System

Abstract

A system is provided.SOLUTION: The system includes a means for receiving family register information uploaded from a user, a means for analyzing the received family register information and extracting necessary data, a means for storing the extracted data in a central database, a means for extracting data from the central database and generating a past register and a family tree, and a means for storing the generated past register and family tree in a cloud system.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Currently, each city, ward, town, and village must spend a huge amount of time and money to collect family register information and create death registers and family trees. Issues also exist regarding legal procedures and the appropriate handling of personal information. Furthermore, manual information management is required every time family register information is updated, necessitating the re-creation of death registers and family trees. These issues reduce the efficiency of administrative work and impair the quality of public services. The objective of this invention is to solve these problems and provide a system that automatically creates up-to-date death registers and family trees efficiently and accurately. [Means for solving the problem]

[0005] The present invention provides a system that receives family register information uploaded by users, analyzes that information, extracts necessary data, and stores it in a central database. Specifically, the system includes the following means: a means for receiving family register information uploaded by users, a means for converting the received family register information into digital text using OCR technology, analyzing it, and extracting necessary data, a means for storing the extracted data in a central database, a means for extracting data from the central database to generate a death register and family tree, and a means for storing the generated death register and family tree in a cloud system. The system also includes a means for generating the death register and family tree using generation AI. This streamlines the collection, management, and updating of family register information, and realizes a system that always automatically generates the latest death register and family tree.

[0006] "User" means an individual or organization that uses the System to upload family register information and generate death registers and family trees from that information.

[0007] "Upload" is the operation of sending a digital file (e.g., a family register copy) owned by the user to the system.

[0008] "Family register information" is data related to a person's family register, including details such as the person's name, date of birth, and parent-child relationships.

[0009] "Means of receiving" refers to the function that the system uses to obtain family register information uploaded by users.

[0010] "Analysis" is the process of deciphering the received household registration information and identifying and extracting the necessary data.

[0011] "Data extraction" is the act of selecting specific items (e.g., name, date of birth) from family register information.

[0012] The "central database" is a database for centrally storing and managing extracted data.

[0013] "Storage means" refers to the functionality for storing the analyzed and extracted data in a central database.

[0014] "Means for extracting data" refers to the function of extracting data from the central database according to specific conditions.

[0015] "Means of generation" refers to the process of creating a family register or family tree based on the extracted data.

[0016] "Generated family registers and genealogies" are genealogies and history books that are automatically created based on the user's family register information.

[0017] A "cloud system" is a remote server system for storing, managing, and accessing data over the Internet.

[0018] "Means for storage" refers to the function for storing the generated family registers and genealogies in a cloud system.

[0019] "OCR technology" is an optical character recognition technology that converts characters contained in paper media or image data into digital text.

[0020] "Generative AI" is an artificial intelligence technology that processes large amounts of data and automatically generates death registers and family trees. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0023] First, the terms used in the following description will be explained.

[0024] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0025] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0026] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0027] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0028] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0032] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0033] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0034] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0036] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0039] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0040] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0041] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0042] This invention is a system that automatically creates up-to-date family registers and genealogies using a central database and cloud-based system based on family register information collected from users' permanent domiciles. The system consists of a user upload, data analysis and extraction, storage in the database, generation of family registers and genealogies using AI, and storage in the cloud system.

[0043] System configuration and specific operation

[0044] 1. User Action:

[0045] Users save the family register information they have obtained at their permanent domicile as a digital file and upload it to the system through the system's web interface. Uploading involves the user selecting and submitting a file using a file selection dialog.

[0046] Example: A user uploads "koseki_tanaka.pdf" to the system.

[0047] 2. Terminal processing:

[0048] The device initially checks the received file to ensure that it is in the correct file format (PDF, JPEG, PNG, etc.). If the file can be read successfully, it is stored in a temporary storage area and prepared for transmission to the server.

[0049] 3. Server processing:

[0050] The server receives the file sent from the device and converts it into digital text using an OCR (Optical Character Recognition) engine. At this time, the server analyzes the text information extracted by OCR and extracts necessary data (such as name, date of birth, parent-child relationship, etc.).

[0051] The extracted data is structured and stored in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[0052] 4. Data extraction and formatting:

[0053] The server extracts specific family information from a central database in response to a user's request, then uses generative AI to format the extracted data into a suitable format for a family register or family tree, creating a generational list and arranging the data based on parent-child relationships.

[0054] Example: The server extracts all data related to the Tanaka family and formats it appropriately to generate a family tree for the "Tanaka family."

[0055] 5. Report generation using generative AI:

[0056] The AI ​​then generates a family register and family tree based on the data formatted by the server, which are then stored in a cloud system.

[0057] Example: The generation AI generates a family tree for the "Tanaka family" and saves it in cloud storage as "Tanaka family genealogy.pdf."

[0058] 6. Use of cloud systems:

[0059] The generated family registers and family trees are stored in a cloud system and can be accessed online via the internet, allowing users to view the most up-to-date family trees.

[0060] Specific examples

[0061] 1. User uploads family register information:

[0062] The user uploads "koseki_tanaka.pdf" through the web interface.

[0063] The terminal receives the file and performs an initial check to send it to the server.

[0064] 2. The server analyzes and extracts the data and registers it in the database:

[0065] The server uses an OCR engine to analyze the file and extract information such as "Taro Tanaka, born January 1, 1990" as digital text, which is then stored in a database.

[0066] 3. Data shaping and generative AI:

[0067] Based on the user's request, the server extracts data about the "Tanaka family" and uses a generation AI to generate "Tanaka family tree.pdf."

[0068] 4. Cloud storage and use:

[0069] The server stores the generated family tree in a cloud system, and users can view the latest family tree online through a web interface.

[0070] In this way, the system provides a series of operations that allow users to efficiently and accurately create family registers and genealogies, and keep the information up to date at all times.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] The user saves the family register information obtained from their permanent domicile as a digital file and accesses the system's web interface. The user clicks the "Upload" button, selects the family register file (e.g., "koseki_tanaka.pdf") from the file selection dialog, and uploads it.

[0074] Step 2:

[0075] The device receives the uploaded file and performs an initial check. It checks whether the file format is appropriate (PDF, JPEG, PNG, etc.) and whether the file can be loaded correctly. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[0076] Step 3:

[0077] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The OCR engine then analyzes the extracted text information to identify and extract the necessary data (such as name, date of birth, and parent-child relationship).

[0078] Step 4:

[0079] The server structures the extracted data and stores it in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[0080] Step 5:

[0081] When a user requests the generation of a family register or family tree, the server extracts data from the central database based on the specified criteria, and then uses the generation AI to format the extracted data and convert it into a format suitable for the family register or family tree.

[0082] Step 6:

[0083] The server saves the generated family register and family tree in the cloud system. The generated family register and family tree are uploaded to the cloud storage as, for example, "Tanaka Family Genealogy.pdf."

[0084] Step 7:

[0085] Users access the cloud system and view the latest family records and genealogy through a web interface, allowing them to access the latest information at any time.

[0086] Step 8:

[0087] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the change and updates the central database. Based on the updated information, the AI ​​generates new family registers and family trees, which are then stored in the cloud system.

[0088] Example 1

[0089] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0090] In conventional family register information management systems, digitizing and analyzing family register information required a great deal of time and effort. Furthermore, updating the digitized data and generating genealogy information in an appropriate format was done manually, resulting in issues with accuracy and efficiency. This made it difficult for users to quickly obtain the latest genealogy information.

[0091] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0092] In this invention, the server includes a means for receiving family register information uploaded by users, a means for converting the received family register information into digital text using optical character recognition technology, a means for extracting necessary data and storing it in a central database, a means for generating genealogy information using artificial intelligence, and a means for storing the generated genealogy information in a cloud computing system, thereby enabling users to efficiently and accurately obtain the latest genealogy information.

[0093] "User" means an individual or corporation that uses this system to upload family register information and generate and view genealogy information.

[0094] "Family register information" refers to public records that include names, dates of birth, parent-child relationships, etc.

[0095] "Means for receiving" means a device or process for retrieving digital files uploaded by users onto the server.

[0096] "Means for analyzing and extracting necessary data" refers to a method or device that identifies and extracts important information (e.g., name, date of birth, parentage, etc.) from the received digital file.

[0097] "Optical character recognition technology" refers to technology that extracts text data from images or scanned documents.

[0098] "Digital text" refers to text data converted from an image or scan using optical character recognition technology.

[0099] "Central database" refers to a database system that centrally manages extracted and stored data.

[0100] "Genealogy information" refers to data showing family lineage and historical lineage, such as family trees and death registers.

[0101] "Generative AI" refers to an AI technology that generates new information (e.g., family trees or death registers) in a specified format based on given data.

[0102] A "cloud computing system" is a service that stores data on the Internet and allows users to access it remotely.

[0103] This invention is a system that automatically generates up-to-date genealogy information based on family register information collected by users from their registered domiciles, using a central database and a cloud computing system.

[0104] First, the user saves the family register information obtained from their permanent domicile as a digital file. This digital file can be in a format such as PDF, JPEG, or PNG. Next, the user uploads this digital file to the system through the web interface. For example, the user selects "koseki_sample.pdf" and clicks the upload button to send it to the system.

[0105] The device performs an initial check of the file received from the user, confirming that the file format is correct and testing that it can be read successfully. If the file is confirmed, it is stored in a temporary storage area and prepared for transmission to the server.

[0106] The server receives the file sent from the device. It receives the HTTP POST request and saves the file in the specified directory. The server then uses OCR (optical character recognition) technology to extract the text data from the file. For example, the Tesseract OCR engine is used in this process. The extracted text data is saved and analyzed for necessary data (such as name, date of birth, and parent-child relationship). Regular expressions and text analysis algorithms are used for the analysis.

[0107] The analyzed data is structured and stored in a central database. An example of specific extracted data is "Name: Taro Tanaka, Date of birth: January 1, 1990, Father: Ichiro Tanaka, Mother: Hanako Tanaka."

[0108] When a user requests the generation of genealogy information, the server extracts and formats the relevant data from a central database. The extracted data is fed into a generative artificial intelligence (generative AI) that generates new information (e.g., a family tree or death register) in the specified format. The generative AI uses a text-based prompt. For example, a prompt might be "Please generate a family tree for the Tanaka family."

[0109] The generated genealogical information is stored as a digital file (e.g., "tanaka_family_tree.pdf") on a cloud computing system. Users can access this information via the internet and view the latest genealogical information. This system enables users to efficiently and accurately obtain, store, and share the latest genealogical information.

[0110] The above is a specific embodiment for carrying out the present invention. This system allows users to quickly process and analyze family register information and keep it up to date.

[0111] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0112] Step 1:

[0113] The user saves the family register information obtained from their permanent domicile as a digital file and uploads this digital file through the system's web interface. As a concrete example, the user selects "koseki_sample.pdf" and clicks the upload button. The input of this step is the "family register information file selected by the user," and the output is "sending the file to the server."

[0114] Step 2:

[0115] The terminal performs an initial check of the file received from the user. Specifically, it checks whether the file format is PDF, JPEG, or PNG, and tests whether it can be read successfully. Once the file is confirmed, it is stored in a temporary storage area. The input of this step is the "file sent by the user," and the output is the "file stored in the temporary storage area."

[0116] Step 3:

[0117] The terminal prepares to send the file from the temporary storage area to the server. Specifically, it moves the file and calls the server sending script. The input of this step is the "file stored in the temporary storage area" and the output is the "file to be sent to the server."

[0118] Step 4:

[0119] The server receives the file sent from the terminal. Specifically, it receives an HTTP POST request and saves the file in a specified directory. The input of this step is the "file sent from the terminal" and the output is the "file saved in the specified directory on the server."

[0120] Step 5:

[0121] The server uses OCR (Optical Character Recognition) technology to extract the text data in the file. For example, it invokes the Tesseract OCR engine to extract the digital text. The input of this step is the file stored in the specified directory on the server, and the output is the extracted text data.

[0122] Step 6:

[0123] The server parses the text data and extracts the necessary data (such as name, date of birth, parent-child relationship, etc.). Specifically, it filters the data using regular expressions and text analysis algorithms. The input of this step is the text data extracted by OCR, and the output is structured data.

[0124] Step 7:

[0125] The server stores the extracted data in a central database. Specifically, it generates SQL queries and inserts them into the database. The input of this step is "structured data" and the output is "data stored in the database."

[0126] Step 8:

[0127] The server extracts specific genealogical information from the central database based on the user's request. Specifically, it generates an SQL select query to extract and format the data. The inputs to this step are the data stored in the database and the user's request, and the output is the formatted genealogical information data.

[0128] Step 9:

[0129] The server inputs the formatted data into the generative AI model to generate genealogy information. As a specific example, the prompt "Please generate a family tree for the Tanaka family" is input, and a file called "tanaka_family_tree.pdf" is generated. The inputs for this step are the formatted family information data and the prompt, and the output is the generated genealogy information file.

[0130] Step 10:

[0131] The server saves the generated genealogy information file in a cloud computing system. Specifically, it calls a cloud storage API and uploads the file. The input of this step is the "generated genealogy information file," and the output is the "file saved in the cloud system."

[0132] Step 11:

[0133] The user views the genealogy information generated through the cloud system. Specifically, the user logs in to the web interface and downloads or views the generated file. The input of this step is the "file stored in the cloud system," and the output is "user viewing of genealogy information."

[0134] (Application example 1)

[0135] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0136] Existing systems for generating family trees and past records based on family register information require users to organize and analyze the information themselves, which is time-consuming and labor-intensive. Furthermore, the generated information may not be easily stored or accessible. Furthermore, there is a lack of means to directly provide family trees and past records to customers in physical stores. To solve these issues, there is a need for an efficient and easy-to-use system for analyzing, generating, and displaying information that utilizes smart devices.

[0137] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0138] In this invention, the server includes means for receiving family register information uploaded by a user, means for analyzing the received family register information and extracting necessary data, means for saving the extracted data in a central database, means for extracting data from the central database to generate a death register and family tree, means for saving the generated death register and family tree in a cloud system, means for analyzing the received family register information using a smart device, and means for displaying the death register and family tree generated by the smart device, thereby enabling users to easily analyze family register information and efficiently generate, display, and save a death register and family tree.

[0139] "User" refers to an individual who uses the system to upload family register information and use the analyzed and generated family registers and genealogies.

[0140] "Family register information" refers to official documents containing data such as the name, date of birth, and kinship relationships of registered individuals.

[0141] "Analysis" refers to the process of extracting necessary information from received digital data and organizing and transforming it.

[0142] "Central database" refers to a centralized storage system for storing extracted digital text and analytical data for later search and retrieval.

[0143] A "kakocho" is a document or digital file that compiles historical records of individuals and families.

[0144] A "family tree" is a visual diagram showing a family's kinship relationships across generations.

[0145] A "cloud system" refers to a network of remote servers for storing and managing data over the Internet.

[0146] "Smart devices" refers to devices with internet connectivity and advanced computing capabilities, such as smartphones, smart glasses, and head-mounted displays.

[0147] "Analysis" refers to the process of processing received data to categorize and organize the information for a specific purpose.

[0148] "Display" refers to the process of visually presenting the generated family register and genealogy data on an interface such as a digital screen.

[0149] "Generative AI" refers to artificial intelligence models used to generate new information or content based on existing data.

[0150] A system for implementing this invention comprises a user, a terminal (a smart device such as a smartphone or smart glasses), and a server.

[0151] Specific actions

[0152] 1. User Action:

[0153] Users use their smartphones or smart glasses to save their family register information as a digital file (e.g., PDF, JPEG, PNG, etc.) and upload it using the system's application.

[0154] For example, a user uploads a file called "koseki_info.pdf" from an application.

[0155] 2. Terminal processing:

[0156] The device initially checks the uploaded file to make sure it is in the correct format. If it is, it temporarily saves the file and sends it to the server.

[0157] 3. Server processing:

[0158] The server receives the file and converts it into digital text using an OCR (Optical Character Recognition) engine, which then analyzes the text to extract necessary data such as name, date of birth, and parent-child relationship.

[0159] The extracted data is stored in a central database, and is registered in the format, for example, "Yamada Taro, born January 1, 1990, father: Yamada Ichiro, mother: Yamada Hanako."

[0160] 4. Data analysis and formatting:

[0161] The server extracts specific genealogical information from a central database in response to user requests, and uses generative AI models to format the data into a suitable format for family registers and family trees.

[0162] 5. Generating family records and genealogies using generative AI:

[0163] The server uses a generative AI model to generate family records and genealogies based on the formatted data, and the generated data is stored in a cloud system.

[0164] 6. Cloud Storage and Access:

[0165] The generated family registers and genealogies are stored in a cloud system and can be accessed online by users via the internet.

[0166] Hardware and Software Use

[0167] Hardware:

[0168] Smartphones, smart glasses

[0169] software:

[0170] OCR engine (pytesseract)

[0171] PDF conversion library (pdf2image)

[0172] HTTP request library (requests)

[0173] Generative AI Models

[0174] Specific examples

[0175] The user uses the smart glasses to scan their family register information file (e.g., "koseki_info.pdf").

[0176] Select Family Tree Generation from the glasses interface.

[0177] The generated family tree is displayed on the smart glasses' display and can be viewed in real time.

[0178] Below is an example of a prompt to send to a generative AI model:

[0179] Generate a family tree based on the following information:

[0180] Name: Taro Yamada

[0181] Date of Birth: January 1, 1990

[0182] Father: Ichiro Yamada

[0183] Mother: Hanako Yamada

[0184] This system allows users to easily and efficiently create, display, and save family records and genealogies.

[0185] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0186] Step 1:

[0187] User Action:

[0188] Users save their family register information as a digital file (e.g., PDF, JPEG, PNG, etc.) using a smartphone or smart glasses, and then upload this file using the application.

[0189] Input: Digital family register information file (e.g. "koseki_info.pdf")

[0190] Output: The uploaded file

[0191] Step 2:

[0192] Terminal handling:

[0193] The device performs an initial check on the uploaded file to ensure that the file format is correct. If the format is correct, the file is temporarily saved and prepared for transmission to the server.

[0194] Input: Uploaded file

[0195] Output: Verified files, files prepared for sending

[0196] Step 3:

[0197] Receiving files from the server:

[0198] The server receives the file sent from the device and prepares it for analysis.

[0199] Input: File sent from terminal

[0200] Output: Received files

[0201] Step 4:

[0202] OCR processing:

[0203] The server uses an OCR (Optical Character Recognition) engine to convert the received file into digital text.

[0204] Input: Received file

[0205] Output: Digital text extracted by OCR

[0206] Step 5:

[0207] Data Analysis:

[0208] The server analyzes the digital text extracted by OCR and extracts the necessary data (such as name, date of birth, parent-child relationship, etc.).

[0209] Input: Digital text extracted by OCR

[0210] Output: Extracted data (e.g., "Yamada Taro, born January 1, 1990, father: Yamada Ichiro, mother: Yamada Hanako")

[0211] Step 6:

[0212] Save to database:

[0213] The server stores the extracted data in a central database.

[0214] Input: Extracted data

[0215] Output: Data stored in the database

[0216] Step 7:

[0217] Extracting genealogy information:

[0218] The server extracts specific genealogy information from a central database in response to a user's request.

[0219] Input: User requests, central database

[0220] Output: Extracted genealogy information

[0221] Step 8:

[0222] Data formatting:

[0223] The server inputs the extracted family information into a generative AI model and formats it into a format suitable for death registers and family trees.

[0224] Input: Extracted genealogy information

[0225] Output: Formatted data

[0226] Step 9:

[0227] Generative AI for generating family trees:

[0228] The server uses a generative AI model to generate a family tree based on the formatted data.

[0229] Input: Formatted data

[0230] Output: The generated pedigree

[0231] Step 10:

[0232] Save to cloud system:

[0233] The server stores the generated family tree in a cloud system.

[0234] Input: Generated pedigree

[0235] Output: Family tree stored in a cloud system

[0236] Step 11:

[0237] User Views:

[0238] Users access the cloud system via the Internet and view the generated family tree.

[0239] Input: Family tree stored in the cloud system, user request to view it

[0240] Output: Family tree displayed on the user's device

[0241] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0242] This invention combines a system that uses a central database and a cloud-based system to automatically create up-to-date family registers and genealogies based on family register information collected from users' permanent domiciles with an emotion engine that recognizes user emotions.The system consists of user uploads, data analysis and extraction, storage in a database, generation of family registers and genealogies using generation AI, storage in a cloud system, and user emotion recognition and content adjustment using the emotion engine.

[0243] System configuration and specific operation

[0244] 1. User Action:

[0245] Users save the family register information they have obtained at their permanent domicile as a digital file and upload it to the system through the system's web interface. Uploading involves the user selecting and submitting a file using a file selection dialog.

[0246] Example: A user uploads "koseki_tanaka.pdf" to the system.

[0247] 2. Terminal processing:

[0248] The device receives the uploaded file and performs an initial check. It checks whether the file format (PDF, JPEG, PNG, etc.) is appropriate and whether the file can be loaded correctly. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[0249] 3. Server processing:

[0250] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The server then analyzes the text information extracted by the OCR engine to identify and extract the necessary data (such as name, date of birth, and parent-child relationship).

[0251] The extracted data is structured and stored in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[0252] 4. Data extraction and formatting:

[0253] In response to a user's request, the server extracts specific family information from a central database. Generative AI is then used to format the extracted data into a suitable format for a family register or family tree. Generational lists are created, arranging the data based on parent-child relationships.

[0254] Example: The server extracts all data related to the Tanaka family and formats it appropriately to generate a family tree for the "Tanaka family."

[0255] 5. Report generation using generative AI:

[0256] The AI ​​then generates a family register and family tree based on the data formatted by the server, which are then stored in a cloud system.

[0257] Example: The generation AI generates a family tree for the "Tanaka family" and saves it in cloud storage as "Tanaka family genealogy.pdf."

[0258] 6. Use of Emotion Engine:

[0259] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. While the user is browsing the family register or family tree, the emotion engine monitors the user's emotions in real time.

[0260] Based on the analyzed emotional information, the format and design of the displayed death register and family tree are automatically adjusted.

[0261] For example, if the system detects that the user is emotional, it will add memorable anecdotes or inspiring quotes to the family tree.

[0262] 7. Use of cloud systems:

[0263] The generated family tree and family records are stored in a cloud system and can be accessed online via the internet. Users can view the most up-to-date family tree, which also reflects emotional customization.

[0264] 8. Continuous updates:

[0265] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the changes and updates the central database. The generation AI then regenerates the family register and family tree and stores them in the cloud system.

[0266] Users' emotional data is also stored in the cloud system and continuously analyzed along with their viewing history of family records and genealogies.

[0267] Specific examples

[0268] 1. User uploads family register information:

[0269] The user uploads "koseki_tanaka.pdf" through the web interface.

[0270] The terminal receives the file and performs an initial check to send it to the server.

[0271] 2. The server analyzes and extracts the data and registers it in the database:

[0272] The server uses an OCR engine to analyze the file and extract information such as "Taro Tanaka, born January 1, 1990" as digital text, which is then stored in a database.

[0273] 3. Data shaping and generative AI:

[0274] Based on the user's request, the server extracts data about the "Tanaka family" and uses a generation AI to generate "Tanaka family tree.pdf."

[0275] 4. Use of Emotion Engine:

[0276] When a user browses the family tree, the emotion engine analyzes the user's emotions in real time and adjusts the display format and content accordingly. For example, if the user is emotional, it will display additional touching episodes.

[0277] 5. Use of cloud systems and continuous updates:

[0278] The server stores the generated family tree in a cloud system, and users can view the latest family tree online through a web interface.

[0279] If changes occur to family register information or emotional data, the system will automatically update to reflect the latest information.

[0280] In this way, the system provides a set of actions to efficiently and accurately create family registers and genealogies, and customize the content based on the user's emotions.

[0281] The processing flow will be explained below.

[0282] Step 1:

[0283] The user saves the family register information obtained from their permanent domicile as a digital file and accesses the system's web interface. The user clicks the "Upload" button, selects the family register file (e.g., "koseki_tanaka.pdf") from the file selection dialog, and uploads it.

[0284] Step 2:

[0285] The device receives the uploaded file and performs an initial check. The device checks whether the file format (PDF, JPEG, PNG, etc.) is appropriate and whether the file can be read normally. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[0286] Step 3:

[0287] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The server then analyzes the text information extracted by the OCR engine to identify and extract the necessary data (such as name, date of birth, parent-child relationship, etc.).

[0288] Step 4:

[0289] The server structures the extracted data and stores it in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[0290] Step 5:

[0291] When a user requests the generation of a family register or family tree, the server extracts data from a central database based on the specified criteria, and then uses the generation AI to format the extracted data and convert it into a format suitable for the family register or family tree.

[0292] Step 6:

[0293] The death register and family tree generated by the AI ​​are saved in a cloud system. For example, they are uploaded to cloud storage as "Tanaka Family Tree.pdf."

[0294] Step 7:

[0295] Users access the cloud system and view the latest family records and genealogy through a web interface, allowing them to access the latest information at any time.

[0296] Step 8:

[0297] When a user is viewing a family tree or family register, the emotion engine analyzes the user's facial expressions and voice to identify their emotional state, and automatically adjusts the format and design of the displayed family tree or family register based on the analyzed emotional information.

[0298] Step 9:

[0299] The server receives data from the emotion engine and updates the display content in real time based on the user's emotions. For example, if the user is emotional, it will add memorable anecdotes or inspiring quotes to the family tree.

[0300] Step 10:

[0301] The user's emotional data is stored in a cloud system and continuously analyzed along with the viewing history of the family tree and past records, allowing the system to customize the user's family tree based on their past emotional state when they next view it.

[0302] Step 11:

[0303] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the change and updates the central database. The generation AI then regenerates the family register and family tree and stores them in the cloud system. The user's emotional data is also updated appropriately to reflect the latest information.

[0304] Example 2

[0305] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0306] Conventional systems for creating family trees and past records require users to manually input and organize data, which is time-consuming and labor-intensive. Generating family trees and past records also requires specialized knowledge, making them difficult for average users to use. Furthermore, the lack of customization features that take user feelings into account makes it difficult to improve user satisfaction.

[0307] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving digital files uploaded by users, means for initially checking the format and content of the received digital files, means for transmitting files that have passed the initial check to the server, means for converting the received digital files into digital text using OCR technology and extracting necessary data, means for saving the extracted data in a central database, means for extracting and formatting data from the central database in response to a user request, means for generating a death register and / or family tree using a generation AI, means for saving the generated death register and / or family tree in a cloud system, means for the user to access the generated data through the cloud system, means including an emotion engine for analyzing the user's facial expressions and voice to identify emotions, means for adjusting display content based on the identified emotions, and means for automatically and continuously updating data. This allows users to easily create death registers and / or family trees, and also provides emotion-based customization functions, providing a highly satisfying experience.

[0308] A "user" is someone who operates the system, uploads digital files, and views the generated family registers and genealogies.

[0309] "Digital files" refers to document or image files stored in a digital format such as PDF, JPEG, or PNG.

[0310] "Receiving means" refers to the functions and devices for incorporating digital files sent by users into the system.

[0311] "Initial checking means" refers to a function or device that checks the format and content of a received digital file and determines whether it is appropriate.

[0312] A "server" is a computer that plays a central role in the system and is a device that performs various processes such as analyzing digital files, operating databases, and using generative AI.

[0313] "OCR technology" stands for optical character recognition technology, which analyzes the character information contained in digital files and extracts it as digital text.

[0314] "Digital text" refers to character data extracted using OCR technology in a format that can be understood by a computer.

[0315] "Data extraction means" refers to a function or device that extracts necessary information such as name, date of birth, and parent-child relationship from digital text.

[0316] The "central database" refers to a data storage system for centrally storing and managing extracted data.

[0317] "Formatting means" refers to the function or device that organizes and arranges data extracted from the central database in a format suitable for family registers and genealogies.

[0318] "Generative AI" refers to systems or software that use artificial intelligence technology to automatically generate death registers and family trees from formatted data.

[0319] A "cloud system" is an online storage system that stores data via the Internet and allows users to access it from anywhere.

[0320] "Access means" refers to the functions and devices that allow users to view and manipulate data stored in a cloud system.

[0321] An "emotion engine" is software or a device that analyzes a user's facial expressions and voice to identify their emotional state.

[0322] The "display content adjustment means" refers to a function or device that automatically changes the display format and content of the death register or family tree based on the emotion identified by the emotion engine.

[0323] "Update means" refers to a function or device that automatically updates the entire system based on new information when the information stored in the database is changed.

[0324] This invention is a system that automatically creates up-to-date family registers and genealogies using a central database and cloud-based system based on family register information collected from users' permanent domiciles. The system also combines an emotion engine that recognizes users' emotions to provide a more customized experience.

[0325] First, the user saves the family register information obtained from their permanent domicile as a digital file (e.g., PDF, JPEG) and uploads it through the system's web interface. The user uploads a digital file such as "koseki_example.pdf." The specific software used is a web browser (e.g., GOOGLE CHROME (registered trademark), Firefox).

[0326] The device then receives the uploaded file and performs an initial check to ensure that the file is in the correct format (PDF, JPEG, PNG, etc.) and can be loaded correctly. The detected file is then stored in a temporary storage area and prepared for transmission to the server. This initial check is performed using a file format inspection tool.

[0327] The server receives the file sent from the terminal and converts the file's contents into digital text using an OCR (Optical Character Recognition) engine (e.g., Tesseract OCR). In this process, the OCR engine extracts information such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" from "koseki_example.pdf." The extracted data is analyzed and stored in a structured central database. An SQL database (e.g., MySQL (registered trademark), PostgreSQL) is used for the central database.

[0328] Additionally, upon user request, the server extracts specific family information from the central database and formats the data. The formatted data is then converted into a format suitable for use in a family register or family tree using a generative AI model. For example, if a user requests the generation of a family tree for the "Tanaka family," the server retrieves the relevant data, and the generative AI generates it as "Tanaka Family Tree.pdf."

[0329] The generated family registers and genealogies are stored in a cloud system and can be accessed online by users via the internet. Cloud storage services such as Amazon S3 and Google Drive are used.

[0330] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. While the user is viewing the family register or family tree, the emotion engine monitors the user's emotions in real time. Based on the analyzed emotional information, the format and design of the displayed family register or family tree is automatically adjusted. For example, if the system recognizes that the user is emotional, it will add memorable episodes or inspiring quotes to the family tree. The emotion engine uses technologies such as Microsoft® Azure® Emotion API and IBM Watson® Tone Analyzer.

[0331] Finally, if any changes occur to the family register information (e.g., new members are added or removed), the system automatically detects the changes and updates the central database. The generation AI then regenerates the family register and family tree and stores it in the cloud system. This entire process allows users to efficiently and accurately create family registers and family trees, and even customize them based on their emotions.

[0332] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0333] Step 1:

[0334] The user uploads their family register information.

[0335] Input: The digital file the user obtained at their permanent address (e.g. "koseki_example.pdf").

[0336] Specific behavior: A user logs in to the web interface, clicks the file upload button, selects "koseki_example.pdf", and performs the upload.

[0337] Output: "koseki_example.pdf" is sent to the system.

[0338] Step 2:

[0339] The terminal initially checks the file and sends it to the server.

[0340] Input: An uploaded digital file (e.g. "koseki_example.pdf").

[0341] Specific operation: The device checks the file format (PDF, JPEG, PNG, etc.) and checks whether the file can be read normally. Uses a file format checker.

[0342] Data processing: Inspect the file format and content to ensure there are no problems.

[0343] Output: Files that pass the initial checks are stored in a temporary storage area, ready to be sent to the server.

[0344] Step 3:

[0345] The server analyzes the file using OCR, extracts the data, and saves it.

[0346] Input: The file sent from the terminal (e.g. "koseki_example.pdf").

[0347] What happens: The server uses an OCR engine (e.g., Tesseract OCR) to convert the file contents into digital text.

[0348] Data processing: Using OCR processing, text information such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is extracted.

[0349] Output: The extracted data is structured and stored in a central database.

[0350] Step 4:

[0351] The server extracts and formats the data from the database.

[0352] Input: Structured data stored in a central database.

[0353] What it does: Extracts specific genealogy information and formats the data according to the user's request.

[0354] Data transformation: The transformation process creates a generational list and arranges the data based on parent-child relationships.

[0355] Output: The formatted data is passed to a generative AI model.

[0356] Step 5:

[0357] Generative AI generates death registers and family trees.

[0358] Input: Formatted data.

[0359] How it works: The generative AI model takes formatted data as input and generates a death register or family tree.

[0360] Data Calculation: Generate the structure and layout of the family tree based on prompts.

[0361] Output: The generated family register and family tree (e.g. "Tanaka Family Tree.pdf") will be created.

[0362] Step 6:

[0363] The server stores the generated data in a cloud system.

[0364] Input: The death register or family tree output by the generation AI (e.g., "Tanaka family family tree.pdf").

[0365] Specific operation: The server uploads data to cloud storage (e.g., Amazon S3, Google Drive).

[0366] Data processing: Uploading data and storing it on the cloud.

[0367] Output: Death registers and family trees stored in a cloud system that can be accessed by users.

[0368] Step 7:

[0369] The emotion engine analyzes user emotions and adjusts content accordingly.

[0370] Input: User facial and voice data.

[0371] Specific operation: The emotion engine uses the camera and microphone to collect and analyze the user's facial expressions and voice.

[0372] Data Computing: Using sentiment analysis algorithms to identify a user's emotional state (e.g., happy, sad, moved).

[0373] Output: Display content is adjusted based on identified emotion data.

[0374] Step 8:

[0375] The server automatically updates the database and cloud system when updated.

[0376] Input: Newly uploaded or changed family register information.

[0377] How it works: When a new digital file is uploaded, the server detects the change, performs OCR analysis, extracts data, updates the database, and regenerates it using generative AI.

[0378] Data processing: Automatic updates to databases and cloud systems.

[0379] Output: The latest family register and genealogy are regenerated and stored in the cloud system.

[0380] This allows the system to efficiently and accurately create family registers and genealogies, customize them based on user sentiment, and automatically update them with the latest information.

[0381] (Application example 2)

[0382] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0383] Conventional genealogy and death register generation systems do not adjust content based on user emotions, resulting in a limited user experience. Furthermore, the convenience of viewing personal information in a paperless manner in a physical store is also an issue. The present invention aims to solve these issues by providing real-time content adjustment using emotion analysis and an interactive in-store experience.

[0384] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving personal information uploaded by a user, means for analyzing the received personal information and extracting necessary data, means for saving the extracted data in a centralized data storage system, means for extracting data from the centralized data storage system to generate a death register and / or a family tree, means for saving the generated death register and / or a family tree on a cloud platform, means for adjusting display content using an emotion engine that identifies the user's emotions, and means for providing emotion-based information to a store display device. This makes it possible to display an interactive death register and / or a family tree according to the user's emotions.

[0385] "User" refers to a person who uses the system to provide personal information and generate and view death registers and genealogy charts.

[0386] "Personal information" refers to information used to identify individuals or determine genealogical relationships, such as family register information.

[0387] "Means for receiving" refers to system components or functions that acquire personal information electronically, in whole or in part.

[0388] "Means of analysis" refers to system components and functions that process received personal information using technologies such as data conversion and character recognition, and extract the necessary data.

[0389] "Extraction means" refers to system components or functions that extract specific information from the analyzed data.

[0390] "Centralized data storage system" refers to a database system that centrally stores and manages analyzed and extracted data.

[0391] "Means for generating" refers to system components and functions that use the extracted data to automatically create death registers and genealogy charts.

[0392] "Cloud infrastructure" refers to a cloud storage system that stores the generated death registers and genealogy charts and makes them accessible via the Internet.

[0393] An "emotion engine" refers to technology or a system that analyzes and identifies the user's emotional state, such as facial expressions and voice.

[0394] "Means for adjusting the displayed content" refers to system components or functions that dynamically change the content and format of the displayed death register or genealogy chart based on emotional information obtained from the emotion engine.

[0395] "Display device" refers to a device (e.g., tablet, large display, etc.) for displaying the generated death register or genealogy chart.

[0396] A specific system for implementing the present invention operates according to the following steps.

[0397] First, a user uses their smartphone to access a display device such as a tablet or large display. When the user uploads their personal information, the device receives this information and sends it to a server.

[0398] The server analyzes the received personal information and extracts the necessary data. This process involves converting the uploaded document into digital text using OCR technology such as Google Cloud Vision. The extracted data is then stored in a centralized data storage system (e.g., AWS® RDS).

[0399] The server then uses this data to generate a family register or genealogy chart upon user request. This process uses a generative AI model (e.g., OpenAI® GPT-4®) to efficiently and accurately generate the content. The generated family register or genealogy chart is stored in a cloud infrastructure (e.g., Amazon S3).

[0400] In parallel, an emotion engine (e.g., Microsoft Azure Cognitive Services) analyzes the user's emotions in real time by monitoring their facial expressions and voice while they browse the family register or genealogy chart to identify their emotional state.

[0401] The server uses this emotional information to dynamically adjust the content displayed. For example, if the emotion engine identifies that the user is emotional, the system will add touching anecdotes or quotes to the death register or family tree. This adjustment is made in real time, allowing users to experience the most appropriate content based on their emotions.

[0402] Furthermore, emotion-based information is automatically provided to store display devices, allowing store staff to provide appropriate support and suggestions to customers.

[0403] In this way, the present invention realizes interactive display of death registers and genealogy charts according to the user's emotions, providing a paperless experience in a physical store.

[0404] For example, a user uploads the family register information for the "Yamada family," and OCR technology extracts information such as "Yamada Taro, born January 1, 1980," and generates a "Yamada Family Tree.pdf" based on this information. The emotion engine analyzes the user's emotions, and if it determines that the user is emotional, it provides the following prompt to the generative AI model:

[0405] "Add inspiring stories and quotes based on the Yamada family tree data and the user's emotional state."

[0406] This prompt enables the generative AI model to generate supplementary content, including inspiring anecdotes and quotes, to provide to users in addition to the Yamada family tree.

[0407] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0408] Step 1:

[0409] The user uploads personal information from their smartphone. The input is the personal information file selected by the user, and the output is the data sent to the device. Specifically, the user accesses the specified web interface, selects the file to upload (e.g., "koseki_yamada.pdf") from the file selection dialog, and presses the send button.

[0410] Step 2:

[0411] The device receives the uploaded file and prepares it to be sent to the server. The input is the file uploaded by the user, and the output is the data to be sent to the server. Specifically, the device checks the file format (PDF, JPEG, PNG, etc.) and checks the file's integrity, and if there are no problems, stores it in a temporary storage area.

[0412] Step 3:

[0413] The server receives the file sent from the device and converts the file contents into digital text using OCR technology. The input is the personal information file sent from the device, and the output is digital text data. Specifically, the server calls the Google Cloud Vision API, analyzes the file, and extracts the text information. For example, the text data obtained is "Yamada Taro, born January 1, 1980."

[0414] Step 4:

[0415] The server parses the digital text, extracts the necessary data (such as name, date of birth, parent-child relationship, etc.), and stores it in a centralized data storage system. The input is the digital text, and the output is a structured database entry. Specifically, the server uses regular expressions and parsing algorithms to extract the data and store it in a database (e.g., AWS RDS).

[0416] Step 5:

[0417] In response to user requests, the server uses a generative AI model to generate a family register or family tree. The input is data extracted from a centralized data storage system, and the output is a PDF file of the generated family register or family tree. Specifically, the server uses OpenAI GPT-4 to generate prompts based on the extracted data and create the family register or family tree. Example: "Yamada Family Tree.pdf" is generated.

[0418] Step 6:

[0419] The generated death registers and genealogy charts are stored on a cloud platform and can be accessed by users. The input is the generated PDF file, and the output is an access link on the cloud storage. Specifically, the server uses a cloud storage service such as Amazon S3 to upload the file and generate an access link.

[0420] Step 7:

[0421] The emotion engine analyzes the user's emotions in real time and adjusts the displayed content. The input is the user's facial expression and voice data, and the output is content adjusted based on the user's emotional state. Specifically, it uses Microsoft Azure Cognitive Services to analyze the user's facial expressions and voice, and the server dynamically adjusts the content based on the obtained emotional information. For example, if the user is moved, an emotional episode will be added.

[0422] Step 8:

[0423] Emotion-based information is provided to display devices in stores. The input is the adjusted content, and the output is what is displayed on the display device. Specifically, the adjusted content is sent from the server to a tablet device or large display, and then displayed on the display device. This enables store staff to provide appropriate support and suggestions to customers.

[0424] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0425] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0426] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0427] [Second embodiment]

[0428] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0429] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0430] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0431] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0432] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0433] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0434] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0435] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0436] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0437] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0438] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0439] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0440] This invention is a system that automatically creates up-to-date family registers and genealogies using a central database and cloud-based system based on family register information collected from users' permanent domiciles. The system consists of a user upload, data analysis and extraction, storage in the database, generation of family registers and genealogies using AI, and storage in the cloud system.

[0441] System configuration and specific operation

[0442] 1. User Action:

[0443] Users save the family register information they have obtained at their permanent domicile as a digital file and upload it to the system through the system's web interface. Uploading involves the user selecting and submitting a file using a file selection dialog.

[0444] Example: A user uploads "koseki_tanaka.pdf" to the system.

[0445] 2. Terminal processing:

[0446] The device initially checks the received file to ensure that it is in the correct file format (PDF, JPEG, PNG, etc.). If the file can be read successfully, it is stored in a temporary storage area and prepared for transmission to the server.

[0447] 3. Server processing:

[0448] The server receives the file sent from the device and converts it into digital text using an OCR (Optical Character Recognition) engine. At this time, the server analyzes the text information extracted by OCR and extracts necessary data (such as name, date of birth, parent-child relationship, etc.).

[0449] The extracted data is structured and stored in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[0450] 4. Data extraction and formatting:

[0451] The server extracts specific family information from a central database in response to a user's request, then uses generative AI to format the extracted data into a suitable format for a family register or family tree, creating a generational list and arranging the data based on parent-child relationships.

[0452] Example: The server extracts all data related to the Tanaka family and formats it appropriately to generate a family tree for the "Tanaka family."

[0453] 5. Report generation using generative AI:

[0454] The AI ​​then generates a family register and family tree based on the data formatted by the server, which are then stored in a cloud system.

[0455] Example: The generation AI generates a family tree for the "Tanaka family" and saves it in cloud storage as "Tanaka family genealogy.pdf."

[0456] 6. Use of cloud systems:

[0457] The generated family registers and family trees are stored in a cloud system and can be accessed online via the internet, allowing users to view the most up-to-date family trees.

[0458] Specific examples

[0459] 1. User uploads family register information:

[0460] The user uploads "koseki_tanaka.pdf" through the web interface.

[0461] The terminal receives the file and performs an initial check to send it to the server.

[0462] 2. The server analyzes and extracts the data and registers it in the database:

[0463] The server uses an OCR engine to analyze the file and extract information such as "Taro Tanaka, born January 1, 1990" as digital text, which is then stored in a database.

[0464] 3. Data shaping and generative AI:

[0465] Based on the user's request, the server extracts data about the "Tanaka family" and uses a generation AI to generate "Tanaka family tree.pdf."

[0466] 4. Cloud storage and use:

[0467] The server stores the generated family tree in a cloud system, and users can view the latest family tree online through a web interface.

[0468] In this way, the system provides a series of operations that allow users to efficiently and accurately create family registers and genealogies, and keep the information up to date at all times.

[0469] The processing flow will be explained below.

[0470] Step 1:

[0471] The user saves the family register information obtained from their permanent domicile as a digital file and accesses the system's web interface. The user clicks the "Upload" button, selects the family register file (e.g., "koseki_tanaka.pdf") from the file selection dialog, and uploads it.

[0472] Step 2:

[0473] The device receives the uploaded file and performs an initial check. It checks whether the file format is appropriate (PDF, JPEG, PNG, etc.) and whether the file can be loaded correctly. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[0474] Step 3:

[0475] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The OCR engine then analyzes the extracted text information to identify and extract the necessary data (such as name, date of birth, and parent-child relationship).

[0476] Step 4:

[0477] The server structures the extracted data and stores it in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[0478] Step 5:

[0479] When a user requests the generation of a family register or family tree, the server extracts data from the central database based on the specified criteria, and then uses the generation AI to format the extracted data and convert it into a format suitable for the family register or family tree.

[0480] Step 6:

[0481] The server saves the generated family register and family tree in the cloud system. The generated family register and family tree are uploaded to the cloud storage as, for example, "Tanaka Family Genealogy.pdf."

[0482] Step 7:

[0483] Users access the cloud system and view the latest family records and genealogy through a web interface, allowing them to access the latest information at any time.

[0484] Step 8:

[0485] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the change and updates the central database. Based on the updated information, the AI ​​generates new family registers and family trees, which are then stored in the cloud system.

[0486] Example 1

[0487] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0488] In conventional family register information management systems, digitizing and analyzing family register information required a great deal of time and effort. Furthermore, updating the digitized data and generating genealogy information in an appropriate format was done manually, resulting in issues with accuracy and efficiency. This made it difficult for users to quickly obtain the latest genealogy information.

[0489] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0490] In this invention, the server includes a means for receiving family register information uploaded by users, a means for converting the received family register information into digital text using optical character recognition technology, a means for extracting necessary data and storing it in a central database, a means for generating genealogy information using artificial intelligence, and a means for storing the generated genealogy information in a cloud computing system, thereby enabling users to efficiently and accurately obtain the latest genealogy information.

[0491] "User" means an individual or corporation that uses this system to upload family register information and generate and view genealogy information.

[0492] "Family register information" refers to public records that include names, dates of birth, parent-child relationships, etc.

[0493] "Means for receiving" means a device or process for retrieving digital files uploaded by users onto the server.

[0494] "Means for analyzing and extracting necessary data" refers to a method or device that identifies and extracts important information (e.g., name, date of birth, parentage, etc.) from the received digital file.

[0495] "Optical character recognition technology" refers to technology that extracts text data from images or scanned documents.

[0496] "Digital text" refers to text data converted from an image or scan using optical character recognition technology.

[0497] "Central database" refers to a database system that centrally manages extracted and stored data.

[0498] "Genealogy information" refers to data showing family lineage and historical lineage, such as family trees and death registers.

[0499] "Generative AI" refers to an AI technology that generates new information (e.g., family trees or death registers) in a specified format based on given data.

[0500] A "cloud computing system" is a service that stores data on the Internet and allows users to access it remotely.

[0501] This invention is a system that automatically generates up-to-date genealogy information based on family register information collected by users from their registered domiciles, using a central database and a cloud computing system.

[0502] First, the user saves the family register information obtained from their permanent domicile as a digital file. This digital file can be in a format such as PDF, JPEG, or PNG. Next, the user uploads this digital file to the system through the web interface. For example, the user selects "koseki_sample.pdf" and clicks the upload button to send it to the system.

[0503] The device performs an initial check of the file received from the user, confirming that the file format is correct and testing that it can be read successfully. If the file is confirmed, it is stored in a temporary storage area and prepared for transmission to the server.

[0504] The server receives the file sent from the device. It receives the HTTP POST request and saves the file in the specified directory. The server then uses OCR (optical character recognition) technology to extract the text data from the file. For example, the Tesseract OCR engine is used in this process. The extracted text data is saved and analyzed for necessary data (such as name, date of birth, and parent-child relationship). Regular expressions and text analysis algorithms are used for the analysis.

[0505] The analyzed data is structured and stored in a central database. An example of specific extracted data is "Name: Taro Tanaka, Date of birth: January 1, 1990, Father: Ichiro Tanaka, Mother: Hanako Tanaka."

[0506] When a user requests the generation of genealogy information, the server extracts and formats the relevant data from a central database. The extracted data is fed into a generative artificial intelligence (generative AI) that generates new information (e.g., a family tree or death register) in the specified format. The generative AI uses a text-based prompt. For example, a prompt might be "Please generate a family tree for the Tanaka family."

[0507] The generated genealogical information is stored as a digital file (e.g., "tanaka_family_tree.pdf") on a cloud computing system. Users can access this information via the internet and view the latest genealogical information. This system enables users to efficiently and accurately obtain, store, and share the latest genealogical information.

[0508] The above is a specific embodiment for carrying out the present invention. This system allows users to quickly process and analyze family register information and keep it up to date.

[0509] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0510] Step 1:

[0511] The user saves the family register information obtained from their permanent domicile as a digital file and uploads this digital file through the system's web interface. As a concrete example, the user selects "koseki_sample.pdf" and clicks the upload button. The input of this step is the "family register information file selected by the user," and the output is "sending the file to the server."

[0512] Step 2:

[0513] The terminal performs an initial check of the file received from the user. Specifically, it checks whether the file format is PDF, JPEG, or PNG, and tests whether it can be read successfully. Once the file is confirmed, it is stored in a temporary storage area. The input of this step is the "file sent by the user," and the output is the "file stored in the temporary storage area."

[0514] Step 3:

[0515] The terminal prepares to send the file from the temporary storage area to the server. Specifically, it moves the file and calls the server sending script. The input of this step is the "file stored in the temporary storage area" and the output is the "file to be sent to the server."

[0516] Step 4:

[0517] The server receives the file sent from the terminal. Specifically, it receives an HTTP POST request and saves the file in a specified directory. The input of this step is the "file sent from the terminal" and the output is the "file saved in the specified directory on the server."

[0518] Step 5:

[0519] The server uses OCR (Optical Character Recognition) technology to extract the text data in the file. For example, it invokes the Tesseract OCR engine to extract the digital text. The input of this step is the file stored in the specified directory on the server, and the output is the extracted text data.

[0520] Step 6:

[0521] The server parses the text data and extracts the necessary data (such as name, date of birth, parent-child relationship, etc.). Specifically, it filters the data using regular expressions and text analysis algorithms. The input of this step is the text data extracted by OCR, and the output is structured data.

[0522] Step 7:

[0523] The server stores the extracted data in a central database. Specifically, it generates SQL queries and inserts them into the database. The input of this step is "structured data" and the output is "data stored in the database."

[0524] Step 8:

[0525] The server extracts specific genealogical information from the central database based on the user's request. Specifically, it generates an SQL select query to extract and format the data. The inputs to this step are the data stored in the database and the user's request, and the output is the formatted genealogical information data.

[0526] Step 9:

[0527] The server inputs the formatted data into the generative AI model to generate genealogy information. As a specific example, the prompt "Please generate a family tree for the Tanaka family" is input, and a file called "tanaka_family_tree.pdf" is generated. The inputs for this step are the formatted family information data and the prompt, and the output is the generated genealogy information file.

[0528] Step 10:

[0529] The server saves the generated genealogy information file in a cloud computing system. Specifically, it calls a cloud storage API and uploads the file. The input of this step is the "generated genealogy information file," and the output is the "file saved in the cloud system."

[0530] Step 11:

[0531] The user views the genealogy information generated through the cloud system. Specifically, the user logs in to the web interface and downloads or views the generated file. The input of this step is the "file stored in the cloud system," and the output is "user viewing of genealogy information."

[0532] (Application example 1)

[0533] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0534] Existing systems for generating family trees and past records based on family register information require users to organize and analyze the information themselves, which is time-consuming and labor-intensive. Furthermore, the generated information may not be easily stored or accessible. Furthermore, there is a lack of means to directly provide family trees and past records to customers in physical stores. To solve these issues, there is a need for an efficient and easy-to-use system for analyzing, generating, and displaying information that utilizes smart devices.

[0535] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0536] In this invention, the server includes means for receiving family register information uploaded by a user, means for analyzing the received family register information and extracting necessary data, means for saving the extracted data in a central database, means for extracting data from the central database to generate a death register and family tree, means for saving the generated death register and family tree in a cloud system, means for analyzing the received family register information using a smart device, and means for displaying the death register and family tree generated by the smart device, thereby enabling users to easily analyze family register information and efficiently generate, display, and save a death register and family tree.

[0537] "User" refers to an individual who uses the system to upload family register information and use the analyzed and generated family registers and genealogies.

[0538] "Family register information" refers to official documents containing data such as the name, date of birth, and kinship relationships of registered individuals.

[0539] "Analysis" refers to the process of extracting necessary information from received digital data and organizing and transforming it.

[0540] "Central database" refers to a centralized storage system for storing extracted digital text and analytical data for later search and retrieval.

[0541] A "kakocho" is a document or digital file that compiles historical records of individuals and families.

[0542] A "family tree" is a visual diagram showing a family's kinship relationships across generations.

[0543] A "cloud system" refers to a network of remote servers for storing and managing data over the Internet.

[0544] "Smart devices" refers to devices with internet connectivity and advanced computing capabilities, such as smartphones, smart glasses, and head-mounted displays.

[0545] "Analysis" refers to the process of processing received data to categorize and organize the information for a specific purpose.

[0546] "Display" refers to the process of visually presenting the generated family register and genealogy data on an interface such as a digital screen.

[0547] "Generative AI" refers to artificial intelligence models used to generate new information or content based on existing data.

[0548] A system for implementing this invention comprises a user, a terminal (a smart device such as a smartphone or smart glasses), and a server.

[0549] Specific actions

[0550] 1. User Action:

[0551] Users use their smartphones or smart glasses to save their family register information as a digital file (e.g., PDF, JPEG, PNG, etc.) and upload it using the system's application.

[0552] For example, a user uploads a file called "koseki_info.pdf" from an application.

[0553] 2. Terminal processing:

[0554] The device initially checks the uploaded file to make sure it is in the correct format. If it is, it temporarily saves the file and sends it to the server.

[0555] 3. Server processing:

[0556] The server receives the file and converts it into digital text using an OCR (Optical Character Recognition) engine, which then analyzes the text to extract necessary data such as name, date of birth, and parent-child relationship.

[0557] The extracted data is stored in a central database, and is registered in the format, for example, "Yamada Taro, born January 1, 1990, father: Yamada Ichiro, mother: Yamada Hanako."

[0558] 4. Data analysis and formatting:

[0559] The server extracts specific genealogical information from a central database in response to user requests, and uses generative AI models to format the data into a suitable format for family registers and family trees.

[0560] 5. Generating family records and genealogies using generative AI:

[0561] The server uses a generative AI model to generate family records and genealogies based on the formatted data, and the generated data is stored in a cloud system.

[0562] 6. Cloud Storage and Access:

[0563] The generated family registers and genealogies are stored in a cloud system and can be accessed online by users via the internet.

[0564] Hardware and Software Use

[0565] Hardware:

[0566] Smartphones, smart glasses

[0567] software:

[0568] OCR engine (pytesseract)

[0569] PDF conversion library (pdf2image)

[0570] HTTP request library (requests)

[0571] Generative AI Models

[0572] Specific examples

[0573] The user uses the smart glasses to scan their family register information file (e.g., "koseki_info.pdf").

[0574] Select Family Tree Generation from the glasses interface.

[0575] The generated family tree is displayed on the smart glasses' display and can be viewed in real time.

[0576] Below is an example of a prompt to send to a generative AI model:

[0577] Generate a family tree based on the following information:

[0578] Name: Taro Yamada

[0579] Date of Birth: January 1, 1990

[0580] Father: Ichiro Yamada

[0581] Mother: Hanako Yamada

[0582] This system allows users to easily and efficiently create, display, and save family records and genealogies.

[0583] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0584] Step 1:

[0585] User Action:

[0586] Users save their family register information as a digital file (e.g., PDF, JPEG, PNG, etc.) using a smartphone or smart glasses, and then upload this file using the application.

[0587] Input: Digital family register information file (e.g. "koseki_info.pdf")

[0588] Output: The uploaded file

[0589] Step 2:

[0590] Terminal handling:

[0591] The device performs an initial check on the uploaded file to ensure that the file format is correct. If the format is correct, the file is temporarily saved and prepared for transmission to the server.

[0592] Input: Uploaded file

[0593] Output: Verified files, files prepared for sending

[0594] Step 3:

[0595] Receiving files from the server:

[0596] The server receives the file sent from the device and prepares it for analysis.

[0597] Input: File sent from terminal

[0598] Output: Received files

[0599] Step 4:

[0600] OCR processing:

[0601] The server uses an OCR (Optical Character Recognition) engine to convert the received file into digital text.

[0602] Input: Received file

[0603] Output: Digital text extracted by OCR

[0604] Step 5:

[0605] Data Analysis:

[0606] The server analyzes the digital text extracted by OCR and extracts the necessary data (such as name, date of birth, parent-child relationship, etc.).

[0607] Input: Digital text extracted by OCR

[0608] Output: Extracted data (e.g., "Yamada Taro, born January 1, 1990, father: Yamada Ichiro, mother: Yamada Hanako")

[0609] Step 6:

[0610] Save to database:

[0611] The server stores the extracted data in a central database.

[0612] Input: Extracted data

[0613] Output: Data stored in the database

[0614] Step 7:

[0615] Extracting genealogy information:

[0616] The server extracts specific genealogy information from a central database in response to a user's request.

[0617] Input: User requests, central database

[0618] Output: Extracted genealogy information

[0619] Step 8:

[0620] Data formatting:

[0621] The server inputs the extracted family information into a generative AI model and formats it into a format suitable for death registers and family trees.

[0622] Input: Extracted genealogy information

[0623] Output: Formatted data

[0624] Step 9:

[0625] Generative AI for generating family trees:

[0626] The server uses a generative AI model to generate a family tree based on the formatted data.

[0627] Input: Formatted data

[0628] Output: The generated pedigree

[0629] Step 10:

[0630] Save to cloud system:

[0631] The server stores the generated family tree in a cloud system.

[0632] Input: Generated pedigree

[0633] Output: Family tree stored in a cloud system

[0634] Step 11:

[0635] User Views:

[0636] Users access the cloud system via the Internet and view the generated family tree.

[0637] Input: Family tree stored in the cloud system, user request to view it

[0638] Output: Family tree displayed on the user's device

[0639] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0640] This invention combines a system that uses a central database and a cloud-based system to automatically create up-to-date family registers and genealogies based on family register information collected from users' permanent domiciles with an emotion engine that recognizes user emotions.The system consists of user uploads, data analysis and extraction, storage in a database, generation of family registers and genealogies using generation AI, storage in a cloud system, and user emotion recognition and content adjustment using the emotion engine.

[0641] System configuration and specific operation

[0642] 1. User Action:

[0643] Users save the family register information they have obtained at their permanent domicile as a digital file and upload it to the system through the system's web interface. Uploading involves the user selecting and submitting a file using a file selection dialog.

[0644] Example: A user uploads "koseki_tanaka.pdf" to the system.

[0645] 2. Terminal processing:

[0646] The device receives the uploaded file and performs an initial check. It checks whether the file format (PDF, JPEG, PNG, etc.) is appropriate and whether the file can be loaded correctly. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[0647] 3. Server processing:

[0648] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The server then analyzes the text information extracted by the OCR engine to identify and extract the necessary data (such as name, date of birth, and parent-child relationship).

[0649] The extracted data is structured and stored in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[0650] 4. Data extraction and formatting:

[0651] In response to a user's request, the server extracts specific family information from a central database. Generative AI is then used to format the extracted data into a suitable format for a family register or family tree. Generational lists are created, arranging the data based on parent-child relationships.

[0652] Example: The server extracts all data related to the Tanaka family and formats it appropriately to generate a family tree for the "Tanaka family."

[0653] 5. Report generation using generative AI:

[0654] The AI ​​then generates a family register and family tree based on the data formatted by the server, which are then stored in a cloud system.

[0655] Example: The generation AI generates a family tree for the "Tanaka family" and saves it in cloud storage as "Tanaka family genealogy.pdf."

[0656] 6. Use of Emotion Engine:

[0657] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. While the user is browsing the family register or family tree, the emotion engine monitors the user's emotions in real time.

[0658] Based on the analyzed emotional information, the format and design of the displayed death register and family tree are automatically adjusted.

[0659] For example, if the system detects that the user is emotional, it will add memorable anecdotes or inspiring quotes to the family tree.

[0660] 7. Use of cloud systems:

[0661] The generated family tree and family records are stored in a cloud system and can be accessed online via the internet. Users can view the most up-to-date family tree, which also reflects emotional customization.

[0662] 8. Continuous updates:

[0663] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the changes and updates the central database. The generation AI then regenerates the family register and family tree and stores them in the cloud system.

[0664] Users' emotional data is also stored in the cloud system and continuously analyzed along with their viewing history of family records and genealogies.

[0665] Specific examples

[0666] 1. User uploads family register information:

[0667] The user uploads "koseki_tanaka.pdf" through the web interface.

[0668] The terminal receives the file and performs an initial check to send it to the server.

[0669] 2. The server analyzes and extracts the data and registers it in the database:

[0670] The server uses an OCR engine to analyze the file and extract information such as "Taro Tanaka, born January 1, 1990" as digital text, which is then stored in a database.

[0671] 3. Data shaping and generative AI:

[0672] Based on the user's request, the server extracts data about the "Tanaka family" and uses a generation AI to generate "Tanaka family tree.pdf."

[0673] 4. Use of Emotion Engine:

[0674] When a user browses the family tree, the emotion engine analyzes the user's emotions in real time and adjusts the display format and content accordingly. For example, if the user is emotional, it will display additional touching episodes.

[0675] 5. Use of cloud systems and continuous updates:

[0676] The server stores the generated family tree in a cloud system, and users can view the latest family tree online through a web interface.

[0677] If changes occur to family register information or emotional data, the system will automatically update to reflect the latest information.

[0678] In this way, the system provides a set of actions to efficiently and accurately create family registers and genealogies, and customize the content based on the user's emotions.

[0679] The processing flow will be explained below.

[0680] Step 1:

[0681] The user saves the family register information obtained from their permanent domicile as a digital file and accesses the system's web interface. The user clicks the "Upload" button, selects the family register file (e.g., "koseki_tanaka.pdf") from the file selection dialog, and uploads it.

[0682] Step 2:

[0683] The device receives the uploaded file and performs an initial check. The device checks whether the file format (PDF, JPEG, PNG, etc.) is appropriate and whether the file can be read normally. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[0684] Step 3:

[0685] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The server then analyzes the text information extracted by the OCR engine to identify and extract the necessary data (such as name, date of birth, parent-child relationship, etc.).

[0686] Step 4:

[0687] The server structures the extracted data and stores it in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[0688] Step 5:

[0689] When a user requests the generation of a family register or family tree, the server extracts data from a central database based on the specified criteria, and then uses the generation AI to format the extracted data and convert it into a format suitable for the family register or family tree.

[0690] Step 6:

[0691] The death register and family tree generated by the AI ​​are saved in a cloud system. For example, they are uploaded to cloud storage as "Tanaka Family Tree.pdf."

[0692] Step 7:

[0693] Users access the cloud system and view the latest family records and genealogy through a web interface, allowing them to access the latest information at any time.

[0694] Step 8:

[0695] When a user is viewing a family tree or family register, the emotion engine analyzes the user's facial expressions and voice to identify their emotional state, and automatically adjusts the format and design of the displayed family tree or family register based on the analyzed emotional information.

[0696] Step 9:

[0697] The server receives data from the emotion engine and updates the display content in real time based on the user's emotions. For example, if the user is emotional, it will add memorable anecdotes or inspiring quotes to the family tree.

[0698] Step 10:

[0699] The user's emotional data is stored in a cloud system and continuously analyzed along with the viewing history of the family tree and past records, allowing the system to customize the user's family tree based on their past emotional state when they next view it.

[0700] Step 11:

[0701] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the change and updates the central database. The generation AI then regenerates the family register and family tree and stores them in the cloud system. The user's emotional data is also updated appropriately to reflect the latest information.

[0702] Example 2

[0703] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0704] Conventional systems for creating family trees and past records require users to manually input and organize data, which is time-consuming and labor-intensive. Generating family trees and past records also requires specialized knowledge, making them difficult for average users to use. Furthermore, the lack of customization features that take user feelings into account makes it difficult to improve user satisfaction.

[0705] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving digital files uploaded by users, means for initially checking the format and content of the received digital files, means for transmitting files that have passed the initial check to the server, means for converting the received digital files into digital text using OCR technology and extracting necessary data, means for saving the extracted data in a central database, means for extracting and formatting data from the central database in response to a user request, means for generating a death register and / or family tree using a generation AI, means for saving the generated death register and / or family tree in a cloud system, means for the user to access the generated data through the cloud system, means including an emotion engine for analyzing the user's facial expressions and voice to identify emotions, means for adjusting display content based on the identified emotions, and means for automatically and continuously updating data. This allows users to easily create death registers and / or family trees, and also provides emotion-based customization functions, providing a highly satisfying experience.

[0706] A "user" is someone who operates the system, uploads digital files, and views the generated family registers and genealogies.

[0707] "Digital files" refers to document or image files stored in a digital format such as PDF, JPEG, or PNG.

[0708] "Receiving means" refers to the functions and devices for incorporating digital files sent by users into the system.

[0709] "Initial checking means" refers to a function or device that checks the format and content of a received digital file and determines whether it is appropriate.

[0710] A "server" is a computer that plays a central role in the system and is a device that performs various processes such as analyzing digital files, operating databases, and using generative AI.

[0711] "OCR technology" stands for optical character recognition technology, which analyzes the character information contained in digital files and extracts it as digital text.

[0712] "Digital text" refers to character data extracted using OCR technology in a format that can be understood by a computer.

[0713] "Data extraction means" refers to a function or device that extracts necessary information such as name, date of birth, and parent-child relationship from digital text.

[0714] The "central database" refers to a data storage system for centrally storing and managing extracted data.

[0715] "Formatting means" refers to the function or device that organizes and arranges data extracted from the central database in a format suitable for family registers and genealogies.

[0716] "Generative AI" refers to systems or software that use artificial intelligence technology to automatically generate death registers and family trees from formatted data.

[0717] A "cloud system" is an online storage system that stores data via the Internet and allows users to access it from anywhere.

[0718] "Access means" refers to the functions and devices that allow users to view and manipulate data stored in a cloud system.

[0719] An "emotion engine" is software or a device that analyzes a user's facial expressions and voice to identify their emotional state.

[0720] The "display content adjustment means" refers to a function or device that automatically changes the display format and content of the death register or family tree based on the emotion identified by the emotion engine.

[0721] "Update means" refers to a function or device that automatically updates the entire system based on new information when the information stored in the database is changed.

[0722] This invention is a system that automatically creates up-to-date family registers and genealogies using a central database and cloud-based system based on family register information collected from users' permanent domiciles. The system also combines an emotion engine that recognizes users' emotions to provide a more customized experience.

[0723] First, the user saves the family register information obtained from their permanent domicile as a digital file (e.g., PDF, JPEG) and uploads it through the system's web interface. The user uploads a digital file such as "koseki_example.pdf." The specific software used is a web browser (e.g., Google Chrome, Firefox).

[0724] The device then receives the uploaded file and performs an initial check to ensure that the file is in the correct format (PDF, JPEG, PNG, etc.) and can be loaded correctly. The detected file is then stored in a temporary storage area and prepared for transmission to the server. This initial check is performed using a file format inspection tool.

[0725] The server receives the file sent from the device and converts the file's contents into digital text using an OCR (Optical Character Recognition) engine (e.g., Tesseract OCR). In this process, the OCR engine extracts information such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" from "koseki_example.pdf." The extracted data is analyzed and stored in a structured central database. An SQL database (e.g., MySQL, PostgreSQL) is used for the central database.

[0726] Additionally, upon user request, the server extracts specific family information from the central database and formats the data. The formatted data is then converted into a format suitable for use in a family register or family tree using a generative AI model. For example, if a user requests the generation of a family tree for the "Tanaka family," the server retrieves the relevant data, and the generative AI generates it as "Tanaka Family Tree.pdf."

[0727] The generated family registers and genealogies are stored in a cloud system and can be accessed online by users via the internet. Cloud storage services include Amazon S3 and Google Drive.

[0728] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. While the user is viewing the family register or family tree, the emotion engine monitors the user's emotions in real time. Based on the analyzed emotional information, the format and design of the displayed family register or family tree is automatically adjusted. For example, if the system recognizes that the user is emotional, it will add memorable episodes or inspiring quotes to the family tree. The emotion engine uses the Microsoft Azure Emotion API and IBM Watson Tone Analyzer, among others.

[0729] Finally, if any changes occur to the family register information (e.g., new members are added or removed), the system automatically detects the changes and updates the central database. The generation AI then regenerates the family register and family tree and stores it in the cloud system. This entire process allows users to efficiently and accurately create family registers and family trees, and even customize them based on their emotions.

[0730] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0731] Step 1:

[0732] The user uploads their family register information.

[0733] Input: The digital file the user obtained at their permanent address (e.g. "koseki_example.pdf").

[0734] Specific behavior: A user logs in to the web interface, clicks the file upload button, selects "koseki_example.pdf", and performs the upload.

[0735] Output: "koseki_example.pdf" is sent to the system.

[0736] Step 2:

[0737] The terminal initially checks the file and sends it to the server.

[0738] Input: An uploaded digital file (e.g. "koseki_example.pdf").

[0739] Specific operation: The device checks the file format (PDF, JPEG, PNG, etc.) and checks whether the file can be read normally. Uses a file format checker.

[0740] Data processing: Inspect the file format and content to ensure there are no problems.

[0741] Output: Files that pass the initial checks are stored in a temporary storage area, ready to be sent to the server.

[0742] Step 3:

[0743] The server analyzes the file using OCR, extracts the data, and saves it.

[0744] Input: The file sent from the terminal (e.g. "koseki_example.pdf").

[0745] What happens: The server uses an OCR engine (e.g., Tesseract OCR) to convert the file contents into digital text.

[0746] Data processing: Using OCR processing, text information such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is extracted.

[0747] Output: The extracted data is structured and stored in a central database.

[0748] Step 4:

[0749] The server extracts and formats the data from the database.

[0750] Input: Structured data stored in a central database.

[0751] What it does: Extracts specific genealogy information and formats the data according to the user's request.

[0752] Data transformation: The transformation process creates a generational list and arranges the data based on parent-child relationships.

[0753] Output: The formatted data is passed to a generative AI model.

[0754] Step 5:

[0755] Generative AI generates death registers and family trees.

[0756] Input: Formatted data.

[0757] How it works: The generative AI model takes formatted data as input and generates a death register or family tree.

[0758] Data Calculation: Generate the structure and layout of the family tree based on prompts.

[0759] Output: The generated family register and family tree (e.g. "Tanaka Family Tree.pdf") will be created.

[0760] Step 6:

[0761] The server stores the generated data in a cloud system.

[0762] Input: The death register or family tree output by the generation AI (e.g., "Tanaka family family tree.pdf").

[0763] Specific operation: The server uploads data to cloud storage (e.g., Amazon S3, Google Drive).

[0764] Data processing: Uploading data and storing it on the cloud.

[0765] Output: Death registers and family trees stored in a cloud system that can be accessed by users.

[0766] Step 7:

[0767] The emotion engine analyzes user emotions and adjusts content accordingly.

[0768] Input: User facial and voice data.

[0769] Specific operation: The emotion engine uses the camera and microphone to collect and analyze the user's facial expressions and voice.

[0770] Data Computing: Using sentiment analysis algorithms to identify a user's emotional state (e.g., happy, sad, moved).

[0771] Output: Display content is adjusted based on identified emotion data.

[0772] Step 8:

[0773] The server automatically updates the database and cloud system when updated.

[0774] Input: Newly uploaded or changed family register information.

[0775] How it works: When a new digital file is uploaded, the server detects the change, performs OCR analysis, extracts data, updates the database, and regenerates it using generative AI.

[0776] Data processing: Automatic updates to databases and cloud systems.

[0777] Output: The latest family register and genealogy are regenerated and stored in the cloud system.

[0778] This allows the system to efficiently and accurately create family registers and genealogies, customize them based on user sentiment, and automatically update them with the latest information.

[0779] (Application example 2)

[0780] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0781] Conventional genealogy and death register generation systems do not adjust content based on user emotions, resulting in a limited user experience. Furthermore, the convenience of viewing personal information in a paperless manner in a physical store is also an issue. The present invention aims to solve these issues by providing real-time content adjustment using emotion analysis and an interactive in-store experience.

[0782] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving personal information uploaded by a user, means for analyzing the received personal information and extracting necessary data, means for saving the extracted data in a centralized data storage system, means for extracting data from the centralized data storage system to generate a death register and / or a family tree, means for saving the generated death register and / or a family tree on a cloud platform, means for adjusting display content using an emotion engine that identifies the user's emotions, and means for providing emotion-based information to a store display device. This makes it possible to display an interactive death register and / or a family tree according to the user's emotions.

[0783] "User" refers to a person who uses the system to provide personal information and generate and view death registers and genealogy charts.

[0784] "Personal information" refers to information used to identify individuals or determine genealogical relationships, such as family register information.

[0785] "Means for receiving" refers to system components or functions that acquire personal information electronically, in whole or in part.

[0786] "Means of analysis" refers to system components and functions that process received personal information using technologies such as data conversion and character recognition, and extract the necessary data.

[0787] "Extraction means" refers to system components or functions that extract specific information from the analyzed data.

[0788] "Centralized data storage system" refers to a database system that centrally stores and manages analyzed and extracted data.

[0789] "Means for generating" refers to system components and functions that use the extracted data to automatically create death registers and genealogy charts.

[0790] "Cloud infrastructure" refers to a cloud storage system that stores the generated death registers and genealogy charts and makes them accessible via the Internet.

[0791] An "emotion engine" refers to technology or a system that analyzes and identifies the user's emotional state, such as facial expressions and voice.

[0792] "Means for adjusting the displayed content" refers to system components or functions that dynamically change the content and format of the displayed death register or genealogy chart based on emotional information obtained from the emotion engine.

[0793] "Display device" refers to a device (e.g., tablet, large display, etc.) for displaying the generated death register or genealogy chart.

[0794] A specific system for implementing the present invention operates according to the following steps.

[0795] First, a user uses their smartphone to access a display device such as a tablet or large display. When the user uploads their personal information, the device receives this information and sends it to a server.

[0796] The server analyzes the received personal information and extracts the necessary data. This process involves converting the uploaded document into digital text using OCR technology such as Google Cloud Vision. The extracted data is then stored in a centralized data storage system (e.g., AWS RDS).

[0797] The server then uses this data to generate a family register or genealogy chart upon user request. This process uses a generative AI model (e.g., OpenAI GPT-4) to generate content efficiently and accurately. The generated family register or genealogy chart is then stored in a cloud infrastructure (e.g., Amazon S3).

[0798] In parallel, an emotion engine (e.g., Microsoft Azure Cognitive Services) analyzes the user's emotions in real time by monitoring their facial expressions and voice while they browse the family register or genealogy chart to identify their emotional state.

[0799] The server uses this emotional information to dynamically adjust the content displayed. For example, if the emotion engine identifies that the user is emotional, the system will add touching anecdotes or quotes to the death register or family tree. This adjustment is made in real time, allowing users to experience the most appropriate content based on their emotions.

[0800] Furthermore, emotion-based information is automatically provided to store display devices, allowing store staff to provide appropriate support and suggestions to customers.

[0801] In this way, the present invention realizes interactive display of death registers and genealogy charts according to the user's emotions, providing a paperless experience in a physical store.

[0802] For example, a user uploads the family register information for the "Yamada family," and OCR technology extracts information such as "Yamada Taro, born January 1, 1980," and generates a "Yamada Family Tree.pdf" based on this information. The emotion engine analyzes the user's emotions, and if it determines that the user is emotional, it provides the following prompt to the generative AI model:

[0803] "Add inspiring stories and quotes based on the Yamada family tree data and the user's emotional state."

[0804] This prompt enables the generative AI model to generate supplementary content, including inspiring anecdotes and quotes, to provide to users in addition to the Yamada family tree.

[0805] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0806] Step 1:

[0807] The user uploads personal information from their smartphone. The input is the personal information file selected by the user, and the output is the data sent to the device. Specifically, the user accesses the specified web interface, selects the file to upload (e.g., "koseki_yamada.pdf") from the file selection dialog, and presses the send button.

[0808] Step 2:

[0809] The device receives the uploaded file and prepares it to be sent to the server. The input is the file uploaded by the user, and the output is the data to be sent to the server. Specifically, the device checks the file format (PDF, JPEG, PNG, etc.) and checks the file's integrity, and if there are no problems, stores it in a temporary storage area.

[0810] Step 3:

[0811] The server receives the file sent from the device and converts the file contents into digital text using OCR technology. The input is the personal information file sent from the device, and the output is digital text data. Specifically, the server calls the Google Cloud Vision API, analyzes the file, and extracts the text information. For example, the text data obtained is "Yamada Taro, born January 1, 1980."

[0812] Step 4:

[0813] The server parses the digital text, extracts the necessary data (such as name, date of birth, parent-child relationship, etc.), and stores it in a centralized data storage system. The input is the digital text, and the output is a structured database entry. Specifically, the server uses regular expressions and parsing algorithms to extract the data and store it in a database (e.g., AWS RDS).

[0814] Step 5:

[0815] In response to user requests, the server uses a generative AI model to generate a family register or family tree. The input is data extracted from a centralized data storage system, and the output is a PDF file of the generated family register or family tree. Specifically, the server uses OpenAI GPT-4 to generate prompts based on the extracted data and create the family register or family tree. Example: "Yamada Family Tree.pdf" is generated.

[0816] Step 6:

[0817] The generated death registers and genealogy charts are stored on a cloud platform and can be accessed by users. The input is the generated PDF file, and the output is an access link on the cloud storage. Specifically, the server uses a cloud storage service such as Amazon S3 to upload the file and generate an access link.

[0818] Step 7:

[0819] The emotion engine analyzes the user's emotions in real time and adjusts the displayed content. The input is the user's facial expression and voice data, and the output is content adjusted based on the user's emotional state. Specifically, it uses Microsoft Azure Cognitive Services to analyze the user's facial expressions and voice, and the server dynamically adjusts the content based on the obtained emotional information. For example, if the user is moved, an emotional episode will be added.

[0820] Step 8:

[0821] Emotion-based information is provided to display devices in stores. The input is the adjusted content, and the output is what is displayed on the display device. Specifically, the adjusted content is sent from the server to a tablet device or large display, and then displayed on the display device. This enables store staff to provide appropriate support and suggestions to customers.

[0822] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0823] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0824] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0825] [Third embodiment]

[0826] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0827] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0828] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0829] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0830] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0831] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0832] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0833] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0834] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0835] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0836] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0837] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0838] This invention is a system that automatically creates up-to-date family registers and genealogies using a central database and cloud-based system based on family register information collected from users' permanent domiciles. The system consists of a user upload, data analysis and extraction, storage in the database, generation of family registers and genealogies using AI, and storage in the cloud system.

[0839] System configuration and specific operation

[0840] 1. User Action:

[0841] Users save the family register information they have obtained at their permanent domicile as a digital file and upload it to the system through the system's web interface. Uploading involves the user selecting and submitting a file using a file selection dialog.

[0842] Example: A user uploads "koseki_tanaka.pdf" to the system.

[0843] 2. Terminal processing:

[0844] The device initially checks the received file to ensure that it is in the correct file format (PDF, JPEG, PNG, etc.). If the file can be read successfully, it is stored in a temporary storage area and prepared for transmission to the server.

[0845] 3. Server processing:

[0846] The server receives the file sent from the device and converts it into digital text using an OCR (Optical Character Recognition) engine. At this time, the server analyzes the text information extracted by OCR and extracts necessary data (such as name, date of birth, parent-child relationship, etc.).

[0847] The extracted data is structured and stored in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[0848] 4. Data extraction and formatting:

[0849] The server extracts specific family information from a central database in response to a user's request, then uses generative AI to format the extracted data into a suitable format for a family register or family tree, creating a generational list and arranging the data based on parent-child relationships.

[0850] Example: The server extracts all data related to the Tanaka family and formats it appropriately to generate a family tree for the "Tanaka family."

[0851] 5. Report generation using generative AI:

[0852] The AI ​​then generates a family register and family tree based on the data formatted by the server, which are then stored in a cloud system.

[0853] Example: The generation AI generates a family tree for the "Tanaka family" and saves it in cloud storage as "Tanaka family genealogy.pdf."

[0854] 6. Use of cloud systems:

[0855] The generated family registers and family trees are stored in a cloud system and can be accessed online via the internet, allowing users to view the most up-to-date family trees.

[0856] Specific examples

[0857] 1. User uploads family register information:

[0858] The user uploads "koseki_tanaka.pdf" through the web interface.

[0859] The terminal receives the file and performs an initial check to send it to the server.

[0860] 2. The server analyzes and extracts the data and registers it in the database:

[0861] The server uses an OCR engine to analyze the file and extract information such as "Taro Tanaka, born January 1, 1990" as digital text, which is then stored in a database.

[0862] 3. Data shaping and generative AI:

[0863] Based on the user's request, the server extracts data about the "Tanaka family" and uses a generation AI to generate "Tanaka family tree.pdf."

[0864] 4. Cloud storage and use:

[0865] The server stores the generated family tree in a cloud system, and users can view the latest family tree online through a web interface.

[0866] In this way, the system provides a series of operations that allow users to efficiently and accurately create family registers and genealogies, and keep the information up to date at all times.

[0867] The processing flow will be explained below.

[0868] Step 1:

[0869] The user saves the family register information obtained from their permanent domicile as a digital file and accesses the system's web interface. The user clicks the "Upload" button, selects the family register file (e.g., "koseki_tanaka.pdf") from the file selection dialog, and uploads it.

[0870] Step 2:

[0871] The device receives the uploaded file and performs an initial check. It checks whether the file format is appropriate (PDF, JPEG, PNG, etc.) and whether the file can be loaded correctly. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[0872] Step 3:

[0873] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The OCR engine then analyzes the extracted text information to identify and extract the necessary data (such as name, date of birth, and parent-child relationship).

[0874] Step 4:

[0875] The server structures the extracted data and stores it in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[0876] Step 5:

[0877] When a user requests the generation of a family register or family tree, the server extracts data from the central database based on the specified criteria, and then uses the generation AI to format the extracted data and convert it into a format suitable for the family register or family tree.

[0878] Step 6:

[0879] The server saves the generated family register and family tree in the cloud system. The generated family register and family tree are uploaded to the cloud storage as, for example, "Tanaka Family Genealogy.pdf."

[0880] Step 7:

[0881] Users access the cloud system and view the latest family records and genealogy through a web interface, allowing them to access the latest information at any time.

[0882] Step 8:

[0883] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the change and updates the central database. Based on the updated information, the AI ​​generates new family registers and family trees, which are then stored in the cloud system.

[0884] Example 1

[0885] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0886] In conventional family register information management systems, digitizing and analyzing family register information required a great deal of time and effort. Furthermore, updating the digitized data and generating genealogy information in an appropriate format was done manually, resulting in issues with accuracy and efficiency. This made it difficult for users to quickly obtain the latest genealogy information.

[0887] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0888] In this invention, the server includes a means for receiving family register information uploaded by users, a means for converting the received family register information into digital text using optical character recognition technology, a means for extracting necessary data and storing it in a central database, a means for generating genealogy information using artificial intelligence, and a means for storing the generated genealogy information in a cloud computing system, thereby enabling users to efficiently and accurately obtain the latest genealogy information.

[0889] "User" means an individual or corporation that uses this system to upload family register information and generate and view genealogy information.

[0890] "Family register information" refers to public records that include names, dates of birth, parent-child relationships, etc.

[0891] "Means for receiving" means a device or process for retrieving digital files uploaded by users onto the server.

[0892] "Means for analyzing and extracting necessary data" refers to a method or device that identifies and extracts important information (e.g., name, date of birth, parentage, etc.) from the received digital file.

[0893] "Optical character recognition technology" refers to technology that extracts text data from images or scanned documents.

[0894] "Digital text" refers to text data converted from an image or scan using optical character recognition technology.

[0895] "Central database" refers to a database system that centrally manages extracted and stored data.

[0896] "Genealogy information" refers to data showing family lineage and historical lineage, such as family trees and death registers.

[0897] "Generative AI" refers to an AI technology that generates new information (e.g., family trees or death registers) in a specified format based on given data.

[0898] A "cloud computing system" is a service that stores data on the Internet and allows users to access it remotely.

[0899] This invention is a system that automatically generates up-to-date genealogy information based on family register information collected by users from their registered domiciles, using a central database and a cloud computing system.

[0900] First, the user saves the family register information obtained from their permanent domicile as a digital file. This digital file can be in a format such as PDF, JPEG, or PNG. Next, the user uploads this digital file to the system through the web interface. For example, the user selects "koseki_sample.pdf" and clicks the upload button to send it to the system.

[0901] The device performs an initial check of the file received from the user, confirming that the file format is correct and testing that it can be read successfully. If the file is confirmed, it is stored in a temporary storage area and prepared for transmission to the server.

[0902] The server receives the file sent from the device. It receives the HTTP POST request and saves the file in the specified directory. The server then uses OCR (optical character recognition) technology to extract the text data from the file. For example, the Tesseract OCR engine is used in this process. The extracted text data is saved and analyzed for necessary data (such as name, date of birth, and parent-child relationship). Regular expressions and text analysis algorithms are used for the analysis.

[0903] The analyzed data is structured and stored in a central database. An example of specific extracted data is "Name: Taro Tanaka, Date of birth: January 1, 1990, Father: Ichiro Tanaka, Mother: Hanako Tanaka."

[0904] When a user requests the generation of genealogy information, the server extracts and formats the relevant data from a central database. The extracted data is fed into a generative artificial intelligence (generative AI) that generates new information (e.g., a family tree or death register) in the specified format. The generative AI uses a text-based prompt. For example, a prompt might be "Please generate a family tree for the Tanaka family."

[0905] The generated genealogical information is stored as a digital file (e.g., "tanaka_family_tree.pdf") on a cloud computing system. Users can access this information via the internet and view the latest genealogical information. This system enables users to efficiently and accurately obtain, store, and share the latest genealogical information.

[0906] The above is a specific embodiment for carrying out the present invention. This system allows users to quickly process and analyze family register information and keep it up to date.

[0907] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0908] Step 1:

[0909] The user saves the family register information obtained from their permanent domicile as a digital file and uploads this digital file through the system's web interface. As a concrete example, the user selects "koseki_sample.pdf" and clicks the upload button. The input of this step is the "family register information file selected by the user," and the output is "sending the file to the server."

[0910] Step 2:

[0911] The terminal performs an initial check of the file received from the user. Specifically, it checks whether the file format is PDF, JPEG, or PNG, and tests whether it can be read successfully. Once the file is confirmed, it is stored in a temporary storage area. The input of this step is the "file sent by the user," and the output is the "file stored in the temporary storage area."

[0912] Step 3:

[0913] The terminal prepares to send the file from the temporary storage area to the server. Specifically, it moves the file and calls the server sending script. The input of this step is the "file stored in the temporary storage area" and the output is the "file to be sent to the server."

[0914] Step 4:

[0915] The server receives the file sent from the terminal. Specifically, it receives an HTTP POST request and saves the file in a specified directory. The input of this step is the "file sent from the terminal" and the output is the "file saved in the specified directory on the server."

[0916] Step 5:

[0917] The server uses OCR (Optical Character Recognition) technology to extract the text data in the file. For example, it invokes the Tesseract OCR engine to extract the digital text. The input of this step is the file stored in the specified directory on the server, and the output is the extracted text data.

[0918] Step 6:

[0919] The server parses the text data and extracts the necessary data (such as name, date of birth, parent-child relationship, etc.). Specifically, it filters the data using regular expressions and text analysis algorithms. The input of this step is the text data extracted by OCR, and the output is structured data.

[0920] Step 7:

[0921] The server stores the extracted data in a central database. Specifically, it generates SQL queries and inserts them into the database. The input of this step is "structured data" and the output is "data stored in the database."

[0922] Step 8:

[0923] The server extracts specific genealogical information from the central database based on the user's request. Specifically, it generates an SQL select query to extract and format the data. The inputs to this step are the data stored in the database and the user's request, and the output is the formatted genealogical information data.

[0924] Step 9:

[0925] The server inputs the formatted data into the generative AI model to generate genealogy information. As a specific example, the prompt "Please generate a family tree for the Tanaka family" is input, and a file called "tanaka_family_tree.pdf" is generated. The inputs for this step are the formatted family information data and the prompt, and the output is the generated genealogy information file.

[0926] Step 10:

[0927] The server saves the generated genealogy information file in a cloud computing system. Specifically, it calls a cloud storage API and uploads the file. The input of this step is the "generated genealogy information file," and the output is the "file saved in the cloud system."

[0928] Step 11:

[0929] The user views the genealogy information generated through the cloud system. Specifically, the user logs in to the web interface and downloads or views the generated file. The input of this step is the "file stored in the cloud system," and the output is "user viewing of genealogy information."

[0930] (Application example 1)

[0931] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0932] Existing systems for generating family trees and past records based on family register information require users to organize and analyze the information themselves, which is time-consuming and labor-intensive. Furthermore, the generated information may not be easily stored or accessible. Furthermore, there is a lack of means to directly provide family trees and past records to customers in physical stores. To solve these issues, there is a need for an efficient and easy-to-use system for analyzing, generating, and displaying information that utilizes smart devices.

[0933] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0934] In this invention, the server includes means for receiving family register information uploaded by a user, means for analyzing the received family register information and extracting necessary data, means for saving the extracted data in a central database, means for extracting data from the central database to generate a death register and family tree, means for saving the generated death register and family tree in a cloud system, means for analyzing the received family register information using a smart device, and means for displaying the death register and family tree generated by the smart device, thereby enabling users to easily analyze family register information and efficiently generate, display, and save a death register and family tree.

[0935] "User" refers to an individual who uses the system to upload family register information and use the analyzed and generated family registers and genealogies.

[0936] "Family register information" refers to official documents containing data such as the name, date of birth, and kinship relationships of registered individuals.

[0937] "Analysis" refers to the process of extracting necessary information from received digital data and organizing and transforming it.

[0938] "Central database" refers to a centralized storage system for storing extracted digital text and analytical data for later search and retrieval.

[0939] A "kakocho" is a document or digital file that compiles historical records of individuals and families.

[0940] A "family tree" is a visual diagram showing a family's kinship relationships across generations.

[0941] A "cloud system" refers to a network of remote servers for storing and managing data over the Internet.

[0942] "Smart devices" refers to devices with internet connectivity and advanced computing capabilities, such as smartphones, smart glasses, and head-mounted displays.

[0943] "Analysis" refers to the process of processing received data to categorize and organize the information for a specific purpose.

[0944] "Display" refers to the process of visually presenting the generated family register and genealogy data on an interface such as a digital screen.

[0945] "Generative AI" refers to artificial intelligence models used to generate new information or content based on existing data.

[0946] A system for implementing this invention comprises a user, a terminal (a smart device such as a smartphone or smart glasses), and a server.

[0947] Specific actions

[0948] 1. User Action:

[0949] Users use their smartphones or smart glasses to save their family register information as a digital file (e.g., PDF, JPEG, PNG, etc.) and upload it using the system's application.

[0950] For example, a user uploads a file called "koseki_info.pdf" from an application.

[0951] 2. Terminal processing:

[0952] The device initially checks the uploaded file to make sure it is in the correct format. If it is, it temporarily saves the file and sends it to the server.

[0953] 3. Server processing:

[0954] The server receives the file and converts it into digital text using an OCR (Optical Character Recognition) engine, which then analyzes the text to extract necessary data such as name, date of birth, and parent-child relationship.

[0955] The extracted data is stored in a central database, and is registered in the format, for example, "Yamada Taro, born January 1, 1990, father: Yamada Ichiro, mother: Yamada Hanako."

[0956] 4. Data analysis and formatting:

[0957] The server extracts specific genealogical information from a central database in response to user requests, and uses generative AI models to format the data into a suitable format for family registers and family trees.

[0958] 5. Generating family records and genealogies using generative AI:

[0959] The server uses a generative AI model to generate family records and genealogies based on the formatted data, and the generated data is stored in a cloud system.

[0960] 6. Cloud Storage and Access:

[0961] The generated family registers and genealogies are stored in a cloud system and can be accessed online by users via the internet.

[0962] Hardware and Software Use

[0963] Hardware:

[0964] Smartphones, smart glasses

[0965] software:

[0966] OCR engine (pytesseract)

[0967] PDF conversion library (pdf2image)

[0968] HTTP request library (requests)

[0969] Generative AI Models

[0970] Specific examples

[0971] The user uses the smart glasses to scan their family register information file (e.g., "koseki_info.pdf").

[0972] Select Family Tree Generation from the glasses interface.

[0973] The generated family tree is displayed on the smart glasses' display and can be viewed in real time.

[0974] Below is an example of a prompt to send to a generative AI model:

[0975] Generate a family tree based on the following information:

[0976] Name: Taro Yamada

[0977] Date of Birth: January 1, 1990

[0978] Father: Ichiro Yamada

[0979] Mother: Hanako Yamada

[0980] This system allows users to easily and efficiently create, display, and save family records and genealogies.

[0981] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0982] Step 1:

[0983] User Action:

[0984] Users save their family register information as a digital file (e.g., PDF, JPEG, PNG, etc.) using a smartphone or smart glasses, and then upload this file using the application.

[0985] Input: Digital family register information file (e.g. "koseki_info.pdf")

[0986] Output: The uploaded file

[0987] Step 2:

[0988] Terminal handling:

[0989] The device performs an initial check on the uploaded file to ensure that the file format is correct. If the format is correct, the file is temporarily saved and prepared for transmission to the server.

[0990] Input: Uploaded file

[0991] Output: Verified files, files prepared for sending

[0992] Step 3:

[0993] Receiving files from the server:

[0994] The server receives the file sent from the device and prepares it for analysis.

[0995] Input: File sent from terminal

[0996] Output: Received files

[0997] Step 4:

[0998] OCR processing:

[0999] The server uses an OCR (Optical Character Recognition) engine to convert the received file into digital text.

[1000] Input: Received file

[1001] Output: Digital text extracted by OCR

[1002] Step 5:

[1003] Data Analysis:

[1004] The server analyzes the digital text extracted by OCR and extracts the necessary data (such as name, date of birth, parent-child relationship, etc.).

[1005] Input: Digital text extracted by OCR

[1006] Output: Extracted data (e.g., "Yamada Taro, born January 1, 1990, father: Yamada Ichiro, mother: Yamada Hanako")

[1007] Step 6:

[1008] Save to database:

[1009] The server stores the extracted data in a central database.

[1010] Input: Extracted data

[1011] Output: Data stored in the database

[1012] Step 7:

[1013] Extracting genealogy information:

[1014] The server extracts specific genealogy information from a central database in response to a user's request.

[1015] Input: User requests, central database

[1016] Output: Extracted genealogy information

[1017] Step 8:

[1018] Data formatting:

[1019] The server inputs the extracted family information into a generative AI model and formats it into a format suitable for death registers and family trees.

[1020] Input: Extracted genealogy information

[1021] Output: Formatted data

[1022] Step 9:

[1023] Generative AI for generating family trees:

[1024] The server uses a generative AI model to generate a family tree based on the formatted data.

[1025] Input: Formatted data

[1026] Output: The generated pedigree

[1027] Step 10:

[1028] Save to cloud system:

[1029] The server stores the generated family tree in a cloud system.

[1030] Input: Generated pedigree

[1031] Output: Family tree stored in a cloud system

[1032] Step 11:

[1033] User Views:

[1034] Users access the cloud system via the Internet and view the generated family tree.

[1035] Input: Family tree stored in the cloud system, user request to view it

[1036] Output: Family tree displayed on the user's device

[1037] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1038] This invention combines a system that uses a central database and a cloud-based system to automatically create up-to-date family registers and genealogies based on family register information collected from users' permanent domiciles with an emotion engine that recognizes user emotions.The system consists of user uploads, data analysis and extraction, storage in a database, generation of family registers and genealogies using generation AI, storage in a cloud system, and user emotion recognition and content adjustment using the emotion engine.

[1039] System configuration and specific operation

[1040] 1. User Action:

[1041] Users save the family register information they have obtained at their permanent domicile as a digital file and upload it to the system through the system's web interface. Uploading involves the user selecting and submitting a file using a file selection dialog.

[1042] Example: A user uploads "koseki_tanaka.pdf" to the system.

[1043] 2. Terminal processing:

[1044] The device receives the uploaded file and performs an initial check. It checks whether the file format (PDF, JPEG, PNG, etc.) is appropriate and whether the file can be loaded correctly. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[1045] 3. Server processing:

[1046] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The server then analyzes the text information extracted by the OCR engine to identify and extract the necessary data (such as name, date of birth, and parent-child relationship).

[1047] The extracted data is structured and stored in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[1048] 4. Data extraction and formatting:

[1049] In response to a user's request, the server extracts specific family information from a central database. Generative AI is then used to format the extracted data into a suitable format for a family register or family tree. Generational lists are created, arranging the data based on parent-child relationships.

[1050] Example: The server extracts all data related to the Tanaka family and formats it appropriately to generate a family tree for the "Tanaka family."

[1051] 5. Report generation using generative AI:

[1052] The AI ​​then generates a family register and family tree based on the data formatted by the server, which are then stored in a cloud system.

[1053] Example: The generation AI generates a family tree for the "Tanaka family" and saves it in cloud storage as "Tanaka family genealogy.pdf."

[1054] 6. Use of Emotion Engine:

[1055] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. While the user is browsing the family register or family tree, the emotion engine monitors the user's emotions in real time.

[1056] Based on the analyzed emotional information, the format and design of the displayed death register and family tree are automatically adjusted.

[1057] For example, if the system detects that the user is emotional, it will add memorable anecdotes or inspiring quotes to the family tree.

[1058] 7. Use of cloud systems:

[1059] The generated family tree and family records are stored in a cloud system and can be accessed online via the internet. Users can view the most up-to-date family tree, which also reflects emotional customization.

[1060] 8. Continuous updates:

[1061] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the changes and updates the central database. The generation AI then regenerates the family register and family tree and stores them in the cloud system.

[1062] Users' emotional data is also stored in the cloud system and continuously analyzed along with their viewing history of family records and genealogies.

[1063] Specific examples

[1064] 1. User uploads family register information:

[1065] The user uploads "koseki_tanaka.pdf" through the web interface.

[1066] The terminal receives the file and performs an initial check to send it to the server.

[1067] 2. The server analyzes and extracts the data and registers it in the database:

[1068] The server uses an OCR engine to analyze the file and extract information such as "Taro Tanaka, born January 1, 1990" as digital text, which is then stored in a database.

[1069] 3. Data shaping and generative AI:

[1070] Based on the user's request, the server extracts data about the "Tanaka family" and uses a generation AI to generate "Tanaka family tree.pdf."

[1071] 4. Use of Emotion Engine:

[1072] When a user browses the family tree, the emotion engine analyzes the user's emotions in real time and adjusts the display format and content accordingly. For example, if the user is emotional, it will display additional touching episodes.

[1073] 5. Use of cloud systems and continuous updates:

[1074] The server stores the generated family tree in a cloud system, and users can view the latest family tree online through a web interface.

[1075] If changes occur to family register information or emotional data, the system will automatically update to reflect the latest information.

[1076] In this way, the system provides a set of actions to efficiently and accurately create family registers and genealogies, and customize the content based on the user's emotions.

[1077] The processing flow will be explained below.

[1078] Step 1:

[1079] The user saves the family register information obtained from their permanent domicile as a digital file and accesses the system's web interface. The user clicks the "Upload" button, selects the family register file (e.g., "koseki_tanaka.pdf") from the file selection dialog, and uploads it.

[1080] Step 2:

[1081] The device receives the uploaded file and performs an initial check. The device checks whether the file format (PDF, JPEG, PNG, etc.) is appropriate and whether the file can be read normally. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[1082] Step 3:

[1083] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The server then analyzes the text information extracted by the OCR engine to identify and extract the necessary data (such as name, date of birth, parent-child relationship, etc.).

[1084] Step 4:

[1085] The server structures the extracted data and stores it in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[1086] Step 5:

[1087] When a user requests the generation of a family register or family tree, the server extracts data from a central database based on the specified criteria, and then uses the generation AI to format the extracted data and convert it into a format suitable for the family register or family tree.

[1088] Step 6:

[1089] The death register and family tree generated by the AI ​​are saved in a cloud system. For example, they are uploaded to cloud storage as "Tanaka Family Tree.pdf."

[1090] Step 7:

[1091] Users access the cloud system and view the latest family records and genealogy through a web interface, allowing them to access the latest information at any time.

[1092] Step 8:

[1093] When a user is viewing a family tree or family register, the emotion engine analyzes the user's facial expressions and voice to identify their emotional state, and automatically adjusts the format and design of the displayed family tree or family register based on the analyzed emotional information.

[1094] Step 9:

[1095] The server receives data from the emotion engine and updates the display content in real time based on the user's emotions. For example, if the user is emotional, it will add memorable anecdotes or inspiring quotes to the family tree.

[1096] Step 10:

[1097] The user's emotional data is stored in a cloud system and continuously analyzed along with the viewing history of the family tree and past records, allowing the system to customize the user's family tree based on their past emotional state when they next view it.

[1098] Step 11:

[1099] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the change and updates the central database. The generation AI then regenerates the family register and family tree and stores them in the cloud system. The user's emotional data is also updated appropriately to reflect the latest information.

[1100] Example 2

[1101] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1102] Conventional systems for creating family trees and past records require users to manually input and organize data, which is time-consuming and labor-intensive. Generating family trees and past records also requires specialized knowledge, making them difficult for average users to use. Furthermore, the lack of customization features that take user feelings into account makes it difficult to improve user satisfaction.

[1103] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving digital files uploaded by users, means for initially checking the format and content of the received digital files, means for transmitting files that have passed the initial check to the server, means for converting the received digital files into digital text using OCR technology and extracting necessary data, means for saving the extracted data in a central database, means for extracting and formatting data from the central database in response to a user request, means for generating a death register and / or family tree using a generation AI, means for saving the generated death register and / or family tree in a cloud system, means for the user to access the generated data through the cloud system, means including an emotion engine for analyzing the user's facial expressions and voice to identify emotions, means for adjusting display content based on the identified emotions, and means for automatically and continuously updating data. This allows users to easily create death registers and / or family trees, and also provides emotion-based customization functions, providing a highly satisfying experience.

[1104] A "user" is someone who operates the system, uploads digital files, and views the generated family registers and genealogies.

[1105] "Digital files" refers to document or image files stored in a digital format such as PDF, JPEG, or PNG.

[1106] "Receiving means" refers to the functions and devices for incorporating digital files sent by users into the system.

[1107] "Initial checking means" refers to a function or device that checks the format and content of a received digital file and determines whether it is appropriate.

[1108] A "server" is a computer that plays a central role in the system and is a device that performs various processes such as analyzing digital files, operating databases, and using generative AI.

[1109] "OCR technology" stands for optical character recognition technology, which analyzes the character information contained in digital files and extracts it as digital text.

[1110] "Digital text" refers to character data extracted using OCR technology in a format that can be understood by a computer.

[1111] "Data extraction means" refers to a function or device that extracts necessary information such as name, date of birth, and parent-child relationship from digital text.

[1112] The "central database" refers to a data storage system for centrally storing and managing extracted data.

[1113] "Formatting means" refers to the function or device that organizes and arranges data extracted from the central database in a format suitable for family registers and genealogies.

[1114] "Generative AI" refers to systems or software that use artificial intelligence technology to automatically generate death registers and family trees from formatted data.

[1115] A "cloud system" is an online storage system that stores data via the Internet and allows users to access it from anywhere.

[1116] "Access means" refers to the functions and devices that allow users to view and manipulate data stored in a cloud system.

[1117] An "emotion engine" is software or a device that analyzes a user's facial expressions and voice to identify their emotional state.

[1118] The "display content adjustment means" refers to a function or device that automatically changes the display format and content of the death register or family tree based on the emotion identified by the emotion engine.

[1119] "Update means" refers to a function or device that automatically updates the entire system based on new information when the information stored in the database is changed.

[1120] This invention is a system that automatically creates up-to-date family registers and genealogies using a central database and cloud-based system based on family register information collected from users' permanent domiciles. The system also combines an emotion engine that recognizes users' emotions to provide a more customized experience.

[1121] First, the user saves the family register information obtained from their permanent domicile as a digital file (e.g., PDF, JPEG) and uploads it through the system's web interface. The user uploads a digital file such as "koseki_example.pdf." The specific software used is a web browser (e.g., Google Chrome, Firefox).

[1122] The device then receives the uploaded file and performs an initial check to ensure that the file is in the correct format (PDF, JPEG, PNG, etc.) and can be loaded correctly. The detected file is then stored in a temporary storage area and prepared for transmission to the server. This initial check is performed using a file format inspection tool.

[1123] The server receives the file sent from the device and converts the file's contents into digital text using an OCR (Optical Character Recognition) engine (e.g., Tesseract OCR). In this process, the OCR engine extracts information such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" from "koseki_example.pdf." The extracted data is analyzed and stored in a structured central database. An SQL database (e.g., MySQL, PostgreSQL) is used for the central database.

[1124] Additionally, upon user request, the server extracts specific family information from the central database and formats the data. The formatted data is then converted into a format suitable for use in a family register or family tree using a generative AI model. For example, if a user requests the generation of a family tree for the "Tanaka family," the server retrieves the relevant data, and the generative AI generates it as "Tanaka Family Tree.pdf."

[1125] The generated family registers and genealogies are stored in a cloud system and can be accessed online by users via the internet. Cloud storage services include Amazon S3 and Google Drive.

[1126] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. While the user is viewing the family register or family tree, the emotion engine monitors the user's emotions in real time. Based on the analyzed emotional information, the format and design of the displayed family register or family tree is automatically adjusted. For example, if the system recognizes that the user is emotional, it will add memorable episodes or inspiring quotes to the family tree. The emotion engine uses the Microsoft Azure Emotion API and IBM Watson Tone Analyzer, among others.

[1127] Finally, if any changes occur to the family register information (e.g., new members are added or removed), the system automatically detects the changes and updates the central database. The generation AI then regenerates the family register and family tree and stores it in the cloud system. This entire process allows users to efficiently and accurately create family registers and family trees, and even customize them based on their emotions.

[1128] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1129] Step 1:

[1130] The user uploads their family register information.

[1131] Input: The digital file the user obtained at their permanent address (e.g. "koseki_example.pdf").

[1132] Specific behavior: A user logs in to the web interface, clicks the file upload button, selects "koseki_example.pdf", and performs the upload.

[1133] Output: "koseki_example.pdf" is sent to the system.

[1134] Step 2:

[1135] The terminal initially checks the file and sends it to the server.

[1136] Input: An uploaded digital file (e.g. "koseki_example.pdf").

[1137] Specific operation: The device checks the file format (PDF, JPEG, PNG, etc.) and checks whether the file can be read normally. Uses a file format checker.

[1138] Data processing: Inspect the file format and content to ensure there are no problems.

[1139] Output: Files that pass the initial checks are stored in a temporary storage area, ready to be sent to the server.

[1140] Step 3:

[1141] The server analyzes the file using OCR, extracts the data, and saves it.

[1142] Input: The file sent from the terminal (e.g. "koseki_example.pdf").

[1143] What happens: The server uses an OCR engine (e.g., Tesseract OCR) to convert the file contents into digital text.

[1144] Data processing: Using OCR processing, text information such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is extracted.

[1145] Output: The extracted data is structured and stored in a central database.

[1146] Step 4:

[1147] The server extracts and formats the data from the database.

[1148] Input: Structured data stored in a central database.

[1149] What it does: Extracts specific genealogy information and formats the data according to the user's request.

[1150] Data transformation: The transformation process creates a generational list and arranges the data based on parent-child relationships.

[1151] Output: The formatted data is passed to a generative AI model.

[1152] Step 5:

[1153] Generative AI generates death registers and family trees.

[1154] Input: Formatted data.

[1155] How it works: The generative AI model takes formatted data as input and generates a death register or family tree.

[1156] Data Calculation: Generate the structure and layout of the family tree based on prompts.

[1157] Output: The generated family register and family tree (e.g. "Tanaka Family Tree.pdf") will be created.

[1158] Step 6:

[1159] The server stores the generated data in a cloud system.

[1160] Input: The death register or family tree output by the generation AI (e.g., "Tanaka family family tree.pdf").

[1161] Specific operation: The server uploads data to cloud storage (e.g., Amazon S3, Google Drive).

[1162] Data processing: Uploading data and storing it on the cloud.

[1163] Output: Death registers and family trees stored in a cloud system that can be accessed by users.

[1164] Step 7:

[1165] The emotion engine analyzes user emotions and adjusts content accordingly.

[1166] Input: User facial and voice data.

[1167] Specific operation: The emotion engine uses the camera and microphone to collect and analyze the user's facial expressions and voice.

[1168] Data Computing: Using sentiment analysis algorithms to identify a user's emotional state (e.g., happy, sad, moved).

[1169] Output: Display content is adjusted based on identified emotion data.

[1170] Step 8:

[1171] The server automatically updates the database and cloud system when updated.

[1172] Input: Newly uploaded or changed family register information.

[1173] How it works: When a new digital file is uploaded, the server detects the change, performs OCR analysis, extracts data, updates the database, and regenerates it using generative AI.

[1174] Data processing: Automatic updates to databases and cloud systems.

[1175] Output: The latest family register and genealogy are regenerated and stored in the cloud system.

[1176] This allows the system to efficiently and accurately create family registers and genealogies, customize them based on user sentiment, and automatically update them with the latest information.

[1177] (Application example 2)

[1178] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1179] Conventional genealogy and death register generation systems do not adjust content based on user emotions, resulting in a limited user experience. Furthermore, the convenience of viewing personal information in a paperless manner in a physical store is also an issue. The present invention aims to solve these issues by providing real-time content adjustment using emotion analysis and an interactive in-store experience.

[1180] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving personal information uploaded by a user, means for analyzing the received personal information and extracting necessary data, means for saving the extracted data in a centralized data storage system, means for extracting data from the centralized data storage system to generate a death register and / or a family tree, means for saving the generated death register and / or a family tree on a cloud platform, means for adjusting display content using an emotion engine that identifies the user's emotions, and means for providing emotion-based information to a store display device. This makes it possible to display an interactive death register and / or a family tree according to the user's emotions.

[1181] "User" refers to a person who uses the system to provide personal information and generate and view death registers and genealogy charts.

[1182] "Personal information" refers to information used to identify individuals or determine genealogical relationships, such as family register information.

[1183] "Means for receiving" refers to system components or functions that acquire personal information electronically, in whole or in part.

[1184] "Means of analysis" refers to system components and functions that process received personal information using technologies such as data conversion and character recognition, and extract the necessary data.

[1185] "Extraction means" refers to system components or functions that extract specific information from the analyzed data.

[1186] "Centralized data storage system" refers to a database system that centrally stores and manages analyzed and extracted data.

[1187] "Means for generating" refers to system components and functions that use the extracted data to automatically create death registers and genealogy charts.

[1188] "Cloud infrastructure" refers to a cloud storage system that stores the generated death registers and genealogy charts and makes them accessible via the Internet.

[1189] An "emotion engine" refers to technology or a system that analyzes and identifies the user's emotional state, such as facial expressions and voice.

[1190] "Means for adjusting the displayed content" refers to system components or functions that dynamically change the content and format of the displayed death register or genealogy chart based on emotional information obtained from the emotion engine.

[1191] "Display device" refers to a device (e.g., tablet, large display, etc.) for displaying the generated death register or genealogy chart.

[1192] A specific system for implementing the present invention operates according to the following steps.

[1193] First, a user uses their smartphone to access a display device such as a tablet or large display. When the user uploads their personal information, the device receives this information and sends it to a server.

[1194] The server analyzes the received personal information and extracts the necessary data. This process involves converting the uploaded document into digital text using OCR technology such as Google Cloud Vision. The extracted data is then stored in a centralized data storage system (e.g., AWS RDS).

[1195] The server then uses this data to generate a family register or genealogy chart upon user request. This process uses a generative AI model (e.g., OpenAI GPT-4) to generate content efficiently and accurately. The generated family register or genealogy chart is then stored in a cloud infrastructure (e.g., Amazon S3).

[1196] In parallel, an emotion engine (e.g., Microsoft Azure Cognitive Services) analyzes the user's emotions in real time by monitoring their facial expressions and voice while they browse the family register or genealogy chart to identify their emotional state.

[1197] The server uses this emotional information to dynamically adjust the content displayed. For example, if the emotion engine identifies that the user is emotional, the system will add touching anecdotes or quotes to the death register or family tree. This adjustment is made in real time, allowing users to experience the most appropriate content based on their emotions.

[1198] Furthermore, emotion-based information is automatically provided to store display devices, allowing store staff to provide appropriate support and suggestions to customers.

[1199] In this way, the present invention realizes interactive display of death registers and genealogy charts according to the user's emotions, providing a paperless experience in a physical store.

[1200] For example, a user uploads the family register information for the "Yamada family," and OCR technology extracts information such as "Yamada Taro, born January 1, 1980," and generates a "Yamada Family Tree.pdf" based on this information. The emotion engine analyzes the user's emotions, and if it determines that the user is emotional, it provides the following prompt to the generative AI model:

[1201] "Add inspiring stories and quotes based on the Yamada family tree data and the user's emotional state."

[1202] This prompt enables the generative AI model to generate supplementary content, including inspiring anecdotes and quotes, to provide to users in addition to the Yamada family tree.

[1203] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1204] Step 1:

[1205] The user uploads personal information from their smartphone. The input is the personal information file selected by the user, and the output is the data sent to the device. Specifically, the user accesses the specified web interface, selects the file to upload (e.g., "koseki_yamada.pdf") from the file selection dialog, and presses the send button.

[1206] Step 2:

[1207] The device receives the uploaded file and prepares it to be sent to the server. The input is the file uploaded by the user, and the output is the data to be sent to the server. Specifically, the device checks the file format (PDF, JPEG, PNG, etc.) and checks the file's integrity, and if there are no problems, stores it in a temporary storage area.

[1208] Step 3:

[1209] The server receives the file sent from the device and converts the file contents into digital text using OCR technology. The input is the personal information file sent from the device, and the output is digital text data. Specifically, the server calls the Google Cloud Vision API, analyzes the file, and extracts the text information. For example, the text data obtained is "Yamada Taro, born January 1, 1980."

[1210] Step 4:

[1211] The server parses the digital text, extracts the necessary data (such as name, date of birth, parent-child relationship, etc.), and stores it in a centralized data storage system. The input is the digital text, and the output is a structured database entry. Specifically, the server uses regular expressions and parsing algorithms to extract the data and store it in a database (e.g., AWS RDS).

[1212] Step 5:

[1213] In response to user requests, the server uses a generative AI model to generate a family register or family tree. The input is data extracted from a centralized data storage system, and the output is a PDF file of the generated family register or family tree. Specifically, the server uses OpenAI GPT-4 to generate prompts based on the extracted data and create the family register or family tree. Example: "Yamada Family Tree.pdf" is generated.

[1214] Step 6:

[1215] The generated death registers and genealogy charts are stored on a cloud platform and can be accessed by users. The input is the generated PDF file, and the output is an access link on the cloud storage. Specifically, the server uses a cloud storage service such as Amazon S3 to upload the file and generate an access link.

[1216] Step 7:

[1217] The emotion engine analyzes the user's emotions in real time and adjusts the displayed content. The input is the user's facial expression and voice data, and the output is content adjusted based on the user's emotional state. Specifically, it uses Microsoft Azure Cognitive Services to analyze the user's facial expressions and voice, and the server dynamically adjusts the content based on the obtained emotional information. For example, if the user is moved, an emotional episode will be added.

[1218] Step 8:

[1219] Emotion-based information is provided to display devices in stores. The input is the adjusted content, and the output is what is displayed on the display device. Specifically, the adjusted content is sent from the server to a tablet device or large display, and then displayed on the display device. This enables store staff to provide appropriate support and suggestions to customers.

[1220] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1221] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1222] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1223] [Fourth embodiment]

[1224] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1225] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1226] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1227] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1228] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1229] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1230] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1231] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1232] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1233] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1234] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1235] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1236] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1237] This invention is a system that automatically creates up-to-date family registers and genealogies using a central database and cloud-based system based on family register information collected from users' permanent domiciles. The system consists of a user upload, data analysis and extraction, storage in the database, generation of family registers and genealogies using AI, and storage in the cloud system.

[1238] System configuration and specific operation

[1239] 1. User Action:

[1240] Users save the family register information they have obtained at their permanent domicile as a digital file and upload it to the system through the system's web interface. Uploading involves the user selecting and submitting a file using a file selection dialog.

[1241] Example: A user uploads "koseki_tanaka.pdf" to the system.

[1242] 2. Terminal processing:

[1243] The device initially checks the received file to ensure that it is in the correct file format (PDF, JPEG, PNG, etc.). If the file can be read successfully, it is stored in a temporary storage area and prepared for transmission to the server.

[1244] 3. Server processing:

[1245] The server receives the file sent from the device and converts it into digital text using an OCR (Optical Character Recognition) engine. At this time, the server analyzes the text information extracted by OCR and extracts necessary data (such as name, date of birth, parent-child relationship, etc.).

[1246] The extracted data is structured and stored in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[1247] 4. Data extraction and formatting:

[1248] The server extracts specific family information from a central database in response to a user's request, then uses generative AI to format the extracted data into a suitable format for a family register or family tree, creating a generational list and arranging the data based on parent-child relationships.

[1249] Example: The server extracts all data related to the Tanaka family and formats it appropriately to generate a family tree for the "Tanaka family."

[1250] 5. Report generation using generative AI:

[1251] The AI ​​then generates a family register and family tree based on the data formatted by the server, which are then stored in a cloud system.

[1252] Example: The generation AI generates a family tree for the "Tanaka family" and saves it in cloud storage as "Tanaka family genealogy.pdf."

[1253] 6. Use of cloud systems:

[1254] The generated family registers and family trees are stored in a cloud system and can be accessed online via the internet, allowing users to view the most up-to-date family trees.

[1255] Specific examples

[1256] 1. User uploads family register information:

[1257] The user uploads "koseki_tanaka.pdf" through the web interface.

[1258] The terminal receives the file and performs an initial check to send it to the server.

[1259] 2. The server analyzes and extracts the data and registers it in the database:

[1260] The server uses an OCR engine to analyze the file and extract information such as "Taro Tanaka, born January 1, 1990" as digital text, which is then stored in a database.

[1261] 3. Data shaping and generative AI:

[1262] Based on the user's request, the server extracts data about the "Tanaka family" and uses a generation AI to generate "Tanaka family tree.pdf."

[1263] 4. Cloud storage and use:

[1264] The server stores the generated family tree in a cloud system, and users can view the latest family tree online through a web interface.

[1265] In this way, the system provides a series of operations that allow users to efficiently and accurately create family registers and genealogies, and keep the information up to date at all times.

[1266] The processing flow will be explained below.

[1267] Step 1:

[1268] The user saves the family register information obtained from their permanent domicile as a digital file and accesses the system's web interface. The user clicks the "Upload" button, selects the family register file (e.g., "koseki_tanaka.pdf") from the file selection dialog, and uploads it.

[1269] Step 2:

[1270] The device receives the uploaded file and performs an initial check. It checks whether the file format is appropriate (PDF, JPEG, PNG, etc.) and whether the file can be loaded correctly. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[1271] Step 3:

[1272] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The OCR engine then analyzes the extracted text information to identify and extract the necessary data (such as name, date of birth, and parent-child relationship).

[1273] Step 4:

[1274] The server structures the extracted data and stores it in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[1275] Step 5:

[1276] When a user requests the generation of a family register or family tree, the server extracts data from the central database based on the specified criteria, and then uses the generation AI to format the extracted data and convert it into a format suitable for the family register or family tree.

[1277] Step 6:

[1278] The server saves the generated family register and family tree in the cloud system. The generated family register and family tree are uploaded to the cloud storage as, for example, "Tanaka Family Genealogy.pdf."

[1279] Step 7:

[1280] Users access the cloud system and view the latest family records and genealogy through a web interface, allowing them to access the latest information at any time.

[1281] Step 8:

[1282] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the change and updates the central database. Based on the updated information, the AI ​​generates new family registers and family trees, which are then stored in the cloud system.

[1283] Example 1

[1284] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1285] In conventional family register information management systems, digitizing and analyzing family register information required a great deal of time and effort. Furthermore, updating the digitized data and generating genealogy information in an appropriate format was done manually, resulting in issues with accuracy and efficiency. This made it difficult for users to quickly obtain the latest genealogy information.

[1286] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1287] In this invention, the server includes a means for receiving family register information uploaded by users, a means for converting the received family register information into digital text using optical character recognition technology, a means for extracting necessary data and storing it in a central database, a means for generating genealogy information using artificial intelligence, and a means for storing the generated genealogy information in a cloud computing system, thereby enabling users to efficiently and accurately obtain the latest genealogy information.

[1288] "User" means an individual or corporation that uses this system to upload family register information and generate and view genealogy information.

[1289] "Family register information" refers to public records that include names, dates of birth, parent-child relationships, etc.

[1290] "Means for receiving" means a device or process for retrieving digital files uploaded by users onto the server.

[1291] "Means for analyzing and extracting necessary data" refers to a method or device that identifies and extracts important information (e.g., name, date of birth, parentage, etc.) from the received digital file.

[1292] "Optical character recognition technology" refers to technology that extracts text data from images or scanned documents.

[1293] "Digital text" refers to text data converted from an image or scan using optical character recognition technology.

[1294] "Central database" refers to a database system that centrally manages extracted and stored data.

[1295] "Genealogy information" refers to data showing family lineage and historical lineage, such as family trees and death registers.

[1296] "Generative AI" refers to an AI technology that generates new information (e.g., family trees or death registers) in a specified format based on given data.

[1297] A "cloud computing system" is a service that stores data on the Internet and allows users to access it remotely.

[1298] This invention is a system that automatically generates up-to-date genealogy information based on family register information collected by users from their registered domiciles, using a central database and a cloud computing system.

[1299] First, the user saves the family register information obtained from their permanent domicile as a digital file. This digital file can be in a format such as PDF, JPEG, or PNG. Next, the user uploads this digital file to the system through the web interface. For example, the user selects "koseki_sample.pdf" and clicks the upload button to send it to the system.

[1300] The device performs an initial check of the file received from the user, confirming that the file format is correct and testing that it can be read successfully. If the file is confirmed, it is stored in a temporary storage area and prepared for transmission to the server.

[1301] The server receives the file sent from the device. It receives the HTTP POST request and saves the file in the specified directory. The server then uses OCR (optical character recognition) technology to extract the text data from the file. For example, the Tesseract OCR engine is used in this process. The extracted text data is saved and analyzed for necessary data (such as name, date of birth, and parent-child relationship). Regular expressions and text analysis algorithms are used for the analysis.

[1302] The analyzed data is structured and stored in a central database. An example of specific extracted data is "Name: Taro Tanaka, Date of birth: January 1, 1990, Father: Ichiro Tanaka, Mother: Hanako Tanaka."

[1303] When a user requests the generation of genealogy information, the server extracts and formats the relevant data from a central database. The extracted data is fed into a generative artificial intelligence (generative AI) that generates new information (e.g., a family tree or death register) in the specified format. The generative AI uses a text-based prompt. For example, a prompt might be "Please generate a family tree for the Tanaka family."

[1304] The generated genealogical information is stored as a digital file (e.g., "tanaka_family_tree.pdf") on a cloud computing system. Users can access this information via the internet and view the latest genealogical information. This system enables users to efficiently and accurately obtain, store, and share the latest genealogical information.

[1305] The above is a specific embodiment for carrying out the present invention. This system allows users to quickly process and analyze family register information and keep it up to date.

[1306] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1307] Step 1:

[1308] The user saves the family register information obtained from their permanent domicile as a digital file and uploads this digital file through the system's web interface. As a concrete example, the user selects "koseki_sample.pdf" and clicks the upload button. The input of this step is the "family register information file selected by the user," and the output is "sending the file to the server."

[1309] Step 2:

[1310] The terminal performs an initial check of the file received from the user. Specifically, it checks whether the file format is PDF, JPEG, or PNG, and tests whether it can be read successfully. Once the file is confirmed, it is stored in a temporary storage area. The input of this step is the "file sent by the user," and the output is the "file stored in the temporary storage area."

[1311] Step 3:

[1312] The terminal prepares to send the file from the temporary storage area to the server. Specifically, it moves the file and calls the server sending script. The input of this step is the "file stored in the temporary storage area" and the output is the "file to be sent to the server."

[1313] Step 4:

[1314] The server receives the file sent from the terminal. Specifically, it receives an HTTP POST request and saves the file in a specified directory. The input of this step is the "file sent from the terminal" and the output is the "file saved in the specified directory on the server."

[1315] Step 5:

[1316] The server uses OCR (Optical Character Recognition) technology to extract the text data in the file. For example, it invokes the Tesseract OCR engine to extract the digital text. The input of this step is the file stored in the specified directory on the server, and the output is the extracted text data.

[1317] Step 6:

[1318] The server parses the text data and extracts the necessary data (such as name, date of birth, parent-child relationship, etc.). Specifically, it filters the data using regular expressions and text analysis algorithms. The input of this step is the text data extracted by OCR, and the output is structured data.

[1319] Step 7:

[1320] The server stores the extracted data in a central database. Specifically, it generates SQL queries and inserts them into the database. The input of this step is "structured data" and the output is "data stored in the database."

[1321] Step 8:

[1322] The server extracts specific genealogical information from the central database based on the user's request. Specifically, it generates an SQL select query to extract and format the data. The inputs to this step are the data stored in the database and the user's request, and the output is the formatted genealogical information data.

[1323] Step 9:

[1324] The server inputs the formatted data into the generative AI model to generate genealogy information. As a specific example, the prompt "Please generate a family tree for the Tanaka family" is input, and a file called "tanaka_family_tree.pdf" is generated. The inputs for this step are the formatted family information data and the prompt, and the output is the generated genealogy information file.

[1325] Step 10:

[1326] The server saves the generated genealogy information file in a cloud computing system. Specifically, it calls a cloud storage API and uploads the file. The input of this step is the "generated genealogy information file," and the output is the "file saved in the cloud system."

[1327] Step 11:

[1328] The user views the genealogy information generated through the cloud system. Specifically, the user logs in to the web interface and downloads or views the generated file. The input of this step is the "file stored in the cloud system," and the output is "user viewing of genealogy information."

[1329] (Application example 1)

[1330] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1331] Existing systems for generating family trees and past records based on family register information require users to organize and analyze the information themselves, which is time-consuming and labor-intensive. Furthermore, the generated information may not be easily stored or accessible. Furthermore, there is a lack of means to directly provide family trees and past records to customers in physical stores. To solve these issues, there is a need for an efficient and easy-to-use system for analyzing, generating, and displaying information that utilizes smart devices.

[1332] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1333] In this invention, the server includes means for receiving family register information uploaded by a user, means for analyzing the received family register information and extracting necessary data, means for saving the extracted data in a central database, means for extracting data from the central database to generate a death register and family tree, means for saving the generated death register and family tree in a cloud system, means for analyzing the received family register information using a smart device, and means for displaying the death register and family tree generated by the smart device, thereby enabling users to easily analyze family register information and efficiently generate, display, and save a death register and family tree.

[1334] "User" refers to an individual who uses the system to upload family register information and use the analyzed and generated family registers and genealogies.

[1335] "Family register information" refers to official documents containing data such as the name, date of birth, and kinship relationships of registered individuals.

[1336] "Analysis" refers to the process of extracting necessary information from received digital data and organizing and transforming it.

[1337] "Central database" refers to a centralized storage system for storing extracted digital text and analytical data for later search and retrieval.

[1338] A "kakocho" is a document or digital file that compiles historical records of individuals and families.

[1339] A "family tree" is a visual diagram showing a family's kinship relationships across generations.

[1340] A "cloud system" refers to a network of remote servers for storing and managing data over the Internet.

[1341] "Smart devices" refers to devices with internet connectivity and advanced computing capabilities, such as smartphones, smart glasses, and head-mounted displays.

[1342] "Analysis" refers to the process of processing received data to categorize and organize the information for a specific purpose.

[1343] "Display" refers to the process of visually presenting the generated family register and genealogy data on an interface such as a digital screen.

[1344] "Generative AI" refers to artificial intelligence models used to generate new information or content based on existing data.

[1345] A system for implementing this invention comprises a user, a terminal (a smart device such as a smartphone or smart glasses), and a server.

[1346] Specific actions

[1347] 1. User Action:

[1348] Users use their smartphones or smart glasses to save their family register information as a digital file (e.g., PDF, JPEG, PNG, etc.) and upload it using the system's application.

[1349] For example, a user uploads a file called "koseki_info.pdf" from an application.

[1350] 2. Terminal processing:

[1351] The device initially checks the uploaded file to make sure it is in the correct format. If it is, it temporarily saves the file and sends it to the server.

[1352] 3. Server processing:

[1353] The server receives the file and converts it into digital text using an OCR (Optical Character Recognition) engine, which then analyzes the text to extract necessary data such as name, date of birth, and parent-child relationship.

[1354] The extracted data is stored in a central database, and is registered in the format, for example, "Yamada Taro, born January 1, 1990, father: Yamada Ichiro, mother: Yamada Hanako."

[1355] 4. Data analysis and formatting:

[1356] The server extracts specific genealogical information from a central database in response to user requests, and uses generative AI models to format the data into a suitable format for family registers and family trees.

[1357] 5. Generating family records and genealogies using generative AI:

[1358] The server uses a generative AI model to generate family records and genealogies based on the formatted data, and the generated data is stored in a cloud system.

[1359] 6. Cloud Storage and Access:

[1360] The generated family registers and genealogies are stored in a cloud system and can be accessed online by users via the internet.

[1361] Hardware and Software Use

[1362] Hardware:

[1363] Smartphones, smart glasses

[1364] software:

[1365] OCR engine (pytesseract)

[1366] PDF conversion library (pdf2image)

[1367] HTTP request library (requests)

[1368] Generative AI Models

[1369] Specific examples

[1370] The user uses the smart glasses to scan their family register information file (e.g., "koseki_info.pdf").

[1371] Select Family Tree Generation from the glasses interface.

[1372] The generated family tree is displayed on the smart glasses' display and can be viewed in real time.

[1373] Below is an example of a prompt to send to a generative AI model:

[1374] Generate a family tree based on the following information:

[1375] Name: Taro Yamada

[1376] Date of Birth: January 1, 1990

[1377] Father: Ichiro Yamada

[1378] Mother: Hanako Yamada

[1379] This system allows users to easily and efficiently create, display, and save family records and genealogies.

[1380] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1381] Step 1:

[1382] User Action:

[1383] Users save their family register information as a digital file (e.g., PDF, JPEG, PNG, etc.) using a smartphone or smart glasses, and then upload this file using the application.

[1384] Input: Digital family register information file (e.g. "koseki_info.pdf")

[1385] Output: The uploaded file

[1386] Step 2:

[1387] Terminal handling:

[1388] The device performs an initial check on the uploaded file to ensure that the file format is correct. If the format is correct, the file is temporarily saved and prepared for transmission to the server.

[1389] Input: Uploaded file

[1390] Output: Verified files, files prepared for sending

[1391] Step 3:

[1392] Receiving files from the server:

[1393] The server receives the file sent from the device and prepares it for analysis.

[1394] Input: File sent from terminal

[1395] Output: Received files

[1396] Step 4:

[1397] OCR processing:

[1398] The server uses an OCR (Optical Character Recognition) engine to convert the received file into digital text.

[1399] Input: Received file

[1400] Output: Digital text extracted by OCR

[1401] Step 5:

[1402] Data Analysis:

[1403] The server analyzes the digital text extracted by OCR and extracts the necessary data (such as name, date of birth, parent-child relationship, etc.).

[1404] Input: Digital text extracted by OCR

[1405] Output: Extracted data (e.g., "Yamada Taro, born January 1, 1990, father: Yamada Ichiro, mother: Yamada Hanako")

[1406] Step 6:

[1407] Save to database:

[1408] The server stores the extracted data in a central database.

[1409] Input: Extracted data

[1410] Output: Data stored in the database

[1411] Step 7:

[1412] Extracting genealogy information:

[1413] The server extracts specific genealogy information from a central database in response to a user's request.

[1414] Input: User requests, central database

[1415] Output: Extracted genealogy information

[1416] Step 8:

[1417] Data formatting:

[1418] The server inputs the extracted family information into a generative AI model and formats it into a format suitable for death registers and family trees.

[1419] Input: Extracted genealogy information

[1420] Output: Formatted data

[1421] Step 9:

[1422] Generative AI for generating family trees:

[1423] The server uses a generative AI model to generate a family tree based on the formatted data.

[1424] Input: Formatted data

[1425] Output: The generated pedigree

[1426] Step 10:

[1427] Save to cloud system:

[1428] The server stores the generated family tree in a cloud system.

[1429] Input: Generated pedigree

[1430] Output: Family tree stored in a cloud system

[1431] Step 11:

[1432] User Views:

[1433] Users access the cloud system via the Internet and view the generated family tree.

[1434] Input: Family tree stored in the cloud system, user request to view it

[1435] Output: Family tree displayed on the user's device

[1436] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1437] This invention combines a system that uses a central database and a cloud-based system to automatically create up-to-date family registers and genealogies based on family register information collected from users' permanent domiciles with an emotion engine that recognizes user emotions.The system consists of user uploads, data analysis and extraction, storage in a database, generation of family registers and genealogies using generation AI, storage in a cloud system, and user emotion recognition and content adjustment using the emotion engine.

[1438] System configuration and specific operation

[1439] 1. User Action:

[1440] Users save the family register information they have obtained at their permanent domicile as a digital file and upload it to the system through the system's web interface. Uploading involves the user selecting and submitting a file using a file selection dialog.

[1441] Example: A user uploads "koseki_tanaka.pdf" to the system.

[1442] 2. Terminal processing:

[1443] The device receives the uploaded file and performs an initial check. It checks whether the file format (PDF, JPEG, PNG, etc.) is appropriate and whether the file can be loaded correctly. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[1444] 3. Server processing:

[1445] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The server then analyzes the text information extracted by the OCR engine to identify and extract the necessary data (such as name, date of birth, and parent-child relationship).

[1446] The extracted data is structured and stored in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[1447] 4. Data extraction and formatting:

[1448] In response to a user's request, the server extracts specific family information from a central database. Generative AI is then used to format the extracted data into a suitable format for a family register or family tree. Generational lists are created, arranging the data based on parent-child relationships.

[1449] Example: The server extracts all data related to the Tanaka family and formats it appropriately to generate a family tree for the "Tanaka family."

[1450] 5. Report generation using generative AI:

[1451] The AI ​​then generates a family register and family tree based on the data formatted by the server, which are then stored in a cloud system.

[1452] Example: The generation AI generates a family tree for the "Tanaka family" and saves it in cloud storage as "Tanaka family genealogy.pdf."

[1453] 6. Use of Emotion Engine:

[1454] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. While the user is browsing the family register or family tree, the emotion engine monitors the user's emotions in real time.

[1455] Based on the analyzed emotional information, the format and design of the displayed death register and family tree are automatically adjusted.

[1456] For example, if the system detects that the user is emotional, it will add memorable anecdotes or inspiring quotes to the family tree.

[1457] 7. Use of cloud systems:

[1458] The generated family tree and family records are stored in a cloud system and can be accessed online via the internet. Users can view the most up-to-date family tree, which also reflects emotional customization.

[1459] 8. Continuous updates:

[1460] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the changes and updates the central database. The generation AI then regenerates the family register and family tree and stores them in the cloud system.

[1461] Users' emotional data is also stored in the cloud system and continuously analyzed along with their viewing history of family records and genealogies.

[1462] Specific examples

[1463] 1. User uploads family register information:

[1464] The user uploads "koseki_tanaka.pdf" through the web interface.

[1465] The terminal receives the file and performs an initial check to send it to the server.

[1466] 2. The server analyzes and extracts the data and registers it in the database:

[1467] The server uses an OCR engine to analyze the file and extract information such as "Taro Tanaka, born January 1, 1990" as digital text, which is then stored in a database.

[1468] 3. Data shaping and generative AI:

[1469] Based on the user's request, the server extracts data about the "Tanaka family" and uses a generation AI to generate "Tanaka family tree.pdf."

[1470] 4. Use of Emotion Engine:

[1471] When a user browses the family tree, the emotion engine analyzes the user's emotions in real time and adjusts the display format and content accordingly. For example, if the user is emotional, it will display additional touching episodes.

[1472] 5. Use of cloud systems and continuous updates:

[1473] The server stores the generated family tree in a cloud system, and users can view the latest family tree online through a web interface.

[1474] If changes occur to family register information or emotional data, the system will automatically update to reflect the latest information.

[1475] In this way, the system provides a set of actions to efficiently and accurately create family registers and genealogies, and customize the content based on the user's emotions.

[1476] The processing flow will be explained below.

[1477] Step 1:

[1478] The user saves the family register information obtained from their permanent domicile as a digital file and accesses the system's web interface. The user clicks the "Upload" button, selects the family register file (e.g., "koseki_tanaka.pdf") from the file selection dialog, and uploads it.

[1479] Step 2:

[1480] The device receives the uploaded file and performs an initial check. The device checks whether the file format (PDF, JPEG, PNG, etc.) is appropriate and whether the file can be read normally. Files that pass the initial check are stored in a temporary storage area and prepared for sending to the server.

[1481] Step 3:

[1482] The server receives the file sent from the device and converts the file contents into digital text using an OCR (Optical Character Recognition) engine. The server then analyzes the text information extracted by the OCR engine to identify and extract the necessary data (such as name, date of birth, parent-child relationship, etc.).

[1483] Step 4:

[1484] The server structures the extracted data and stores it in a central database. For example, data such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is registered in the database.

[1485] Step 5:

[1486] When a user requests the generation of a family register or family tree, the server extracts data from a central database based on the specified criteria, and then uses the generation AI to format the extracted data and convert it into a format suitable for the family register or family tree.

[1487] Step 6:

[1488] The death register and family tree generated by the AI ​​are saved in a cloud system. For example, they are uploaded to cloud storage as "Tanaka Family Tree.pdf."

[1489] Step 7:

[1490] Users access the cloud system and view the latest family records and genealogy through a web interface, allowing them to access the latest information at any time.

[1491] Step 8:

[1492] When a user is viewing a family tree or family register, the emotion engine analyzes the user's facial expressions and voice to identify their emotional state, and automatically adjusts the format and design of the displayed family tree or family register based on the analyzed emotional information.

[1493] Step 9:

[1494] The server receives data from the emotion engine and updates the display content in real time based on the user's emotions. For example, if the user is emotional, it will add memorable anecdotes or inspiring quotes to the family tree.

[1495] Step 10:

[1496] The user's emotional data is stored in a cloud system and continuously analyzed along with the viewing history of the family tree and past records, allowing the system to customize the user's family tree based on their past emotional state when they next view it.

[1497] Step 11:

[1498] When changes occur to family register information (such as the addition of a new member or removal from the family register), the server automatically detects the change and updates the central database. The generation AI then regenerates the family register and family tree and stores them in the cloud system. The user's emotional data is also updated appropriately to reflect the latest information.

[1499] Example 2

[1500] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1501] Conventional systems for creating family trees and past records require users to manually input and organize data, which is time-consuming and labor-intensive. Generating family trees and past records also requires specialized knowledge, making them difficult for average users to use. Furthermore, the lack of customization features that take user feelings into account makes it difficult to improve user satisfaction.

[1502] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving digital files uploaded by users, means for initially checking the format and content of the received digital files, means for transmitting files that have passed the initial check to the server, means for converting the received digital files into digital text using OCR technology and extracting necessary data, means for saving the extracted data in a central database, means for extracting and formatting data from the central database in response to a user request, means for generating a death register and / or family tree using a generation AI, means for saving the generated death register and / or family tree in a cloud system, means for the user to access the generated data through the cloud system, means including an emotion engine for analyzing the user's facial expressions and voice to identify emotions, means for adjusting display content based on the identified emotions, and means for automatically and continuously updating data. This allows users to easily create death registers and / or family trees, and also provides emotion-based customization functions, providing a highly satisfying experience.

[1503] A "user" is someone who operates the system, uploads digital files, and views the generated family registers and genealogies.

[1504] "Digital files" refers to document or image files stored in a digital format such as PDF, JPEG, or PNG.

[1505] "Receiving means" refers to the functions and devices for incorporating digital files sent by users into the system.

[1506] "Initial checking means" refers to a function or device that checks the format and content of a received digital file and determines whether it is appropriate.

[1507] A "server" is a computer that plays a central role in the system and is a device that performs various processes such as analyzing digital files, operating databases, and using generative AI.

[1508] "OCR technology" stands for optical character recognition technology, which analyzes the character information contained in digital files and extracts it as digital text.

[1509] "Digital text" refers to character data extracted using OCR technology in a format that can be understood by a computer.

[1510] "Data extraction means" refers to a function or device that extracts necessary information such as name, date of birth, and parent-child relationship from digital text.

[1511] The "central database" refers to a data storage system for centrally storing and managing extracted data.

[1512] "Formatting means" refers to the function or device that organizes and arranges data extracted from the central database in a format suitable for family registers and genealogies.

[1513] "Generative AI" refers to systems or software that use artificial intelligence technology to automatically generate death registers and family trees from formatted data.

[1514] A "cloud system" is an online storage system that stores data via the Internet and allows users to access it from anywhere.

[1515] "Access means" refers to the functions and devices that allow users to view and manipulate data stored in a cloud system.

[1516] An "emotion engine" is software or a device that analyzes a user's facial expressions and voice to identify their emotional state.

[1517] The "display content adjustment means" refers to a function or device that automatically changes the display format and content of the death register or family tree based on the emotion identified by the emotion engine.

[1518] "Update means" refers to a function or device that automatically updates the entire system based on new information when the information stored in the database is changed.

[1519] This invention is a system that automatically creates up-to-date family registers and genealogies using a central database and cloud-based system based on family register information collected from users' permanent domiciles. The system also combines an emotion engine that recognizes users' emotions to provide a more customized experience.

[1520] First, the user saves the family register information obtained from their permanent domicile as a digital file (e.g., PDF, JPEG) and uploads it through the system's web interface. The user uploads a digital file such as "koseki_example.pdf." The specific software used is a web browser (e.g., Google Chrome, Firefox).

[1521] The device then receives the uploaded file and performs an initial check to ensure that the file is in the correct format (PDF, JPEG, PNG, etc.) and can be loaded correctly. The detected file is then stored in a temporary storage area and prepared for transmission to the server. This initial check is performed using a file format inspection tool.

[1522] The server receives the file sent from the device and converts the file's contents into digital text using an OCR (Optical Character Recognition) engine (e.g., Tesseract OCR). In this process, the OCR engine extracts information such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" from "koseki_example.pdf." The extracted data is analyzed and stored in a structured central database. An SQL database (e.g., MySQL, PostgreSQL) is used for the central database.

[1523] Additionally, upon user request, the server extracts specific family information from the central database and formats the data. The formatted data is then converted into a format suitable for use in a family register or family tree using a generative AI model. For example, if a user requests the generation of a family tree for the "Tanaka family," the server retrieves the relevant data, and the generative AI generates it as "Tanaka Family Tree.pdf."

[1524] The generated family registers and genealogies are stored in a cloud system and can be accessed online by users via the internet. Cloud storage services include Amazon S3 and Google Drive.

[1525] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. While the user is viewing the family register or family tree, the emotion engine monitors the user's emotions in real time. Based on the analyzed emotional information, the format and design of the displayed family register or family tree is automatically adjusted. For example, if the system recognizes that the user is emotional, it will add memorable episodes or inspiring quotes to the family tree. The emotion engine uses the Microsoft Azure Emotion API and IBM Watson Tone Analyzer, among others.

[1526] Finally, if any changes occur to the family register information (e.g., new members are added or removed), the system automatically detects the changes and updates the central database. The generation AI then regenerates the family register and family tree and stores it in the cloud system. This entire process allows users to efficiently and accurately create family registers and family trees, and even customize them based on their emotions.

[1527] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1528] Step 1:

[1529] The user uploads their family register information.

[1530] Input: The digital file the user obtained at their permanent address (e.g. "koseki_example.pdf").

[1531] Specific behavior: A user logs in to the web interface, clicks the file upload button, selects "koseki_example.pdf", and performs the upload.

[1532] Output: "koseki_example.pdf" is sent to the system.

[1533] Step 2:

[1534] The terminal initially checks the file and sends it to the server.

[1535] Input: An uploaded digital file (e.g. "koseki_example.pdf").

[1536] Specific operation: The device checks the file format (PDF, JPEG, PNG, etc.) and checks whether the file can be read normally. Uses a file format checker.

[1537] Data processing: Inspect the file format and content to ensure there are no problems.

[1538] Output: Files that pass the initial checks are stored in a temporary storage area, ready to be sent to the server.

[1539] Step 3:

[1540] The server analyzes the file using OCR, extracts the data, and saves it.

[1541] Input: The file sent from the terminal (e.g. "koseki_example.pdf").

[1542] What happens: The server uses an OCR engine (e.g., Tesseract OCR) to convert the file contents into digital text.

[1543] Data processing: Using OCR processing, text information such as "Taro Tanaka, born January 1, 1990, father: Ichiro Tanaka, mother: Hanako Tanaka" is extracted.

[1544] Output: The extracted data is structured and stored in a central database.

[1545] Step 4:

[1546] The server extracts and formats the data from the database.

[1547] Input: Structured data stored in a central database.

[1548] What it does: Extracts specific genealogy information and formats the data according to the user's request.

[1549] Data transformation: The transformation process creates a generational list and arranges the data based on parent-child relationships.

[1550] Output: The formatted data is passed to a generative AI model.

[1551] Step 5:

[1552] Generative AI generates death registers and family trees.

[1553] Input: Formatted data.

[1554] How it works: The generative AI model takes formatted data as input and generates a death register or family tree.

[1555] Data Calculation: Generate the structure and layout of the family tree based on prompts.

[1556] Output: The generated family register and family tree (e.g. "Tanaka Family Tree.pdf") will be created.

[1557] Step 6:

[1558] The server stores the generated data in a cloud system.

[1559] Input: The death register or family tree output by the generation AI (e.g., "Tanaka family family tree.pdf").

[1560] Specific operation: The server uploads data to cloud storage (e.g., Amazon S3, Google Drive).

[1561] Data processing: Uploading data and storing it on the cloud.

[1562] Output: Death registers and family trees stored in a cloud system that can be accessed by users.

[1563] Step 7:

[1564] The emotion engine analyzes user emotions and adjusts content accordingly.

[1565] Input: User facial and voice data.

[1566] Specific operation: The emotion engine uses the camera and microphone to collect and analyze the user's facial expressions and voice.

[1567] Data Computing: Using sentiment analysis algorithms to identify a user's emotional state (e.g., happy, sad, moved).

[1568] Output: Display content is adjusted based on identified emotion data.

[1569] Step 8:

[1570] The server automatically updates the database and cloud system when updated.

[1571] Input: Newly uploaded or changed family register information.

[1572] How it works: When a new digital file is uploaded, the server detects the change, performs OCR analysis, extracts data, updates the database, and regenerates it using generative AI.

[1573] Data processing: Automatic updates to databases and cloud systems.

[1574] Output: The latest family register and genealogy are regenerated and stored in the cloud system.

[1575] This allows the system to efficiently and accurately create family registers and genealogies, customize them based on user sentiment, and automatically update them with the latest information.

[1576] (Application example 2)

[1577] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1578] Conventional genealogy and death register generation systems do not adjust content based on user emotions, resulting in a limited user experience. Furthermore, the convenience of viewing personal information in a paperless manner in a physical store is also an issue. The present invention aims to solve these issues by providing real-time content adjustment using emotion analysis and an interactive in-store experience.

[1579] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving personal information uploaded by a user, means for analyzing the received personal information and extracting necessary data, means for saving the extracted data in a centralized data storage system, means for extracting data from the centralized data storage system to generate a death register and / or a family tree, means for saving the generated death register and / or a family tree on a cloud platform, means for adjusting display content using an emotion engine that identifies the user's emotions, and means for providing emotion-based information to a store display device. This makes it possible to display an interactive death register and / or a family tree according to the user's emotions.

[1580] "User" refers to a person who uses the system to provide personal information and generate and view death registers and genealogy charts.

[1581] "Personal information" refers to information used to identify individuals or determine genealogical relationships, such as family register information.

[1582] "Means for receiving" refers to system components or functions that acquire personal information electronically, in whole or in part.

[1583] "Means of analysis" refers to system components and functions that process received personal information using technologies such as data conversion and character recognition, and extract the necessary data.

[1584] "Extraction means" refers to system components or functions that extract specific information from the analyzed data.

[1585] "Centralized data storage system" refers to a database system that centrally stores and manages analyzed and extracted data.

[1586] "Means for generating" refers to system components and functions that use the extracted data to automatically create death registers and genealogy charts.

[1587] "Cloud infrastructure" refers to a cloud storage system that stores the generated death registers and genealogy charts and makes them accessible via the Internet.

[1588] An "emotion engine" refers to technology or a system that analyzes and identifies the user's emotional state, such as facial expressions and voice.

[1589] "Means for adjusting the displayed content" refers to system components or functions that dynamically change the content and format of the displayed death register or genealogy chart based on emotional information obtained from the emotion engine.

[1590] "Display device" refers to a device (e.g., tablet, large display, etc.) for displaying the generated death register or genealogy chart.

[1591] A specific system for implementing the present invention operates according to the following steps.

[1592] First, a user uses their smartphone to access a display device such as a tablet or large display. When the user uploads their personal information, the device receives this information and sends it to a server.

[1593] The server analyzes the received personal information and extracts the necessary data. This process involves converting the uploaded document into digital text using OCR technology such as Google Cloud Vision. The extracted data is then stored in a centralized data storage system (e.g., AWS RDS).

[1594] The server then uses this data to generate a family register or genealogy chart upon user request. This process uses a generative AI model (e.g., OpenAI GPT-4) to generate content efficiently and accurately. The generated family register or genealogy chart is then stored in a cloud infrastructure (e.g., Amazon S3).

[1595] In parallel, an emotion engine (e.g., Microsoft Azure Cognitive Services) analyzes the user's emotions in real time by monitoring their facial expressions and voice while they browse the family register or genealogy chart to identify their emotional state.

[1596] The server uses this emotional information to dynamically adjust the content displayed. For example, if the emotion engine identifies that the user is emotional, the system will add touching anecdotes or quotes to the death register or family tree. This adjustment is made in real time, allowing users to experience the most appropriate content based on their emotions.

[1597] Furthermore, emotion-based information is automatically provided to store display devices, allowing store staff to provide appropriate support and suggestions to customers.

[1598] In this way, the present invention realizes interactive display of death registers and genealogy charts according to the user's emotions, providing a paperless experience in a physical store.

[1599] For example, a user uploads the family register information for the "Yamada family," and OCR technology extracts information such as "Yamada Taro, born January 1, 1980," and generates a "Yamada Family Tree.pdf" based on this information. The emotion engine analyzes the user's emotions, and if it determines that the user is emotional, it provides the following prompt to the generative AI model:

[1600] "Add inspiring stories and quotes based on the Yamada family tree data and the user's emotional state."

[1601] This prompt enables the generative AI model to generate supplementary content, including inspiring anecdotes and quotes, to provide to users in addition to the Yamada family tree.

[1602] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1603] Step 1:

[1604] The user uploads personal information from their smartphone. The input is the personal information file selected by the user, and the output is the data sent to the device. Specifically, the user accesses the specified web interface, selects the file to upload (e.g., "koseki_yamada.pdf") from the file selection dialog, and presses the send button.

[1605] Step 2:

[1606] The device receives the uploaded file and prepares it to be sent to the server. The input is the file uploaded by the user, and the output is the data to be sent to the server. Specifically, the device checks the file format (PDF, JPEG, PNG, etc.) and checks the file's integrity, and if there are no problems, stores it in a temporary storage area.

[1607] Step 3:

[1608] The server receives the file sent from the device and converts the file contents into digital text using OCR technology. The input is the personal information file sent from the device, and the output is digital text data. Specifically, the server calls the Google Cloud Vision API, analyzes the file, and extracts the text information. For example, the text data obtained is "Yamada Taro, born January 1, 1980."

[1609] Step 4:

[1610] The server parses the digital text, extracts the necessary data (such as name, date of birth, parent-child relationship, etc.), and stores it in a centralized data storage system. The input is the digital text, and the output is a structured database entry. Specifically, the server uses regular expressions and parsing algorithms to extract the data and store it in a database (e.g., AWS RDS).

[1611] Step 5:

[1612] In response to user requests, the server uses a generative AI model to generate a family register or family tree. The input is data extracted from a centralized data storage system, and the output is a PDF file of the generated family register or family tree. Specifically, the server uses OpenAI GPT-4 to generate prompts based on the extracted data and create the family register or family tree. Example: "Yamada Family Tree.pdf" is generated.

[1613] Step 6:

[1614] The generated death registers and genealogy charts are stored on a cloud platform and can be accessed by users. The input is the generated PDF file, and the output is an access link on the cloud storage. Specifically, the server uses a cloud storage service such as Amazon S3 to upload the file and generate an access link.

[1615] Step 7:

[1616] The emotion engine analyzes the user's emotions in real time and adjusts the displayed content. The input is the user's facial expression and voice data, and the output is content adjusted based on the user's emotional state. Specifically, it uses Microsoft Azure Cognitive Services to analyze the user's facial expressions and voice, and the server dynamically adjusts the content based on the obtained emotional information. For example, if the user is moved, an emotional episode will be added.

[1617] Step 8:

[1618] Emotion-based information is provided to display devices in stores. The input is the adjusted content, and the output is what is displayed on the display device. Specifically, the adjusted content is sent from the server to a tablet device or large display, and then displayed on the display device. This enables store staff to provide appropriate support and suggestions to customers.

[1619] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1620] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1621] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1622] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1623] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1624] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1625] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1626] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1627] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1628] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1629] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1630] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1631] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1632] 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.

[1633] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1634] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1635] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1636] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1637] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1638] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1639] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1640] The following is further disclosed regarding the above embodiment.

[1641] (Claim 1)

[1642] A means for receiving family register information uploaded by a user;

[1643] A means for analyzing the received family register information and extracting necessary data;

[1644] means for storing the extracted data in a central database;

[1645] A means of extracting data from a central database to generate family registers and pedigrees;

[1646] A system including a means for storing the generated family register and family tree in a cloud system.

[1647] (Claim 2)

[1648] 10. The system of claim 1, further comprising means for converting the received family register information into digital text using OCR technology.

[1649] (Claim 3)

[1650] The system of claim 1, further comprising means for generating a family register or a family tree using the generation AI.

[1651] "Example 1"

[1652] (Claim 1)

[1653] A means for receiving family register information uploaded by a user;

[1654] A means for analyzing the received family register information and extracting necessary data;

[1655] means for storing the extracted data in a central database;

[1656] means for extracting data from the central database to generate genealogy information;

[1657] The system includes means for storing the generated genealogy information in a cloud computing system.

[1658] (Claim 2)

[1659] 10. The system of claim 1, further comprising means for converting the received family register information into digital text using optical character recognition technology.

[1660] (Claim 3)

[1661] 10. The system of claim 1, further comprising means for using generative artificial intelligence to effect generation of the genealogy information.

[1662] "Application Example 1"

[1663] (Claim 1)

[1664] A means for receiving family register information uploaded by a user;

[1665] A means for analyzing the received family register information and extracting necessary data;

[1666] means for storing the extracted data in a central database;

[1667] A means of extracting data from a central database to generate family registers and pedigrees;

[1668] A means of storing the generated family register and family tree in a cloud system,

[1669] A means for analyzing the received family register information using a smart device;

[1670] A system including a means for displaying a family tree or a family record generated by a smart device.

[1671] (Claim 2)

[1672] 10. The system of claim 1, further comprising means for converting the received family register information into digital text using OCR technology.

[1673] (Claim 3)

[1674] The system of claim 1, further comprising means for generating a family register or a family tree using the generation AI.

[1675] (Claim 4)

[1676] 10. The system of claim 1, further comprising: means for analyzing the family register information uploaded by the smart device and transmitting the extracted data to the cloud system.

[1677] "Example 2: Combining Emotion Engines"

[1678] (Claim 1)

[1679] means for receiving digital files uploaded by users;

[1680] means for performing an initial check of the format and content of received digital files;

[1681] means for transmitting files that pass the initial check to a server;

[1682] A means for converting the received digital file into digital text using OCR technology and extracting the required data;

[1683] means for storing the extracted data in a central database;

[1684] a means for extracting and formatting data from the central database in response to user requests;

[1685] A means to generate family records and genealogies using generative AI,

[1686] A means of storing the generated family register and family tree in a cloud system,

[1687] A means for users to access data generated through the cloud system; and

[1688] means including an emotion engine that analyzes a user's facial expression and voice to identify emotions;

[1689] means for adjusting the displayed content based on the identified emotion;

[1690] A system that includes an automated means for continuous data updating.

[1691] (Claim 2)

[1692] 10. The system of claim 1, further comprising means for converting the received digital file into digital text using OCR technology to extract the required information.

[1693] (Claim 3)

[1694] The system according to claim 1, further comprising means for generating a family register or a family tree using the generation AI.

[1695] "Application example 2 when combining emotion engines"

[1696] (Claim 1)

[1697] A means of receiving personal information uploaded by users;

[1698] A means for analyzing the received personal information and extracting necessary data;

[1699] means for storing the extracted data in a centralized data storage system;

[1700] a means for extracting data from a centralized data storage system to generate a death register or a genealogy chart;

[1701] A means to store the generated family register and genealogy chart on a cloud platform,

[1702] means for adjusting the displayed content using an emotion engine that identifies the emotion of the user;

[1703] A system including means for providing emotion-based information on a display device in a store.

[1704] (Claim 2)

[1705] 10. The system of claim 1, further comprising means for converting the received personal information into digital text using character recognition techniques.

[1706] (Claim 3)

[1707] 10. The system of claim 1, further comprising means for generating a family tree or genealogy using the generative AI model. [Explanation of symbols]

[1708] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving family register information uploaded by a user; A means for analyzing the received family register information and extracting necessary data; means for storing the extracted data in a central database; A means of extracting data from a central database to generate family registers and pedigrees; A system including a means for storing the generated family register and family tree in a cloud system.

2. 10. The system of claim 1, further comprising means for converting the received family register information into digital text using OCR technology.

3. The system according to claim 1, further comprising means for generating a family register or a family tree using the generation AI.

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