System

Abstract

A system is provided.SOLUTION: A system comprising: means for transmitting a request from a user device to a AI; means for analyzing, by the AI, contents of the request; means for transmitting a request to a server based on the analyzed contents of the request; means for acquiring, by the server, information from a database based on the request; means for returning the acquired information to the user device; and means for presenting, by the user device, the returned information to the user.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] In modern society, various daily chores consume time and energy. In particular, tasks such as scheduling meetings and searching for store information are becoming increasingly tedious, hindering efficient user activities. Furthermore, insufficient information sharing between different systems and services makes it difficult for users to obtain a consistent experience. This leads to problems such as reduced productivity and increased stress. [Means for solving the problem]

[0005] The present invention provides a system including a means for sending a request from a user terminal to an AI, a means for the AI ​​to analyze the request content, a means for sending a request to a server based on the analyzed request content, a means for the server to obtain information from a database based on the request, a means for returning the obtained information to the user terminal, and a means for the user terminal to present the returned information to the user.

[0006] We also propose a configuration that includes a means for the server to retrieve specific date candidates from a database based on a request, a means for presenting those date candidates to the user and confirming the user's selection on the server, and a means for the server to notify other related AIs of the confirmed date, as well as a configuration that includes a means for the server to retrieve specific store information from a database based on a request and present that store information to the user.

[0007] This allows users to easily perform complicated scheduling and store searches through AI, enabling them to live an efficient and stress-free life.

[0008] A "user terminal" is a device or equipment operated by a user that can send requests to an AI and receive responses.

[0009] "AI" is an abbreviation for artificial intelligence, and has the function of analyzing user requests, sending requests to the server, and providing the obtained information to the user.

[0010] A "server" is a computer system that receives requests from an AI over a network, retrieves the necessary information from a database, and responds to the AI.

[0011] A "database" is an information management system that systematically stores information and provides specific information in response to a request from a server.

[0012] "Request content" refers to specific requests or commands that users give to the AI, and indicates tasks such as scheduling appointments or searching for store information.

[0013] A "request" is a specific request that an AI sends to a server, prompting the server to execute the request.

[0014] "Candidate dates" are multiple dates and times that may be available for a particular task (e.g., holding a meeting).

[0015] "Store information" is detailed information about a specific store, including location information, business hours, reviews, etc.

[0016] A "response" is information provided by the server to the AI, and includes data and information resulting from the request.

[0017] "Presentation" refers to the act of AI displaying information to the user, informing the user of the results in a way that is easy for the user to understand. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram 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

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

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

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention is a system that efficiently handles a user's daily chores by linking a user terminal, a server, AI, and a database. In this system, the user can issue various requests to the AI ​​through the terminal. A specific embodiment of this system is described below.

[0040] System configuration

[0041] User device:

[0042] This is a device that users can operate, such as a smartphone, tablet, or PC. Users can send requests to AI through the device and receive the processing results.

[0043] AI:

[0044] It is an artificial intelligence that is set up for each user, and receives and analyzes the user's request. Based on the analysis results, it sends a request to the server, receives a response from the server, and presents it to the user.

[0045] server:

[0046] It is installed on a network and receives requests from AI. Based on the request, it retrieves the necessary information from the database and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations.

[0047] Database:

[0048] It is an information management system that stores necessary data, such as meeting schedule options, store information, etc. It provides related data in response to requests from the server.

[0049] Processing flow

[0050] The user operates the device to send a request to the AI, such as "Please arrange a meeting for next week." The AI ​​receives this request, analyzes the content, and determines that the meeting date needs to be adjusted. The AI ​​then sends a request to the server along with detailed information such as the list of meeting participants and the desired date.

[0051] The server receives the request and queries the database to obtain possible meeting dates. The server then returns the obtained date options to the AI, which then presents them on the user's device. The user then selects the desired date from the options presented.

[0052] The date selected by the user is sent to the AI ​​via the device, which then sends the selection to the server. The server then coordinates with other related AIs to confirm the final date. This information is then stored in the database again, and the confirmed date is notified to the relevant parties.

[0053] Also, if a user requests "find a nearby cafe," the AI ​​will send a request to the server based on the user's current location and desired conditions. The server will retrieve the relevant store information from the database and respond to the AI. The AI ​​will then display this information on the user's device, allowing the user to check nearby cafes.

[0054] Specific examples

[0055] Meeting scheduling example:

[0056] The user sends a request to the AI ​​from their device saying, "Please arrange a meeting for next week."

[0057] The AI ​​sends a request to the server based on the list of conference participants and the desired date.

[0058] The server retrieves schedule candidates from the database and returns them.

[0059] The AI ​​presents possible dates on the user's device, and the user selects the desired date.

[0060] The server notifies other related AIs of the confirmed schedule and completes the final adjustments.

[0061] Store information search example:

[0062] The user sends a request to the AI ​​from their device to "find a nearby cafe."

[0063] The AI ​​requests the user's current location and desired conditions from the server.

[0064] The server retrieves the relevant store information from the database and responds to the AI.

[0065] AI presents store information on the user's device.

[0066] This invention allows users to automate tedious tasks and perform daily tasks more efficiently and conveniently. This system is expected to significantly reduce users' time and effort, and reduce stress.

[0067] The processing flow will be explained below.

[0068] Meeting Scheduling Process Steps

[0069] Step 1:

[0070] The user operates the terminal and inputs a request to "schedule a meeting for next week."

[0071] Step 2:

[0072] The terminal sends the input request to the user's AI.

[0073] Step 3:

[0074] The user AI analyzes the request and determines that a meeting schedule needs to be adjusted.

[0075] Step 4:

[0076] The user AI sends a request to the server, adding detailed information such as the list of meeting participants and the desired date.

[0077] Step 5:

[0078] The server analyzes the received request and queries the database to obtain the required data.

[0079] Step 6:

[0080] The database searches for possible meeting dates and returns the results to the server.

[0081] Step 7:

[0082] The server compiles the schedule suggestions received from the database and responds to the user AI.

[0083] Step 8:

[0084] The user AI receives the response from the server and presents possible dates on the user's device.

[0085] Step 9:

[0086] The user selects the desired date from the presented date options and performs an operation to confirm the selection.

[0087] Step 10:

[0088] The device sends the date selected by the user to the user AI.

[0089] Step 11:

[0090] The user AI sends the confirmed schedule to the server.

[0091] Step 12:

[0092] The server stores the confirmed schedule information in a database and notifies the AI ​​of other meeting participants of that information.

[0093] Store information search processing steps

[0094] Step 1:

[0095] The user operates the terminal and inputs a request such as "Please find a nearby cafe."

[0096] Step 2:

[0097] The terminal sends the input request to the user's AI.

[0098] Step 3:

[0099] The user AI analyzes the request and determines that a search for a cafe is required.

[0100] Step 4:

[0101] The user AI sends a request to the server along with the user's current location and desired conditions.

[0102] Step 5:

[0103] The server analyzes the received request and queries the database to obtain the required data.

[0104] Step 6:

[0105] The database searches for cafe information that matches the specified conditions and returns the results to the server.

[0106] Step 7:

[0107] The server compiles the cafe information received from the database and responds to the user AI.

[0108] Step 8:

[0109] The user AI receives the response from the server and displays the cafe information on the user's device.

[0110] Step 9:

[0111] The user checks the presented cafe information and decides on a destination if necessary.

[0112] Example 1

[0113] 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."

[0114] In modern business environments and everyday life, users spend a great deal of time and effort on complex tasks and organizing information. There is a particular need for efficient and fast ways to complete everyday tasks, such as scheduling meetings or searching for store information. However, conventional systems often require users to manually search for information or schedule appointments, which can be perceived as inefficient. Therefore, there is a need for systems that allow users to more efficiently complete everyday tasks.

[0115] 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.

[0116] In this invention, the server includes a means for sending a request from a user terminal to an AI model, a means for the AI ​​model to analyze the request content, and a means for sending a request to the server based on the analyzed request content. This allows the user to efficiently process complicated tasks. The server also includes a means for acquiring information from an information management system based on the request, a means for returning the acquired information to the user terminal, and a means for the user terminal to present the returned information to the user. This allows the user to quickly obtain the information they need and saves them time and effort. Furthermore, this system includes a means for the server to acquire specific date options and store information from the information management system based on the request and present that information to the user. This automates the scheduling of meetings and searching for store information, significantly saving the user time and effort.

[0117] A "user terminal" is a device operated by a user, such as a smartphone, tablet, or PC.

[0118] An "AI model" refers to an artificial intelligence system that receives and analyzes user requests and processes the necessary information.

[0119] A "server" is a central processing unit installed on a network that receives requests from an AI model and processes them accordingly.

[0120] A "request" is a request for specific information sent from a user device through an AI model to a server.

[0121] An "information management system" is a system that stores information in a form such as a database and provides it to a server when needed.

[0122] "Analysis" is the procedure by which an AI model understands the request received from a user and takes appropriate action.

[0123] "Provision" refers to the act of a server or information management system obtaining the necessary information and returning it to the user device or AI model.

[0124] "Date options" are options for available dates and times for a meeting or event.

[0125] "Store information" refers to detailed information about a specific store, including its location, business hours, and services offered.

[0126] "Notification" is a means by which the server notifies relevant AI models and users of confirmed information.

[0127] The present invention is a system consisting of a user terminal, a server, an AI model, and an information management system. This system is designed to help users efficiently complete complex daily tasks. Specific embodiments of this system are described below.

[0128] Hardware and software used

[0129] User device:

[0130] A user terminal is a device operated by a user, such as a smartphone, tablet, or PC. Users can use these devices to send requests to the system and receive the processing results.

[0131] AI model:

[0132] The AI ​​model uses artificial intelligence technology for natural language processing, specifically a generative AI model such as OpenAI's GPT-4, to receive and analyze user requests and generate appropriate responses.

[0133] server:

[0134] The server receives requests from the AI ​​model and queries the information management system based on those requests. The server is typically operated using a server instance from Amazon Web Services (AWS) or Google Cloud Platform (GCP).

[0135] Information Management System:

[0136] The information management system uses database technology, such as Oracle Database or MySQL. This system stores the necessary information (such as potential meeting dates and store information) and provides the information in response to server requests.

[0137] Example of the system (meeting schedule adjustment)

[0138] A user device sends a request to the AI ​​model saying, "Please reschedule a meeting for next week." The AI ​​model (GPT-4) that receives this request analyzes the request and determines that a "meeting rescheduling" is necessary. The AI ​​model then sends a request to the server with detailed information such as a list of meeting participants and the desired date.

[0139] The server receives the request and queries an information management system (e.g., a MySQL database) to obtain possible meeting dates. The server returns the obtained date options to the AI ​​model, which then presents them to the user's device. The user selects the desired date from the presented options. This selection is sent back to the AI ​​model via the device, and the AI ​​model sends this selection to the server. The server then works with other related AI models to confirm the final date. This information is then stored back in the information management system, and the confirmed date is notified to the relevant parties.

[0140] Example of the system (store information search)

[0141] A user device sends a request to the AI ​​model saying, "Please find a nearby cafe." The AI ​​model (GPT-4) analyzes the user's current location and desired conditions and generates a request to the server. This request includes specific location information, such as "Shibuya Ward, Tokyo."

[0142] The server receives the request and queries an information management system (e.g., Oracle Database) to obtain the relevant store information. The server then returns the obtained store information to the AI ​​model, which then presents it to the user's device. The user can then make a decision based on the presented cafe information.

[0143] Prompt Sentence Examples

[0144] Here are some example prompts that users can enter into a generative AI model:

[0145] "We'd like to arrange a meeting date for next week. The participants are A, B, and C. Possible dates are: October 1st, October 2nd, and October 3rd."

[0146] "I'm looking for a nearby cafe. I'm currently in Shibuya, Tokyo, and I'd prefer a place with Wi-Fi."

[0147] By using the system of the present invention, users can quickly and efficiently complete tedious daily tasks, which is expected to significantly save users time and effort and reduce stress.

[0148] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0149] Step 1:

[0150] The user enters the request at the terminal.

[0151] Users operate their smartphones or PCs, input requests such as "Please arrange a meeting for next week" or "Please find a nearby cafe," and press the send button.

[0152] Input: User request (request in text format)

[0153] Output: Sending a request from the device to the AI ​​model

[0154] Step 2:

[0155] The device sends the request to the AI ​​model.

[0156] The device receives the text data entered by the user and issues an HTTP request to send it to the AI ​​model via the Internet.

[0157] Input: User request (text data)

[0158] Output: HTTP request to the AI ​​model

[0159] Step 3:

[0160] The AI ​​model analyzes the request.

[0161] The AI ​​model (e.g., GPT-4) analyzes the received request and identifies the required tasks. At this stage, the AI ​​model understands the request and extracts the data needed for the next step (e.g., participant list).

[0162] Input: HTTP request (user requested data)

[0163] Output: Analysis results (task identification and extraction of necessary data)

[0164] Step 4:

[0165] The AI ​​model sends a request to the server.

[0166] Based on the analysis results, the AI ​​model generates a request containing the necessary information and sends it to the server in JSON format.

[0167] Input: Analysis results (identification of tasks and extraction of necessary data)

[0168] Output: Request to server (JSON format)

[0169] Step 5:

[0170] The server receives the request.

[0171] The server receives requests sent by the AI ​​model, logs the request content, and begins processing.

[0172] Input: Request (JSON format)

[0173] Output: Logging and preparing for processing

[0174] Step 6:

[0175] The server queries the information management system.

[0176] Based on the received request, the server queries the information management system (database) using an SQL query.

[0177] Input: Request content

[0178] Output: SQL query executed

[0179] Step 7:

[0180] The information management system provides the information.

[0181] In response to an inquiry from the server, the information management system responds with saved meeting schedule information and store information.

[0182] Input: SQL query

[0183] Output: Required information (meeting date options or store information)

[0184] Step 8:

[0185] The server returns the provided information to the AI ​​model.

[0186] The server processes the information obtained from the information management system and sends it back to the AI ​​model.

[0187] Input: Required information (meeting date options or store information)

[0188] Output: Response to the AI ​​model

[0189] Step 9:

[0190] The AI ​​model presents the results on the user's device.

[0191] The AI ​​model organizes the information it receives in a way that is easy for the user to understand and displays the results on the user's device, for example, "Possible dates for next week's meetings are October 1st, 2nd, and 3rd."

[0192] Input: Response information from the server

[0193] Output: Display of results (formatted information) on the user's device

[0194] Step 10:

[0195] The user makes a selection or confirms the results.

[0196] The user checks the suggested dates and store information and selects the appropriate option. For example, they select "October 2nd" and press the select button.

[0197] Input: Information presented to the user

[0198] Output: User's selection

[0199] Step 11:

[0200] The device sends the selection results to the AI ​​model.

[0201] The device retrieves the user's selection and issues another HTTP request to send it to the AI ​​model.

[0202] Input: User selection result

[0203] Output: HTTP request to the AI ​​model

[0204] Step 12:

[0205] The AI ​​model sends the selection results to the server.

[0206] The AI ​​model sends the user's selection results to the server in JSON format.

[0207] Input: User selection result (HTTP request)

[0208] Output: JSON request to the server

[0209] Step 13:

[0210] The server makes the final adjustments and stores the data in the information management system.

[0211] The server also integrates information from other related AI models to determine the final meeting schedule, which is then stored in the information management system.

[0212] Input: User selections (JSON request) and information from other AI models

[0213] Output: Save the finalized meeting schedule

[0214] Step 14:

[0215] Information management systems will be updated and necessary parties will be notified.

[0216] The updated information is saved in the information management system, and the system sends emails and in-app notifications to relevant parties.

[0217] Input: Finalized meeting dates

[0218] Output: Notification to relevant parties (email, in-app notification)

[0219] (Application example 1)

[0220] 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."

[0221] Conventional autonomous vehicles lack systems that allow users to efficiently handle everyday chores, requiring many tasks to be performed manually while driving, resulting in low convenience. In particular, the wide range of tasks that drivers must perform, such as setting destinations, checking traffic conditions, and managing entertainment, can be cumbersome and may affect safety. Another issue is the insufficient provision of real-time information, making it difficult to respond quickly to user requests.

[0222] 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.

[0223] In this invention, the server includes a means for providing traffic information and entertainment information, a means for setting a destination by voice, and a means for presenting acquired traffic information to the user and providing entertainment information. This allows the user to easily set a destination, check traffic conditions, and manage entertainment in an autonomous vehicle by voice, significantly improving convenience and safety. It also enables real-time information provision, enabling rapid response.

[0224] A "user terminal" is an information device operated by a user, such as a smartphone, tablet, or PC.

[0225] "AI" refers to artificial intelligence that analyzes user requests and sends instructions to the server based on the results.

[0226] A "server" is a device that receives requests from AI over a network, retrieves information from a database, and responds.

[0227] A "database" is an information management system that stores various types of information and provides necessary data based on requests.

[0228] "Traffic information" refers to information about road and traffic conditions when an autonomous vehicle is heading to its destination.

[0229] "Entertainment information" refers to information about content that users can enjoy, including music, videos, news, and the like.

[0230] "Voice-based destination setting means" refers to a method of analyzing a user's voice input and determining the destination of an autonomous vehicle based on the set destination.

[0231] "Real-time information provision" refers to providing information immediately based on the current situation.

[0232] "Request analysis" refers to the process by which AI understands the content of requests received from users and issues appropriate instructions or requests.

[0233] "Means for presenting" refers to a method for directly presenting acquired information to a user, and includes methods such as a display and audio output.

[0234] The present invention provides a system that efficiently processes various tasks within an autonomous vehicle by linking a user terminal, a server, an AI, and a database. In this system, the user can issue requests to the AI ​​through the terminal. Specific embodiments of this system are described below.

[0235] System configuration

[0236] User device:

[0237] An information device operated by a user, such as a smartphone, tablet, or in-car display, allows the user to send requests to AI through the device and receive the processing results.

[0238] AI:

[0239] This is an artificial intelligence that is set up for each user and receives and analyzes the user's request. It sends instructions to the server based on the analysis results, receives responses from the server, and presents them to the user. The AI ​​uses generative AI models to perform speech recognition and natural language analysis.

[0240] server:

[0241] It is installed on a network and receives requests from AI. It retrieves the necessary information from a database based on the request and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations. It uses a cloud server or an on-premise server.

[0242] Database:

[0243] It is an information management system that stores necessary data, such as traffic and entertainment information. It provides related information in response to requests from the server. Database software such as MySQL or PostgreSQL is used.

[0244] Specific examples

[0245] Destination setting example:

[0246] The user sends a voice request from their device to the AI ​​saying, "Set the destination to Shibuya." The AI ​​analyzes the voice and obtains the destination as text. The AI ​​then instructs the server that the destination is Shibuya. The server uses this information to send a traffic information request and obtains traffic conditions from a database. The server returns the obtained traffic information to the AI, which then displays it on the user's device. The user can check the traffic information provided and give instructions such as route changes if necessary.

[0247] Examples of entertainment information provided:

[0248] When a user makes a voice request such as "Play some relaxing music," the AI ​​analyzes the request and sends a request for entertainment information to the server. The server retrieves a music list based on the user's preferences from a database and returns that information to the AI. The AI ​​then presents the retrieved music list to the user's device and automatically plays the music.

[0249] The specific hardware and software used

[0250] Hardware: smartphones, tablets, in-vehicle displays, cloud servers

[0251] Software: Generative AI model, MySQL, PostgreSQL, speech recognition library (speech_recognition), speech synthesis library (pyttsx3)

[0252] Prompt Sentence Examples

[0253] The processing steps when the user says "Set destination to Shibuya" are explained below.

[0254] 1. Analyze the user's voice and obtain the destination as text.

[0255] 2. Based on the acquired destination, traffic conditions are obtained from the traffic information API.

[0256] 3. Notify users when traffic conditions are congested.

[0257] 4. Recommending your preferred entertainment based on your user ID.

[0258] This invention allows users to easily handle complicated tasks by voice even in autonomous vehicles, significantly improving convenience and safety. It also enables real-time information provision, enabling rapid response.

[0259] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0260] Step 1:

[0261] The user operates the device and sends a voice request such as "Set destination to Shibuya." The input is the user's voice, and the device must be equipped with a microphone. The output is voice data. Based on this, the device collects the voice data and sends it to the AI ​​for analysis.

[0262] Step 2:

[0263] The AI ​​analyzes the received voice data. The input is voice data, and the output is textual destination information (in this case, "Shibuya"). The AI ​​uses a generative AI model to perform voice recognition and convert the voice data into text. Specifically, the speech_recognition library is used to convert voice to text.

[0264] Step 3:

[0265] Based on the analyzed destination information, the AI ​​sends a request to the server. The input is the destination information text data "Shibuya," and the output is the request data to the server. The server receives the destination information and begins obtaining traffic information.

[0266] Step 4:

[0267] Based on the request received by the server, traffic information is retrieved from the database. The input is the destination text data "Shibuya" and the output is traffic information data. The server calls the traffic information API and retrieves traffic conditions based on the specified destination.

[0268] Step 5:

[0269] The server returns the traffic information it has acquired to the AI. The input is traffic information data, and the output is response data to the AI. The server then sends the traffic information it has acquired from the database back to the AI.

[0270] Step 6:

[0271] The AI ​​analyzes the traffic information it receives and presents it to the user. The input is traffic information data, and the output is display data on the user's device. Specifically, the AI ​​displays the acquired traffic information on the device in a format that is easy for the user to understand. Traffic conditions are presented to the user using the device's display and audio output functions.

[0272] Step 7:

[0273] Based on the information provided, the user approves or changes the destination by voice. The input is the user's voice command, and the output is the final destination information. The AI ​​again analyzes the user's voice command and determines the final destination.

[0274] Step 8:

[0275] The AI ​​sends the final destination back to the server, which then determines the driving route based on this and reflects it in the navigation system. The input is the final destination information and the output is navigation data. The server works in conjunction with the navigation system to optimize the route of the autonomous vehicle.

[0276] This will allow users to easily set destinations and check traffic information by voice, improving the convenience and safety of self-driving vehicles.

[0277] 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.

[0278] This invention is a system that efficiently handles users' daily chores and provides services optimized based on the user's emotional state by linking a user terminal, server, AI, database, and emotion engine. In this system, the user can issue various requests to the AI ​​through the terminal, and the emotion engine recognizes the user's emotions and optimizes the request content and results.

[0279] System configuration

[0280] User device:

[0281] This is a device that users can operate, such as a smartphone, tablet, or PC. Users can send requests to AI through the device and receive the processing results.

[0282] AI:

[0283] It is an artificial intelligence that is set up for each user, and receives and analyzes the user's request. Based on the analysis results, it sends a request to the server, receives a response from the server, and presents it to the user.

[0284] server:

[0285] It is installed on a network and receives requests from AI. Based on the request, it retrieves the necessary information from the database and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations.

[0286] Database:

[0287] It is an information management system that stores necessary data, such as meeting schedule options, store information, etc. It provides related data in response to requests from the server.

[0288] Emotion Engine:

[0289] This module recognizes and analyzes the user's emotions, judging their emotional state by analyzing voice, facial expressions, text, etc. The emotion engine then optimizes the request content based on the results and provides it to the AI.

[0290] Processing flow

[0291] The user operates their device to send a request to the AI, such as "Please reschedule a meeting next week." At this point, the emotion engine analyzes the user's voice and facial expressions, and if the user is feeling stressed, for example, it provides that emotional state to the AI. Based on this emotional information and the request, the AI ​​determines that the meeting needs to be rescheduled.

[0292] Next, the AI ​​adds detailed information such as a list of meeting participants and desired dates, and also sends a request along with emotional information to the server. The server receives the request and retrieves candidate dates from its database. The server then returns the candidate dates to the AI.

[0293] The AI ​​presents the proposed dates to the user's device, prioritizing the most appropriate ones based on the user's emotional information. The user selects the desired date from the presented options and confirms it. The device then sends the user's selected date to the AI, which then sends the selection to the server to confirm it.

[0294] The server will then work with other related AIs to determine the final schedule, store the information in a database, and notify the relevant parties of the final schedule.

[0295] Similarly, if a user requests, "Please find a nearby cafe," the emotion engine will recognize and analyze the user's emotions and provide them to the AI ​​along with the user's current location and desired conditions. The AI ​​will then send a request to the server, which will retrieve the relevant store information from its database and respond. The AI ​​will then present the retrieved store information on the user's device and provide appropriate information based on the emotional information.

[0296] Specific examples

[0297] Meeting scheduling example:

[0298] The user sends a request to the AI ​​from their device saying, "Please arrange a meeting for next week."

[0299] The emotion engine analyzes the user's voice and facial expressions and determines whether the user is feeling stressed.

[0300] The AI ​​sends a request to the server based on emotional information, the list of meeting participants, and the desired date and time.

[0301] The server retrieves possible dates from the database and responds to the AI.

[0302] The AI ​​presents possible dates to the user's device and prioritizes them appropriately based on emotional information.

[0303] The user selects and confirms the desired date.

[0304] The server stores the confirmed schedule in a database and notifies other related AIs.

[0305] Store information search example:

[0306] The user sends a request to the AI ​​from their device to "find a nearby cafe."

[0307] The emotion engine analyzes the user's emotions and determines, for example, that they want to relax.

[0308] The AI ​​sends a request to the server, adding its current location, desired conditions, and emotional information.

[0309] The server retrieves the relevant cafe information from the database and responds to the AI.

[0310] The AI ​​presents store information to the user's device and prioritizes appropriate cafes based on emotional information.

[0311] The present invention allows users to automate tedious tasks and receive services optimized according to their emotional state, improving their quality of life.

[0312] The processing flow will be explained below.

[0313] Meeting Scheduling Process Steps

[0314] Step 1:

[0315] The user operates the terminal and inputs a request to "schedule a meeting for next week."

[0316] Step 2:

[0317] The device sends the input request to the AI, and at the same time, it also acquires the user's facial expressions and voice data and sends them to the emotion engine.

[0318] Step 3:

[0319] The emotion engine analyzes the user's facial expressions and voice data and determines whether the user is feeling stressed.

[0320] Step 4:

[0321] The emotion engine sends the analysis results to the AI, providing the user's emotional state.

[0322] Step 5:

[0323] Based on the request and emotional information, the user AI determines that the meeting schedule needs to be adjusted and sends a request to the server along with a list of meeting participants and the desired date.

[0324] Step 6:

[0325] The server analyzes the received request and queries the database to obtain the required data.

[0326] Step 7:

[0327] The database searches for possible meeting dates and returns the results to the server.

[0328] Step 8:

[0329] The server compiles the schedule suggestions received from the database and responds to the user AI.

[0330] Step 9:

[0331] The user AI receives the response from the server and presents the suggested dates to the user's device, with the display order optimized based on emotional information.

[0332] Step 10:

[0333] The user selects the desired date from the presented date options and performs an operation to confirm the selection.

[0334] Step 11:

[0335] The device sends the user's selected date to the AI.

[0336] Step 12:

[0337] The user AI sends the confirmed schedule to the server.

[0338] Step 13:

[0339] The server stores the confirmed schedule information in a database and notifies the AI ​​of other meeting participants of that information.

[0340] Store information search processing steps

[0341] Step 1:

[0342] The user operates the terminal and inputs a request such as "Please find a nearby cafe."

[0343] Step 2:

[0344] The device sends the input request to the AI, and at the same time, it also acquires the user's facial expressions and voice data and sends them to the emotion engine.

[0345] Step 3:

[0346] The emotion engine analyzes the user's facial expressions and voice data and determines that the user wants to relax.

[0347] Step 4:

[0348] The emotion engine sends the analysis results to the AI, providing the user's emotional state.

[0349] Step 5:

[0350] Based on the request and emotional information, the user AI sends a request to the server along with the user's current location and desired conditions.

[0351] Step 6:

[0352] The server analyzes the received request and queries the database to obtain the required data.

[0353] Step 7:

[0354] The database searches for cafe information that matches the conditions and returns the results to the server.

[0355] Step 8:

[0356] The server compiles the cafe information received from the database and responds to the user AI.

[0357] Step 9:

[0358] The user AI receives the response from the server and displays the cafe information on the user's device, with the display order optimized based on the user's emotional information.

[0359] Step 10:

[0360] The user checks the presented cafe information and decides where to visit.

[0361] Example 2

[0362] 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."

[0363] Conventional information processing systems provide information uniformly without considering the user's emotional state, making it difficult to provide optimal services tailored to the user's situation. Another problem is that they lack the means to help users efficiently complete complex tasks. This has the drawback of not sufficiently improving the user's quality of life.

[0364] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0365] In this invention, the server includes a means for analyzing the emotional state of the user and providing the result to the artificial intelligence, a means for the artificial intelligence to analyze the request content and send the request to the server, and a means for the server to retrieve information from a database and respond to the user, thereby enabling optimal information provision and task processing according to the user's emotional state.

[0366] A "user terminal" is a device operated by a user, and includes devices such as smartphones, tablets, and personal computers.

[0367] "Artificial intelligence" is a system that analyzes user requests, generates requests based on the results, and sends them to the server.

[0368] A "server" is a central processing unit installed on a network that receives requests from artificial intelligence, retrieves the necessary information from a database, and returns it to the artificial intelligence.

[0369] A "database" is an information management system that can be accessed by a server and stores various types of data.

[0370] The "emotion engine" is a module that analyzes the user's voice, facial expressions, text, etc. to determine their emotional state and provides the results to artificial intelligence.

[0371] "Request" refers to the request or content of the request that a user makes to an artificial intelligence through a user terminal.

[0372] "Request" refers to the analyzed request and request for necessary information that the artificial intelligence sends to the server.

[0373] "Response" refers to response data that the server provides to the user terminal via artificial intelligence with information obtained based on the request.

[0374] MODE FOR CARRYING OUT THE INVENTION

[0375] The present invention is a system that efficiently handles a user's daily chores and provides optimized services based on the user's emotional state by linking a user terminal, artificial intelligence, a server, a database, and an emotion engine.

[0376] Users can issue various requests to the AI ​​through their devices. The emotion engine recognizes the user's emotions and optimizes the request and its results. User devices include smartphones, tablets, and personal computers, and user requests and operations are carried out through these devices.

[0377] User Device

[0378] Users operate their devices to send requests to the AI ​​via voice or text, such as "Please arrange a meeting for next week."

[0379] artificial intelligence

[0380] The AI ​​receives requests from users, analyzes them, and sends requests to the server based on the analysis results. The requests include detailed information such as a list of meeting participants and desired dates.

[0381] server

[0382] The server receives requests from the AI ​​and retrieves the necessary information from the database, such as potential meeting dates or information about nearby cafes, and then returns the retrieved information to the AI.

[0383] Database

[0384] The database is an information management system that stores various data, such as meeting schedule options and store information. The server retrieves relevant data from the database based on a request.

[0385] Emotion Engine

[0386] The emotion engine analyzes the user's voice, facial expressions, text, etc. to determine the user's emotional state. For example, it recognizes whether the user is feeling stressed or relaxed and provides the results to the AI. The emotion engine optimizes the request content based on the user's emotional state and provides feedback to the AI.

[0387] Specific examples

[0388] Meeting schedule adjustment

[0389] When a user requests that a meeting be rescheduled for next week, the emotion engine analyzes the user's voice and facial expressions and determines, for example, that the user is feeling stressed. The AI ​​sends a request to the server based on the emotion information, the list of meeting participants, and the desired date. The server retrieves candidate dates from the database and sends a response to the AI. The AI ​​presents the candidate dates to the user's device, appropriately prioritizing them based on the emotion information. The user selects and confirms the desired date. The server saves the confirmed date in the database and notifies other related AIs.

[0390] Store information search

[0391] When a user requests "find a nearby cafe," the emotion engine analyzes the user's emotions and determines, for example, that they want to relax. The AI ​​attaches their current location, desired conditions, and emotional information and sends a request to the server. The server retrieves relevant cafe information from the database and responds to the AI. The AI ​​then presents store information on the user's device and prioritizes the display of appropriate cafes based on the emotional information.

[0392] Prompt Sentence Examples

[0393] Meeting scheduling prompt:

[0394] plaintext

[0395] "I'd like to reschedule our meeting next week. The list of participants is: [Participant list]. My preferred date is either Monday or Tuesday next week."

[0396] Prompt for store information search:

[0397] plaintext

[0398] "I'd like to find a relaxing cafe nearby. You are currently located at [user location]."

[0399] The system allows users to automate tedious tasks and receive services optimized according to their emotional state, improving their quality of life.

[0400] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0401] Meeting Scheduling Process Steps

[0402] Step 1:

[0403] The user sends a request to the AI ​​to schedule a meeting from their device.

[0404] How it works: The user uses the device's voice input function or keyboard to request, "Please arrange a meeting for next week." The device converts this voice or text into digital data and sends it to the AI.

[0405] Input: User voice and text data

[0406] Output: Digitized request data

[0407] Step 2:

[0408] The emotion engine analyzes the user's emotions.

[0409] How it works: The device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The emotion engine analyzes this data to determine the user's emotional state. The emotion engine generates emotional data such as stress level and sends it to the AI.

[0410] Input: User's facial expression data, voice data

[0411] Output: User's emotional state (e.g., stress level)

[0412] Step 3:

[0413] The AI ​​generates a request based on the request content and emotional information and sends it to the server.

[0414] Specific operation: The AI ​​analyzes the user's request and the emotional information obtained from the emotion engine, and generates request data including a list of meeting participants and the desired schedule. The generated request is then sent to the server.

[0415] Input: User request data, emotional information

[0416] Output: Request data

[0417] Step 4:

[0418] The server retrieves schedule candidates from the database based on the request.

[0419] Specific operation: The server queries the database based on the received request data to obtain possible meeting dates for the next week. For example, possible dates such as "Monday at 3 PM" and "Tuesday at 11 AM" are extracted.

[0420] Input: Request data

[0421] Output: Date candidate data

[0422] Step 5:

[0423] The server returns the obtained schedule options to the AI.

[0424] Specific operation: The server sends the schedule candidate data to the AI. The schedule candidate data is in JSON format, XML format, etc.

[0425] Input: Date candidate data

[0426] Output: Response data

[0427] Step 6:

[0428] The AI ​​presents the response data to the user's device and prioritizes the most suitable dates based on emotional information.

[0429] Specific operation: The AI ​​analyzes the received response data and presents suggested dates on the user's device. If the emotional state is stressful, it prioritizes dates that are less stressful.

[0430] Input: Response data, emotion information

[0431] Output: Date options displayed on the user's device

[0432] Step 7:

[0433] The user selects and confirms the desired date.

[0434] Specific operation: The user selects the desired date from the presented date options and confirms it on the device. The selected date is sent to the AI.

[0435] Input: User selected data

[0436] Output: Confirmed schedule data

[0437] Step 8:

[0438] The AI ​​sends the confirmed schedule to the server and makes the final decision.

[0439] Specific operation: The AI ​​sends the confirmed schedule data to the server, which stores this data in a database and sends notifications to all relevant devices and parties.

[0440] Input: Confirmed schedule data

[0441] Output: Schedule data and notification data stored in the database

[0442] Store information search processing steps

[0443] Step 1:

[0444] The user sends a store information search request to the AI ​​from their device.

[0445] How it works: The user uses the device's voice input function or keyboard to request, "Please find a nearby cafe." The device converts this voice or text into digital data and sends it to the AI.

[0446] Input: User voice and text data

[0447] Output: Digitized request data

[0448] Step 2:

[0449] The emotion engine analyzes the user's emotions.

[0450] Specific operation: The device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The emotion engine analyzes this data and determines the user's emotional state. The emotion engine generates emotion data such as "I want to relax" and sends it to the AI.

[0451] Input: User's facial expression data, voice data

[0452] Output: User's emotional state (e.g., wanting to relax)

[0453] Step 3:

[0454] The AI ​​generates a request based on the request content and emotional information and sends it to the server.

[0455] Specific operation: The AI ​​analyzes the user's request and the emotional information obtained from the emotion engine, and generates request data including the user's current location, desired conditions, and emotional information. The generated request is then sent to the server.

[0456] Input: User request data, emotional information, current location data

[0457] Output: Request data

[0458] Step 4:

[0459] The server retrieves store information from the database based on the request.

[0460] Specific operation: The server queries the database based on the received request data to retrieve information about cafes near the current location. For example, it extracts information such as "Cafe A: Quiet and has Wi-Fi, Cafe B: Spacious seating."

[0461] Input: Request data

[0462] Output: Store information data

[0463] Step 5:

[0464] The server returns the acquired store information to the AI.

[0465] Specific operation: The server sends store information data to the AI. The store information data is in JSON format, XML format, etc.

[0466] Input: Store information data

[0467] Output: Response data

[0468] Step 6:

[0469] The AI ​​presents the response data to the user's device and prioritizes the most suitable stores based on emotional information.

[0470] Specific operation: The AI ​​analyzes the received response data and displays store information on the user's device. If the emotional state is "Relaxed," quiet and comfortable cafes will be displayed first.

[0471] Input: Response data, emotion information

[0472] Output: Store information displayed on the user's device

[0473] This detailed processing flow allows users to efficiently handle daily tasks and receive optimal services according to their emotional state.

[0474] (Application example 2)

[0475] 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."

[0476] Conventional systems provide simple information and process tasks without considering the user's emotional state, resulting in low user satisfaction. It is also difficult to quickly and efficiently provide optimal results to users. Furthermore, there is a lack of support for optimal decision-making based on the user's emotions, even when it comes to specific store information or schedule adjustments.

[0477] The specification processing by the specification 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 the emotion engine to recognize the user's emotions and provide the optimal result; means for the emotion engine to send a request to the server and retrieve specific date candidates from a database; means for presenting date candidates to the user and displaying them preferentially based on emotional information; means for the emotion engine to confirm the user's selection to the server; means for the server to notify other related AIs of the confirmed date; means for the emotion engine to send a request to the server and retrieve specific store information from a database; and means for displaying store information preferentially based on emotional information. This allows the provision of optimal services and information according to the user's emotional state, improving user satisfaction and enabling quick and efficient decision-making.

[0478] A "user terminal" is a device operated by a user, such as a smartphone, tablet, or PC.

[0479] "AI" is an artificial intelligence that is set up for each user and has the ability to receive and analyze user requests.

[0480] A "server" is a device installed on a network that receives requests from AI, retrieves the necessary information from a database, and returns that information to the AI.

[0481] "Database" means an information management system that stores necessary data and provides relevant data upon request.

[0482] The "emotion engine" is a module for recognizing and analyzing the user's emotions, and determines the user's emotional state by analyzing voice, facial expressions, text, etc.

[0483] "Request content" refers to the information and tasks that the user sends to the AI ​​via their device.

[0484] A "request" is a request that an AI sends to a server, and includes the request content and emotional information.

[0485] "Candidate dates" are possible date and time options retrieved from a server or database and used for scheduling.

[0486] "Store information" refers to information about a specific store, including its location, the services and products it offers, and so on.

[0487] "Priority display" refers to displaying the information or options that are most relevant to the user based on emotional information before others.

[0488] This invention is a system that combines user terminals, servers, AI, databases, and emotion engines to provide services optimized based on user emotions, allowing users to efficiently handle everyday chores such as shopping and scheduling.

[0489] The user terminal is a device such as a smartphone, tablet, or PC that provides an interface for users to operate. Users can send various requests to the AI ​​through the terminal.

[0490] The AI ​​receives and analyzes user requests. Based on the analysis results, it sends a request to the server to obtain the necessary information. It also works in conjunction with the emotion engine to provide an optimized response based on the user's emotional state.

[0491] The server receives requests from the AI ​​and retrieves the necessary information from the database. Taking into account the analysis results of the emotion engine, it returns the retrieved information to the AI. The server also oversees the overall operation of the system and manages collaboration between multiple AIs and databases.

[0492] The database stores various data such as possible meeting dates and store information, and provides related data in response to requests from the server.

[0493] The emotion engine recognizes and analyzes emotions through the user's voice, facial expressions, text, etc., and provides the results to the AI, allowing the AI ​​to provide optimal services that take into account the user's emotional state.

[0494] The system process involves a user operating a device to send a request to the AI, such as "Please reschedule a meeting next week." The emotion engine analyzes voice and facial expressions, and if the user is feeling stressed, for example, it provides that emotional state to the AI. Based on the emotional information and the request, the AI ​​determines that the meeting needs to be rescheduled.

[0495] Next, the AI ​​sends detailed information such as the list of meeting participants and desired dates as a request to the server, along with emotional information. The server receives the request and retrieves candidate dates for the meeting by referencing its database. The retrieved candidate dates are returned from the server to the AI. The AI ​​then presents the returned candidate dates on the user's device, prioritizing the more appropriate ones based on the emotional information. The user selects the desired date from the presented candidate dates and performs an operation to confirm it. The server then works with other related AIs to confirm the final date and stores that information in a database. The confirmed date is then notified to the relevant parties.

[0496] In the example of searching for store information, the user can request, "Please find a nearby cafe." The emotion engine analyzes the user's emotions and determines, for example, that they want to relax. The AI ​​sends a request to the server along with their current location, desired conditions, and emotional information, and the server responds by retrieving relevant store information from a database. The AI ​​then presents the retrieved store information on the user's device and prioritizes the display of appropriate cafes based on the emotional information.

[0497] As a concrete example, when a user uses an application in a physical store, they can install a dedicated shopping assistant app on their smartphone. When the user starts the app and inputs that they are looking for relaxation products, the emotion engine analyzes the input data and recognizes that the user is feeling like they want to relax. It then guides the user to the location of relaxation-related products (such as aroma candles and healing music) within the store.

[0498] Example prompts to send to the generative AI model:

[0499] "Analyze the user's emotions and, if they feel like relaxing, recommend the most suitable relaxation products. Also, guide them to the location of the products in the store where the user is currently located."

[0500] In this way, by providing optimal services and information based on the user's emotional state, it is possible to improve user satisfaction and support quick and efficient decision-making.

[0501] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0502] Step 1:

[0503] The user inputs a request into the terminal and sends it.

[0504] The user uses a device such as a smartphone to input the details of their request, such as the product they want to purchase or the store information they want to find, and presses the send button. At this time, voice, facial expression, and text data are collected as input data by the device. The input data includes, for example, the text "I want to relax" and the accompanying facial expression data.

[0505] Step 2:

[0506] The device sends input data to the emotion engine.

[0507] The device sends the collected voice, facial expression, and text data to an emotion engine, which runs on the cloud and analyzes the data to determine the user's emotional state. Based on the input data, the emotion state is identified using voice recognition and image analysis algorithms.

[0508] Step 3:

[0509] The emotion engine analyzes the user's emotions and provides the results to the AI.

[0510] The emotion engine analyzes the input data sent and identifies the user's emotional state (e.g., feeling like they want to relax). The emotion information generated based on the emotion analysis is passed to the AI. At this point, the analysis result is generated as "the user feels like they want to relax."

[0511] Step 4:

[0512] The AI ​​sends a request to the server based on the request content and emotional information.

[0513] The AI ​​combines the user's request with emotional information and sends a request to the server. The request data includes specific details of the request (e.g., "Please find me a product that helps me relax") along with emotional information. The AI ​​determines which category the request falls into and sends it to the server as an appropriate request.

[0514] Step 5:

[0515] The server receives the request and retrieves the information from the database.

[0516] The server receives a request from the AI ​​and references the database based on the request. For example, if the request is for "relaxing products," the server searches the database for relevant product information (e.g., aroma candles, healing music, etc.). The retrieved information includes data such as the product name, category, price, and location within the store.

[0517] Step 6:

[0518] The server returns the information it has obtained to the AI.

[0519] The server organizes the information retrieved from the database and sends it back to the AI. The response data includes prioritized product and store information based on user sentiment, and the AI ​​receives information optimized for the user.

[0520] Step 7:

[0521] The AI ​​sends the results back to the user's device and presents them to the user.

[0522] The AI ​​analyzes the information returned by the server and displays it on the user's device in the optimal order based on the user's emotional state. For example, if the user feels like relaxing, it will prioritize products with a relaxing effect. The information also includes the location of the displayed products and stores.

[0523] Step 8:

[0524] The user makes a selection and confirms it based on the information displayed.

[0525] The user selects the desired product or store from the information displayed on the device and presses the confirm button. The selection and confirmation data are then sent from the device to the AI. The selection data includes information about the product the user ultimately became interested in and the store they wish to use.

[0526] Step 9:

[0527] The AI ​​confirms the user's selection to the server and notifies any related AIs.

[0528] The AI ​​sends the user's selection data to the server and confirms the selection. The server stores the confirmed information in a database and notifies other related AIs, allowing other systems and applications to provide optimal services based on the user's selection.

[0529] Example prompts to send to the generative AI model:

[0530] "Analyze the user's emotions and, if they feel like relaxing, recommend the most suitable relaxation products. Also, guide them to the location of the products in the store where the user is currently located."

[0531] In this way, optimal services and information are provided based on the user's emotional state, improving user satisfaction.

[0532] 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.

[0533] 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.

[0534] 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.

[0535] [Second embodiment]

[0536] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0537] 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.

[0538] 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).

[0539] 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.

[0540] 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.

[0541] 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).

[0542] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0543] 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.

[0544] 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.

[0545] 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.

[0546] 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.

[0547] 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."

[0548] The present invention is a system that efficiently handles a user's daily chores by linking a user terminal, a server, AI, and a database. In this system, the user can issue various requests to the AI ​​through the terminal. A specific embodiment of this system is described below.

[0549] System configuration

[0550] User device:

[0551] This is a device that users can operate, such as a smartphone, tablet, or PC. Users can send requests to AI through the device and receive the processing results.

[0552] AI:

[0553] It is an artificial intelligence that is set up for each user, and receives and analyzes the user's request. Based on the analysis results, it sends a request to the server, receives a response from the server, and presents it to the user.

[0554] server:

[0555] It is installed on a network and receives requests from AI. Based on the request, it retrieves the necessary information from the database and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations.

[0556] Database:

[0557] It is an information management system that stores necessary data, such as meeting schedule options, store information, etc. It provides related data in response to requests from the server.

[0558] Processing flow

[0559] The user operates the device to send a request to the AI, such as "Please arrange a meeting for next week." The AI ​​receives this request, analyzes the content, and determines that the meeting date needs to be adjusted. The AI ​​then sends a request to the server along with detailed information such as the list of meeting participants and the desired date.

[0560] The server receives the request and queries the database to obtain possible meeting dates. The server then returns the obtained date options to the AI, which then presents them on the user's device. The user then selects the desired date from the options presented.

[0561] The date selected by the user is sent to the AI ​​via the device, which then sends the selection to the server. The server then coordinates with other related AIs to confirm the final date. This information is then stored in the database again, and the confirmed date is notified to the relevant parties.

[0562] Also, if a user requests "find a nearby cafe," the AI ​​will send a request to the server based on the user's current location and desired conditions. The server will retrieve the relevant store information from the database and respond to the AI. The AI ​​will then display this information on the user's device, allowing the user to check nearby cafes.

[0563] Specific examples

[0564] Meeting scheduling example:

[0565] The user sends a request to the AI ​​from their device saying, "Please arrange a meeting for next week."

[0566] The AI ​​sends a request to the server based on the list of conference participants and the desired date.

[0567] The server retrieves schedule candidates from the database and returns them.

[0568] The AI ​​presents possible dates on the user's device, and the user selects the desired date.

[0569] The server notifies other related AIs of the confirmed schedule and completes the final adjustments.

[0570] Store information search example:

[0571] The user sends a request to the AI ​​from their device to "find a nearby cafe."

[0572] The AI ​​requests the user's current location and desired conditions from the server.

[0573] The server retrieves the relevant store information from the database and responds to the AI.

[0574] AI presents store information on the user's device.

[0575] This invention allows users to automate tedious tasks and perform daily tasks more efficiently and conveniently. This system is expected to significantly reduce users' time and effort, and reduce stress.

[0576] The processing flow will be explained below.

[0577] Meeting Scheduling Process Steps

[0578] Step 1:

[0579] The user operates the terminal and inputs a request to "schedule a meeting for next week."

[0580] Step 2:

[0581] The terminal sends the input request to the user's AI.

[0582] Step 3:

[0583] The user AI analyzes the request and determines that a meeting schedule needs to be adjusted.

[0584] Step 4:

[0585] The user AI sends a request to the server, adding detailed information such as the list of meeting participants and the desired date.

[0586] Step 5:

[0587] The server analyzes the received request and queries the database to obtain the required data.

[0588] Step 6:

[0589] The database searches for possible meeting dates and returns the results to the server.

[0590] Step 7:

[0591] The server compiles the schedule suggestions received from the database and responds to the user AI.

[0592] Step 8:

[0593] The user AI receives the response from the server and presents possible dates on the user's device.

[0594] Step 9:

[0595] The user selects the desired date from the presented date options and performs an operation to confirm the selection.

[0596] Step 10:

[0597] The device sends the date selected by the user to the user AI.

[0598] Step 11:

[0599] The user AI sends the confirmed schedule to the server.

[0600] Step 12:

[0601] The server stores the confirmed schedule information in a database and notifies the AI ​​of other meeting participants of that information.

[0602] Store information search processing steps

[0603] Step 1:

[0604] The user operates the terminal and inputs a request such as "Please find a nearby cafe."

[0605] Step 2:

[0606] The terminal sends the input request to the user's AI.

[0607] Step 3:

[0608] The user AI analyzes the request and determines that a search for a cafe is required.

[0609] Step 4:

[0610] The user AI sends a request to the server along with the user's current location and desired conditions.

[0611] Step 5:

[0612] The server analyzes the received request and queries the database to obtain the required data.

[0613] Step 6:

[0614] The database searches for cafe information that matches the specified conditions and returns the results to the server.

[0615] Step 7:

[0616] The server compiles the cafe information received from the database and responds to the user AI.

[0617] Step 8:

[0618] The user AI receives the response from the server and displays the cafe information on the user's device.

[0619] Step 9:

[0620] The user checks the presented cafe information and decides on a destination if necessary.

[0621] Example 1

[0622] 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."

[0623] In modern business environments and everyday life, users spend a great deal of time and effort on complex tasks and organizing information. There is a particular need for efficient and fast ways to complete everyday tasks, such as scheduling meetings or searching for store information. However, conventional systems often require users to manually search for information or schedule appointments, which can be perceived as inefficient. Therefore, there is a need for systems that allow users to more efficiently complete everyday tasks.

[0624] 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.

[0625] In this invention, the server includes a means for sending a request from a user terminal to an AI model, a means for the AI ​​model to analyze the request content, and a means for sending a request to the server based on the analyzed request content. This allows the user to efficiently process complicated tasks. The server also includes a means for acquiring information from an information management system based on the request, a means for returning the acquired information to the user terminal, and a means for the user terminal to present the returned information to the user. This allows the user to quickly obtain the information they need and saves them time and effort. Furthermore, this system includes a means for the server to acquire specific date options and store information from the information management system based on the request and present that information to the user. This automates the scheduling of meetings and searching for store information, significantly saving the user time and effort.

[0626] A "user terminal" is a device operated by a user, such as a smartphone, tablet, or PC.

[0627] An "AI model" refers to an artificial intelligence system that receives and analyzes user requests and processes the necessary information.

[0628] A "server" is a central processing unit installed on a network that receives requests from an AI model and processes them accordingly.

[0629] A "request" is a request for specific information sent from a user device through an AI model to a server.

[0630] An "information management system" is a system that stores information in a form such as a database and provides it to a server when needed.

[0631] "Analysis" is the procedure by which an AI model understands the request received from a user and takes appropriate action.

[0632] "Provision" refers to the act of a server or information management system obtaining the necessary information and returning it to the user device or AI model.

[0633] "Date options" are options for available dates and times for a meeting or event.

[0634] "Store information" refers to detailed information about a specific store, including its location, business hours, and services offered.

[0635] "Notification" is a means by which the server notifies relevant AI models and users of confirmed information.

[0636] The present invention is a system consisting of a user terminal, a server, an AI model, and an information management system. This system is designed to help users efficiently complete complex daily tasks. Specific embodiments of this system are described below.

[0637] Hardware and software used

[0638] User device:

[0639] A user terminal is a device operated by a user, such as a smartphone, tablet, or PC. Users can use these devices to send requests to the system and receive the processing results.

[0640] AI model:

[0641] The AI ​​model uses artificial intelligence technology for natural language processing, specifically a generative AI model such as OpenAI's GPT-4, to receive and analyze user requests and generate appropriate responses.

[0642] server:

[0643] The server receives requests from the AI ​​model and queries the information management system based on those requests. The server is typically operated using a server instance from Amazon Web Services (AWS) or Google Cloud Platform (GCP).

[0644] Information Management System:

[0645] The information management system uses database technology, such as Oracle Database or MySQL. This system stores the necessary information (such as potential meeting dates and store information) and provides the information in response to server requests.

[0646] Example of the system (meeting schedule adjustment)

[0647] A user device sends a request to the AI ​​model saying, "Please reschedule a meeting for next week." The AI ​​model (GPT-4) that receives this request analyzes the request and determines that a "meeting rescheduling" is necessary. The AI ​​model then sends a request to the server with detailed information such as a list of meeting participants and the desired date.

[0648] The server receives the request and queries an information management system (e.g., a MySQL database) to obtain possible meeting dates. The server returns the obtained date options to the AI ​​model, which then presents them to the user's device. The user selects the desired date from the presented options. This selection is sent back to the AI ​​model via the device, and the AI ​​model sends this selection to the server. The server then works with other related AI models to confirm the final date. This information is then stored back in the information management system, and the confirmed date is notified to the relevant parties.

[0649] Example of the system (store information search)

[0650] A user device sends a request to the AI ​​model saying, "Please find a nearby cafe." The AI ​​model (GPT-4) analyzes the user's current location and desired conditions and generates a request to the server. This request includes specific location information, such as "Shibuya Ward, Tokyo."

[0651] The server receives the request and queries an information management system (e.g., Oracle Database) to obtain the relevant store information. The server then returns the obtained store information to the AI ​​model, which then presents it to the user's device. The user can then make a decision based on the presented cafe information.

[0652] Prompt Sentence Examples

[0653] Here are some example prompts that users can enter into a generative AI model:

[0654] "We'd like to arrange a meeting date for next week. The participants are A, B, and C. Possible dates are: October 1st, October 2nd, and October 3rd."

[0655] "I'm looking for a nearby cafe. I'm currently in Shibuya, Tokyo, and I'd prefer a place with Wi-Fi."

[0656] By using the system of the present invention, users can quickly and efficiently complete tedious daily tasks, which is expected to significantly save users time and effort and reduce stress.

[0657] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0658] Step 1:

[0659] The user enters the request at the terminal.

[0660] Users operate their smartphones or PCs, input requests such as "Please arrange a meeting for next week" or "Please find a nearby cafe," and press the send button.

[0661] Input: User request (request in text format)

[0662] Output: Sending a request from the device to the AI ​​model

[0663] Step 2:

[0664] The device sends the request to the AI ​​model.

[0665] The device receives the text data entered by the user and issues an HTTP request to send it to the AI ​​model via the Internet.

[0666] Input: User request (text data)

[0667] Output: HTTP request to the AI ​​model

[0668] Step 3:

[0669] The AI ​​model analyzes the request.

[0670] The AI ​​model (e.g., GPT-4) analyzes the received request and identifies the required tasks. At this stage, the AI ​​model understands the request and extracts the data needed for the next step (e.g., participant list).

[0671] Input: HTTP request (user requested data)

[0672] Output: Analysis results (task identification and extraction of necessary data)

[0673] Step 4:

[0674] The AI ​​model sends a request to the server.

[0675] Based on the analysis results, the AI ​​model generates a request containing the necessary information and sends it to the server in JSON format.

[0676] Input: Analysis results (identification of tasks and extraction of necessary data)

[0677] Output: Request to server (JSON format)

[0678] Step 5:

[0679] The server receives the request.

[0680] The server receives requests sent by the AI ​​model, logs the request content, and begins processing.

[0681] Input: Request (JSON format)

[0682] Output: Logging and preparing for processing

[0683] Step 6:

[0684] The server queries the information management system.

[0685] Based on the received request, the server queries the information management system (database) using an SQL query.

[0686] Input: Request content

[0687] Output: SQL query executed

[0688] Step 7:

[0689] The information management system provides the information.

[0690] In response to an inquiry from the server, the information management system responds with saved meeting schedule information and store information.

[0691] Input: SQL query

[0692] Output: Required information (meeting date options or store information)

[0693] Step 8:

[0694] The server returns the provided information to the AI ​​model.

[0695] The server processes the information obtained from the information management system and sends it back to the AI ​​model.

[0696] Input: Required information (meeting date options or store information)

[0697] Output: Response to the AI ​​model

[0698] Step 9:

[0699] The AI ​​model presents the results on the user's device.

[0700] The AI ​​model organizes the information it receives in a way that is easy for the user to understand and displays the results on the user's device, for example, "Possible dates for next week's meetings are October 1st, 2nd, and 3rd."

[0701] Input: Response information from the server

[0702] Output: Display of results (formatted information) on the user's device

[0703] Step 10:

[0704] The user makes a selection or confirms the results.

[0705] The user checks the suggested dates and store information and selects the appropriate option. For example, they select "October 2nd" and press the select button.

[0706] Input: Information presented to the user

[0707] Output: User's selection

[0708] Step 11:

[0709] The device sends the selection results to the AI ​​model.

[0710] The device retrieves the user's selection and issues another HTTP request to send it to the AI ​​model.

[0711] Input: User selection result

[0712] Output: HTTP request to the AI ​​model

[0713] Step 12:

[0714] The AI ​​model sends the selection results to the server.

[0715] The AI ​​model sends the user's selection results to the server in JSON format.

[0716] Input: User selection result (HTTP request)

[0717] Output: JSON request to the server

[0718] Step 13:

[0719] The server makes the final adjustments and stores the data in the information management system.

[0720] The server also integrates information from other related AI models to determine the final meeting schedule, which is then stored in the information management system.

[0721] Input: User selections (JSON request) and information from other AI models

[0722] Output: Save the finalized meeting schedule

[0723] Step 14:

[0724] Information management systems will be updated and necessary parties will be notified.

[0725] The updated information is saved in the information management system, and the system sends emails and in-app notifications to relevant parties.

[0726] Input: Finalized meeting dates

[0727] Output: Notification to relevant parties (email, in-app notification)

[0728] (Application example 1)

[0729] 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."

[0730] Conventional autonomous vehicles lack systems that allow users to efficiently handle everyday chores, requiring many tasks to be performed manually while driving, resulting in low convenience. In particular, the wide range of tasks that drivers must perform, such as setting destinations, checking traffic conditions, and managing entertainment, can be cumbersome and may affect safety. Another issue is the insufficient provision of real-time information, making it difficult to respond quickly to user requests.

[0731] 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.

[0732] In this invention, the server includes a means for providing traffic information and entertainment information, a means for setting a destination by voice, and a means for presenting acquired traffic information to the user and providing entertainment information. This allows the user to easily set a destination, check traffic conditions, and manage entertainment in an autonomous vehicle by voice, significantly improving convenience and safety. It also enables real-time information provision, enabling rapid response.

[0733] A "user terminal" is an information device operated by a user, such as a smartphone, tablet, or PC.

[0734] "AI" refers to artificial intelligence that analyzes user requests and sends instructions to the server based on the results.

[0735] A "server" is a device that receives requests from AI over a network, retrieves information from a database, and responds.

[0736] A "database" is an information management system that stores various types of information and provides necessary data based on requests.

[0737] "Traffic information" refers to information about road and traffic conditions when an autonomous vehicle is heading to its destination.

[0738] "Entertainment information" refers to information about content that users can enjoy, including music, videos, news, and the like.

[0739] "Voice-based destination setting means" refers to a method of analyzing a user's voice input and determining the destination of an autonomous vehicle based on the set destination.

[0740] "Real-time information provision" refers to providing information immediately based on the current situation.

[0741] "Request analysis" refers to the process by which AI understands the content of requests received from users and issues appropriate instructions or requests.

[0742] "Means for presenting" refers to a method for directly presenting acquired information to a user, and includes methods such as a display and audio output.

[0743] The present invention provides a system that efficiently processes various tasks within an autonomous vehicle by linking a user terminal, a server, an AI, and a database. In this system, the user can issue requests to the AI ​​through the terminal. Specific embodiments of this system are described below.

[0744] System configuration

[0745] User device:

[0746] An information device operated by a user, such as a smartphone, tablet, or in-car display, allows the user to send requests to AI through the device and receive the processing results.

[0747] AI:

[0748] This is an artificial intelligence that is set up for each user and receives and analyzes the user's request. It sends instructions to the server based on the analysis results, receives responses from the server, and presents them to the user. The AI ​​uses generative AI models to perform speech recognition and natural language analysis.

[0749] server:

[0750] It is installed on a network and receives requests from AI. It retrieves the necessary information from a database based on the request and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations. It uses a cloud server or an on-premise server.

[0751] Database:

[0752] It is an information management system that stores necessary data, such as traffic and entertainment information. It provides related information in response to requests from the server. Database software such as MySQL or PostgreSQL is used.

[0753] Specific examples

[0754] Destination setting example:

[0755] The user sends a voice request from their device to the AI ​​saying, "Set the destination to Shibuya." The AI ​​analyzes the voice and obtains the destination as text. The AI ​​then instructs the server that the destination is Shibuya. The server uses this information to send a traffic information request and obtains traffic conditions from a database. The server returns the obtained traffic information to the AI, which then displays it on the user's device. The user can check the traffic information provided and give instructions such as route changes if necessary.

[0756] Examples of entertainment information provided:

[0757] When a user makes a voice request such as "Play some relaxing music," the AI ​​analyzes the request and sends a request for entertainment information to the server. The server retrieves a music list based on the user's preferences from a database and returns that information to the AI. The AI ​​then presents the retrieved music list to the user's device and automatically plays the music.

[0758] The specific hardware and software used

[0759] Hardware: smartphones, tablets, in-vehicle displays, cloud servers

[0760] Software: Generative AI model, MySQL, PostgreSQL, speech recognition library (speech_recognition), speech synthesis library (pyttsx3)

[0761] Prompt Sentence Examples

[0762] The processing steps when the user says "Set destination to Shibuya" are explained below.

[0763] 1. Analyze the user's voice and obtain the destination as text.

[0764] 2. Based on the acquired destination, traffic conditions are obtained from the traffic information API.

[0765] 3. Notify users when traffic conditions are congested.

[0766] 4. Recommending your preferred entertainment based on your user ID.

[0767] This invention allows users to easily handle complicated tasks by voice even in autonomous vehicles, significantly improving convenience and safety. It also enables real-time information provision, enabling rapid response.

[0768] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0769] Step 1:

[0770] The user operates the device and sends a voice request such as "Set destination to Shibuya." The input is the user's voice, and the device must be equipped with a microphone. The output is voice data. Based on this, the device collects the voice data and sends it to the AI ​​for analysis.

[0771] Step 2:

[0772] The AI ​​analyzes the received voice data. The input is voice data, and the output is textual destination information (in this case, "Shibuya"). The AI ​​uses a generative AI model to perform voice recognition and convert the voice data into text. Specifically, the speech_recognition library is used to convert voice to text.

[0773] Step 3:

[0774] Based on the analyzed destination information, the AI ​​sends a request to the server. The input is the destination information text data "Shibuya," and the output is the request data to the server. The server receives the destination information and begins obtaining traffic information.

[0775] Step 4:

[0776] Based on the request received by the server, traffic information is retrieved from the database. The input is the destination text data "Shibuya" and the output is traffic information data. The server calls the traffic information API and retrieves traffic conditions based on the specified destination.

[0777] Step 5:

[0778] The server returns the traffic information it has acquired to the AI. The input is traffic information data, and the output is response data to the AI. The server then sends the traffic information it has acquired from the database back to the AI.

[0779] Step 6:

[0780] The AI ​​analyzes the traffic information it receives and presents it to the user. The input is traffic information data, and the output is display data on the user's device. Specifically, the AI ​​displays the acquired traffic information on the device in a format that is easy for the user to understand. Traffic conditions are presented to the user using the device's display and audio output functions.

[0781] Step 7:

[0782] Based on the information provided, the user approves or changes the destination by voice. The input is the user's voice command, and the output is the final destination information. The AI ​​again analyzes the user's voice command and determines the final destination.

[0783] Step 8:

[0784] The AI ​​sends the final destination back to the server, which then determines the driving route based on this and reflects it in the navigation system. The input is the final destination information and the output is navigation data. The server works in conjunction with the navigation system to optimize the route of the autonomous vehicle.

[0785] This will allow users to easily set destinations and check traffic information by voice, improving the convenience and safety of self-driving vehicles.

[0786] 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.

[0787] This invention is a system that efficiently handles users' daily chores and provides services optimized based on the user's emotional state by linking a user terminal, server, AI, database, and emotion engine. In this system, the user can issue various requests to the AI ​​through the terminal, and the emotion engine recognizes the user's emotions and optimizes the request content and results.

[0788] System configuration

[0789] User device:

[0790] This is a device that users can operate, such as a smartphone, tablet, or PC. Users can send requests to AI through the device and receive the processing results.

[0791] AI:

[0792] It is an artificial intelligence that is set up for each user, and receives and analyzes the user's request. Based on the analysis results, it sends a request to the server, receives a response from the server, and presents it to the user.

[0793] server:

[0794] It is installed on a network and receives requests from AI. Based on the request, it retrieves the necessary information from the database and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations.

[0795] Database:

[0796] It is an information management system that stores necessary data, such as meeting schedule options, store information, etc. It provides related data in response to requests from the server.

[0797] Emotion Engine:

[0798] This module recognizes and analyzes the user's emotions, judging their emotional state by analyzing voice, facial expressions, text, etc. The emotion engine then optimizes the request content based on the results and provides it to the AI.

[0799] Processing flow

[0800] The user operates their device to send a request to the AI, such as "Please reschedule a meeting next week." At this point, the emotion engine analyzes the user's voice and facial expressions, and if the user is feeling stressed, for example, it provides that emotional state to the AI. Based on this emotional information and the request, the AI ​​determines that the meeting needs to be rescheduled.

[0801] Next, the AI ​​adds detailed information such as a list of meeting participants and desired dates, and also sends a request along with emotional information to the server. The server receives the request and retrieves candidate dates from its database. The server then returns the candidate dates to the AI.

[0802] The AI ​​presents the proposed dates to the user's device, prioritizing the most appropriate ones based on the user's emotional information. The user selects the desired date from the presented options and confirms it. The device then sends the user's selected date to the AI, which then sends the selection to the server to confirm it.

[0803] The server will then work with other related AIs to determine the final schedule, store the information in a database, and notify the relevant parties of the final schedule.

[0804] Similarly, if a user requests, "Please find a nearby cafe," the emotion engine will recognize and analyze the user's emotions and provide them to the AI ​​along with the user's current location and desired conditions. The AI ​​will then send a request to the server, which will retrieve the relevant store information from its database and respond. The AI ​​will then present the retrieved store information on the user's device and provide appropriate information based on the emotional information.

[0805] Specific examples

[0806] Meeting scheduling example:

[0807] The user sends a request to the AI ​​from their device saying, "Please arrange a meeting for next week."

[0808] The emotion engine analyzes the user's voice and facial expressions and determines whether the user is feeling stressed.

[0809] The AI ​​sends a request to the server based on emotional information, the list of meeting participants, and the desired date and time.

[0810] The server retrieves possible dates from the database and responds to the AI.

[0811] The AI ​​presents possible dates to the user's device and prioritizes them appropriately based on emotional information.

[0812] The user selects and confirms the desired date.

[0813] The server stores the confirmed schedule in a database and notifies other related AIs.

[0814] Store information search example:

[0815] The user sends a request to the AI ​​from their device to "find a nearby cafe."

[0816] The emotion engine analyzes the user's emotions and determines, for example, that they want to relax.

[0817] The AI ​​sends a request to the server, adding its current location, desired conditions, and emotional information.

[0818] The server retrieves the relevant cafe information from the database and responds to the AI.

[0819] The AI ​​presents store information to the user's device and prioritizes appropriate cafes based on emotional information.

[0820] The present invention allows users to automate tedious tasks and receive services optimized according to their emotional state, improving their quality of life.

[0821] The processing flow will be explained below.

[0822] Meeting Scheduling Process Steps

[0823] Step 1:

[0824] The user operates the terminal and inputs a request to "schedule a meeting for next week."

[0825] Step 2:

[0826] The device sends the input request to the AI, and at the same time, it also acquires the user's facial expressions and voice data and sends them to the emotion engine.

[0827] Step 3:

[0828] The emotion engine analyzes the user's facial expressions and voice data and determines whether the user is feeling stressed.

[0829] Step 4:

[0830] The emotion engine sends the analysis results to the AI, providing the user's emotional state.

[0831] Step 5:

[0832] Based on the request and emotional information, the user AI determines that the meeting schedule needs to be adjusted and sends a request to the server along with a list of meeting participants and the desired date.

[0833] Step 6:

[0834] The server analyzes the received request and queries the database to obtain the required data.

[0835] Step 7:

[0836] The database searches for possible meeting dates and returns the results to the server.

[0837] Step 8:

[0838] The server compiles the schedule suggestions received from the database and responds to the user AI.

[0839] Step 9:

[0840] The user AI receives the response from the server and presents the suggested dates to the user's device, with the display order optimized based on emotional information.

[0841] Step 10:

[0842] The user selects the desired date from the presented date options and performs an operation to confirm the selection.

[0843] Step 11:

[0844] The device sends the user's selected date to the AI.

[0845] Step 12:

[0846] The user AI sends the confirmed schedule to the server.

[0847] Step 13:

[0848] The server stores the confirmed schedule information in a database and notifies the AI ​​of other meeting participants of that information.

[0849] Store information search processing steps

[0850] Step 1:

[0851] The user operates the terminal and inputs a request such as "Please find a nearby cafe."

[0852] Step 2:

[0853] The device sends the input request to the AI, and at the same time, it also acquires the user's facial expressions and voice data and sends them to the emotion engine.

[0854] Step 3:

[0855] The emotion engine analyzes the user's facial expressions and voice data and determines that the user wants to relax.

[0856] Step 4:

[0857] The emotion engine sends the analysis results to the AI, providing the user's emotional state.

[0858] Step 5:

[0859] Based on the request and emotional information, the user AI sends a request to the server along with the user's current location and desired conditions.

[0860] Step 6:

[0861] The server analyzes the received request and queries the database to obtain the required data.

[0862] Step 7:

[0863] The database searches for cafe information that matches the conditions and returns the results to the server.

[0864] Step 8:

[0865] The server compiles the cafe information received from the database and responds to the user AI.

[0866] Step 9:

[0867] The user AI receives the response from the server and displays the cafe information on the user's device, with the display order optimized based on the user's emotional information.

[0868] Step 10:

[0869] The user checks the presented cafe information and decides where to visit.

[0870] Example 2

[0871] 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."

[0872] Conventional information processing systems provide information uniformly without considering the user's emotional state, making it difficult to provide optimal services tailored to the user's situation. Another problem is that they lack the means to help users efficiently complete complex tasks. This has the drawback of not sufficiently improving the user's quality of life.

[0873] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0874] In this invention, the server includes a means for analyzing the emotional state of the user and providing the result to the artificial intelligence, a means for the artificial intelligence to analyze the request content and send the request to the server, and a means for the server to retrieve information from a database and respond to the user, thereby enabling optimal information provision and task processing according to the user's emotional state.

[0875] A "user terminal" is a device operated by a user, and includes devices such as smartphones, tablets, and personal computers.

[0876] "Artificial intelligence" is a system that analyzes user requests, generates requests based on the results, and sends them to the server.

[0877] A "server" is a central processing unit installed on a network that receives requests from artificial intelligence, retrieves the necessary information from a database, and returns it to the artificial intelligence.

[0878] A "database" is an information management system that can be accessed by a server and stores various types of data.

[0879] The "emotion engine" is a module that analyzes the user's voice, facial expressions, text, etc. to determine their emotional state and provides the results to artificial intelligence.

[0880] "Request" refers to the request or content of the request that a user makes to an artificial intelligence through a user terminal.

[0881] "Request" refers to the analyzed request and request for necessary information that the artificial intelligence sends to the server.

[0882] "Response" refers to response data that the server provides to the user terminal via artificial intelligence with information obtained based on the request.

[0883] MODE FOR CARRYING OUT THE INVENTION

[0884] The present invention is a system that efficiently handles a user's daily chores and provides optimized services based on the user's emotional state by linking a user terminal, artificial intelligence, a server, a database, and an emotion engine.

[0885] Users can issue various requests to the AI ​​through their devices. The emotion engine recognizes the user's emotions and optimizes the request and its results. User devices include smartphones, tablets, and personal computers, and user requests and operations are carried out through these devices.

[0886] User Device

[0887] Users operate their devices to send requests to the AI ​​via voice or text, such as "Please arrange a meeting for next week."

[0888] artificial intelligence

[0889] The AI ​​receives requests from users, analyzes them, and sends requests to the server based on the analysis results. The requests include detailed information such as a list of meeting participants and desired dates.

[0890] server

[0891] The server receives requests from the AI ​​and retrieves the necessary information from the database, such as potential meeting dates or information about nearby cafes, and then returns the retrieved information to the AI.

[0892] Database

[0893] The database is an information management system that stores various data, such as meeting schedule options and store information. The server retrieves relevant data from the database based on a request.

[0894] Emotion Engine

[0895] The emotion engine analyzes the user's voice, facial expressions, text, etc. to determine the user's emotional state. For example, it recognizes whether the user is feeling stressed or relaxed and provides the results to the AI. The emotion engine optimizes the request content based on the user's emotional state and provides feedback to the AI.

[0896] Specific examples

[0897] Meeting schedule adjustment

[0898] When a user requests that a meeting be rescheduled for next week, the emotion engine analyzes the user's voice and facial expressions and determines, for example, that the user is feeling stressed. The AI ​​sends a request to the server based on the emotion information, the list of meeting participants, and the desired date. The server retrieves candidate dates from the database and sends a response to the AI. The AI ​​presents the candidate dates to the user's device, appropriately prioritizing them based on the emotion information. The user selects and confirms the desired date. The server saves the confirmed date in the database and notifies other related AIs.

[0899] Store information search

[0900] When a user requests "find a nearby cafe," the emotion engine analyzes the user's emotions and determines, for example, that they want to relax. The AI ​​attaches their current location, desired conditions, and emotional information and sends a request to the server. The server retrieves relevant cafe information from the database and responds to the AI. The AI ​​then presents store information on the user's device and prioritizes the display of appropriate cafes based on the emotional information.

[0901] Prompt Sentence Examples

[0902] Meeting scheduling prompt:

[0903] plaintext

[0904] "I'd like to reschedule our meeting next week. The list of participants is: [Participant list]. My preferred date is either Monday or Tuesday next week."

[0905] Prompt for store information search:

[0906] plaintext

[0907] "I'd like to find a relaxing cafe nearby. You are currently located at [user location]."

[0908] The system allows users to automate tedious tasks and receive services optimized according to their emotional state, improving their quality of life.

[0909] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0910] Meeting Scheduling Process Steps

[0911] Step 1:

[0912] The user sends a request to the AI ​​to schedule a meeting from their device.

[0913] How it works: The user uses the device's voice input function or keyboard to request, "Please arrange a meeting for next week." The device converts this voice or text into digital data and sends it to the AI.

[0914] Input: User voice and text data

[0915] Output: Digitized request data

[0916] Step 2:

[0917] The emotion engine analyzes the user's emotions.

[0918] How it works: The device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The emotion engine analyzes this data to determine the user's emotional state. The emotion engine generates emotional data such as stress level and sends it to the AI.

[0919] Input: User's facial expression data, voice data

[0920] Output: User's emotional state (e.g., stress level)

[0921] Step 3:

[0922] The AI ​​generates a request based on the request content and emotional information and sends it to the server.

[0923] Specific operation: The AI ​​analyzes the user's request and the emotional information obtained from the emotion engine, and generates request data including a list of meeting participants and the desired schedule. The generated request is then sent to the server.

[0924] Input: User request data, emotional information

[0925] Output: Request data

[0926] Step 4:

[0927] The server retrieves schedule candidates from the database based on the request.

[0928] Specific operation: The server queries the database based on the received request data to obtain possible meeting dates for the next week. For example, possible dates such as "Monday at 3 PM" and "Tuesday at 11 AM" are extracted.

[0929] Input: Request data

[0930] Output: Date candidate data

[0931] Step 5:

[0932] The server returns the obtained schedule options to the AI.

[0933] Specific operation: The server sends the schedule candidate data to the AI. The schedule candidate data is in JSON format, XML format, etc.

[0934] Input: Date candidate data

[0935] Output: Response data

[0936] Step 6:

[0937] The AI ​​presents the response data to the user's device and prioritizes the most suitable dates based on emotional information.

[0938] Specific operation: The AI ​​analyzes the received response data and presents suggested dates on the user's device. If the emotional state is stressful, it prioritizes dates that are less stressful.

[0939] Input: Response data, emotion information

[0940] Output: Date options displayed on the user's device

[0941] Step 7:

[0942] The user selects and confirms the desired date.

[0943] Specific operation: The user selects the desired date from the presented date options and confirms it on the device. The selected date is sent to the AI.

[0944] Input: User selected data

[0945] Output: Confirmed schedule data

[0946] Step 8:

[0947] The AI ​​sends the confirmed schedule to the server and makes the final decision.

[0948] Specific operation: The AI ​​sends the confirmed schedule data to the server, which stores this data in a database and sends notifications to all relevant devices and parties.

[0949] Input: Confirmed schedule data

[0950] Output: Schedule data and notification data stored in the database

[0951] Store information search processing steps

[0952] Step 1:

[0953] The user sends a store information search request to the AI ​​from their device.

[0954] How it works: The user uses the device's voice input function or keyboard to request, "Please find a nearby cafe." The device converts this voice or text into digital data and sends it to the AI.

[0955] Input: User voice and text data

[0956] Output: Digitized request data

[0957] Step 2:

[0958] The emotion engine analyzes the user's emotions.

[0959] Specific operation: The device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The emotion engine analyzes this data and determines the user's emotional state. The emotion engine generates emotion data such as "I want to relax" and sends it to the AI.

[0960] Input: User's facial expression data, voice data

[0961] Output: User's emotional state (e.g., wanting to relax)

[0962] Step 3:

[0963] The AI ​​generates a request based on the request content and emotional information and sends it to the server.

[0964] Specific operation: The AI ​​analyzes the user's request and the emotional information obtained from the emotion engine, and generates request data including the user's current location, desired conditions, and emotional information. The generated request is then sent to the server.

[0965] Input: User request data, emotional information, current location data

[0966] Output: Request data

[0967] Step 4:

[0968] The server retrieves store information from the database based on the request.

[0969] Specific operation: The server queries the database based on the received request data to retrieve information about cafes near the current location. For example, it extracts information such as "Cafe A: Quiet and has Wi-Fi, Cafe B: Spacious seating."

[0970] Input: Request data

[0971] Output: Store information data

[0972] Step 5:

[0973] The server returns the acquired store information to the AI.

[0974] Specific operation: The server sends store information data to the AI. The store information data is in JSON format, XML format, etc.

[0975] Input: Store information data

[0976] Output: Response data

[0977] Step 6:

[0978] The AI ​​presents the response data to the user's device and prioritizes the most suitable stores based on emotional information.

[0979] Specific operation: The AI ​​analyzes the received response data and displays store information on the user's device. If the emotional state is "Relaxed," quiet and comfortable cafes will be displayed first.

[0980] Input: Response data, emotion information

[0981] Output: Store information displayed on the user's device

[0982] This detailed processing flow allows users to efficiently handle daily tasks and receive optimal services according to their emotional state.

[0983] (Application example 2)

[0984] 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."

[0985] Conventional systems provide simple information and process tasks without considering the user's emotional state, resulting in low user satisfaction. It is also difficult to quickly and efficiently provide optimal results to users. Furthermore, there is a lack of support for optimal decision-making based on the user's emotions, even when it comes to specific store information or schedule adjustments.

[0986] The specification processing by the specification 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 the emotion engine to recognize the user's emotions and provide the optimal result; means for the emotion engine to send a request to the server and retrieve specific date candidates from a database; means for presenting date candidates to the user and displaying them preferentially based on emotional information; means for the emotion engine to confirm the user's selection to the server; means for the server to notify other related AIs of the confirmed date; means for the emotion engine to send a request to the server and retrieve specific store information from a database; and means for displaying store information preferentially based on emotional information. This allows the provision of optimal services and information according to the user's emotional state, improving user satisfaction and enabling quick and efficient decision-making.

[0987] A "user terminal" is a device operated by a user, such as a smartphone, tablet, or PC.

[0988] "AI" is an artificial intelligence that is set up for each user and has the ability to receive and analyze user requests.

[0989] A "server" is a device installed on a network that receives requests from AI, retrieves the necessary information from a database, and returns that information to the AI.

[0990] "Database" means an information management system that stores necessary data and provides relevant data upon request.

[0991] The "emotion engine" is a module for recognizing and analyzing the user's emotions, and determines the user's emotional state by analyzing voice, facial expressions, text, etc.

[0992] "Request content" refers to the information and tasks that the user sends to the AI ​​via their device.

[0993] A "request" is a request that an AI sends to a server, and includes the request content and emotional information.

[0994] "Candidate dates" are possible date and time options retrieved from a server or database and used for scheduling.

[0995] "Store information" refers to information about a specific store, including its location, the services and products it offers, and so on.

[0996] "Priority display" refers to displaying the information or options that are most relevant to the user based on emotional information before others.

[0997] This invention is a system that combines user terminals, servers, AI, databases, and emotion engines to provide services optimized based on user emotions, allowing users to efficiently handle everyday chores such as shopping and scheduling.

[0998] The user terminal is a device such as a smartphone, tablet, or PC that provides an interface for users to operate. Users can send various requests to the AI ​​through the terminal.

[0999] The AI ​​receives and analyzes user requests. Based on the analysis results, it sends a request to the server to obtain the necessary information. It also works in conjunction with the emotion engine to provide an optimized response based on the user's emotional state.

[1000] The server receives requests from the AI ​​and retrieves the necessary information from the database. Taking into account the analysis results of the emotion engine, it returns the retrieved information to the AI. The server also oversees the overall operation of the system and manages collaboration between multiple AIs and databases.

[1001] The database stores various data such as possible meeting dates and store information, and provides related data in response to requests from the server.

[1002] The emotion engine recognizes and analyzes emotions through the user's voice, facial expressions, text, etc., and provides the results to the AI, allowing the AI ​​to provide optimal services that take into account the user's emotional state.

[1003] The system process involves a user operating a device to send a request to the AI, such as "Please reschedule a meeting next week." The emotion engine analyzes voice and facial expressions, and if the user is feeling stressed, for example, it provides that emotional state to the AI. Based on the emotional information and the request, the AI ​​determines that the meeting needs to be rescheduled.

[1004] Next, the AI ​​sends detailed information such as the list of meeting participants and desired dates as a request to the server, along with emotional information. The server receives the request and retrieves candidate dates for the meeting by referencing its database. The retrieved candidate dates are returned from the server to the AI. The AI ​​then presents the returned candidate dates on the user's device, prioritizing the more appropriate ones based on the emotional information. The user selects the desired date from the presented candidate dates and performs an operation to confirm it. The server then works with other related AIs to confirm the final date and stores that information in a database. The confirmed date is then notified to the relevant parties.

[1005] In the example of searching for store information, the user can request, "Please find a nearby cafe." The emotion engine analyzes the user's emotions and determines, for example, that they want to relax. The AI ​​sends a request to the server along with their current location, desired conditions, and emotional information, and the server responds by retrieving relevant store information from a database. The AI ​​then presents the retrieved store information on the user's device and prioritizes the display of appropriate cafes based on the emotional information.

[1006] As a concrete example, when a user uses an application in a physical store, they can install a dedicated shopping assistant app on their smartphone. When the user starts the app and inputs that they are looking for relaxation products, the emotion engine analyzes the input data and recognizes that the user is feeling like they want to relax. It then guides the user to the location of relaxation-related products (such as aroma candles and healing music) within the store.

[1007] Example prompts to send to the generative AI model:

[1008] "Analyze the user's emotions and, if they feel like relaxing, recommend the most suitable relaxation products. Also, guide them to the location of the products in the store where the user is currently located."

[1009] In this way, by providing optimal services and information based on the user's emotional state, it is possible to improve user satisfaction and support quick and efficient decision-making.

[1010] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1011] Step 1:

[1012] The user inputs a request into the terminal and sends it.

[1013] The user uses a device such as a smartphone to input the details of their request, such as the product they want to purchase or the store information they want to find, and presses the send button. At this time, voice, facial expression, and text data are collected as input data by the device. The input data includes, for example, the text "I want to relax" and the accompanying facial expression data.

[1014] Step 2:

[1015] The device sends input data to the emotion engine.

[1016] The device sends the collected voice, facial expression, and text data to an emotion engine, which runs on the cloud and analyzes the data to determine the user's emotional state. Based on the input data, the emotion state is identified using voice recognition and image analysis algorithms.

[1017] Step 3:

[1018] The emotion engine analyzes the user's emotions and provides the results to the AI.

[1019] The emotion engine analyzes the input data sent and identifies the user's emotional state (e.g., feeling like they want to relax). The emotion information generated based on the emotion analysis is passed to the AI. At this point, the analysis result is generated as "the user feels like they want to relax."

[1020] Step 4:

[1021] The AI ​​sends a request to the server based on the request content and emotional information.

[1022] The AI ​​combines the user's request with emotional information and sends a request to the server. The request data includes specific details of the request (e.g., "Please find me a product that helps me relax") along with emotional information. The AI ​​determines which category the request falls into and sends it to the server as an appropriate request.

[1023] Step 5:

[1024] The server receives the request and retrieves the information from the database.

[1025] The server receives a request from the AI ​​and references the database based on the request. For example, if the request is for "relaxing products," the server searches the database for relevant product information (e.g., aroma candles, healing music, etc.). The retrieved information includes data such as the product name, category, price, and location within the store.

[1026] Step 6:

[1027] The server returns the information it has obtained to the AI.

[1028] The server organizes the information retrieved from the database and sends it back to the AI. The response data includes prioritized product and store information based on user sentiment, and the AI ​​receives information optimized for the user.

[1029] Step 7:

[1030] The AI ​​sends the results back to the user's device and presents them to the user.

[1031] The AI ​​analyzes the information returned by the server and displays it on the user's device in the optimal order based on the user's emotional state. For example, if the user feels like relaxing, it will prioritize products with a relaxing effect. The information also includes the location of the displayed products and stores.

[1032] Step 8:

[1033] The user makes a selection and confirms it based on the information displayed.

[1034] The user selects the desired product or store from the information displayed on the device and presses the confirm button. The selection and confirmation data are then sent from the device to the AI. The selection data includes information about the product the user ultimately became interested in and the store they wish to use.

[1035] Step 9:

[1036] The AI ​​confirms the user's selection to the server and notifies any related AIs.

[1037] The AI ​​sends the user's selection data to the server and confirms the selection. The server stores the confirmed information in a database and notifies other related AIs, allowing other systems and applications to provide optimal services based on the user's selection.

[1038] Example prompts to send to the generative AI model:

[1039] "Analyze the user's emotions and, if they feel like relaxing, recommend the most suitable relaxation products. Also, guide them to the location of the products in the store where the user is currently located."

[1040] In this way, optimal services and information are provided based on the user's emotional state, improving user satisfaction.

[1041] 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.

[1042] 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.

[1043] 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.

[1044] [Third embodiment]

[1045] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1046] 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.

[1047] 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).

[1048] 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.

[1049] 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.

[1050] 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).

[1051] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1052] 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.

[1053] 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.

[1054] 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.

[1055] 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.

[1056] 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."

[1057] The present invention is a system that efficiently handles a user's daily chores by linking a user terminal, a server, AI, and a database. In this system, the user can issue various requests to the AI ​​through the terminal. A specific embodiment of this system is described below.

[1058] System configuration

[1059] User device:

[1060] This is a device that users can operate, such as a smartphone, tablet, or PC. Users can send requests to AI through the device and receive the processing results.

[1061] AI:

[1062] It is an artificial intelligence that is set up for each user, and receives and analyzes the user's request. Based on the analysis results, it sends a request to the server, receives a response from the server, and presents it to the user.

[1063] server:

[1064] It is installed on a network and receives requests from AI. Based on the request, it retrieves the necessary information from the database and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations.

[1065] Database:

[1066] It is an information management system that stores necessary data, such as meeting schedule options, store information, etc. It provides related data in response to requests from the server.

[1067] Processing flow

[1068] The user operates the device to send a request to the AI, such as "Please arrange a meeting for next week." The AI ​​receives this request, analyzes the content, and determines that the meeting date needs to be adjusted. The AI ​​then sends a request to the server along with detailed information such as the list of meeting participants and the desired date.

[1069] The server receives the request and queries the database to obtain possible meeting dates. The server then returns the obtained date options to the AI, which then presents them on the user's device. The user then selects the desired date from the options presented.

[1070] The date selected by the user is sent to the AI ​​via the device, which then sends the selection to the server. The server then coordinates with other related AIs to confirm the final date. This information is then stored in the database again, and the confirmed date is notified to the relevant parties.

[1071] Also, if a user requests "find a nearby cafe," the AI ​​will send a request to the server based on the user's current location and desired conditions. The server will retrieve the relevant store information from the database and respond to the AI. The AI ​​will then display this information on the user's device, allowing the user to check nearby cafes.

[1072] Specific examples

[1073] Meeting scheduling example:

[1074] The user sends a request to the AI ​​from their device saying, "Please arrange a meeting for next week."

[1075] The AI ​​sends a request to the server based on the list of conference participants and the desired date.

[1076] The server retrieves schedule candidates from the database and returns them.

[1077] The AI ​​presents possible dates on the user's device, and the user selects the desired date.

[1078] The server notifies other related AIs of the confirmed schedule and completes the final adjustments.

[1079] Store information search example:

[1080] The user sends a request to the AI ​​from their device to "find a nearby cafe."

[1081] The AI ​​requests the user's current location and desired conditions from the server.

[1082] The server retrieves the relevant store information from the database and responds to the AI.

[1083] AI presents store information on the user's device.

[1084] This invention allows users to automate tedious tasks and perform daily tasks more efficiently and conveniently. This system is expected to significantly reduce users' time and effort, and reduce stress.

[1085] The processing flow will be explained below.

[1086] Meeting Scheduling Process Steps

[1087] Step 1:

[1088] The user operates the terminal and inputs a request to "schedule a meeting for next week."

[1089] Step 2:

[1090] The terminal sends the input request to the user's AI.

[1091] Step 3:

[1092] The user AI analyzes the request and determines that a meeting schedule needs to be adjusted.

[1093] Step 4:

[1094] The user AI sends a request to the server, adding detailed information such as the list of meeting participants and the desired date.

[1095] Step 5:

[1096] The server analyzes the received request and queries the database to obtain the required data.

[1097] Step 6:

[1098] The database searches for possible meeting dates and returns the results to the server.

[1099] Step 7:

[1100] The server compiles the schedule suggestions received from the database and responds to the user AI.

[1101] Step 8:

[1102] The user AI receives the response from the server and presents possible dates on the user's device.

[1103] Step 9:

[1104] The user selects the desired date from the presented date options and performs an operation to confirm the selection.

[1105] Step 10:

[1106] The device sends the date selected by the user to the user AI.

[1107] Step 11:

[1108] The user AI sends the confirmed schedule to the server.

[1109] Step 12:

[1110] The server stores the confirmed schedule information in a database and notifies the AI ​​of other meeting participants of that information.

[1111] Store information search processing steps

[1112] Step 1:

[1113] The user operates the terminal and inputs a request such as "Please find a nearby cafe."

[1114] Step 2:

[1115] The terminal sends the input request to the user's AI.

[1116] Step 3:

[1117] The user AI analyzes the request and determines that a search for a cafe is required.

[1118] Step 4:

[1119] The user AI sends a request to the server along with the user's current location and desired conditions.

[1120] Step 5:

[1121] The server analyzes the received request and queries the database to obtain the required data.

[1122] Step 6:

[1123] The database searches for cafe information that matches the specified conditions and returns the results to the server.

[1124] Step 7:

[1125] The server compiles the cafe information received from the database and responds to the user AI.

[1126] Step 8:

[1127] The user AI receives the response from the server and displays the cafe information on the user's device.

[1128] Step 9:

[1129] The user checks the presented cafe information and decides on a destination if necessary.

[1130] Example 1

[1131] 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."

[1132] In modern business environments and everyday life, users spend a great deal of time and effort on complex tasks and organizing information. There is a particular need for efficient and fast ways to complete everyday tasks, such as scheduling meetings or searching for store information. However, conventional systems often require users to manually search for information or schedule appointments, which can be perceived as inefficient. Therefore, there is a need for systems that allow users to more efficiently complete everyday tasks.

[1133] 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.

[1134] In this invention, the server includes a means for sending a request from a user terminal to an AI model, a means for the AI ​​model to analyze the request content, and a means for sending a request to the server based on the analyzed request content. This allows the user to efficiently process complicated tasks. The server also includes a means for acquiring information from an information management system based on the request, a means for returning the acquired information to the user terminal, and a means for the user terminal to present the returned information to the user. This allows the user to quickly obtain the information they need and saves them time and effort. Furthermore, this system includes a means for the server to acquire specific date options and store information from the information management system based on the request and present that information to the user. This automates the scheduling of meetings and searching for store information, significantly saving the user time and effort.

[1135] A "user terminal" is a device operated by a user, such as a smartphone, tablet, or PC.

[1136] An "AI model" refers to an artificial intelligence system that receives and analyzes user requests and processes the necessary information.

[1137] A "server" is a central processing unit installed on a network that receives requests from an AI model and processes them accordingly.

[1138] A "request" is a request for specific information sent from a user device through an AI model to a server.

[1139] An "information management system" is a system that stores information in a form such as a database and provides it to a server when needed.

[1140] "Analysis" is the procedure by which an AI model understands the request received from a user and takes appropriate action.

[1141] "Provision" refers to the act of a server or information management system obtaining the necessary information and returning it to the user device or AI model.

[1142] "Date options" are options for available dates and times for a meeting or event.

[1143] "Store information" refers to detailed information about a specific store, including its location, business hours, and services offered.

[1144] "Notification" is a means by which the server notifies relevant AI models and users of confirmed information.

[1145] The present invention is a system consisting of a user terminal, a server, an AI model, and an information management system. This system is designed to help users efficiently complete complex daily tasks. Specific embodiments of this system are described below.

[1146] Hardware and software used

[1147] User device:

[1148] A user terminal is a device operated by a user, such as a smartphone, tablet, or PC. Users can use these devices to send requests to the system and receive the processing results.

[1149] AI model:

[1150] The AI ​​model uses artificial intelligence technology for natural language processing, specifically a generative AI model such as OpenAI's GPT-4, to receive and analyze user requests and generate appropriate responses.

[1151] server:

[1152] The server receives requests from the AI ​​model and queries the information management system based on those requests. The server is typically operated using a server instance from Amazon Web Services (AWS) or Google Cloud Platform (GCP).

[1153] Information Management System:

[1154] The information management system uses database technology, such as Oracle Database or MySQL. This system stores the necessary information (such as potential meeting dates and store information) and provides the information in response to server requests.

[1155] Example of the system (meeting schedule adjustment)

[1156] A user device sends a request to the AI ​​model saying, "Please reschedule a meeting for next week." The AI ​​model (GPT-4) that receives this request analyzes the request and determines that a "meeting rescheduling" is necessary. The AI ​​model then sends a request to the server with detailed information such as a list of meeting participants and the desired date.

[1157] The server receives the request and queries an information management system (e.g., a MySQL database) to obtain possible meeting dates. The server returns the obtained date options to the AI ​​model, which then presents them to the user's device. The user selects the desired date from the presented options. This selection is sent back to the AI ​​model via the device, and the AI ​​model sends this selection to the server. The server then works with other related AI models to confirm the final date. This information is then stored back in the information management system, and the confirmed date is notified to the relevant parties.

[1158] Example of the system (store information search)

[1159] A user device sends a request to the AI ​​model saying, "Please find a nearby cafe." The AI ​​model (GPT-4) analyzes the user's current location and desired conditions and generates a request to the server. This request includes specific location information, such as "Shibuya Ward, Tokyo."

[1160] The server receives the request and queries an information management system (e.g., Oracle Database) to obtain the relevant store information. The server then returns the obtained store information to the AI ​​model, which then presents it to the user's device. The user can then make a decision based on the presented cafe information.

[1161] Prompt Sentence Examples

[1162] Here are some example prompts that users can enter into a generative AI model:

[1163] "We'd like to arrange a meeting date for next week. The participants are A, B, and C. Possible dates are: October 1st, October 2nd, and October 3rd."

[1164] "I'm looking for a nearby cafe. I'm currently in Shibuya, Tokyo, and I'd prefer a place with Wi-Fi."

[1165] By using the system of the present invention, users can quickly and efficiently complete tedious daily tasks, which is expected to significantly save users time and effort and reduce stress.

[1166] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1167] Step 1:

[1168] The user enters the request at the terminal.

[1169] Users operate their smartphones or PCs, input requests such as "Please arrange a meeting for next week" or "Please find a nearby cafe," and press the send button.

[1170] Input: User request (request in text format)

[1171] Output: Sending a request from the device to the AI ​​model

[1172] Step 2:

[1173] The device sends the request to the AI ​​model.

[1174] The device receives the text data entered by the user and issues an HTTP request to send it to the AI ​​model via the Internet.

[1175] Input: User request (text data)

[1176] Output: HTTP request to the AI ​​model

[1177] Step 3:

[1178] The AI ​​model analyzes the request.

[1179] The AI ​​model (e.g., GPT-4) analyzes the received request and identifies the required tasks. At this stage, the AI ​​model understands the request and extracts the data needed for the next step (e.g., participant list).

[1180] Input: HTTP request (user requested data)

[1181] Output: Analysis results (task identification and extraction of necessary data)

[1182] Step 4:

[1183] The AI ​​model sends a request to the server.

[1184] Based on the analysis results, the AI ​​model generates a request containing the necessary information and sends it to the server in JSON format.

[1185] Input: Analysis results (identification of tasks and extraction of necessary data)

[1186] Output: Request to server (JSON format)

[1187] Step 5:

[1188] The server receives the request.

[1189] The server receives requests sent by the AI ​​model, logs the request content, and begins processing.

[1190] Input: Request (JSON format)

[1191] Output: Logging and preparing for processing

[1192] Step 6:

[1193] The server queries the information management system.

[1194] Based on the received request, the server queries the information management system (database) using an SQL query.

[1195] Input: Request content

[1196] Output: SQL query executed

[1197] Step 7:

[1198] The information management system provides the information.

[1199] In response to an inquiry from the server, the information management system responds with saved meeting schedule information and store information.

[1200] Input: SQL query

[1201] Output: Required information (meeting date options or store information)

[1202] Step 8:

[1203] The server returns the provided information to the AI ​​model.

[1204] The server processes the information obtained from the information management system and sends it back to the AI ​​model.

[1205] Input: Required information (meeting date options or store information)

[1206] Output: Response to the AI ​​model

[1207] Step 9:

[1208] The AI ​​model presents the results on the user's device.

[1209] The AI ​​model organizes the information it receives in a way that is easy for the user to understand and displays the results on the user's device, for example, "Possible dates for next week's meetings are October 1st, 2nd, and 3rd."

[1210] Input: Response information from the server

[1211] Output: Display of results (formatted information) on the user's device

[1212] Step 10:

[1213] The user makes a selection or confirms the results.

[1214] The user checks the suggested dates and store information and selects the appropriate option. For example, they select "October 2nd" and press the select button.

[1215] Input: Information presented to the user

[1216] Output: User's selection

[1217] Step 11:

[1218] The device sends the selection results to the AI ​​model.

[1219] The device retrieves the user's selection and issues another HTTP request to send it to the AI ​​model.

[1220] Input: User selection result

[1221] Output: HTTP request to the AI ​​model

[1222] Step 12:

[1223] The AI ​​model sends the selection results to the server.

[1224] The AI ​​model sends the user's selection results to the server in JSON format.

[1225] Input: User selection result (HTTP request)

[1226] Output: JSON request to the server

[1227] Step 13:

[1228] The server makes the final adjustments and stores the data in the information management system.

[1229] The server also integrates information from other related AI models to determine the final meeting schedule, which is then stored in the information management system.

[1230] Input: User selections (JSON request) and information from other AI models

[1231] Output: Save the finalized meeting schedule

[1232] Step 14:

[1233] Information management systems will be updated and necessary parties will be notified.

[1234] The updated information is saved in the information management system, and the system sends emails and in-app notifications to relevant parties.

[1235] Input: Finalized meeting dates

[1236] Output: Notification to relevant parties (email, in-app notification)

[1237] (Application example 1)

[1238] 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."

[1239] Conventional autonomous vehicles lack systems that allow users to efficiently handle everyday chores, requiring many tasks to be performed manually while driving, resulting in low convenience. In particular, the wide range of tasks that drivers must perform, such as setting destinations, checking traffic conditions, and managing entertainment, can be cumbersome and may affect safety. Another issue is the insufficient provision of real-time information, making it difficult to respond quickly to user requests.

[1240] 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.

[1241] In this invention, the server includes a means for providing traffic information and entertainment information, a means for setting a destination by voice, and a means for presenting acquired traffic information to the user and providing entertainment information. This allows the user to easily set a destination, check traffic conditions, and manage entertainment in an autonomous vehicle by voice, significantly improving convenience and safety. It also enables real-time information provision, enabling rapid response.

[1242] A "user terminal" is an information device operated by a user, such as a smartphone, tablet, or PC.

[1243] "AI" refers to artificial intelligence that analyzes user requests and sends instructions to the server based on the results.

[1244] A "server" is a device that receives requests from AI over a network, retrieves information from a database, and responds.

[1245] A "database" is an information management system that stores various types of information and provides necessary data based on requests.

[1246] "Traffic information" refers to information about road and traffic conditions when an autonomous vehicle is heading to its destination.

[1247] "Entertainment information" refers to information about content that users can enjoy, including music, videos, news, and the like.

[1248] "Voice-based destination setting means" refers to a method of analyzing a user's voice input and determining the destination of an autonomous vehicle based on the set destination.

[1249] "Real-time information provision" refers to providing information immediately based on the current situation.

[1250] "Request analysis" refers to the process by which AI understands the content of requests received from users and issues appropriate instructions or requests.

[1251] "Means for presenting" refers to a method for directly presenting acquired information to a user, and includes methods such as a display and audio output.

[1252] The present invention provides a system that efficiently processes various tasks within an autonomous vehicle by linking a user terminal, a server, an AI, and a database. In this system, the user can issue requests to the AI ​​through the terminal. Specific embodiments of this system are described below.

[1253] System configuration

[1254] User device:

[1255] An information device operated by a user, such as a smartphone, tablet, or in-car display, allows the user to send requests to AI through the device and receive the processing results.

[1256] AI:

[1257] This is an artificial intelligence that is set up for each user and receives and analyzes the user's request. It sends instructions to the server based on the analysis results, receives responses from the server, and presents them to the user. The AI ​​uses generative AI models to perform speech recognition and natural language analysis.

[1258] server:

[1259] It is installed on a network and receives requests from AI. It retrieves the necessary information from a database based on the request and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations. It uses a cloud server or an on-premise server.

[1260] Database:

[1261] It is an information management system that stores necessary data, such as traffic and entertainment information. It provides related information in response to requests from the server. Database software such as MySQL or PostgreSQL is used.

[1262] Specific examples

[1263] Destination setting example:

[1264] The user sends a voice request from their device to the AI ​​saying, "Set the destination to Shibuya." The AI ​​analyzes the voice and obtains the destination as text. The AI ​​then instructs the server that the destination is Shibuya. The server uses this information to send a traffic information request and obtains traffic conditions from a database. The server returns the obtained traffic information to the AI, which then displays it on the user's device. The user can check the traffic information provided and give instructions such as route changes if necessary.

[1265] Examples of entertainment information provided:

[1266] When a user makes a voice request such as "Play some relaxing music," the AI ​​analyzes the request and sends a request for entertainment information to the server. The server retrieves a music list based on the user's preferences from a database and returns that information to the AI. The AI ​​then presents the retrieved music list to the user's device and automatically plays the music.

[1267] The specific hardware and software used

[1268] Hardware: smartphones, tablets, in-vehicle displays, cloud servers

[1269] Software: Generative AI model, MySQL, PostgreSQL, speech recognition library (speech_recognition), speech synthesis library (pyttsx3)

[1270] Prompt Sentence Examples

[1271] The processing steps when the user says "Set destination to Shibuya" are explained below.

[1272] 1. Analyze the user's voice and obtain the destination as text.

[1273] 2. Based on the acquired destination, traffic conditions are obtained from the traffic information API.

[1274] 3. Notify users when traffic conditions are congested.

[1275] 4. Recommending your preferred entertainment based on your user ID.

[1276] This invention allows users to easily handle complicated tasks by voice even in autonomous vehicles, significantly improving convenience and safety. It also enables real-time information provision, enabling rapid response.

[1277] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1278] Step 1:

[1279] The user operates the device and sends a voice request such as "Set destination to Shibuya." The input is the user's voice, and the device must be equipped with a microphone. The output is voice data. Based on this, the device collects the voice data and sends it to the AI ​​for analysis.

[1280] Step 2:

[1281] The AI ​​analyzes the received voice data. The input is voice data, and the output is textual destination information (in this case, "Shibuya"). The AI ​​uses a generative AI model to perform voice recognition and convert the voice data into text. Specifically, the speech_recognition library is used to convert voice to text.

[1282] Step 3:

[1283] Based on the analyzed destination information, the AI ​​sends a request to the server. The input is the destination information text data "Shibuya," and the output is the request data to the server. The server receives the destination information and begins obtaining traffic information.

[1284] Step 4:

[1285] Based on the request received by the server, traffic information is retrieved from the database. The input is the destination text data "Shibuya" and the output is traffic information data. The server calls the traffic information API and retrieves traffic conditions based on the specified destination.

[1286] Step 5:

[1287] The server returns the traffic information it has acquired to the AI. The input is traffic information data, and the output is response data to the AI. The server then sends the traffic information it has acquired from the database back to the AI.

[1288] Step 6:

[1289] The AI ​​analyzes the traffic information it receives and presents it to the user. The input is traffic information data, and the output is display data on the user's device. Specifically, the AI ​​displays the acquired traffic information on the device in a format that is easy for the user to understand. Traffic conditions are presented to the user using the device's display and audio output functions.

[1290] Step 7:

[1291] Based on the information provided, the user approves or changes the destination by voice. The input is the user's voice command, and the output is the final destination information. The AI ​​again analyzes the user's voice command and determines the final destination.

[1292] Step 8:

[1293] The AI ​​sends the final destination back to the server, which then determines the driving route based on this and reflects it in the navigation system. The input is the final destination information and the output is navigation data. The server works in conjunction with the navigation system to optimize the route of the autonomous vehicle.

[1294] This will allow users to easily set destinations and check traffic information by voice, improving the convenience and safety of self-driving vehicles.

[1295] 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.

[1296] This invention is a system that efficiently handles users' daily chores and provides services optimized based on the user's emotional state by linking a user terminal, server, AI, database, and emotion engine. In this system, the user can issue various requests to the AI ​​through the terminal, and the emotion engine recognizes the user's emotions and optimizes the request content and results.

[1297] System configuration

[1298] User device:

[1299] This is a device that users can operate, such as a smartphone, tablet, or PC. Users can send requests to AI through the device and receive the processing results.

[1300] AI:

[1301] It is an artificial intelligence that is set up for each user, and receives and analyzes the user's request. Based on the analysis results, it sends a request to the server, receives a response from the server, and presents it to the user.

[1302] server:

[1303] It is installed on a network and receives requests from AI. Based on the request, it retrieves the necessary information from the database and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations.

[1304] Database:

[1305] It is an information management system that stores necessary data, such as meeting schedule options, store information, etc. It provides related data in response to requests from the server.

[1306] Emotion Engine:

[1307] This module recognizes and analyzes the user's emotions, judging their emotional state by analyzing voice, facial expressions, text, etc. The emotion engine then optimizes the request content based on the results and provides it to the AI.

[1308] Processing flow

[1309] The user operates their device to send a request to the AI, such as "Please reschedule a meeting next week." At this point, the emotion engine analyzes the user's voice and facial expressions, and if the user is feeling stressed, for example, it provides that emotional state to the AI. Based on this emotional information and the request, the AI ​​determines that the meeting needs to be rescheduled.

[1310] Next, the AI ​​adds detailed information such as a list of meeting participants and desired dates, and also sends a request along with emotional information to the server. The server receives the request and retrieves candidate dates from its database. The server then returns the candidate dates to the AI.

[1311] The AI ​​presents the proposed dates to the user's device, prioritizing the most appropriate ones based on the user's emotional information. The user selects the desired date from the presented options and confirms it. The device then sends the user's selected date to the AI, which then sends the selection to the server to confirm it.

[1312] The server will then work with other related AIs to determine the final schedule, store the information in a database, and notify the relevant parties of the final schedule.

[1313] Similarly, if a user requests, "Please find a nearby cafe," the emotion engine will recognize and analyze the user's emotions and provide them to the AI ​​along with the user's current location and desired conditions. The AI ​​will then send a request to the server, which will retrieve the relevant store information from its database and respond. The AI ​​will then present the retrieved store information on the user's device and provide appropriate information based on the emotional information.

[1314] Specific examples

[1315] Meeting scheduling example:

[1316] The user sends a request to the AI ​​from their device saying, "Please arrange a meeting for next week."

[1317] The emotion engine analyzes the user's voice and facial expressions and determines whether the user is feeling stressed.

[1318] The AI ​​sends a request to the server based on emotional information, the list of meeting participants, and the desired date and time.

[1319] The server retrieves possible dates from the database and responds to the AI.

[1320] The AI ​​presents possible dates to the user's device and prioritizes them appropriately based on emotional information.

[1321] The user selects and confirms the desired date.

[1322] The server stores the confirmed schedule in a database and notifies other related AIs.

[1323] Store information search example:

[1324] The user sends a request to the AI ​​from their device to "find a nearby cafe."

[1325] The emotion engine analyzes the user's emotions and determines, for example, that they want to relax.

[1326] The AI ​​sends a request to the server, adding its current location, desired conditions, and emotional information.

[1327] The server retrieves the relevant cafe information from the database and responds to the AI.

[1328] The AI ​​presents store information to the user's device and prioritizes appropriate cafes based on emotional information.

[1329] The present invention allows users to automate tedious tasks and receive services optimized according to their emotional state, improving their quality of life.

[1330] The processing flow will be explained below.

[1331] Meeting Scheduling Process Steps

[1332] Step 1:

[1333] The user operates the terminal and inputs a request to "schedule a meeting for next week."

[1334] Step 2:

[1335] The device sends the input request to the AI, and at the same time, it also acquires the user's facial expressions and voice data and sends them to the emotion engine.

[1336] Step 3:

[1337] The emotion engine analyzes the user's facial expressions and voice data and determines whether the user is feeling stressed.

[1338] Step 4:

[1339] The emotion engine sends the analysis results to the AI, providing the user's emotional state.

[1340] Step 5:

[1341] Based on the request and emotional information, the user AI determines that the meeting schedule needs to be adjusted and sends a request to the server along with a list of meeting participants and the desired date.

[1342] Step 6:

[1343] The server analyzes the received request and queries the database to obtain the required data.

[1344] Step 7:

[1345] The database searches for possible meeting dates and returns the results to the server.

[1346] Step 8:

[1347] The server compiles the schedule suggestions received from the database and responds to the user AI.

[1348] Step 9:

[1349] The user AI receives the response from the server and presents the suggested dates to the user's device, with the display order optimized based on emotional information.

[1350] Step 10:

[1351] The user selects the desired date from the presented date options and performs an operation to confirm the selection.

[1352] Step 11:

[1353] The device sends the user's selected date to the AI.

[1354] Step 12:

[1355] The user AI sends the confirmed schedule to the server.

[1356] Step 13:

[1357] The server stores the confirmed schedule information in a database and notifies the AI ​​of other meeting participants of that information.

[1358] Store information search processing steps

[1359] Step 1:

[1360] The user operates the terminal and inputs a request such as "Please find a nearby cafe."

[1361] Step 2:

[1362] The device sends the input request to the AI, and at the same time, it also acquires the user's facial expressions and voice data and sends them to the emotion engine.

[1363] Step 3:

[1364] The emotion engine analyzes the user's facial expressions and voice data and determines that the user wants to relax.

[1365] Step 4:

[1366] The emotion engine sends the analysis results to the AI, providing the user's emotional state.

[1367] Step 5:

[1368] Based on the request and emotional information, the user AI sends a request to the server along with the user's current location and desired conditions.

[1369] Step 6:

[1370] The server analyzes the received request and queries the database to obtain the required data.

[1371] Step 7:

[1372] The database searches for cafe information that matches the conditions and returns the results to the server.

[1373] Step 8:

[1374] The server compiles the cafe information received from the database and responds to the user AI.

[1375] Step 9:

[1376] The user AI receives the response from the server and displays the cafe information on the user's device, with the display order optimized based on the user's emotional information.

[1377] Step 10:

[1378] The user checks the presented cafe information and decides where to visit.

[1379] Example 2

[1380] 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."

[1381] Conventional information processing systems provide information uniformly without considering the user's emotional state, making it difficult to provide optimal services tailored to the user's situation. Another problem is that they lack the means to help users efficiently complete complex tasks. This has the drawback of not sufficiently improving the user's quality of life.

[1382] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1383] In this invention, the server includes a means for analyzing the emotional state of the user and providing the result to the artificial intelligence, a means for the artificial intelligence to analyze the request content and send the request to the server, and a means for the server to retrieve information from a database and respond to the user, thereby enabling optimal information provision and task processing according to the user's emotional state.

[1384] A "user terminal" is a device operated by a user, and includes devices such as smartphones, tablets, and personal computers.

[1385] "Artificial intelligence" is a system that analyzes user requests, generates requests based on the results, and sends them to the server.

[1386] A "server" is a central processing unit installed on a network that receives requests from artificial intelligence, retrieves the necessary information from a database, and returns it to the artificial intelligence.

[1387] A "database" is an information management system that can be accessed by a server and stores various types of data.

[1388] The "emotion engine" is a module that analyzes the user's voice, facial expressions, text, etc. to determine their emotional state and provides the results to artificial intelligence.

[1389] "Request" refers to the request or content of the request that a user makes to an artificial intelligence through a user terminal.

[1390] "Request" refers to the analyzed request and request for necessary information that the artificial intelligence sends to the server.

[1391] "Response" refers to response data that the server provides to the user terminal via artificial intelligence with information obtained based on the request.

[1392] MODE FOR CARRYING OUT THE INVENTION

[1393] The present invention is a system that efficiently handles a user's daily chores and provides optimized services based on the user's emotional state by linking a user terminal, artificial intelligence, a server, a database, and an emotion engine.

[1394] Users can issue various requests to the AI ​​through their devices. The emotion engine recognizes the user's emotions and optimizes the request and its results. User devices include smartphones, tablets, and personal computers, and user requests and operations are carried out through these devices.

[1395] User Device

[1396] Users operate their devices to send requests to the AI ​​via voice or text, such as "Please arrange a meeting for next week."

[1397] artificial intelligence

[1398] The AI ​​receives requests from users, analyzes them, and sends requests to the server based on the analysis results. The requests include detailed information such as a list of meeting participants and desired dates.

[1399] server

[1400] The server receives requests from the AI ​​and retrieves the necessary information from the database, such as potential meeting dates or information about nearby cafes, and then returns the retrieved information to the AI.

[1401] Database

[1402] The database is an information management system that stores various data, such as meeting schedule options and store information. The server retrieves relevant data from the database based on a request.

[1403] Emotion Engine

[1404] The emotion engine analyzes the user's voice, facial expressions, text, etc. to determine the user's emotional state. For example, it recognizes whether the user is feeling stressed or relaxed and provides the results to the AI. The emotion engine optimizes the request content based on the user's emotional state and provides feedback to the AI.

[1405] Specific examples

[1406] Meeting schedule adjustment

[1407] When a user requests that a meeting be rescheduled for next week, the emotion engine analyzes the user's voice and facial expressions and determines, for example, that the user is feeling stressed. The AI ​​sends a request to the server based on the emotion information, the list of meeting participants, and the desired date. The server retrieves candidate dates from the database and sends a response to the AI. The AI ​​presents the candidate dates to the user's device, appropriately prioritizing them based on the emotion information. The user selects and confirms the desired date. The server saves the confirmed date in the database and notifies other related AIs.

[1408] Store information search

[1409] When a user requests "find a nearby cafe," the emotion engine analyzes the user's emotions and determines, for example, that they want to relax. The AI ​​attaches their current location, desired conditions, and emotional information and sends a request to the server. The server retrieves relevant cafe information from the database and responds to the AI. The AI ​​then presents store information on the user's device and prioritizes the display of appropriate cafes based on the emotional information.

[1410] Prompt Sentence Examples

[1411] Meeting scheduling prompt:

[1412] plaintext

[1413] "I'd like to reschedule our meeting next week. The list of participants is: [Participant list]. My preferred date is either Monday or Tuesday next week."

[1414] Prompt for store information search:

[1415] plaintext

[1416] "I'd like to find a relaxing cafe nearby. You are currently located at [user location]."

[1417] The system allows users to automate tedious tasks and receive services optimized according to their emotional state, improving their quality of life.

[1418] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1419] Meeting Scheduling Process Steps

[1420] Step 1:

[1421] The user sends a request to the AI ​​to schedule a meeting from their device.

[1422] How it works: The user uses the device's voice input function or keyboard to request, "Please arrange a meeting for next week." The device converts this voice or text into digital data and sends it to the AI.

[1423] Input: User voice and text data

[1424] Output: Digitized request data

[1425] Step 2:

[1426] The emotion engine analyzes the user's emotions.

[1427] How it works: The device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The emotion engine analyzes this data to determine the user's emotional state. The emotion engine generates emotional data such as stress level and sends it to the AI.

[1428] Input: User's facial expression data, voice data

[1429] Output: User's emotional state (e.g., stress level)

[1430] Step 3:

[1431] The AI ​​generates a request based on the request content and emotional information and sends it to the server.

[1432] Specific operation: The AI ​​analyzes the user's request and the emotional information obtained from the emotion engine, and generates request data including a list of meeting participants and the desired schedule. The generated request is then sent to the server.

[1433] Input: User request data, emotional information

[1434] Output: Request data

[1435] Step 4:

[1436] The server retrieves schedule candidates from the database based on the request.

[1437] Specific operation: The server queries the database based on the received request data to obtain possible meeting dates for the next week. For example, possible dates such as "Monday at 3 PM" and "Tuesday at 11 AM" are extracted.

[1438] Input: Request data

[1439] Output: Date candidate data

[1440] Step 5:

[1441] The server returns the obtained schedule options to the AI.

[1442] Specific operation: The server sends the schedule candidate data to the AI. The schedule candidate data is in JSON format, XML format, etc.

[1443] Input: Date candidate data

[1444] Output: Response data

[1445] Step 6:

[1446] The AI ​​presents the response data to the user's device and prioritizes the most suitable dates based on emotional information.

[1447] Specific operation: The AI ​​analyzes the received response data and presents suggested dates on the user's device. If the emotional state is stressful, it prioritizes dates that are less stressful.

[1448] Input: Response data, emotion information

[1449] Output: Date options displayed on the user's device

[1450] Step 7:

[1451] The user selects and confirms the desired date.

[1452] Specific operation: The user selects the desired date from the presented date options and confirms it on the device. The selected date is sent to the AI.

[1453] Input: User selected data

[1454] Output: Confirmed schedule data

[1455] Step 8:

[1456] The AI ​​sends the confirmed schedule to the server and makes the final decision.

[1457] Specific operation: The AI ​​sends the confirmed schedule data to the server, which stores this data in a database and sends notifications to all relevant devices and parties.

[1458] Input: Confirmed schedule data

[1459] Output: Schedule data and notification data stored in the database

[1460] Store information search processing steps

[1461] Step 1:

[1462] The user sends a store information search request to the AI ​​from their device.

[1463] How it works: The user uses the device's voice input function or keyboard to request, "Please find a nearby cafe." The device converts this voice or text into digital data and sends it to the AI.

[1464] Input: User voice and text data

[1465] Output: Digitized request data

[1466] Step 2:

[1467] The emotion engine analyzes the user's emotions.

[1468] Specific operation: The device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The emotion engine analyzes this data and determines the user's emotional state. The emotion engine generates emotion data such as "I want to relax" and sends it to the AI.

[1469] Input: User's facial expression data, voice data

[1470] Output: User's emotional state (e.g., wanting to relax)

[1471] Step 3:

[1472] The AI ​​generates a request based on the request content and emotional information and sends it to the server.

[1473] Specific operation: The AI ​​analyzes the user's request and the emotional information obtained from the emotion engine, and generates request data including the user's current location, desired conditions, and emotional information. The generated request is then sent to the server.

[1474] Input: User request data, emotional information, current location data

[1475] Output: Request data

[1476] Step 4:

[1477] The server retrieves store information from the database based on the request.

[1478] Specific operation: The server queries the database based on the received request data to retrieve information about cafes near the current location. For example, it extracts information such as "Cafe A: Quiet and has Wi-Fi, Cafe B: Spacious seating."

[1479] Input: Request data

[1480] Output: Store information data

[1481] Step 5:

[1482] The server returns the acquired store information to the AI.

[1483] Specific operation: The server sends store information data to the AI. The store information data is in JSON format, XML format, etc.

[1484] Input: Store information data

[1485] Output: Response data

[1486] Step 6:

[1487] The AI ​​presents the response data to the user's device and prioritizes the most suitable stores based on emotional information.

[1488] Specific operation: The AI ​​analyzes the received response data and displays store information on the user's device. If the emotional state is "Relaxed," quiet and comfortable cafes will be displayed first.

[1489] Input: Response data, emotion information

[1490] Output: Store information displayed on the user's device

[1491] This detailed processing flow allows users to efficiently handle daily tasks and receive optimal services according to their emotional state.

[1492] (Application example 2)

[1493] 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."

[1494] Conventional systems provide simple information and process tasks without considering the user's emotional state, resulting in low user satisfaction. It is also difficult to quickly and efficiently provide optimal results to users. Furthermore, there is a lack of support for optimal decision-making based on the user's emotions, even when it comes to specific store information or schedule adjustments.

[1495] The specification processing by the specification 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 the emotion engine to recognize the user's emotions and provide the optimal result; means for the emotion engine to send a request to the server and retrieve specific date candidates from a database; means for presenting date candidates to the user and displaying them preferentially based on emotional information; means for the emotion engine to confirm the user's selection to the server; means for the server to notify other related AIs of the confirmed date; means for the emotion engine to send a request to the server and retrieve specific store information from a database; and means for displaying store information preferentially based on emotional information. This allows the provision of optimal services and information according to the user's emotional state, improving user satisfaction and enabling quick and efficient decision-making.

[1496] A "user terminal" is a device operated by a user, such as a smartphone, tablet, or PC.

[1497] "AI" is an artificial intelligence that is set up for each user and has the ability to receive and analyze user requests.

[1498] A "server" is a device installed on a network that receives requests from AI, retrieves the necessary information from a database, and returns that information to the AI.

[1499] "Database" means an information management system that stores necessary data and provides relevant data upon request.

[1500] The "emotion engine" is a module for recognizing and analyzing the user's emotions, and determines the user's emotional state by analyzing voice, facial expressions, text, etc.

[1501] "Request content" refers to the information and tasks that the user sends to the AI ​​via their device.

[1502] A "request" is a request that an AI sends to a server, and includes the request content and emotional information.

[1503] "Candidate dates" are possible date and time options retrieved from a server or database and used for scheduling.

[1504] "Store information" refers to information about a specific store, including its location, the services and products it offers, and so on.

[1505] "Priority display" refers to displaying the information or options that are most relevant to the user based on emotional information before others.

[1506] This invention is a system that combines user terminals, servers, AI, databases, and emotion engines to provide services optimized based on user emotions, allowing users to efficiently handle everyday chores such as shopping and scheduling.

[1507] The user terminal is a device such as a smartphone, tablet, or PC that provides an interface for users to operate. Users can send various requests to the AI ​​through the terminal.

[1508] The AI ​​receives and analyzes user requests. Based on the analysis results, it sends a request to the server to obtain the necessary information. It also works in conjunction with the emotion engine to provide an optimized response based on the user's emotional state.

[1509] The server receives requests from the AI ​​and retrieves the necessary information from the database. Taking into account the analysis results of the emotion engine, it returns the retrieved information to the AI. The server also oversees the overall operation of the system and manages collaboration between multiple AIs and databases.

[1510] The database stores various data such as possible meeting dates and store information, and provides related data in response to requests from the server.

[1511] The emotion engine recognizes and analyzes emotions through the user's voice, facial expressions, text, etc., and provides the results to the AI, allowing the AI ​​to provide optimal services that take into account the user's emotional state.

[1512] The system process involves a user operating a device to send a request to the AI, such as "Please reschedule a meeting next week." The emotion engine analyzes voice and facial expressions, and if the user is feeling stressed, for example, it provides that emotional state to the AI. Based on the emotional information and the request, the AI ​​determines that the meeting needs to be rescheduled.

[1513] Next, the AI ​​sends detailed information such as the list of meeting participants and desired dates as a request to the server, along with emotional information. The server receives the request and retrieves candidate dates for the meeting by referencing its database. The retrieved candidate dates are returned from the server to the AI. The AI ​​then presents the returned candidate dates on the user's device, prioritizing the more appropriate ones based on the emotional information. The user selects the desired date from the presented candidate dates and performs an operation to confirm it. The server then works with other related AIs to confirm the final date and stores that information in a database. The confirmed date is then notified to the relevant parties.

[1514] In the example of searching for store information, the user can request, "Please find a nearby cafe." The emotion engine analyzes the user's emotions and determines, for example, that they want to relax. The AI ​​sends a request to the server along with their current location, desired conditions, and emotional information, and the server responds by retrieving relevant store information from a database. The AI ​​then presents the retrieved store information on the user's device and prioritizes the display of appropriate cafes based on the emotional information.

[1515] As a concrete example, when a user uses an application in a physical store, they can install a dedicated shopping assistant app on their smartphone. When the user starts the app and inputs that they are looking for relaxation products, the emotion engine analyzes the input data and recognizes that the user is feeling like they want to relax. It then guides the user to the location of relaxation-related products (such as aroma candles and healing music) within the store.

[1516] Example prompts to send to the generative AI model:

[1517] "Analyze the user's emotions and, if they feel like relaxing, recommend the most suitable relaxation products. Also, guide them to the location of the products in the store where the user is currently located."

[1518] In this way, by providing optimal services and information based on the user's emotional state, it is possible to improve user satisfaction and support quick and efficient decision-making.

[1519] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1520] Step 1:

[1521] The user inputs a request into the terminal and sends it.

[1522] The user uses a device such as a smartphone to input the details of their request, such as the product they want to purchase or the store information they want to find, and presses the send button. At this time, voice, facial expression, and text data are collected as input data by the device. The input data includes, for example, the text "I want to relax" and the accompanying facial expression data.

[1523] Step 2:

[1524] The device sends input data to the emotion engine.

[1525] The device sends the collected voice, facial expression, and text data to an emotion engine, which runs on the cloud and analyzes the data to determine the user's emotional state. Based on the input data, the emotion state is identified using voice recognition and image analysis algorithms.

[1526] Step 3:

[1527] The emotion engine analyzes the user's emotions and provides the results to the AI.

[1528] The emotion engine analyzes the input data sent and identifies the user's emotional state (e.g., feeling like they want to relax). The emotion information generated based on the emotion analysis is passed to the AI. At this point, the analysis result is generated as "the user feels like they want to relax."

[1529] Step 4:

[1530] The AI ​​sends a request to the server based on the request content and emotional information.

[1531] The AI ​​combines the user's request with emotional information and sends a request to the server. The request data includes specific details of the request (e.g., "Please find me a product that helps me relax") along with emotional information. The AI ​​determines which category the request falls into and sends it to the server as an appropriate request.

[1532] Step 5:

[1533] The server receives the request and retrieves the information from the database.

[1534] The server receives a request from the AI ​​and references the database based on the request. For example, if the request is for "relaxing products," the server searches the database for relevant product information (e.g., aroma candles, healing music, etc.). The retrieved information includes data such as the product name, category, price, and location within the store.

[1535] Step 6:

[1536] The server returns the information it has obtained to the AI.

[1537] The server organizes the information retrieved from the database and sends it back to the AI. The response data includes prioritized product and store information based on user sentiment, and the AI ​​receives information optimized for the user.

[1538] Step 7:

[1539] The AI ​​sends the results back to the user's device and presents them to the user.

[1540] The AI ​​analyzes the information returned by the server and displays it on the user's device in the optimal order based on the user's emotional state. For example, if the user feels like relaxing, it will prioritize products with a relaxing effect. The information also includes the location of the displayed products and stores.

[1541] Step 8:

[1542] The user makes a selection and confirms it based on the information displayed.

[1543] The user selects the desired product or store from the information displayed on the device and presses the confirm button. The selection and confirmation data are then sent from the device to the AI. The selection data includes information about the product the user ultimately became interested in and the store they wish to use.

[1544] Step 9:

[1545] The AI ​​confirms the user's selection to the server and notifies any related AIs.

[1546] The AI ​​sends the user's selection data to the server and confirms the selection. The server stores the confirmed information in a database and notifies other related AIs, allowing other systems and applications to provide optimal services based on the user's selection.

[1547] Example prompts to send to the generative AI model:

[1548] "Analyze the user's emotions and, if they feel like relaxing, recommend the most suitable relaxation products. Also, guide them to the location of the products in the store where the user is currently located."

[1549] In this way, optimal services and information are provided based on the user's emotional state, improving user satisfaction.

[1550] 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.

[1551] 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.

[1552] 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.

[1553] [Fourth embodiment]

[1554] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1555] 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.

[1556] 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).

[1557] 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.

[1558] 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.

[1559] 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).

[1560] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1561] 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.

[1562] 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.

[1563] 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.

[1564] 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.

[1565] 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.

[1566] 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."

[1567] The present invention is a system that efficiently handles a user's daily chores by linking a user terminal, a server, AI, and a database. In this system, the user can issue various requests to the AI ​​through the terminal. A specific embodiment of this system is described below.

[1568] System configuration

[1569] User device:

[1570] This is a device that users can operate, such as a smartphone, tablet, or PC. Users can send requests to AI through the device and receive the processing results.

[1571] AI:

[1572] It is an artificial intelligence that is set up for each user, and receives and analyzes the user's request. Based on the analysis results, it sends a request to the server, receives a response from the server, and presents it to the user.

[1573] server:

[1574] It is installed on a network and receives requests from AI. Based on the request, it retrieves the necessary information from the database and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations.

[1575] Database:

[1576] It is an information management system that stores necessary data, such as meeting schedule options, store information, etc. It provides related data in response to requests from the server.

[1577] Processing flow

[1578] The user operates the device to send a request to the AI, such as "Please arrange a meeting for next week." The AI ​​receives this request, analyzes the content, and determines that the meeting date needs to be adjusted. The AI ​​then sends a request to the server along with detailed information such as the list of meeting participants and the desired date.

[1579] The server receives the request and queries the database to obtain possible meeting dates. The server then returns the obtained date options to the AI, which then presents them on the user's device. The user then selects the desired date from the options presented.

[1580] The date selected by the user is sent to the AI ​​via the device, which then sends the selection to the server. The server then coordinates with other related AIs to confirm the final date. This information is then stored in the database again, and the confirmed date is notified to the relevant parties.

[1581] Also, if a user requests "find a nearby cafe," the AI ​​will send a request to the server based on the user's current location and desired conditions. The server will retrieve the relevant store information from the database and respond to the AI. The AI ​​will then display this information on the user's device, allowing the user to check nearby cafes.

[1582] Specific examples

[1583] Meeting scheduling example:

[1584] The user sends a request to the AI ​​from their device saying, "Please arrange a meeting for next week."

[1585] The AI ​​sends a request to the server based on the list of conference participants and the desired date.

[1586] The server retrieves schedule candidates from the database and returns them.

[1587] The AI ​​presents possible dates on the user's device, and the user selects the desired date.

[1588] The server notifies other related AIs of the confirmed schedule and completes the final adjustments.

[1589] Store information search example:

[1590] The user sends a request to the AI ​​from their device to "find a nearby cafe."

[1591] The AI ​​requests the user's current location and desired conditions from the server.

[1592] The server retrieves the relevant store information from the database and responds to the AI.

[1593] AI presents store information on the user's device.

[1594] This invention allows users to automate tedious tasks and perform daily tasks more efficiently and conveniently. This system is expected to significantly reduce users' time and effort, and reduce stress.

[1595] The processing flow will be explained below.

[1596] Meeting Scheduling Process Steps

[1597] Step 1:

[1598] The user operates the terminal and inputs a request to "schedule a meeting for next week."

[1599] Step 2:

[1600] The terminal sends the input request to the user's AI.

[1601] Step 3:

[1602] The user AI analyzes the request and determines that a meeting schedule needs to be adjusted.

[1603] Step 4:

[1604] The user AI sends a request to the server, adding detailed information such as the list of meeting participants and the desired date.

[1605] Step 5:

[1606] The server analyzes the received request and queries the database to obtain the required data.

[1607] Step 6:

[1608] The database searches for possible meeting dates and returns the results to the server.

[1609] Step 7:

[1610] The server compiles the schedule suggestions received from the database and responds to the user AI.

[1611] Step 8:

[1612] The user AI receives the response from the server and presents possible dates on the user's device.

[1613] Step 9:

[1614] The user selects the desired date from the presented date options and performs an operation to confirm the selection.

[1615] Step 10:

[1616] The device sends the date selected by the user to the user AI.

[1617] Step 11:

[1618] The user AI sends the confirmed schedule to the server.

[1619] Step 12:

[1620] The server stores the confirmed schedule information in a database and notifies the AI ​​of other meeting participants of that information.

[1621] Store information search processing steps

[1622] Step 1:

[1623] The user operates the terminal and inputs a request such as "Please find a nearby cafe."

[1624] Step 2:

[1625] The terminal sends the input request to the user's AI.

[1626] Step 3:

[1627] The user AI analyzes the request and determines that a search for a cafe is required.

[1628] Step 4:

[1629] The user AI sends a request to the server along with the user's current location and desired conditions.

[1630] Step 5:

[1631] The server analyzes the received request and queries the database to obtain the required data.

[1632] Step 6:

[1633] The database searches for cafe information that matches the specified conditions and returns the results to the server.

[1634] Step 7:

[1635] The server compiles the cafe information received from the database and responds to the user AI.

[1636] Step 8:

[1637] The user AI receives the response from the server and displays the cafe information on the user's device.

[1638] Step 9:

[1639] The user checks the presented cafe information and decides on a destination if necessary.

[1640] Example 1

[1641] 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."

[1642] In modern business environments and everyday life, users spend a great deal of time and effort on complex tasks and organizing information. There is a particular need for efficient and fast ways to complete everyday tasks, such as scheduling meetings or searching for store information. However, conventional systems often require users to manually search for information or schedule appointments, which can be perceived as inefficient. Therefore, there is a need for systems that allow users to more efficiently complete everyday tasks.

[1643] 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.

[1644] In this invention, the server includes a means for sending a request from a user terminal to an AI model, a means for the AI ​​model to analyze the request content, and a means for sending a request to the server based on the analyzed request content. This allows the user to efficiently process complicated tasks. The server also includes a means for acquiring information from an information management system based on the request, a means for returning the acquired information to the user terminal, and a means for the user terminal to present the returned information to the user. This allows the user to quickly obtain the information they need and saves them time and effort. Furthermore, this system includes a means for the server to acquire specific date options and store information from the information management system based on the request and present that information to the user. This automates the scheduling of meetings and searching for store information, significantly saving the user time and effort.

[1645] A "user terminal" is a device operated by a user, such as a smartphone, tablet, or PC.

[1646] An "AI model" refers to an artificial intelligence system that receives and analyzes user requests and processes the necessary information.

[1647] A "server" is a central processing unit installed on a network that receives requests from an AI model and processes them accordingly.

[1648] A "request" is a request for specific information sent from a user device through an AI model to a server.

[1649] An "information management system" is a system that stores information in a form such as a database and provides it to a server when needed.

[1650] "Analysis" is the procedure by which an AI model understands the request received from a user and takes appropriate action.

[1651] "Provision" refers to the act of a server or information management system obtaining the necessary information and returning it to the user device or AI model.

[1652] "Date options" are options for available dates and times for a meeting or event.

[1653] "Store information" refers to detailed information about a specific store, including its location, business hours, and services offered.

[1654] "Notification" is a means by which the server notifies relevant AI models and users of confirmed information.

[1655] The present invention is a system consisting of a user terminal, a server, an AI model, and an information management system. This system is designed to help users efficiently complete complex daily tasks. Specific embodiments of this system are described below.

[1656] Hardware and software used

[1657] User device:

[1658] A user terminal is a device operated by a user, such as a smartphone, tablet, or PC. Users can use these devices to send requests to the system and receive the processing results.

[1659] AI model:

[1660] The AI ​​model uses artificial intelligence technology for natural language processing, specifically a generative AI model such as OpenAI's GPT-4, to receive and analyze user requests and generate appropriate responses.

[1661] server:

[1662] The server receives requests from the AI ​​model and queries the information management system based on those requests. The server is typically operated using a server instance from Amazon Web Services (AWS) or Google Cloud Platform (GCP).

[1663] Information Management System:

[1664] The information management system uses database technology, such as Oracle Database or MySQL. This system stores the necessary information (such as potential meeting dates and store information) and provides the information in response to server requests.

[1665] Example of the system (meeting schedule adjustment)

[1666] A user device sends a request to the AI ​​model saying, "Please reschedule a meeting for next week." The AI ​​model (GPT-4) that receives this request analyzes the request and determines that a "meeting rescheduling" is necessary. The AI ​​model then sends a request to the server with detailed information such as a list of meeting participants and the desired date.

[1667] The server receives the request and queries an information management system (e.g., a MySQL database) to obtain possible meeting dates. The server returns the obtained date options to the AI ​​model, which then presents them to the user's device. The user selects the desired date from the presented options. This selection is sent back to the AI ​​model via the device, and the AI ​​model sends this selection to the server. The server then works with other related AI models to confirm the final date. This information is then stored back in the information management system, and the confirmed date is notified to the relevant parties.

[1668] Example of the system (store information search)

[1669] A user device sends a request to the AI ​​model saying, "Please find a nearby cafe." The AI ​​model (GPT-4) analyzes the user's current location and desired conditions and generates a request to the server. This request includes specific location information, such as "Shibuya Ward, Tokyo."

[1670] The server receives the request and queries an information management system (e.g., Oracle Database) to obtain the relevant store information. The server then returns the obtained store information to the AI ​​model, which then presents it to the user's device. The user can then make a decision based on the presented cafe information.

[1671] Prompt Sentence Examples

[1672] Here are some example prompts that users can enter into a generative AI model:

[1673] "We'd like to arrange a meeting date for next week. The participants are A, B, and C. Possible dates are: October 1st, October 2nd, and October 3rd."

[1674] "I'm looking for a nearby cafe. I'm currently in Shibuya, Tokyo, and I'd prefer a place with Wi-Fi."

[1675] By using the system of the present invention, users can quickly and efficiently complete tedious daily tasks, which is expected to significantly save users time and effort and reduce stress.

[1676] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1677] Step 1:

[1678] The user enters the request at the terminal.

[1679] Users operate their smartphones or PCs, input requests such as "Please arrange a meeting for next week" or "Please find a nearby cafe," and press the send button.

[1680] Input: User request (request in text format)

[1681] Output: Sending a request from the device to the AI ​​model

[1682] Step 2:

[1683] The device sends the request to the AI ​​model.

[1684] The device receives the text data entered by the user and issues an HTTP request to send it to the AI ​​model via the Internet.

[1685] Input: User request (text data)

[1686] Output: HTTP request to the AI ​​model

[1687] Step 3:

[1688] The AI ​​model analyzes the request.

[1689] The AI ​​model (e.g., GPT-4) analyzes the received request and identifies the required tasks. At this stage, the AI ​​model understands the request and extracts the data needed for the next step (e.g., participant list).

[1690] Input: HTTP request (user requested data)

[1691] Output: Analysis results (task identification and extraction of necessary data)

[1692] Step 4:

[1693] The AI ​​model sends a request to the server.

[1694] Based on the analysis results, the AI ​​model generates a request containing the necessary information and sends it to the server in JSON format.

[1695] Input: Analysis results (identification of tasks and extraction of necessary data)

[1696] Output: Request to server (JSON format)

[1697] Step 5:

[1698] The server receives the request.

[1699] The server receives requests sent by the AI ​​model, logs the request content, and begins processing.

[1700] Input: Request (JSON format)

[1701] Output: Logging and preparing for processing

[1702] Step 6:

[1703] The server queries the information management system.

[1704] Based on the received request, the server queries the information management system (database) using an SQL query.

[1705] Input: Request content

[1706] Output: SQL query executed

[1707] Step 7:

[1708] The information management system provides the information.

[1709] In response to an inquiry from the server, the information management system responds with saved meeting schedule information and store information.

[1710] Input: SQL query

[1711] Output: Required information (meeting date options or store information)

[1712] Step 8:

[1713] The server returns the provided information to the AI ​​model.

[1714] The server processes the information obtained from the information management system and sends it back to the AI ​​model.

[1715] Input: Required information (meeting date options or store information)

[1716] Output: Response to the AI ​​model

[1717] Step 9:

[1718] The AI ​​model presents the results on the user's device.

[1719] The AI ​​model organizes the information it receives in a way that is easy for the user to understand and displays the results on the user's device, for example, "Possible dates for next week's meetings are October 1st, 2nd, and 3rd."

[1720] Input: Response information from the server

[1721] Output: Display of results (formatted information) on the user's device

[1722] Step 10:

[1723] The user makes a selection or confirms the results.

[1724] The user checks the suggested dates and store information and selects the appropriate option. For example, they select "October 2nd" and press the select button.

[1725] Input: Information presented to the user

[1726] Output: User's selection

[1727] Step 11:

[1728] The device sends the selection results to the AI ​​model.

[1729] The device retrieves the user's selection and issues another HTTP request to send it to the AI ​​model.

[1730] Input: User selection result

[1731] Output: HTTP request to the AI ​​model

[1732] Step 12:

[1733] The AI ​​model sends the selection results to the server.

[1734] The AI ​​model sends the user's selection results to the server in JSON format.

[1735] Input: User selection result (HTTP request)

[1736] Output: JSON request to the server

[1737] Step 13:

[1738] The server makes the final adjustments and stores the data in the information management system.

[1739] The server also integrates information from other related AI models to determine the final meeting schedule, which is then stored in the information management system.

[1740] Input: User selections (JSON request) and information from other AI models

[1741] Output: Save the finalized meeting schedule

[1742] Step 14:

[1743] Information management systems will be updated and necessary parties will be notified.

[1744] The updated information is saved in the information management system, and the system sends emails and in-app notifications to relevant parties.

[1745] Input: Finalized meeting dates

[1746] Output: Notification to relevant parties (email, in-app notification)

[1747] (Application example 1)

[1748] 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."

[1749] Conventional autonomous vehicles lack systems that allow users to efficiently handle everyday chores, requiring many tasks to be performed manually while driving, resulting in low convenience. In particular, the wide range of tasks that drivers must perform, such as setting destinations, checking traffic conditions, and managing entertainment, can be cumbersome and may affect safety. Another issue is the insufficient provision of real-time information, making it difficult to respond quickly to user requests.

[1750] 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.

[1751] In this invention, the server includes a means for providing traffic information and entertainment information, a means for setting a destination by voice, and a means for presenting acquired traffic information to the user and providing entertainment information. This allows the user to easily set a destination, check traffic conditions, and manage entertainment in an autonomous vehicle by voice, significantly improving convenience and safety. It also enables real-time information provision, enabling rapid response.

[1752] A "user terminal" is an information device operated by a user, such as a smartphone, tablet, or PC.

[1753] "AI" refers to artificial intelligence that analyzes user requests and sends instructions to the server based on the results.

[1754] A "server" is a device that receives requests from AI over a network, retrieves information from a database, and responds.

[1755] A "database" is an information management system that stores various types of information and provides necessary data based on requests.

[1756] "Traffic information" refers to information about road and traffic conditions when an autonomous vehicle is heading to its destination.

[1757] "Entertainment information" refers to information about content that users can enjoy, including music, videos, news, and the like.

[1758] "Voice-based destination setting means" refers to a method of analyzing a user's voice input and determining the destination of an autonomous vehicle based on the set destination.

[1759] "Real-time information provision" refers to providing information immediately based on the current situation.

[1760] "Request analysis" refers to the process by which AI understands the content of requests received from users and issues appropriate instructions or requests.

[1761] "Means for presenting" refers to a method for directly presenting acquired information to a user, and includes methods such as a display and audio output.

[1762] The present invention provides a system that efficiently processes various tasks within an autonomous vehicle by linking a user terminal, a server, an AI, and a database. In this system, the user can issue requests to the AI ​​through the terminal. Specific embodiments of this system are described below.

[1763] System configuration

[1764] User device:

[1765] An information device operated by a user, such as a smartphone, tablet, or in-car display, allows the user to send requests to AI through the device and receive the processing results.

[1766] AI:

[1767] This is an artificial intelligence that is set up for each user and receives and analyzes the user's request. It sends instructions to the server based on the analysis results, receives responses from the server, and presents them to the user. The AI ​​uses generative AI models to perform speech recognition and natural language analysis.

[1768] server:

[1769] It is installed on a network and receives requests from AI. It retrieves the necessary information from a database based on the request and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations. It uses a cloud server or an on-premise server.

[1770] Database:

[1771] It is an information management system that stores necessary data, such as traffic and entertainment information. It provides related information in response to requests from the server. Database software such as MySQL or PostgreSQL is used.

[1772] Specific examples

[1773] Destination setting example:

[1774] The user sends a voice request from their device to the AI ​​saying, "Set the destination to Shibuya." The AI ​​analyzes the voice and obtains the destination as text. The AI ​​then instructs the server that the destination is Shibuya. The server uses this information to send a traffic information request and obtains traffic conditions from a database. The server returns the obtained traffic information to the AI, which then displays it on the user's device. The user can check the traffic information provided and give instructions such as route changes if necessary.

[1775] Examples of entertainment information provided:

[1776] When a user makes a voice request such as "Play some relaxing music," the AI ​​analyzes the request and sends a request for entertainment information to the server. The server retrieves a music list based on the user's preferences from a database and returns that information to the AI. The AI ​​then presents the retrieved music list to the user's device and automatically plays the music.

[1777] The specific hardware and software used

[1778] Hardware: smartphones, tablets, in-vehicle displays, cloud servers

[1779] Software: Generative AI model, MySQL, PostgreSQL, speech recognition library (speech_recognition), speech synthesis library (pyttsx3)

[1780] Prompt Sentence Examples

[1781] The processing steps when the user says "Set destination to Shibuya" are explained below.

[1782] 1. Analyze the user's voice and obtain the destination as text.

[1783] 2. Based on the acquired destination, traffic conditions are obtained from the traffic information API.

[1784] 3. Notify users when traffic conditions are congested.

[1785] 4. Recommending your preferred entertainment based on your user ID.

[1786] This invention allows users to easily handle complicated tasks by voice even in autonomous vehicles, significantly improving convenience and safety. It also enables real-time information provision, enabling rapid response.

[1787] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1788] Step 1:

[1789] The user operates the device and sends a voice request such as "Set destination to Shibuya." The input is the user's voice, and the device must be equipped with a microphone. The output is voice data. Based on this, the device collects the voice data and sends it to the AI ​​for analysis.

[1790] Step 2:

[1791] The AI ​​analyzes the received voice data. The input is voice data, and the output is textual destination information (in this case, "Shibuya"). The AI ​​uses a generative AI model to perform voice recognition and convert the voice data into text. Specifically, the speech_recognition library is used to convert voice to text.

[1792] Step 3:

[1793] Based on the analyzed destination information, the AI ​​sends a request to the server. The input is the destination information text data "Shibuya," and the output is the request data to the server. The server receives the destination information and begins obtaining traffic information.

[1794] Step 4:

[1795] Based on the request received by the server, traffic information is retrieved from the database. The input is the destination text data "Shibuya" and the output is traffic information data. The server calls the traffic information API and retrieves traffic conditions based on the specified destination.

[1796] Step 5:

[1797] The server returns the traffic information it has acquired to the AI. The input is traffic information data, and the output is response data to the AI. The server then sends the traffic information it has acquired from the database back to the AI.

[1798] Step 6:

[1799] The AI ​​analyzes the traffic information it receives and presents it to the user. The input is traffic information data, and the output is display data on the user's device. Specifically, the AI ​​displays the acquired traffic information on the device in a format that is easy for the user to understand. Traffic conditions are presented to the user using the device's display and audio output functions.

[1800] Step 7:

[1801] Based on the information provided, the user approves or changes the destination by voice. The input is the user's voice command, and the output is the final destination information. The AI ​​again analyzes the user's voice command and determines the final destination.

[1802] Step 8:

[1803] The AI ​​sends the final destination back to the server, which then determines the driving route based on this and reflects it in the navigation system. The input is the final destination information and the output is navigation data. The server works in conjunction with the navigation system to optimize the route of the autonomous vehicle.

[1804] This will allow users to easily set destinations and check traffic information by voice, improving the convenience and safety of self-driving vehicles.

[1805] 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.

[1806] This invention is a system that efficiently handles users' daily chores and provides services optimized based on the user's emotional state by linking a user terminal, server, AI, database, and emotion engine. In this system, the user can issue various requests to the AI ​​through the terminal, and the emotion engine recognizes the user's emotions and optimizes the request content and results.

[1807] System configuration

[1808] User device:

[1809] This is a device that users can operate, such as a smartphone, tablet, or PC. Users can send requests to AI through the device and receive the processing results.

[1810] AI:

[1811] It is an artificial intelligence that is set up for each user, and receives and analyzes the user's request. Based on the analysis results, it sends a request to the server, receives a response from the server, and presents it to the user.

[1812] server:

[1813] It is installed on a network and receives requests from AI. Based on the request, it retrieves the necessary information from the database and returns that information to the AI. It manages the connection between multiple AIs and databases and oversees overall operations.

[1814] Database:

[1815] It is an information management system that stores necessary data, such as meeting schedule options, store information, etc. It provides related data in response to requests from the server.

[1816] Emotion Engine:

[1817] This module recognizes and analyzes the user's emotions, judging their emotional state by analyzing voice, facial expressions, text, etc. The emotion engine then optimizes the request content based on the results and provides it to the AI.

[1818] Processing flow

[1819] The user operates their device to send a request to the AI, such as "Please reschedule a meeting next week." At this point, the emotion engine analyzes the user's voice and facial expressions, and if the user is feeling stressed, for example, it provides that emotional state to the AI. Based on this emotional information and the request, the AI ​​determines that the meeting needs to be rescheduled.

[1820] Next, the AI ​​adds detailed information such as a list of meeting participants and desired dates, and also sends a request along with emotional information to the server. The server receives the request and retrieves candidate dates from its database. The server then returns the candidate dates to the AI.

[1821] The AI ​​presents the proposed dates to the user's device, prioritizing the most appropriate ones based on the user's emotional information. The user selects the desired date from the presented options and confirms it. The device then sends the user's selected date to the AI, which then sends the selection to the server to confirm it.

[1822] The server will then work with other related AIs to determine the final schedule, store the information in a database, and notify the relevant parties of the final schedule.

[1823] Similarly, if a user requests, "Please find a nearby cafe," the emotion engine will recognize and analyze the user's emotions and provide them to the AI ​​along with the user's current location and desired conditions. The AI ​​will then send a request to the server, which will retrieve the relevant store information from its database and respond. The AI ​​will then present the retrieved store information on the user's device and provide appropriate information based on the emotional information.

[1824] Specific examples

[1825] Meeting scheduling example:

[1826] The user sends a request to the AI ​​from their device saying, "Please arrange a meeting for next week."

[1827] The emotion engine analyzes the user's voice and facial expressions and determines whether the user is feeling stressed.

[1828] The AI ​​sends a request to the server based on emotional information, the list of meeting participants, and the desired date and time.

[1829] The server retrieves possible dates from the database and responds to the AI.

[1830] The AI ​​presents possible dates to the user's device and prioritizes them appropriately based on emotional information.

[1831] The user selects and confirms the desired date.

[1832] The server stores the confirmed schedule in a database and notifies other related AIs.

[1833] Store information search example:

[1834] The user sends a request to the AI ​​from their device to "find a nearby cafe."

[1835] The emotion engine analyzes the user's emotions and determines, for example, that they want to relax.

[1836] The AI ​​sends a request to the server, adding its current location, desired conditions, and emotional information.

[1837] The server retrieves the relevant cafe information from the database and responds to the AI.

[1838] The AI ​​presents store information to the user's device and prioritizes appropriate cafes based on emotional information.

[1839] The present invention allows users to automate tedious tasks and receive services optimized according to their emotional state, improving their quality of life.

[1840] The processing flow will be explained below.

[1841] Meeting Scheduling Process Steps

[1842] Step 1:

[1843] The user operates the terminal and inputs a request to "schedule a meeting for next week."

[1844] Step 2:

[1845] The device sends the input request to the AI, and at the same time, it also acquires the user's facial expressions and voice data and sends them to the emotion engine.

[1846] Step 3:

[1847] The emotion engine analyzes the user's facial expressions and voice data and determines whether the user is feeling stressed.

[1848] Step 4:

[1849] The emotion engine sends the analysis results to the AI, providing the user's emotional state.

[1850] Step 5:

[1851] Based on the request and emotional information, the user AI determines that the meeting schedule needs to be adjusted and sends a request to the server along with a list of meeting participants and the desired date.

[1852] Step 6:

[1853] The server analyzes the received request and queries the database to obtain the required data.

[1854] Step 7:

[1855] The database searches for possible meeting dates and returns the results to the server.

[1856] Step 8:

[1857] The server compiles the schedule suggestions received from the database and responds to the user AI.

[1858] Step 9:

[1859] The user AI receives the response from the server and presents the suggested dates to the user's device, with the display order optimized based on emotional information.

[1860] Step 10:

[1861] The user selects the desired date from the presented date options and performs an operation to confirm the selection.

[1862] Step 11:

[1863] The device sends the user's selected date to the AI.

[1864] Step 12:

[1865] The user AI sends the confirmed schedule to the server.

[1866] Step 13:

[1867] The server stores the confirmed schedule information in a database and notifies the AI ​​of other meeting participants of that information.

[1868] Store information search processing steps

[1869] Step 1:

[1870] The user operates the terminal and inputs a request such as "Please find a nearby cafe."

[1871] Step 2:

[1872] The device sends the input request to the AI, and at the same time, it also acquires the user's facial expressions and voice data and sends them to the emotion engine.

[1873] Step 3:

[1874] The emotion engine analyzes the user's facial expressions and voice data and determines that the user wants to relax.

[1875] Step 4:

[1876] The emotion engine sends the analysis results to the AI, providing the user's emotional state.

[1877] Step 5:

[1878] Based on the request and emotional information, the user AI sends a request to the server along with the user's current location and desired conditions.

[1879] Step 6:

[1880] The server analyzes the received request and queries the database to obtain the required data.

[1881] Step 7:

[1882] The database searches for cafe information that matches the conditions and returns the results to the server.

[1883] Step 8:

[1884] The server compiles the cafe information received from the database and responds to the user AI.

[1885] Step 9:

[1886] The user AI receives the response from the server and displays the cafe information on the user's device, with the display order optimized based on the user's emotional information.

[1887] Step 10:

[1888] The user checks the presented cafe information and decides where to visit.

[1889] Example 2

[1890] 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."

[1891] Conventional information processing systems provide information uniformly without considering the user's emotional state, making it difficult to provide optimal services tailored to the user's situation. Another problem is that they lack the means to help users efficiently complete complex tasks. This has the drawback of not sufficiently improving the user's quality of life.

[1892] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1893] In this invention, the server includes a means for analyzing the emotional state of the user and providing the result to the artificial intelligence, a means for the artificial intelligence to analyze the request content and send the request to the server, and a means for the server to retrieve information from a database and respond to the user, thereby enabling optimal information provision and task processing according to the user's emotional state.

[1894] A "user terminal" is a device operated by a user, and includes devices such as smartphones, tablets, and personal computers.

[1895] "Artificial intelligence" is a system that analyzes user requests, generates requests based on the results, and sends them to the server.

[1896] A "server" is a central processing unit installed on a network that receives requests from artificial intelligence, retrieves the necessary information from a database, and returns it to the artificial intelligence.

[1897] A "database" is an information management system that can be accessed by a server and stores various types of data.

[1898] The "emotion engine" is a module that analyzes the user's voice, facial expressions, text, etc. to determine their emotional state and provides the results to artificial intelligence.

[1899] "Request" refers to the request or content of the request that a user makes to an artificial intelligence through a user terminal.

[1900] "Request" refers to the analyzed request and request for necessary information that the artificial intelligence sends to the server.

[1901] "Response" refers to response data that the server provides to the user terminal via artificial intelligence with information obtained based on the request.

[1902] MODE FOR CARRYING OUT THE INVENTION

[1903] The present invention is a system that efficiently handles a user's daily chores and provides optimized services based on the user's emotional state by linking a user terminal, artificial intelligence, a server, a database, and an emotion engine.

[1904] Users can issue various requests to the AI ​​through their devices. The emotion engine recognizes the user's emotions and optimizes the request and its results. User devices include smartphones, tablets, and personal computers, and user requests and operations are carried out through these devices.

[1905] User Device

[1906] Users operate their devices to send requests to the AI ​​via voice or text, such as "Please arrange a meeting for next week."

[1907] artificial intelligence

[1908] The AI ​​receives requests from users, analyzes them, and sends requests to the server based on the analysis results. The requests include detailed information such as a list of meeting participants and desired dates.

[1909] server

[1910] The server receives requests from the AI ​​and retrieves the necessary information from the database, such as potential meeting dates or information about nearby cafes, and then returns the retrieved information to the AI.

[1911] Database

[1912] The database is an information management system that stores various data, such as meeting schedule options and store information. The server retrieves relevant data from the database based on a request.

[1913] Emotion Engine

[1914] The emotion engine analyzes the user's voice, facial expressions, text, etc. to determine the user's emotional state. For example, it recognizes whether the user is feeling stressed or relaxed and provides the results to the AI. The emotion engine optimizes the request content based on the user's emotional state and provides feedback to the AI.

[1915] Specific examples

[1916] Meeting schedule adjustment

[1917] When a user requests that a meeting be rescheduled for next week, the emotion engine analyzes the user's voice and facial expressions and determines, for example, that the user is feeling stressed. The AI ​​sends a request to the server based on the emotion information, the list of meeting participants, and the desired date. The server retrieves candidate dates from the database and sends a response to the AI. The AI ​​presents the candidate dates to the user's device, appropriately prioritizing them based on the emotion information. The user selects and confirms the desired date. The server saves the confirmed date in the database and notifies other related AIs.

[1918] Store information search

[1919] When a user requests "find a nearby cafe," the emotion engine analyzes the user's emotions and determines, for example, that they want to relax. The AI ​​attaches their current location, desired conditions, and emotional information and sends a request to the server. The server retrieves relevant cafe information from the database and responds to the AI. The AI ​​then presents store information on the user's device and prioritizes the display of appropriate cafes based on the emotional information.

[1920] Prompt Sentence Examples

[1921] Meeting scheduling prompt:

[1922] plaintext

[1923] "I'd like to reschedule our meeting next week. The list of participants is: [Participant list]. My preferred date is either Monday or Tuesday next week."

[1924] Prompt for store information search:

[1925] plaintext

[1926] "I'd like to find a relaxing cafe nearby. You are currently located at [user location]."

[1927] The system allows users to automate tedious tasks and receive services optimized according to their emotional state, improving their quality of life.

[1928] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1929] Meeting Scheduling Process Steps

[1930] Step 1:

[1931] The user sends a request to the AI ​​to schedule a meeting from their device.

[1932] How it works: The user uses the device's voice input function or keyboard to request, "Please arrange a meeting for next week." The device converts this voice or text into digital data and sends it to the AI.

[1933] Input: User voice and text data

[1934] Output: Digitized request data

[1935] Step 2:

[1936] The emotion engine analyzes the user's emotions.

[1937] How it works: The device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The emotion engine analyzes this data to determine the user's emotional state. The emotion engine generates emotional data such as stress level and sends it to the AI.

[1938] Input: User's facial expression data, voice data

[1939] Output: User's emotional state (e.g., stress level)

[1940] Step 3:

[1941] The AI ​​generates a request based on the request content and emotional information and sends it to the server.

[1942] Specific operation: The AI ​​analyzes the user's request and the emotional information obtained from the emotion engine, and generates request data including a list of meeting participants and the desired schedule. The generated request is then sent to the server.

[1943] Input: User request data, emotional information

[1944] Output: Request data

[1945] Step 4:

[1946] The server retrieves schedule candidates from the database based on the request.

[1947] Specific operation: The server queries the database based on the received request data to obtain possible meeting dates for the next week. For example, possible dates such as "Monday at 3 PM" and "Tuesday at 11 AM" are extracted.

[1948] Input: Request data

[1949] Output: Date candidate data

[1950] Step 5:

[1951] The server returns the obtained schedule options to the AI.

[1952] Specific operation: The server sends the schedule candidate data to the AI. The schedule candidate data is in JSON format, XML format, etc.

[1953] Input: Date candidate data

[1954] Output: Response data

[1955] Step 6:

[1956] The AI ​​presents the response data to the user's device and prioritizes the most suitable dates based on emotional information.

[1957] Specific operation: The AI ​​analyzes the received response data and presents suggested dates on the user's device. If the emotional state is stressful, it prioritizes dates that are less stressful.

[1958] Input: Response data, emotion information

[1959] Output: Date options displayed on the user's device

[1960] Step 7:

[1961] The user selects and confirms the desired date.

[1962] Specific operation: The user selects the desired date from the presented date options and confirms it on the device. The selected date is sent to the AI.

[1963] Input: User selected data

[1964] Output: Confirmed schedule data

[1965] Step 8:

[1966] The AI ​​sends the confirmed schedule to the server and makes the final decision.

[1967] Specific operation: The AI ​​sends the confirmed schedule data to the server, which stores this data in a database and sends notifications to all relevant devices and parties.

[1968] Input: Confirmed schedule data

[1969] Output: Schedule data and notification data stored in the database

[1970] Store information search processing steps

[1971] Step 1:

[1972] The user sends a store information search request to the AI ​​from their device.

[1973] How it works: The user uses the device's voice input function or keyboard to request, "Please find a nearby cafe." The device converts this voice or text into digital data and sends it to the AI.

[1974] Input: User voice and text data

[1975] Output: Digitized request data

[1976] Step 2:

[1977] The emotion engine analyzes the user's emotions.

[1978] Specific operation: The device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The emotion engine analyzes this data and determines the user's emotional state. The emotion engine generates emotion data such as "I want to relax" and sends it to the AI.

[1979] Input: User's facial expression data, voice data

[1980] Output: User's emotional state (e.g., wanting to relax)

[1981] Step 3:

[1982] The AI ​​generates a request based on the request content and emotional information and sends it to the server.

[1983] Specific operation: The AI ​​analyzes the user's request and the emotional information obtained from the emotion engine, and generates request data including the user's current location, desired conditions, and emotional information. The generated request is then sent to the server.

[1984] Input: User request data, emotional information, current location data

[1985] Output: Request data

[1986] Step 4:

[1987] The server retrieves store information from the database based on the request.

[1988] Specific operation: The server queries the database based on the received request data to retrieve information about cafes near the current location. For example, it extracts information such as "Cafe A: Quiet and has Wi-Fi, Cafe B: Spacious seating."

[1989] Input: Request data

[1990] Output: Store information data

[1991] Step 5:

[1992] The server returns the acquired store information to the AI.

[1993] Specific operation: The server sends store information data to the AI. The store information data is in JSON format, XML format, etc.

[1994] Input: Store information data

[1995] Output: Response data

[1996] Step 6:

[1997] The AI ​​presents the response data to the user's device and prioritizes the most suitable stores based on emotional information.

[1998] Specific operation: The AI ​​analyzes the received response data and displays store information on the user's device. If the emotional state is "Relaxed," quiet and comfortable cafes will be displayed first.

[1999] Input: Response data, emotion information

[2000] Output: Store information displayed on the user's device

[2001] This detailed processing flow allows users to efficiently handle daily tasks and receive optimal services according to their emotional state.

[2002] (Application example 2)

[2003] 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."

[2004] Conventional systems provide simple information and process tasks without considering the user's emotional state, resulting in low user satisfaction. It is also difficult to quickly and efficiently provide optimal results to users. Furthermore, there is a lack of support for optimal decision-making based on the user's emotions, even when it comes to specific store information or schedule adjustments.

[2005] The specification processing by the specification 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 the emotion engine to recognize the user's emotions and provide the optimal result; means for the emotion engine to send a request to the server and retrieve specific date candidates from a database; means for presenting date candidates to the user and displaying them preferentially based on emotional information; means for the emotion engine to confirm the user's selection to the server; means for the server to notify other related AIs of the confirmed date; means for the emotion engine to send a request to the server and retrieve specific store information from a database; and means for displaying store information preferentially based on emotional information. This allows the provision of optimal services and information according to the user's emotional state, improving user satisfaction and enabling quick and efficient decision-making.

[2006] A "user terminal" is a device operated by a user, such as a smartphone, tablet, or PC.

[2007] "AI" is an artificial intelligence that is set up for each user and has the ability to receive and analyze user requests.

[2008] A "server" is a device installed on a network that receives requests from AI, retrieves the necessary information from a database, and returns that information to the AI.

[2009] "Database" means an information management system that stores necessary data and provides relevant data upon request.

[2010] The "emotion engine" is a module for recognizing and analyzing the user's emotions, and determines the user's emotional state by analyzing voice, facial expressions, text, etc.

[2011] "Request content" refers to the information and tasks that the user sends to the AI ​​via their device.

[2012] A "request" is a request that an AI sends to a server, and includes the request content and emotional information.

[2013] "Candidate dates" are possible date and time options retrieved from a server or database and used for scheduling.

[2014] "Store information" refers to information about a specific store, including its location, the services and products it offers, and so on.

[2015] "Priority display" refers to displaying the information or options that are most relevant to the user based on emotional information before others.

[2016] This invention is a system that combines user terminals, servers, AI, databases, and emotion engines to provide services optimized based on user emotions, allowing users to efficiently handle everyday chores such as shopping and scheduling.

[2017] The user terminal is a device such as a smartphone, tablet, or PC that provides an interface for users to operate. Users can send various requests to the AI ​​through the terminal.

[2018] The AI ​​receives and analyzes user requests. Based on the analysis results, it sends a request to the server to obtain the necessary information. It also works in conjunction with the emotion engine to provide an optimized response based on the user's emotional state.

[2019] The server receives requests from the AI ​​and retrieves the necessary information from the database. Taking into account the analysis results of the emotion engine, it returns the retrieved information to the AI. The server also oversees the overall operation of the system and manages collaboration between multiple AIs and databases.

[2020] The database stores various data such as possible meeting dates and store information, and provides related data in response to requests from the server.

[2021] The emotion engine recognizes and analyzes emotions through the user's voice, facial expressions, text, etc., and provides the results to the AI, allowing the AI ​​to provide optimal services that take into account the user's emotional state.

[2022] The system process involves a user operating a device to send a request to the AI, such as "Please reschedule a meeting next week." The emotion engine analyzes voice and facial expressions, and if the user is feeling stressed, for example, it provides that emotional state to the AI. Based on the emotional information and the request, the AI ​​determines that the meeting needs to be rescheduled.

[2023] Next, the AI ​​sends detailed information such as the list of meeting participants and desired dates as a request to the server, along with emotional information. The server receives the request and retrieves candidate dates for the meeting by referencing its database. The retrieved candidate dates are returned from the server to the AI. The AI ​​then presents the returned candidate dates on the user's device, prioritizing the more appropriate ones based on the emotional information. The user selects the desired date from the presented candidate dates and performs an operation to confirm it. The server then works with other related AIs to confirm the final date and stores that information in a database. The confirmed date is then notified to the relevant parties.

[2024] In the example of searching for store information, the user can request, "Please find a nearby cafe." The emotion engine analyzes the user's emotions and determines, for example, that they want to relax. The AI ​​sends a request to the server along with their current location, desired conditions, and emotional information, and the server responds by retrieving relevant store information from a database. The AI ​​then presents the retrieved store information on the user's device and prioritizes the display of appropriate cafes based on the emotional information.

[2025] As a concrete example, when a user uses an application in a physical store, they can install a dedicated shopping assistant app on their smartphone. When the user starts the app and inputs that they are looking for relaxation products, the emotion engine analyzes the input data and recognizes that the user is feeling like they want to relax. It then guides the user to the location of relaxation-related products (such as aroma candles and healing music) within the store.

[2026] Example prompts to send to the generative AI model:

[2027] "Analyze the user's emotions and, if they feel like relaxing, recommend the most suitable relaxation products. Also, guide them to the location of the products in the store where the user is currently located."

[2028] In this way, by providing optimal services and information based on the user's emotional state, it is possible to improve user satisfaction and support quick and efficient decision-making.

[2029] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2030] Step 1:

[2031] The user inputs a request into the terminal and sends it.

[2032] The user uses a device such as a smartphone to input the details of their request, such as the product they want to purchase or the store information they want to find, and presses the send button. At this time, voice, facial expression, and text data are collected as input data by the device. The input data includes, for example, the text "I want to relax" and the accompanying facial expression data.

[2033] Step 2:

[2034] The device sends input data to the emotion engine.

[2035] The device sends the collected voice, facial expression, and text data to an emotion engine, which runs on the cloud and analyzes the data to determine the user's emotional state. Based on the input data, the emotion state is identified using voice recognition and image analysis algorithms.

[2036] Step 3:

[2037] The emotion engine analyzes the user's emotions and provides the results to the AI.

[2038] The emotion engine analyzes the input data sent and identifies the user's emotional state (e.g., feeling like they want to relax). The emotion information generated based on the emotion analysis is passed to the AI. At this point, the analysis result is generated as "the user feels like they want to relax."

[2039] Step 4:

[2040] The AI ​​sends a request to the server based on the request content and emotional information.

[2041] The AI ​​combines the user's request with emotional information and sends a request to the server. The request data includes specific details of the request (e.g., "Please find me a product that helps me relax") along with emotional information. The AI ​​determines which category the request falls into and sends it to the server as an appropriate request.

[2042] Step 5:

[2043] The server receives the request and retrieves the information from the database.

[2044] The server receives a request from the AI ​​and references the database based on the request. For example, if the request is for "relaxing products," the server searches the database for relevant product information (e.g., aroma candles, healing music, etc.). The retrieved information includes data such as the product name, category, price, and location within the store.

[2045] Step 6:

[2046] The server returns the information it has obtained to the AI.

[2047] The server organizes the information retrieved from the database and sends it back to the AI. The response data includes prioritized product and store information based on user sentiment, and the AI ​​receives information optimized for the user.

[2048] Step 7:

[2049] The AI ​​sends the results back to the user's device and presents them to the user.

[2050] The AI ​​analyzes the information returned by the server and displays it on the user's device in the optimal order based on the user's emotional state. For example, if the user feels like relaxing, it will prioritize products with a relaxing effect. The information also includes the location of the displayed products and stores.

[2051] Step 8:

[2052] The user makes a selection and confirms it based on the information displayed.

[2053] The user selects the desired product or store from the information displayed on the device and presses the confirm button. The selection and confirmation data are then sent from the device to the AI. The selection data includes information about the product the user ultimately became interested in and the store they wish to use.

[2054] Step 9:

[2055] The AI ​​confirms the user's selection to the server and notifies any related AIs.

[2056] The AI ​​sends the user's selection data to the server and confirms the selection. The server stores the confirmed information in a database and notifies other related AIs, allowing other systems and applications to provide optimal services based on the user's selection.

[2057] Example prompts to send to the generative AI model:

[2058] "Analyze the user's emotions and, if they feel like relaxing, recommend the most suitable relaxation products. Also, guide them to the location of the products in the store where the user is currently located."

[2059] In this way, optimal services and information are provided based on the user's emotional state, improving user satisfaction.

[2060] 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.

[2061] 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.

[2062] 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.

[2063] 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.

[2064] 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.

[2065] 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.

[2066] 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).

[2067] 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.

[2068] 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."

[2069] 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.

[2070] 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).

[2071] 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.

[2072] 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.

[2073] 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.

[2074] 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.

[2075] 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.

[2076] 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.

[2077] 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.

[2078] 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.

[2079] 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.

[2080] 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.

[2081] The following is further disclosed regarding the above embodiment.

[2082] (Claim 1)

[2083] A means to send requests to AI from the user device,

[2084] The means by which AI analyzes the request content,

[2085] A means for sending a request to a server based on the analyzed request content;

[2086] a means for the server to retrieve information from a database based on the request;

[2087] A means for returning the acquired information to the user terminal;

[2088] A means for the user terminal to present the returned information to the user;

[2089] A system including:

[2090] (Claim 2)

[2091] a means for the server to retrieve specific candidate dates from a database based on the request;

[2092] a means for presenting the candidate dates to the user and confirming the user's selection to the server;

[2093] A means for the server to notify other related AIs of the confirmed schedule,

[2094] The system of claim 1 further comprising:

[2095] (Claim 3)

[2096] A means for the server to retrieve specific store information from a database based on a request;

[2097] A means of presenting that store information to users,

[2098] The system of claim 1 furt...

Claims

1. A means to send requests to AI from the user device, The means by which AI analyzes the request content, A means for sending a request to a server based on the analyzed request content; a means for the server to retrieve information from a database based on the request; A means for returning the acquired information to the user terminal; A means for the user terminal to present the returned information to the user; A system including:

2. a means for the server to retrieve specific candidate dates from a database based on the request; a means for presenting the candidate dates to the user and confirming the user's selection to the server; A means for the server to notify other related AIs of the confirmed schedule, The system of claim 1 further comprising:

3. A means for the server to retrieve specific store information from a database based on a request; A means of presenting that store information to users, The system of claim 1 further comprising:

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