs a dedicated application on their device and begins acquiring information about an item. Specifically, the user either takes a picture of the item (e.g., a book) with their camera or scans a QR code. The input at this time is the camera image or QR code data, and the output is the initial data necessary for identifying the item.

[0454] Step 2:

[0455] The terminal analyzes the acquired image or code data. Using image processing software, it extracts text information and barcode information from the image. Through this analysis process, the raw image data as input is converted into item identification information as output. Specifically, it performs ISBN code reading using optical character recognition technology.

[0456] Step 3:

[0457] The terminal sends the generated identification information to the server. This communication is conducted securely over the internet. The input is the identification information, and the output is the status of the completion of data transfer to the server. Specifically, this operation includes data transmission using the HTTPS protocol.

[0458] Step 4:

[0459] The server registers the received identification information in the database. This registration process stores the item information within the server. The input is the identification information sent from the terminal, and the output is the database update status indicating that the item has been registered. Specifically, an insertion operation is performed in the database using an SQL statement.

[0460] Step 5:

[0461] The server uses a generative AI model to analyze the user's usage history and preferences based on information in the database. The input for this analysis is the user's past database information, and the output is a suggestion of the optimal usage plan for the user. Specifically, it analyzes past reading history and suggests relevant new books.

[0462] Step 6:

[0463] The server notifies the user of the usage plan generated based on the analysis results. The input is the suggested data generated by the AI ​​model, and the output is the notification information sent to the user. Specifically, the suggested information is sent via the app's notification function or email service.

[0464] Step 7:

[0465] The user selects unwanted items within the application and sends that information to the server. The input is the selected items, and the output is the update status of the unwanted item information sent to the server. Specifically, the unwanted items are tagged using the UI.

[0466] Step 8:

[0467] The server analyzes information on unwanted items and presents the user with the market value and resale options for those items. The input is information on unwanted items submitted by the user, and the output is market value data and resale suggestions. Specifically, it collects, analyzes, and provides real-time market data.

[0468] (Application Example 1)

[0469] Next, we will explain Application Example 1. In the following explanation, 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."

[0470] Consumers own many items in their daily lives, but there is a lack of efficient means to manage and recycle them. In particular, finding ways to dispose of unwanted items or options for reuse is difficult and time-consuming when done individually. There is a need to provide a system that solves this problem and promotes the effective use of possessions.

[0471] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0472] In this invention, the server includes means for automatically registering ownership information, means for suggesting the most suitable usage plan to the user based on that ownership information, means for efficiently reusing or redistributing ownership information that is no longer needed, and means for analyzing the market value of registered items and suggesting the most suitable disposal method. This enables users to efficiently manage and redistribute their possessions.

[0473] "Possession information" refers to identifiable information about all items owned by the user, including a record of the characteristics and condition of those items.

[0474] "Methods for automatic registration" refers to technologies that include a process of registering information about an item into a system without human intervention by photographing or scanning the item.

[0475] "Means of suggesting usage plans" refers to a function within the system that presents users with the most suitable plan for using items based on registered ownership information.

[0476] "Means of reuse or redistribution" refers to a function that embodies the process of making unwanted personal information usable again or circulating it in the market.

[0477] "Methods for analyzing market value" refer to techniques that utilize information about an item to evaluate and calculate how much value that item has in the market.

[0478] "Means of proposing the optimal disposal method" refers to the function of a system that presents the most effective and economical disposal method for an item, based on its condition and market value.

[0479] This invention is a system that efficiently manages users' possessions and promotes reuse and redistribution. Users automatically register their ownership information by taking a picture of their items with their smartphone's camera or scanning a QR code. The registered information is sent to a server, which processes this information in various ways. Specifically, the server analyzes the identification information of the items and evaluates their market value.

[0480] The server suggests the optimal disposal method for unwanted items based on their market value. This suggestion is implemented using AI technology, taking into account the user's past usage history and market trends. Users receive suggestions through application notifications, enabling efficient resale.

[0481] The server's judgment process utilizes machine learning algorithms, and the open-source computer vision library OpenCV is used for image analysis of objects. The user's terminal processes object information using a Python program and sends it to the server.

[0482] As a concrete example, consider a case where a user photographs and registers an unwanted electronic device. In this case, the server analyzes the current market value of the electronic device and suggests the most suitable online marketplace for sale. Furthermore, by utilizing the capabilities of a generative AI model, it is possible to recommend alternative products tailored to the user's interests.

[0483] An example of a prompt for a generative AI model is, "Analyze the value of a smartphone that is not currently in use and suggest the most suitable sales channel."

[0484] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0485] Step 1:

[0486] The user takes a picture of their belongings using their device and inputs information about the items into the device through an application. The input image data is processed as visual data necessary for identifying the items.

[0487] Step 2:

[0488] The device analyzes the captured image data using OpenCV to extract characteristic information about the item. This characteristic information includes the item's shape, brand logo, label information, etc., and serves as basic data for identification. The output is the analyzed item identification information.

[0489] Step 3:

[0490] The analyzed identification information is sent from the terminal to the server. The server registers the received identification information in a database and uses a generative AI model to evaluate its market value. This model calculates the value based on the item's past transaction data and market trends. The output is the item's market value and its detailed information.

[0491] Step 4:

[0492] The server generates notifications to suggest the optimal disposal method to the user based on the calculated market value. Specifically, it uses AI to analyze information on reusable online marketplaces and exchangeable items, and sends this information to the user as a push notification. The output is a specific disposal suggestion sent to the user.

[0493] Step 5:

[0494] The user receives server suggestions via their terminal and selects the most suitable disposal method according to their preferences. The selected information is sent back from the terminal to the server, and processing to initiate redistribution is performed as needed. The output is a notification to the user of the selected redistribution method and the commencement of the associated operations.

[0495] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0496] Embodiments of the present invention provide a system and method that promotes the effective use of possessions by efficiently managing user ownership information and combining it with an emotion engine that recognizes the user's emotional state. This system enables automatic registration of ownership information, proposal of an optimal usage plan for the user, and reuse and redistribution of items.

[0497] Users install a dedicated application on their device and obtain ownership information by taking a picture of an item using the camera or scanning a QR code. The device analyzes this information and sends it to the server. The server registers the received information in a database and manages the items. This eliminates the need for manual registration.

[0498] Furthermore, the server utilizes an emotion engine to recognize the user's emotional state. It analyzes voice and facial expression data in real time to understand the user's emotions. Based on this emotional information, AI technology dynamically generates optimal reading schedules and suggestions for using items for the user, and notifies the device.

[0499] For example, after a user registers a book, if the emotion engine detects the user's calm emotional state, it will suggest books in relaxing genres. Similarly, if the user is feeling stressed, it will suggest books with uplifting content. Furthermore, for items that the user deems unnecessary, it will offer resale options and buyback prices in the market to promote efficient reuse.

[0500] In this way, the present invention provides an embodiment that, by working in conjunction with an emotion engine, further enhances the management and use of possessions and realizes meaningful suggestions for the user.

[0501] The following describes the processing flow.

[0502] Step 1:

[0503] The user launches a dedicated application and obtains ownership information by taking a picture of the item with the device's camera or scanning a QR code.

[0504] Step 2:

[0505] The device analyzes the image or code data it acquires and extracts the item name and related information. This information is then sent to the server.

[0506] Step 3:

[0507] The server registers the received item information in the database and updates the user's ownership list.

[0508] Step 4:

[0509] The emotion engine collects data from the device to analyze the user's voice and facial expressions. This data is collected in real time with the user's consent.

[0510] Step 5:

[0511] The device performs sentiment analysis to identify the user's emotional state (e.g., relaxed, stressed, etc.). The results are then sent to the server.

[0512] Step 6:

[0513] The server uses AI technology to generate optimal item usage suggestions for the user based on emotional and ownership information. This also takes into account past usage history and external factors.

[0514] Step 7:

[0515] The server generates suggestions and sends them to the terminal, notifying the user. The terminal then provides suggestions such as the use of items or rereading schedules tailored to the user's emotions.

[0516] Step 8:

[0517] When a user specifies unwanted items on their device and initiates the resale process, the server displays market prices and resale options.

[0518] Step 9:

[0519] When a user selects an option, the server proceeds with the redistribution process based on that selection. This process is carried out in conjunction with other distribution services.

[0520] Through this series of steps, the system makes suggestions that respond to the user's emotions and supports the management and effective use of their possessions.

[0521] (Example 2)

[0522] Next, we will describe Example 2. 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."

[0523] In recent years, there has been a growing demand for systems that efficiently manage and effectively utilize personal belongings and information. However, conventional systems have faced challenges such as the cumbersome process of registering personal information and the difficulty in proposing plans that take into account the user's emotional state. Furthermore, methods for efficiently reusing unwanted items are still insufficient.

[0524] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0525] In this invention, the server includes means for automatically registering ownership information, means for proposing an optimal activity plan to the user based on the user's emotional state, and means for analyzing emotional data in real time and recognizing the user's emotional state. This not only streamlines the management of possessions but also enables personalized suggestions tailored to the user and effectively promotes the reuse of unwanted items.

[0526] "Ownership information" refers to detailed information about items and related data owned by the user.

[0527] "Automatic registration methods" refer to technologies for registering information about items within a system without requiring manual operation by the user.

[0528] "Means of proposing the optimal activity plan for the user" refers to technology that presents the most appropriate actions and options based on the user's information and circumstances.

[0529] "Emotional data" refers to data that can be obtained from audio and video, indicating the user's emotional state.

[0530] "Real-time analysis" refers to technologies that process data simultaneously with its collection, making the results immediately available for use.

[0531] "Means for recognizing emotional states" refers to technologies for identifying a user's emotions and specifying their state.

[0532] "Means of reuse or redistribution" refers to technologies that efficiently re-evaluate unwanted items based on ownership information, find new use value in them, and then distribute them.

[0533] As an embodiment of this invention, a system is described in which a user, a terminal, and a server cooperate to manage ownership information and realize emotion-based suggestions.

[0534] Users obtain information about their possessions using a device with a dedicated application installed. Specifically, users can obtain detailed information about items by taking a picture of the item using the device's camera or by scanning a QR code. This information includes data that can be accurately read using image analysis technology and identification code parsers.

[0535] The terminal analyzes the acquired information, converts the data into an appropriate format, and sends it to the server. Advanced image recognition algorithms and code analysis libraries are used for the analysis. The server registers the received data in a database, handling the registration and management of owned items. This entire process eliminates the need for users to manually register information.

[0536] Furthermore, the server uses an emotion engine to analyze voice and facial expression data acquired from the user in real time. This makes it possible to accurately recognize the user's emotional state. Based on this emotional information, the server uses a generative AI model to generate prompt sentences and create suggestions based on them.

[0537] For example, if the emotion engine determines that the user is in a calm emotional state and needs to relax, the server generates a prompt in the form of "Please suggest books that will help me relax" and sends it to the AI ​​model. The AI ​​model then generates a list of the most suitable books based on that prompt and presents the results to the user.

[0538] Furthermore, for items owned by the user that the user deems unnecessary, the server presents options for resale in the market or offers a purchase price, thereby promoting the reuse of the items. In this way, the present invention enables efficient management and effective utilization of possessions, and can provide users with a comprehensive range of suggestions.

[0539] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0540] Step 1:

[0541] The user launches a dedicated application installed on their device. With the application open, they use the device's camera to take a picture of an item or scan a QR code. The input is image data or QR code data of the item. This data is analyzed by the device using image analysis or code analysis to extract ownership information of the item. The output is the analyzed item information.

[0542] Step 2:

[0543] The terminal sends analyzed item information to the server. This information includes details such as item name, purchase date, and price. The input is ownership information obtained through image analysis or code analysis. The terminal converts this information into an appropriate format and transfers it to the server via the network. The output is the transferred ownership information data.

[0544] Step 3:

[0545] The server registers ownership information received from the terminal into the database. The input is ownership information data transferred from the terminal. The server checks the data format and registers it in the database while performing data conversion as necessary. The output is the updated database.

[0546] Step 4:

[0547] The server uses an emotion engine to recognize the user's emotional state. Voice data and facial expression data acquired from the user are input. The emotion engine analyzes this data in real time to identify the user's emotional state. The output is the recognized emotional state data.

[0548] Step 5:

[0549] The server uses a generative AI model to create suggestions based on emotional state data and ownership information. The input consists of emotional state data and ownership information. The server sends this data to the AI ​​model as a prompt (e.g., "Please suggest relaxing books"), generating the most suitable suggestions. The output is the generated suggestions.

[0550] Step 6:

[0551] The server notifies the terminal of the generated suggestions. The input is the suggestions obtained from the AI ​​model. The server converts the suggestions into a format that is easy for the user to understand and sends it to the terminal. The output is the displayed suggestions.

[0552] Step 7:

[0553] Users utilize items or reuse unwanted items based on the suggested options. Depending on the user's choices, reuse options or buyback prices for items may be presented. The input is the suggested content notified by the server. The user selects an action based on this. The output is the result of the user's effective use or reuse of the items.

[0554] (Application Example 2)

[0555] Next, we will explain application example 2. In the following explanation, 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."

[0556] Traditional brick-and-mortar retail systems often struggle to provide personalized service based on individual customer emotional states, relying instead on uniform marketing strategies. This makes it difficult to improve customer satisfaction and maximize purchasing intent. Furthermore, there is a challenge in the insufficient promotion of the redistribution and reuse of owned goods, resulting in inefficient utilization of materials.

[0557] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0558] In this invention, the server includes means for automatically registering ownership information and the emotional state of users, means for determining the emotional state of buyers based on the information and providing appropriate product information in real time, and means for efficiently redistributing unwanted items and promoting reuse. This enables personalized sales strategies for individual customers and promotes the effective use of goods.

[0559] "Ownership information" refers to data about items owned by the user, such as information about the item's name, type, value, and usage status.

[0560] "User's emotional state" refers to the user's emotional tendencies at that particular moment, including states such as comfort, relaxation, and stress.

[0561] "Image analysis" is a technology that uses digital video data to extract the characteristics of an object and analyze that information.

[0562] "Code recognition" is a technology that reads codes such as QR codes and barcodes and retrieves related information.

[0563] A "buyer" refers to an individual or legal entity that intends to purchase goods or services.

[0564] "Intelligent technology" refers to technology that uses artificial intelligence to analyze things and make appropriate judgments and suggestions.

[0565] "Redistribution" refers to the process of bringing goods that have already been put on the market back into circulation, making them ready for sale again.

[0566] "Reuse" refers to the act of using unwanted items again in a different form, and is an act of making efficient use of resources without waste.

[0567] The central element of this system is a program that automatically registers and manages ownership information and the emotional state of users. This system is implemented using smartphones, smart glasses, and servers.

[0568] First, the user takes a picture of their belongings with the camera on their smartphone or smart glasses, and the system performs image analysis or code recognition. This utilizes image recognition software such as the Google Cloud Vision API. The recognized information is sent from the device to the server. The server registers this data in a database and manages it as ownership information.

[0569] Next, to assess the user's emotional state, real-time facial and audio data is collected from the device. This utilizes a camera and microphone to capture the user's facial expressions. The collected data is then analyzed using emotion analysis tools such as the Azure Emotion API to determine the user's emotional state.

[0570] Based on this data, the server understands the buyer's emotional state and uses artificial intelligence to generate product information tailored to the user. By utilizing intelligent technology, it's possible to provide products and special offers that match a specific buyer's historical usage patterns and current emotional state. For example, if a buyer is determined to be relaxed, they will be offered product information and special sale announcements appropriate for that state. In this way, the individual buyer's experience is personalized, improving satisfaction.

[0571] As a concrete example, if facial analysis reveals that a customer is relaxed while in a store, special discount information will be immediately displayed to that customer through smart glasses. This is expected to attract the customer's attention and increase their willingness to purchase. An example of a prompt message provided by the generating AI model is, "Immediately recommend special discount information to the relaxed customer."

[0572] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0573] Step 1:

[0574] The user takes a picture of an item using a smartphone or smart glasses. The device receives the captured image data as input and performs image analysis using the Google Cloud Vision API. As a result, ownership information such as the item's name and category is output.

[0575] Step 2:

[0576] Ownership information is sent from the terminal to the server. The server registers and manages the ownership information received as input in its database. This information is also used to update the user's list of owned items.

[0577] Step 3:

[0578] The device captures the user's facial expressions and voice in real time. The data collected using the camera and microphone is analyzed using the Azure Emotion API. The input for this analysis is real-time facial expression and voice data, and the output is the user's emotional state.

[0579] Step 4:

[0580] The server generates appropriate product information and suggestions based on the user's emotional state and ownership information. Utilizing intelligent technology, it analyzes data based on the input emotional state and historical usage trends, and uses prompts to generate appropriate product information. This output becomes personalized product information and special offers for each individual user.

[0581] Step 5:

[0582] The generated product information is sent from the server to the terminal. Users receive this information in real time via smart glasses or smartphones. This output functions as marketing information to increase the user's purchasing intent.

[0583] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0584] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0585] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0586] [Fourth Embodiment]

[0587] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0588] As shown in Figure 7, the 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.

[0589] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0590] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0591] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0592] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0593] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0594] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0595] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0596] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0597] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0598] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0599] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0600] Embodiments of the present invention provide a system and method for efficiently managing ownership information and promoting reuse or redistribution. Users utilize the present invention by installing a dedicated application on their terminal. First, the user obtains information about an item they own by taking a picture of the item using the terminal's camera or by scanning a QR code. The terminal analyzes this obtained information to generate identification information and transmits it to a server.

[0601] The server registers item information in a database based on the received identification information. This database is responsible for aggregating and managing information on all items owned by the user. The registered information is used as basic data to provide the user with various usage suggestions. The server uses AI technology to analyze the user's usage history and preferences based on the registered ownership information. This generates an optimal usage plan for the user, which is then proposed to the user via email or app notifications.

[0602] Furthermore, users can specify items they deem unnecessary. Based on this information, the server presents the user with market buy prices and resale options. This allows users to route unwanted items to appropriate resale channels, promoting the effective use of goods.

[0603] As a concrete example, when a user registers a book, registration is completed by taking a picture of the book's cover with the device's camera. The server analyzes the genres of books the user has read in the past and uses AI to predict and suggest books that the user might enjoy reading next. If a book is unwanted, its resale value or potential exchange partners are suggested, enabling further circulation. In this way, the present invention provides a form that comprehensively supports the management and use of a user's possessions.

[0604] The following describes the processing flow.

[0605] Step 1:

[0606] The user launches a dedicated application and either takes a picture of their belongings with the device's camera or scans a QR code.

[0607] Step 2:

[0608] The device either analyzes object information from an image using optical character recognition (OCR) technology, or obtains information directly from a code.

[0609] Step 3:

[0610] The terminal sends the analyzed or acquired item information to the server and requests its registration in the database.

[0611] Step 4:

[0612] The server registers the received item information in the database and checks for duplicates by comparing it with existing ownership information.

[0613] Step 5:

[0614] The server uses AI to analyze the user's past usage history and external factors, and generates an optimal usage plan based on their possessions.

[0615] Step 6:

[0616] The server generates a usage plan and notifies the terminal, presenting the suggested plan to the user.

[0617] Step 7:

[0618] Users can designate unwanted items on the app on their device and initiate the process of redistributing or reusing them.

[0619] Step 8:

[0620] The server calculates the market purchase price and resale options for the specified item and presents them to the user.

[0621] Step 9:

[0622] The user selects their preferred method from the presented resale options and confirms the procedure via the terminal.

[0623] In this way, the entire system functions, enabling the management and effective use of users' possessions.

[0624] (Example 1)

[0625] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0626] The challenge lies in addressing the difficulty in providing users with optimal usage plans while simultaneously promoting the effective use of goods by enabling owners to efficiently manage their possessions and facilitate their reuse and redistribution. In particular, there is a need to reduce the burden of manually managing information about possessions and to provide advanced usage suggestions using AI technology.

[0627] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0628] In this invention, the server includes a terminal device that automatically registers ownership information, a computing device that proposes an optimal usage plan to the user based on that ownership information, and means for recirculating unwanted possessions. This streamlines the management of ownership information and enables appropriate usage suggestions to the user and the recirculation of unwanted items.

[0629] "Ownership information" refers to detailed data about items owned by individual users, including item identification information and attribute information.

[0630] A "terminal device" is a device operated by the user, equipped with a camera, display, etc., to acquire and display information about items.

[0631] A "computational device" is a device that analyzes data based on owned information and plays a role in generating an optimal usage plan using AI technology.

[0632] A "generative AI model" refers to artificial intelligence technology used to analyze ownership information and usage history, and to make data-driven predictions and suggestions.

[0633] An "image processing device" refers to a device or software that analyzes image data of an object and extracts necessary information.

[0634] A "code analysis device" is a device or software used to read coded information such as QR codes and barcodes and convert it into data.

[0635] The system of the present invention is designed to efficiently manage ownership information, provide optimal usage plans, and facilitate the redistribution of goods. Specific embodiments thereof are described below.

[0636] The user installs a dedicated application on their device. This device is a standard smartphone or tablet equipped with a camera and a QR code reader. The application provides an interface for the user to manage items and analyzes images and codes that are captured.

[0637] When a user photographs an item, the device uses image processing software to extract the necessary information from the image. Similarly, when a QR code is scanned, code analysis software accurately reads the data. This generates identification information for the item.

[0638] The device sends the generated identification information to the server. This server uses an advanced database management system to efficiently register and manage item information. Based on this information, the server utilizes a generative AI model to analyze the user's past usage history and preferences. This generates an optimal usage plan for the user, which is then suggested via app notifications and email.

[0639] As a concrete example, when a user manages the books they own at home, they take a picture of the book's cover with the device's camera. The device reads the corresponding ISBN code and other information and sends it to the server. The server generates suggestions for the next book to read based on the user's past reading history. An example of a prompt to the generating AI model in this case would be, "Please provide information to make the best next purchase suggestion based on the user's past purchase history."

[0640] Furthermore, when a user selects unwanted items from their management list, the server provides market price data and information on available exchange channels. Based on this information, the user can efficiently redistribute the items. This comprehensively supports the effective use and management of possessions.

[0641] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0642] Step 1:

[0643] The user installs a dedicated application on their device and begins acquiring information about an item. Specifically, the user either takes a picture of the item (e.g., a book) with their camera or scans a QR code. The input at this time is the camera image or QR code data, and the output is the initial data necessary for identifying the item.

[0644] Step 2:

[0645] The terminal analyzes the acquired image or code data. Using image processing software, it extracts text information and barcode information from the image. Through this analysis process, the raw image data as input is converted into item identification information as output. Specifically, it performs ISBN code reading using optical character recognition technology.

[0646] Step 3:

[0647] The terminal sends the generated identification information to the server. This communication is conducted securely over the internet. The input is the identification information, and the output is the status of the completion of data transfer to the server. Specifically, this operation includes data transmission using the HTTPS protocol.

[0648] Step 4:

[0649] The server registers the received identification information in the database. This registration process stores the item information within the server. The input is the identification information sent from the terminal, and the output is the database update status indicating that the item has been registered. Specifically, an insertion operation is performed in the database using an SQL statement.

[0650] Step 5:

[0651] The server uses a generative AI model to analyze the user's usage history and preferences based on information in the database. The input for this analysis is the user's past database information, and the output is a suggestion of the optimal usage plan for the user. Specifically, it analyzes past reading history and suggests relevant new books.

[0652] Step 6:

[0653] The server notifies the user of the usage plan generated based on the analysis results. The input is the suggested data generated by the AI ​​model, and the output is the notification information sent to the user. Specifically, the suggested information is sent via the app's notification function or email service.

[0654] Step 7:

[0655] The user selects unwanted items within the application and sends that information to the server. The input is the selected items, and the output is the update status of the unwanted item information sent to the server. Specifically, the unwanted items are tagged using the UI.

[0656] Step 8:

[0657] The server analyzes information on unwanted items and presents the user with the market value and resale options for those items. The input is information on unwanted items submitted by the user, and the output is market value data and resale suggestions. Specifically, it collects, analyzes, and provides real-time market data.

[0658] (Application Example 1)

[0659] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0660] Consumers own many items in their daily lives, but there is a lack of efficient means to manage and recycle them. In particular, finding ways to dispose of unwanted items or options for reuse is difficult and time-consuming when done individually. There is a need to provide a system that solves this problem and promotes the effective use of possessions.

[0661] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0662] In this invention, the server includes means for automatically registering ownership information, means for suggesting the most suitable usage plan to the user based on that ownership information, means for efficiently reusing or redistributing ownership information that is no longer needed, and means for analyzing the market value of registered items and suggesting the most suitable disposal method. This enables users to efficiently manage and redistribute their possessions.

[0663] "Possession information" refers to identifiable information about all items owned by the user, including a record of the characteristics and condition of those items.

[0664] "Methods for automatic registration" refers to technologies that include a process of registering information about an item into a system without human intervention by photographing or scanning the item.

[0665] "Means of suggesting usage plans" refers to a function within the system that presents users with the most suitable plan for using items based on registered ownership information.

[0666] "Means of reuse or redistribution" refers to a function that embodies the process of making unwanted personal information usable again or circulating it in the market.

[0667] "Methods for analyzing market value" refer to techniques that utilize information about an item to evaluate and calculate how much value that item has in the market.

[0668] "Means of proposing the optimal disposal method" refers to the function of a system that presents the most effective and economical disposal method for an item, based on its condition and market value.

[0669] This invention is a system that efficiently manages users' possessions and promotes reuse and redistribution. Users automatically register their ownership information by taking a picture of their items with their smartphone's camera or scanning a QR code. The registered information is sent to a server, which processes this information in various ways. Specifically, the server analyzes the identification information of the items and evaluates their market value.

[0670] The server suggests the optimal disposal method for unwanted items based on their market value. This suggestion is implemented using AI technology, taking into account the user's past usage history and market trends. Users receive suggestions through application notifications, enabling efficient resale.

[0671] The server's judgment process utilizes machine learning algorithms, and the open-source computer vision library OpenCV is used for image analysis of objects. The user's terminal processes object information using a Python program and sends it to the server.

[0672] As a concrete example, consider a case where a user photographs and registers an unwanted electronic device. In this case, the server analyzes the current market value of the electronic device and suggests the most suitable online marketplace for sale. Furthermore, by utilizing the capabilities of a generative AI model, it is possible to recommend alternative products tailored to the user's interests.

[0673] An example of a prompt for a generative AI model is, "Analyze the value of a smartphone that is not currently in use and suggest the most suitable sales channel."

[0674] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0675] Step 1:

[0676] The user takes a picture of their belongings using their device and inputs information about the items into the device through an application. The input image data is processed as visual data necessary for identifying the items.

[0677] Step 2:

[0678] The device analyzes the captured image data using OpenCV to extract characteristic information about the item. This characteristic information includes the item's shape, brand logo, label information, etc., and serves as basic data for identification. The output is the analyzed item identification information.

[0679] Step 3:

[0680] The analyzed identification information is sent from the terminal to the server. The server registers the received identification information in a database and uses a generative AI model to evaluate its market value. This model calculates the value based on the item's past transaction data and market trends. The output is the item's market value and its detailed information.

[0681] Step 4:

[0682] The server generates notifications to suggest the optimal disposal method to the user based on the calculated market value. Specifically, it uses AI to analyze information on reusable online marketplaces and exchangeable items, and sends this information to the user as a push notification. The output is a specific disposal suggestion sent to the user.

[0683] Step 5:

[0684] The user receives server suggestions via their terminal and selects the most suitable disposal method according to their preferences. The selected information is sent back from the terminal to the server, and processing to initiate redistribution is performed as needed. The output is a notification to the user of the selected redistribution method and the commencement of the associated operations.

[0685] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0686] Embodiments of the present invention provide a system and method that promotes the effective use of possessions by efficiently managing user ownership information and combining it with an emotion engine that recognizes the user's emotional state. This system enables automatic registration of ownership information, proposal of an optimal usage plan for the user, and reuse and redistribution of items.

[0687] Users install a dedicated application on their device and obtain ownership information by taking a picture of an item using the camera or scanning a QR code. The device analyzes this information and sends it to the server. The server registers the received information in a database and manages the items. This eliminates the need for manual registration.

[0688] Furthermore, the server utilizes an emotion engine to recognize the user's emotional state. It analyzes voice and facial expression data in real time to understand the user's emotions. Based on this emotional information, AI technology dynamically generates optimal reading schedules and suggestions for using items for the user, and notifies the device.

[0689] For example, after a user registers a book, if the emotion engine detects the user's calm emotional state, it will suggest books in relaxing genres. Similarly, if the user is feeling stressed, it will suggest books with uplifting content. Furthermore, for items that the user deems unnecessary, it will offer resale options and buyback prices in the market to promote efficient reuse.

[0690] In this way, the present invention provides an embodiment that, by working in conjunction with an emotion engine, further enhances the management and use of possessions and realizes meaningful suggestions for the user.

[0691] The following describes the processing flow.

[0692] Step 1:

[0693] The user launches a dedicated application and obtains ownership information by taking a picture of the item with the device's camera or scanning a QR code.

[0694] Step 2:

[0695] The device analyzes the image or code data it acquires and extracts the item name and related information. This information is then sent to the server.

[0696] Step 3:

[0697] The server registers the received item information in the database and updates the user's ownership list.

[0698] Step 4:

[0699] The emotion engine collects data from the device to analyze the user's voice and facial expressions. This data is collected in real time with the user's consent.

[0700] Step 5:

[0701] The device performs sentiment analysis to identify the user's emotional state (e.g., relaxed, stressed, etc.). The results are then sent to the server.

[0702] Step 6:

[0703] The server uses AI technology to generate optimal item usage suggestions for the user based on emotional and ownership information. This also takes into account past usage history and external factors.

[0704] Step 7:

[0705] The server generates suggestions and sends them to the terminal, notifying the user. The terminal then provides suggestions such as the use of items or rereading schedules tailored to the user's emotions.

[0706] Step 8:

[0707] When a user specifies unwanted items on their device and initiates the resale process, the server displays market prices and resale options.

[0708] Step 9:

[0709] When a user selects an option, the server proceeds with the redistribution process based on that selection. This process is carried out in conjunction with other distribution services.

[0710] Through this series of steps, the system makes suggestions that respond to the user's emotions and supports the management and effective use of their possessions.

[0711] (Example 2)

[0712] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0713] In recent years, there has been a growing demand for systems that efficiently manage and effectively utilize personal belongings and information. However, conventional systems have faced challenges such as the cumbersome process of registering personal information and the difficulty in proposing plans that take into account the user's emotional state. Furthermore, methods for efficiently reusing unwanted items are still insufficient.

[0714] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0715] In this invention, the server includes means for automatically registering ownership information, means for proposing an optimal activity plan to the user based on the user's emotional state, and means for analyzing emotional data in real time and recognizing the user's emotional state. This not only streamlines the management of possessions but also enables personalized suggestions tailored to the user and effectively promotes the reuse of unwanted items.

[0716] "Ownership information" refers to detailed information about items and related data owned by the user.

[0717] "Automatic registration methods" refer to technologies for registering information about items within a system without requiring manual operation by the user.

[0718] "Means of proposing the optimal activity plan for the user" refers to technology that presents the most appropriate actions and options based on the user's information and circumstances.

[0719] "Emotional data" refers to data that can be obtained from audio and video, indicating the user's emotional state.

[0720] "Real-time analysis" refers to technologies that process data simultaneously with its collection, making the results immediately available for use.

[0721] "Means for recognizing emotional states" refers to technologies for identifying a user's emotions and specifying their state.

[0722] "Means of reuse or redistribution" refers to technologies that efficiently re-evaluate unwanted items based on ownership information, find new use value in them, and then distribute them.

[0723] As an embodiment of this invention, a system is described in which a user, a terminal, and a server cooperate to manage ownership information and realize emotion-based suggestions.

[0724] Users obtain information about their possessions using a device with a dedicated application installed. Specifically, users can obtain detailed information about items by taking a picture of the item using the device's camera or by scanning a QR code. This information includes data that can be accurately read using image analysis technology and identification code parsers.

[0725] The terminal analyzes the acquired information, converts the data into an appropriate format, and sends it to the server. Advanced image recognition algorithms and code analysis libraries are used for the analysis. The server registers the received data in a database, handling the registration and management of owned items. This entire process eliminates the need for users to manually register information.

[0726] Furthermore, the server uses an emotion engine to analyze voice and facial expression data acquired from the user in real time. This makes it possible to accurately recognize the user's emotional state. Based on this emotional information, the server uses a generative AI model to generate prompt sentences and create suggestions based on them.

[0727] For example, if the emotion engine determines that the user is in a calm emotional state and needs to relax, the server generates a prompt in the form of "Please suggest books that will help me relax" and sends it to the AI ​​model. The AI ​​model then generates a list of the most suitable books based on that prompt and presents the results to the user.

[0728] Furthermore, for items owned by the user that the user deems unnecessary, the server presents options for resale in the market or offers a purchase price, thereby promoting the reuse of the items. In this way, the present invention enables efficient management and effective utilization of possessions, and can provide users with a comprehensive range of suggestions.

[0729] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0730] Step 1:

[0731] The user launches a dedicated application installed on their device. With the application open, they use the device's camera to take a picture of an item or scan a QR code. The input is image data or QR code data of the item. This data is analyzed by the device using image analysis or code analysis to extract ownership information of the item. The output is the analyzed item information.

[0732] Step 2:

[0733] The terminal sends analyzed item information to the server. This information includes details such as item name, purchase date, and price. The input is ownership information obtained through image analysis or code analysis. The terminal converts this information into an appropriate format and transfers it to the server via the network. The output is the transferred ownership information data.

[0734] Step 3:

[0735] The server registers ownership information received from the terminal into the database. The input is ownership information data transferred from the terminal. The server checks the data format and registers it in the database while performing data conversion as necessary. The output is the updated database.

[0736] Step 4:

[0737] The server uses an emotion engine to recognize the user's emotional state. Voice data and facial expression data acquired from the user are input. The emotion engine analyzes this data in real time to identify the user's emotional state. The output is the recognized emotional state data.

[0738] Step 5:

[0739] The server uses a generative AI model to create suggestions based on emotional state data and ownership information. The input consists of emotional state data and ownership information. The server sends this data to the AI ​​model as a prompt (e.g., "Please suggest relaxing books"), generating the most suitable suggestions. The output is the generated suggestions.

[0740] Step 6:

[0741] The server notifies the terminal of the generated suggestions. The input is the suggestions obtained from the AI ​​model. The server converts the suggestions into a format that is easy for the user to understand and sends it to the terminal. The output is the displayed suggestions.

[0742] Step 7:

[0743] Users utilize items or reuse unwanted items based on the suggested options. Depending on the user's choices, reuse options or buyback prices for items may be presented. The input is the suggested content notified by the server. The user selects an action based on this. The output is the result of the user's effective use or reuse of the items.

[0744] (Application Example 2)

[0745] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0746] Traditional brick-and-mortar retail systems often struggle to provide personalized service based on individual customer emotional states, relying instead on uniform marketing strategies. This makes it difficult to improve customer satisfaction and maximize purchasing intent. Furthermore, there is a challenge in the insufficient promotion of the redistribution and reuse of owned goods, resulting in inefficient utilization of materials.

[0747] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0748] In this invention, the server includes means for automatically registering ownership information and the emotional state of users, means for determining the emotional state of buyers based on the information and providing appropriate product information in real time, and means for efficiently redistributing unwanted items and promoting reuse. This enables personalized sales strategies for individual customers and promotes the effective use of goods.

[0749] "Ownership information" refers to data about items owned by the user, such as information about the item's name, type, value, and usage status.

[0750] "User's emotional state" refers to the user's emotional tendencies at that particular moment, including states such as comfort, relaxation, and stress.

[0751] "Image analysis" is a technology that uses digital video data to extract the characteristics of an object and analyze that information.

[0752] "Code recognition" is a technology that reads codes such as QR codes and barcodes and retrieves related information.

[0753] A "buyer" refers to an individual or legal entity that intends to purchase goods or services.

[0754] "Intelligent technology" refers to technology that uses artificial intelligence to analyze things and make appropriate judgments and suggestions.

[0755] "Redistribution" refers to the process of bringing goods that have already been put on the market back into circulation, making them ready for sale again.

[0756] "Reuse" refers to the act of using unwanted items again in a different form, and is an act of making efficient use of resources without waste.

[0757] The central element of this system is a program that automatically registers and manages ownership information and the emotional state of users. This system is implemented using smartphones, smart glasses, and servers.

[0758] First, the user takes a picture of their belongings with the camera on their smartphone or smart glasses, and the system performs image analysis or code recognition. This utilizes image recognition software such as the Google Cloud Vision API. The recognized information is sent from the device to the server. The server registers this data in a database and manages it as ownership information.

[0759] Next, to assess the user's emotional state, real-time facial and audio data is collected from the device. This utilizes a camera and microphone to capture the user's facial expressions. The collected data is then analyzed using emotion analysis tools such as the Azure Emotion API to determine the user's emotional state.

[0760] Based on this data, the server understands the buyer's emotional state and uses artificial intelligence to generate product information tailored to the user. By utilizing intelligent technology, it's possible to provide products and special offers that match a specific buyer's historical usage patterns and current emotional state. For example, if a buyer is determined to be relaxed, they will be offered product information and special sale announcements appropriate for that state. In this way, the individual buyer's experience is personalized, improving satisfaction.

[0761] As a concrete example, if facial analysis reveals that a customer is relaxed while in a store, special discount information will be immediately displayed to that customer through smart glasses. This is expected to attract the customer's attention and increase their willingness to purchase. An example of a prompt message provided by the generating AI model is, "Immediately recommend special discount information to the relaxed customer."

[0762] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0763] Step 1:

[0764] The user takes a picture of an item using a smartphone or smart glasses. The device receives the captured image data as input and performs image analysis using the Google Cloud Vision API. As a result, ownership information such as the item's name and category is output.

[0765] Step 2:

[0766] Ownership information is sent from the terminal to the server. The server registers and manages the ownership information received as input in its database. This information is also used to update the user's list of owned items.

[0767] Step 3:

[0768] The device captures the user's facial expressions and voice in real time. The data collected using the camera and microphone is analyzed using the Azure Emotion API. The input for this analysis is real-time facial expression and voice data, and the output is the user's emotional state.

[0769] Step 4:

[0770] The server generates appropriate product information and suggestions based on the user's emotional state and ownership information. Utilizing intelligent technology, it analyzes data based on the input emotional state and historical usage trends, and uses prompts to generate appropriate product information. This output becomes personalized product information and special offers for each individual user.

[0771] Step 5:

[0772] The generated product information is sent from the server to the terminal. Users receive this information in real time via smart glasses or smartphones. This output functions as marketing information to increase the user's purchasing intent.

[0773] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0774] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0775] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0776] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0777] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0778] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0779] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0780] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0781] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0782] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0783] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0784] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0785] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0786] 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.

[0787] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0788] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0789] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0790] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0791] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0792] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0793] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0794] The following is further disclosed regarding the embodiments described above.

[0795] (Claim 1)

[0796] A means of automatically registering ownership information,

[0797] A means of suggesting the most suitable reading schedule to the user based on their ownership information,

[0798] Means for efficiently reusing or redistributing unwanted personal information,

[0799] A system that includes this.

[0800] (Claim 2)

[0801] The system according to claim 1, wherein the ownership information is collected using image recognition or code analysis.

[0802] (Claim 3)

[0803] The system according to claim 1, wherein the proposed means uses artificial intelligence technology to create an optimal plan based on the user's historical usage patterns and external factors.

[0804] "Example 1"

[0805] (Claim 1)

[0806] A terminal device that automatically registers ownership information,

[0807] A computing device that proposes the optimal usage plan to the user based on the ownership information,

[0808] Means of recirculating unwanted possessions,

[0809] A means equipped with a generative AI model for analyzing the user's past usage history and preferences,

[0810] A system that includes this.

[0811] (Claim 2)

[0812] The system according to claim 1, wherein the aforementioned ownership information is acquired by an image processing device or a code analysis device.

[0813] (Claim 3)

[0814] The system according to claim 1, wherein the computing device uses artificial intelligence technology to create an optimal plan based on the user's historical usage patterns.

[0815] "Application Example 1"

[0816] (Claim 1)

[0817] A means of automatically registering ownership information,

[0818] A means of proposing the most suitable usage plan to the user based on that ownership information,

[0819] Means for efficiently reusing or redistributing unwanted personal information,

[0820] A means of analyzing the market value of registered items and proposing the optimal disposal method,

[0821] A system that includes this.

[0822] (Claim 2)

[0823] The system according to claim 1, wherein the ownership information is collected using visual data recognition or coding analysis.

[0824] (Claim 3)

[0825] The system according to claim 1, wherein the proposed means uses machine learning technology to create an optimal plan based on the user's past usage patterns and environmental conditions.

[0826] "Example 2 of combining an emotion engine"

[0827] (Claim 1)

[0828] A means of automatically registering ownership information,

[0829] A means of proposing an optimal activity plan to the user based on their possessed information and emotional state,

[0830] A means of analyzing emotional data in real time to recognize the user's emotional state,

[0831] Means for efficiently reusing or redistributing unwanted personal information,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, wherein the ownership information is collected using image analysis or identification code analysis.

[0835] (Claim 3)

[0836] The system according to claim 1, wherein the proposed means uses generative artificial intelligence technology to create an optimal plan based on the user's historical usage patterns and external factors.

[0837] "Application example 2 when combining with an emotional engine"

[0838] (Claim 1)

[0839] A means for automatically registering ownership information and the emotional state of users,

[0840] A means to determine the emotional state of the buyer based on that information and provide appropriate product information in real time,

[0841] A means to efficiently redistribute unwanted items and promote reuse,

[0842] A system that includes this.

[0843] (Claim 2)

[0844] The system according to claim 1, wherein the ownership information is collected using image analysis or code recognition.

[0845] (Claim 3)

[0846] The system according to claim 1, wherein the proposed means uses intelligent technology to generate optimal product information based on the buyer's historical usage trends and external factors. [Explanation of Symbols]

[0847] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of automatically registering ownership information, A means of suggesting the most suitable reading schedule to the user based on their ownership information, Means for efficiently reusing or redistributing unwanted personal information, A system that includes this.

2. The system according to claim 1, wherein the aforementioned ownership information is collected using image recognition or code analysis.

3. The system according to claim 1, wherein the proposed means uses artificial intelligence technology to create an optimal plan based on the user's historical usage patterns and external factors.

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