System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving user input of a child's age, interests, budget, and means of transportation; means for searching for relevant spot and activity information from various sources; means for generating a plan for the child's interests based on the search results; means for providing the generated plan to the user; and means for receiving feedback from the user to improve the accuracy of the system.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] When going out with small children, choosing places and activities that the children can enjoy can be a time-consuming and burdensome task for parents. Furthermore, gathering appropriate information online requires a great deal of time and effort. In particular, there is a lack of systems that automatically suggest places that match a child's interests and budget. [Means for solving the problem]

[0005] The present invention provides a system including means for receiving information on a child's age, interests, budget, and mode of transportation input by a user, means for searching for related spot and activity information from various sources, means for generating a plan suited to the child's interests based on the search results, means for providing the generated plan to the user, and means for receiving feedback from the user to improve the accuracy of the system, thereby enabling parents to easily find the best destination for an outing and efficiently create a plan suited to their child's interests.

[0006] "User" refers to the person who plans and selects outings and activities with their child.

[0007] "Children" refers to minors who go out with the user.

[0008] "Age" refers to the number of years since the child was born.

[0009] "Interests" refer to activities or subjects that children have a strong interest in and find enjoyable.

[0010] "Budget" refers to the maximum amount of money you can spend on going out or doing activities.

[0011] "Transportation" refers to the means of transportation used by the user and their children to reach their destination.

[0012] "Source" refers to a medium that provides various information, such as an internet website or an internal database.

[0013] A "spot" refers to a specific place or facility that is chosen as a destination for outings.

[0014] "Activity" refers to specific activities and experiences you have while out and about.

[0015] "Profile" refers to data that compiles information about a user and their child.

[0016] "Filtering" refers to the process of selecting necessary information and excluding unnecessary information.

[0017] "Plan" refers to planning everything from choosing a destination to specific dates and routes.

[0018] "Feedback" refers to evaluations and opinions provided by users after they have gone out.

[0019] "System" refers to a series of mechanisms and programs that handle user information input, data search, plan generation, and feedback analysis. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] The system of the present invention suggests optimal outings and activities for children based on information entered by the user. The system includes a terminal that receives the user's input information, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[0042] 1. Basic configuration

[0043] Entering your user profile

[0044] The user activates the system and enters the child's age, interests, budget, and mode of transportation into a terminal, which then transmits this information to the server.

[0045] Profile analysis and database search

[0046] The server analyzes the received user profile, narrowing it down based on age, interests, budget, and mode of transportation, and then searches for relevant spots and activities from databases and internet sources.

[0047] Plan Generation

[0048] The server analyzes the search results and generates an optimal plan that takes into account budget and transportation options, including the names of specific spots, directions, travel time, financial costs, and details of activities that can be enjoyed within the spots.

[0049] Providing suggestions

[0050] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[0051] Gathering feedback and improving the system

[0052] After leaving the house, users input their feedback into their device and send it to the server, which analyzes it and uses it as data to improve the accuracy of future suggestions.

[0053] 2. Program Processing Overview

[0054] When the device sends the user profile to the server, the server first filters the target activities based on age information, lists spots and activities that are appropriate for the user's age, and then prioritizes the selected spots using interest information.

[0055] For example, if the user is targeting a 3-year-old child who loves trains, the server will search for railway museums, local train ride experiences, railway parks, etc. Among these spots, it will further narrow down the search to those that are reachable within the budget.

[0056] The generated plan includes specific directions (e.g., 30 minutes by train, 10 minutes by bus), admission fees (e.g., 1,000 yen for adults, free for children), and details of activities within the spot (e.g., mini train, driving simulator). This information is sent from the server to the terminal and displayed to the user.

[0057] The feedback provided by users after going out is an important factor in improving the system. The server receives this feedback and uses it to improve the accuracy of the database and the proposed algorithm.

[0058] 3. Specific Examples

[0059] Case study: Going out with a 3-year-old who loves trains

[0060] 1. The user launches the application and enters the following information into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," and "Method of transportation: Train."

[0061] 2. The device sends the profile to the server.

[0062] 3. The server parses the received information and searches for rail-related activity.

[0063] 4. The server retrieves candidates such as "Railway Museum," "Local Railway Ride Experience," and "Railway Park" from the database, and generates a specific plan for each candidate that takes into account transportation access and admission fees.

[0064] 5. The server sends the generated plan list to the terminal.

[0065] 6. The device displays the candidate plans to the user.

[0066] Example: "Railway Museum Plan"

[0067] Directions: 30 minutes by train, 10 minutes by bus

[0068] Admission fee: 1000 yen for adults, free for children

[0069] Activities: Mini train, driving simulator

[0070] 7. The user selects one of the proposed plans and plans their outing.

[0071] 8. After leaving the home, the user enters feedback into the application and sends it to the server.

[0072] 9. The server analyzes the feedback and uses it to improve the accuracy of future plan generation.

[0073] This invention allows parents to efficiently find suitable outings and plan trips that fit their children's interests, and also uses feedback to improve the accuracy of the system's suggestions.

[0074] The processing flow will be explained below.

[0075] Step 1:

[0076] The user launches the application and enters information such as the child's age, interests, budget, and mode of transportation into the input screen. This information is then saved on the device as a profile.

[0077] Step 2:

[0078] The terminal transmits the saved profile information to the server, where it is converted into a data format and transmitted.

[0079] Step 3:

[0080] The server analyzes the received profile information, which then filters recommended activities and places based on age and interests.

[0081] Step 4:

[0082] The server searches for relevant spot and activity information from internal databases and internet sources. The search results include details such as the spot name, address, directions, admission fees, and activity details.

[0083] Step 5:

[0084] The server generates multiple itineraries based on the search results, taking into account the user's budget and transportation options, with each itinerary including specific travel times, costs, and details of activities to enjoy.

[0085] Step 6:

[0086] The server sends the generated plans to the terminal, where the information is converted into a display format and sent.

[0087] Step 7:

[0088] The terminal displays the received plans to the user, who can then select the most suitable one from the presented plans.

[0089] Step 8:

[0090] After the trip, the user enters feedback into the application, including satisfaction with the trip, areas for improvement, and activities that were enjoyed.

[0091] Step 9:

[0092] The terminal transmits the collected feedback information to the server, which also converts the feedback information into a data format before transmitting it.

[0093] Step 10:

[0094] The server receives and analyzes the feedback information, and the results of the analysis are used to update the database and improve the plan generation algorithm.

[0095] This series of steps allows users to efficiently find outings that match their children's interests, and allows the server to continuously improve the accuracy of its suggestions.

[0096] Example 1

[0097] 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."

[0098] Conventional systems that suggest destinations and activities do not adequately consider the user's various information (age, interests, budget, mode of transportation), and therefore may not provide optimal suggestions. Furthermore, feedback functions to improve the accuracy of suggestions are often insufficient. Therefore, there is a need for a system that can analyze the user's input information in detail and provide specific and optimal plans.

[0099] 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.

[0100] In this invention, the server includes means for receiving information input by the user such as the user's age, interests, budget, and mode of transportation, means for searching for related place and activity information from various sources, and means for generating a plan suited to the user's interests based on the search results, thereby enabling the server to suggest destinations and activities optimized for the user's individual needs.

[0101] "User" refers to an individual who uses the system to input information to receive suggestions for destinations and activities.

[0102] "User age" refers to the age information of a child entered by a user as a basis for recommending specific destinations or activities.

[0103] "Interests" refers to the preferences and areas of interest of a user or their child that are taken into account when recommending a particular destination or activity.

[0104] A "budget" refers to a monetary limit that a user sets for a destination or activity.

[0105] "Transportation" refers to the transportation method (e.g., train, car, bus, etc.) that the user will use to reach the suggested destination or activity.

[0106] "Source" refers to a database or Internet resource that the server accesses to obtain relevant location or activity information.

[0107] "Place" refers to a specific geographic location or facility that is suggested as a destination.

[0108] "Activities" refers to specific activities and events that can be done while out and about.

[0109] "Plans" refers to detailed suggestions of destinations and activities generated based on the user's profile information.

[0110] "Feedback" refers to the experiences and opinions that users input into the system after actually going out.

[0111] "Accuracy" refers to a performance indicator that indicates how appropriate the destinations and activities provided by the system are in relation to the user's expectations and needs.

[0112] The system of the present invention aims to suggest optimal destinations and activities for children based on detailed information (age, interests, budget, and mode of transportation) entered by the user. The system is mainly composed of three elements: a terminal that receives user input, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[0113] Entering your user profile

[0114] The user launches the application and enters their child's age (e.g., 3 years old), interest (e.g., railways), budget (e.g., 5,000 yen), and mode of transportation (e.g., train) into the device. This information is sent from the device to the server. The input screen has a user-friendly UI design, providing easy-to-enter forms and drop-down menus.

[0115] Profile analysis and database search

[0116] The server analyzes the received profile information. The analytical tool used here is a generative AI model. Based on the analyzed profile information, a database of related places and activities is searched. For example, for a profile of a "3-year-old child who loves trains," the server retrieves information such as "railway museums" and "local train ride experiences" from the database.

[0117] Plan Generation

[0118] Based on the information acquired by the server, the optimal plan is generated, taking into account budget and means of transportation. This generation process also uses a generative AI model to build proposals optimized for the user profile. As a specific example, a "Railway Museum Plan" is generated. A specific example is shown below:

[0119] Railway Museum Plan

[0120] Directions: 30 minutes by train, 10 minutes by bus

[0121] Admission fee: 1000 yen for adults, free for children

[0122] Activities: Mini train, driving simulator

[0123] View Suggestions

[0124] The generated plan is sent from the server to the terminal, which then displays the plan to the user. A screen has been developed that displays the plan details in a visually easy-to-understand design.

[0125] Gathering feedback and improving the system

[0126] After leaving the facility, users enter their feedback into the device and send it to the server. Feedback is collected using evaluation forms and free-form comment fields. For example, users can enter specific impressions such as, "I had a lot of fun riding the miniature trains at the railway museum, but the driving simulator was out of order." This feedback is analyzed by the server and used as training data for the generative AI model, improving the accuracy of the system's suggestions.

[0127] Example prompt

[0128] Specific examples of prompts include:

[0129] "Age: 3 years old" "Interest: Trains" "Budget: 5,000 yen" "Method of transportation: Train"

[0130] In this way, the system receives and analyzes information from the user in a series of steps, and proposes the optimal outing plan. Subsequent feedback is collected and analyzed to continuously improve the accuracy of the system.

[0131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0132] Step 1:

[0133] The user starts the application and enters detailed information about their child (age, interests, budget, and mode of transportation). Specifically, they enter age "3 years old," interest "railway," budget "5,000 yen," and mode of transportation "train." This input is collected by the device and processed in the next step.

[0134] Input: Age, interests, budget, transportation information

[0135] Output: User profile data

[0136] Step 2:

[0137] The device sends the collected user profile data to the server. The data is encrypted and sent securely. Specifically, the device transfers the data using the HTTPS protocol.

[0138] Input: User profile data

[0139] Output: User profile data sent to the server

[0140] Step 3:

[0141] The server analyzes the received user profile data. A generative AI model is used here. The server analyzes each item in the profile (age, interests, budget, mode of transportation) and classifies it into a specific category. For example, an age of "3 years old" would be classified as "Toddlers," and an interest of "Railways" would be classified as "Transportation."

[0142] Input: User profile data

[0143] Output: Analyzed profile data (data classified by category)

[0144] Step 4:

[0145] The server searches the database based on the parsed profile data. During this search process, it retrieves information about related places and activities (e.g., railway museums, local train ride experiences). The server uses SQL queries to retrieve relevant entries from the database.

[0146] Input: Analyzed profile data

[0147] Output: Search results data (list of related places and activities)

[0148] Step 5:

[0149] The server generates the optimal plan based on the search results, taking into account budget and means of transportation. This generation process again uses the generative AI model to build a plan optimized for the user profile. As a specific example, a "Railway Museum Plan" is generated, which includes directions (30 minutes by train, 10 minutes by bus), admission fees (1,000 yen for adults, free for children), and activities (mini train, driving simulator).

[0150] Input: Search result data, generative AI model

[0151] Output: Optimal plan data

[0152] Step 6:

[0153] The server sends the generated plan to the device. During this process, the data is formatted and sent in a format that is easy for the user to view. The device uses responsive design to display the plan in a visually easy-to-understand layout for the user.

[0154] Input: Optimal plan data

[0155] Output: Plan data sent to the device

[0156] Step 7:

[0157] The user checks the generated plan and makes specific plans for the trip. After the trip, the user enters feedback into the application. The feedback input screen includes an evaluation form and a free-form comment field, where the user can enter their specific experiences and opinions.

[0158] Input: Feedback based on the user's actual experience

[0159] Output: Feedback data

[0160] Step 8:

[0161] The server analyzes the received feedback data. This analysis uses a generative AI model to evaluate the feedback data and use it to improve the accuracy of the next proposal. The server also updates the database and uses it for the next search and plan generation.

[0162] Input: Feedback data

[0163] Output: Updated database, training data for accuracy improvement

[0164] (Application example 1)

[0165] 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."

[0166] Modern parents face the challenge of finding the right destinations and activities for their children based on their interests, age, budget, and transportation. Particularly when planning activities in physical stores, it can be difficult to find the best options from the vast amount of information available, making it difficult to quickly obtain the right information. To solve this problem, a system is needed that automatically suggests the best physical store activities based on user-entered information.

[0167] 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.

[0168] In this invention, the server includes means for receiving information on the child's age, interests, budget, and transportation method input by the user, means for searching for related spot and activity information from various information sources, and means for generating a plan suited to the child's interests based on the search results. This makes it possible to suggest optimal activities at physical stores based on the profile information input by the user, and to generate and provide a detailed plan to the user.

[0169] "Means for receiving user-entered information on a child's age, interests, budget, and mode of transportation" refers to an interface that allows parents to use an application or device to enter their child's basic data and interests, the daily budget, and the mode of transportation they will use.

[0170] "Means for searching for relevant spot and activity information from various sources" refers to a function that utilizes the Internet, databases, and other information providing services to collect appropriate spot and activity information based on the profile entered by the user.

[0171] The "means of generating a plan suited to the child's interests based on the search results" refers to an algorithm that uses the collected information to select destinations and activities that are best suited to the child's age and interests, and creates a specific visiting plan.

[0172] The "means for providing the generated plan to the user" is a function for displaying the generated visiting plan and activity proposals on the user's terminal.

[0173] "Means for receiving feedback from users and improving the accuracy of the system" refers to a function that receives users' impressions and ratings of the activities they have actually undertaken and the spots they have visited, and uses this information to improve the system's suggestion algorithm.

[0174] The "means for suggesting activities at physical stores" is a function that selects activities that can be carried out at physical stores that can actually be visited from the collected activity information and suggests them to the user.

[0175] The "means for generating detailed plans for activities at physical stores and providing them to users" is a function for creating plans for selected physical store activities, including details such as specific visit schedules, access methods, and costs, and presenting these plans to users.

[0176] A system embodying the present invention is described in detail below.

[0177] Basic system configuration

[0178] 1. Enter your user profile

[0179] Users launch a smartphone application and enter information about their child's age, interests, budget, and mode of transportation, which is then sent from the device to the server.

[0180] 2. Profile analysis and database search

[0181] The server then parses the received user profile using a web framework called Flask, then searches an SQLite database and relevant sources on the internet to gather activity information based on age, interests, budget, and mode of transportation.

[0182] 3. Plan Generation

[0183] The server then generates a plan that best suits the user's profile based on the search results. This plan takes into account budget and transportation options, and focuses on activities at physical stores. The plan includes the names of destinations, directions, travel time, financial costs, and details of activities.

[0184] 4. Providing Proposals

[0185] The generated plan is sent to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[0186] 5. Gathering feedback and improving the system

[0187] After leaving the house, users input their feedback into their devices and send it to the server, which analyzes the feedback and uses the data to improve the system's suggestion algorithm.

[0188] Specific processing details

[0189] 1. Data Receipt and Analysis

[0190] The server receives user-submitted profile information using the Flask API, stores it in JSON format, and filters relevant activities based on a SQLite database.

[0191] 2. Searching and filtering information

[0192] The server queries an SQLite database to find activities appropriate for the child's age and interests, while also taking into account budget and transportation options. For example, it searches for activities that fit the criteria, such as "places within a bicycle ride for a 5-year-old child who loves animals and has a budget of under 3,000 yen."

[0193] 3. Plan Generation and Delivery

[0194] Based on the extracted activity information, a detailed itinerary is generated, including specific directions to the locations, costs, travel times, and details of the activities you can enjoy. The generated itinerary is then sent to the user's device in JSON format.

[0195] 4. Feedback Analysis

[0196] After going out based on the provided plan, the user provides feedback through the application, which is analyzed by the server to improve the accuracy of future recommendation algorithms.

[0197] Examples and prompts

[0198] For example, if a 5-year-old child loves animals, has a budget of 3,000 yen, and can travel within a cycling distance, the following information would be entered:

[0199] example:

[0200] UserProfile:

[0201] Age: 5

[0202] Interest: Animals

[0203] Budget: 3000

[0204] Transport: Bicycle

[0205] Proposed plan:

[0206] 1. Name: Zoo

[0207] Description: Animal interaction corner, penguin show

[0208] Cost: Admission - 500 yen for adults, 300 yen for children

[0209] Transportation: 15 minutes by bicycle

[0210] This allows users to quickly plan optimal outings and provide children with a fun experience that suits their interests.

[0211] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0212] Step 1:

[0213] The user launches a smartphone application and enters information about the child's age, interests, budget, and transportation method.

[0214] Input: Children's ages, interests, budget, transportation

[0215] Output: JSON format of the input data

[0216] What it does: A user uses a form in the application to enter details about their child, which are then sent to the server in JSON format.

[0217] Step 2:

[0218] The terminal transmits user data to the server.

[0219] Input: JSON data entered by the user

[0220] Output: Send data to the server

[0221] How it works: The smartphone sends user input information to an API endpoint over the Internet, using the Flask framework.

[0222] Step 3:

[0223] The server parses the received user data and retrieves the appropriate activity information from the SQLite database.

[0224] Input: User data in JSON format

[0225] Output: A list of activity information based on the user profile.

[0226] What it does: The server uses Flask to receive the JSON data and queries an SQLite database to filter activities based on age, interests, budget, and mode of transportation.

[0227] Step 4:

[0228] The server generates an appropriate plan.

[0229] Input: Filtered activity information

[0230] Output: A list of detailed visit plans

[0231] Specific Actions: The server creates a specific itinerary based on the search results, including location names, directions, travel time, costs, and activity details.

[0232] Step 5:

[0233] The server sends the generated plan to the terminal.

[0234] Input: List of detailed visit plans

[0235] Output: Send data to the user's terminal

[0236] Specific operation: The generated visit plan is sent from the server to the user's smartphone in JSON format. The Flask framework and REST API are used.

[0237] Step 6:

[0238] The terminal displays the proposed plan to the user.

[0239] Input: JSON data of detailed visit plan

[0240] Output: Plan information displayed on screen

[0241] Specific operation: The smartphone application extracts the visit plan from the received JSON data and displays it on the user interface.

[0242] Step 7:

[0243] Go out based on the plan selected by the user.

[0244] Input: Selected plan information

[0245] Output: Real-world outing experience

[0246] Specific behavior: Visit designated physical stores and activities according to the plan selected by the user.

[0247] Step 8:

[0248] Users provide feedback after their trip.

[0249] Input: Feedback information

[0250] Output: Send feedback data to the server

[0251] What happens: The user uses the feedback form within the application to enter and submit their thoughts and ratings about the activity they visited.

[0252] Step 9:

[0253] The server receives the feedback, stores it in a database and analyzes it.

[0254] Input: Feedback data

[0255] Output: Analysis results and system improvement data

[0256] How it works: The server receives the feedback data, analyzes it, and stores the results in a database to improve the accuracy of future activity suggestions.

[0257] 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.

[0258] The system of the present invention suggests optimal destinations and activities for children based on information entered by the user, and also has the ability to recognize the user's emotions and adjust suggestions based on those emotions. The system includes a terminal that receives the user's input information, a server that analyzes the information and recognizes emotions, and a network that exchanges information between the server and the terminal.

[0259] 1. Basic configuration

[0260] Entering your user profile

[0261] The user starts the system and enters information about their child's age, interests, budget, mode of transportation, and their own emotional state on the input screen. This information is then saved on the device as a profile.

[0262] Profile analysis and database search

[0263] The server then analyzes the received profile information, filtering recommended activities and places based on the child's age and interests.

[0264] Analysis by emotion engine

[0265] Furthermore, the server is equipped with an emotion engine that analyzes the user's emotion information and adjusts the proposed plan based on the emotion data entered by the user.

[0266] Database search

[0267] The server searches its internal database and internet sources for relevant spot and activity information, and the search results include details such as the spot name, address, directions, admission fees, and activity details.

[0268] Plan Generation

[0269] The server analyzes the search results and generates multiple itineraries, each including specific travel times, costs, and details of activities to enjoy, taking into account the user's budget, transportation options, and emotions identified by the emotion engine.

[0270] Providing suggestions

[0271] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[0272] Gathering feedback and improving the system

[0273] After leaving the house, the user inputs feedback into the device and sends it to the server. The server analyzes this feedback and uses it to improve the accuracy of the system. The feedback is also analyzed as emotional information to further improve the accuracy of the next suggestion.

[0274] 2. Program Processing Overview

[0275] When a device sends a user profile to the server, the server first analyzes the profile information, filters the target activities based on age information, and then prioritizes the selected spots using interest information.

[0276] In parallel, the emotion engine analyzes the emotion data entered by the user. The analysis results are reflected in the plan generation process, and suggestions appropriate to the user's emotional state are made.

[0277] For example, if the user is targeting a 3-year-old child who loves trains, the server will search for railway museums, local train ride experiences, railway parks, etc. Among these spots, it will further narrow down the search to those that are reachable within the budget.

[0278] The generated plan includes specific directions (e.g., 30 minutes by train, 10 minutes by bus), admission fees (e.g., 1,000 yen for adults, free for children), and details of activities within the spot (e.g., mini train, driving simulator). This information is sent from the server to the terminal and displayed to the user.

[0279] The feedback provided by users after going out is an important factor in improving the system. The server receives this feedback and uses it to improve the accuracy of the database and the proposal algorithm. The feedback also includes emotional information, which is reflected in the next proposal.

[0280] 3. Specific Examples

[0281] Case study: Going out with a 3-year-old who loves trains

[0282] 1. The user launches the application and enters the following into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," "Method of transportation: Train," and "Emotion: Feeling excited."

[0283] 2. The device sends the profile to the server.

[0284] 3. The server parses the received information and searches for rail-related activity.

[0285] 4. The server retrieves candidates such as "Railway Museum," "Local Railway Ride Experience," and "Railway Park" from the database, and generates a specific plan for each candidate that takes into account transportation access and admission fees.

[0286] 5. The server sends the generated plan list to the terminal.

[0287] 6. The device displays the candidate plans to the user.

[0288] Example: "Railway Museum Plan"

[0289] Directions: 30 minutes by train, 10 minutes by bus

[0290] Admission fee: 1000 yen for adults, free for children

[0291] Activities: Mini train, driving simulator

[0292] 7. The user selects one of the proposed plans and plans their outing.

[0293] 8. After leaving the home, the user inputs feedback into the application and sends it to the server. The feedback includes emotional information.

[0294] 9. The server analyzes the feedback and improves the accuracy of future suggestions.

[0295] This invention allows parents to efficiently find suitable outing destinations and plan trips that fit their children's interests. In addition, the introduction of an emotion engine allows for more appropriate suggestions based on the user's emotions.

[0296] The processing flow will be explained below.

[0297] Step 1:

[0298] The user launches the application and enters information about their child's age, interests, budget, mode of transportation, and current emotions (e.g., excited, tired, excited, etc.). This information is stored on the device as a profile.

[0299] Step 2:

[0300] The device sends the saved profile information to the server, which converts the profile information into a data format and sends it to the server via secure communication.

[0301] Step 3:

[0302] The server analyzes the received profile information, filtering recommended activities based on the child's age and using interest information to prioritize relevant activities and places.

[0303] Step 4:

[0304] The server uses an emotion engine to analyze the emotion data entered by the user. For example, if the user enters "fun," the server will prioritize plans that correspond to that emotion.

[0305] Step 5:

[0306] The server searches for relevant spot and activity information from internal databases and internet sources. The search results include details such as the spot name, address, directions, admission fees, and activity details.

[0307] Step 6:

[0308] The server generates multiple itineraries based on the search results, taking into account the user's budget, transportation options, and emotional information. Each itinerary includes specific travel times, costs, and details of activities that can be enjoyed.

[0309] Step 7:

[0310] The server sends the generated plans to the terminal, where the information is converted into a display format and sent in a format that is easy for the user to understand.

[0311] Step 8:

[0312] The terminal displays the received plans to the user, who can then select the most suitable one from the presented plans and plan their outing.

[0313] Step 9:

[0314] After the trip, users enter feedback into the application, including specific experiences, satisfaction, areas for improvement, and emotional information during the trip.

[0315] Step 10:

[0316] The terminal transmits the collected feedback information to the server, which also converts the feedback information into a data format before transmitting it.

[0317] Step 11:

[0318] The server receives and analyzes the feedback information. The analysis results are reflected in updating the database and improving the plan generation algorithm. In addition, the user's emotional information is used in the next proposal.

[0319] This series of steps allows users to efficiently find outings that match their child's interests and current emotions, and allows the server to continuously improve the accuracy of its suggestions.

[0320] Example 2

[0321] 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."

[0322] Conventional systems could suggest suitable outings and activities for children based on information entered by the user, but they did not provide suggestions that took into account the user's emotional information. As a result, they were unable to suggest optimal outings based on the user's emotions, making it difficult to improve the quality of the user experience. Furthermore, there was a lack of effort to collect feedback and use it to improve the accuracy of the system. This made it difficult to improve the accuracy of suggestions and user satisfaction.

[0323] 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.

[0324] In this invention, the server includes means for receiving information on the child's age, interests, budget, and mode of transportation input by the user, means for receiving user emotion information, means for analyzing the profile information and emotion information and prioritizing recommended activities and spots, means for searching for related spot and activity information from various information sources, means for generating a plan suited to the child's interests and the user's emotions based on the search results, means for providing the generated plan to the user, and means for receiving user feedback and improving the accuracy of the system. This makes it possible to suggest optimal destinations and activities taking the user's emotions into consideration, and realizes continuous improvement of the system's accuracy based on the feedback.

[0325] "User" refers to an individual who uses the system and enters information to find out about their child's outings and activities.

[0326] "Profile Information" refers to information entered by the user regarding their child's age, interests, budget, and transportation.

[0327] "Emotion information" refers to information input by the user about their own emotions and mental state.

[0328] "Server" refers to a computer system that receives profile information and emotion information, analyzes them, searches various information sources, generates an optimal plan, and provides it to the user.

[0329] "Filtering" refers to the process of selecting recommended activities and places based on profile information and sentiment information.

[0330] "Various sources" refers to internal databases and internet sources, including information on travel destinations and activities.

[0331] "Plan" refers to suggestions for destinations and activities generated based on the user's and children's interests, budget, emotions, and transportation options.

[0332] "Generation" refers to the server analyzing profile information and emotional information and creating plans for outings and activities based on that information.

[0333] "Feedback" refers to evaluations, impressions, and information for improvement of the system provided by users after going out.

[0334] "Improved accuracy" refers to using feedback to improve the system's suggestions and analytical capabilities, thereby increasing the quality of suggestions from the next time onwards.

[0335] The present invention is a system that suggests optimal destinations and activities for children based on information input by the user, such as their age, interests, budget, mode of transportation, and emotional state. The system includes a terminal that receives the information input by the user, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[0336] The user launches the application and enters the following information into the profile entry screen:

[0337] Child's age (e.g., 3 years old)

[0338] Interests (e.g., railways)

[0339] Budget (e.g. 5,000 yen)

[0340] Transportation (e.g. train)

[0341] Your (user's) emotional information (e.g., feeling excited)

[0342] The device receives this profile information and sends it to the server, which then performs the necessary analysis. Specifically, the server is equipped with a data analysis engine and an emotion engine, which perform detailed analysis of the profile information and emotion information.

[0343] Hardware and Software Used

[0344] Device: Input device such as smartphone, tablet, PC, etc.

[0345] Servers: Cloud computers and local servers

[0346] Analysis engine: Database management system, sentiment analysis model

[0347] Communication networks: Internet and local networks

[0348] Data processing and calculation

[0349] The server processes and calculates data in the following steps.

[0350] 1. Profile Analysis: A data analysis engine filters suitable activity suggestions based on age, interests, budget and mode of transportation.

[0351] 2. Emotion data analysis: The emotion engine analyzes the user's emotional information and reflects it in the proposed plan.

[0352] 3. Database Search: The server searches its internal database and internet sources for relevant spot and activity information, including spot names, addresses, directions, admission fees, and activity details.

[0353] 4. Plan Generation: Based on the search results, multiple plans are generated taking into account the user's budget, means of transportation, and emotions.

[0354] 5. Providing proposals: The generated plan is sent from the server to the terminal and displayed to the user.

[0355] 6. Collect feedback and improve the system's accuracy: After going out, users enter feedback, which is used to improve the accuracy of the next suggestion.

[0356] Specific examples

[0357] For example, if a user is looking for a place to go for their 3-year-old child who loves trains, the following process will be executed:

[0358] 1. The user launches the application and enters the following into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," "Method of transportation: Train," and "Emotion: Feeling excited."

[0359] 2. The device sends the profile information to the server.

[0360] 3. The server analyzes the profile and emotional information and searches a database for related spots and activities (e.g., railway museums, local railway ride experiences, railway parks).

[0361] 4. The server generates a specific plan (e.g., Railway Museum Plan - Directions: 30 minutes by train, 10 minutes by bus / Admission fee: 1,000 yen for adults, free for children / Activities: mini train, driving simulator).

[0362] 5. The device displays the proposed plan to the user.

[0363] 6. After the user leaves the house, they enter their feedback into the application and send it to the server, which improves the accuracy of suggestions for the next trip.

[0364] Prompt Sentence Examples

[0365] Below is an example of a prompt that the user can enter.

[0366] "Age: 3, Interests: Trains, Budget: 5,000 yen, Transportation: Train, Emotions: Feeling excited"

[0367] This allows users to efficiently find the perfect outing destination that matches their child's interests and their own emotions. The server uses the feedback to improve the accuracy of the system, and future suggestions will be more accurate.

[0368] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0369] Processing Steps

[0370] Step 1: Fill in your user profile

[0371] The user launches the application and enters their child's age, interests, budget, mode of transportation, and their own emotional information into the profile entry screen. The information entered is as follows:

[0372] Child's age: 3 years old

[0373] Interests: Railways

[0374] Budget: 5,000 yen

[0375] Means of transportation: train

[0376] Emotional information: Feeling excited

[0377] Input data: Child's age, interests, budget, transportation, emotional information

[0378] Output data: User profile information

[0379] Step 2: Sending the profile to the server

[0380] The device sends the user's profile information to the server via an HTTP request. The data includes the child's age, interests, budget, mode of transportation, and emotional information.

[0381] Input data: User profile information

[0382] Output data: Profile information sent to the server

[0383] Step 3: Parse the profile information

[0384] The server analyzes the received profile information, and a data analysis engine filters suitable activity suggestions based on age, interests, budget, and mode of transportation, generating a filtered list of activities as a result of the analysis.

[0385] Input data: Profile information sent to the server

[0386] Processing: Analyzes profile information and filters activity candidates

[0387] Output data: Filtered activity list

[0388] Step 4: Analyze the sentiment data

[0389] The emotion engine installed on the server analyzes the emotion data entered by the user, and the analysis results are taken into consideration when generating a plan based on the user's emotion.

[0390] Input data: User's emotional information

[0391] Processing content: Emotion data analysis

[0392] Output data: Sentiment analysis results

[0393] Step 5: Database Search

[0394] The server retrieves relevant spot and activity information from an internal database and various external sources, including spot names, addresses, directions, admission fees, and activity details.

[0395] Input data: filtered activity list, sentiment analysis results

[0396] Processing content: Database search, acquisition of related information

[0397] Output data: Detailed information about spots and activities

[0398] Step 6: Generate a plan

[0399] The server generates multiple plans based on the search results, taking into account the user's budget, transportation means, and emotions. Each plan includes details of specific transportation means, travel time, expenses, and activities that can be enjoyed.

[0400] Input data: detailed information on spots and activities, user budget and transportation method, sentiment analysis results

[0401] Process: Generate plan, create plan details

[0402] Output data: List of generated plans

[0403] Step 7: Provide a proposal

[0404] The server sends the generated plan list to the terminal, which receives it and displays it to the user. The user can then select the most suitable plan from the proposed plans.

[0405] Input data: List of generated plans

[0406] Output data: Plan list sent to the device, plans displayed to the user

[0407] Step 8: Gather feedback and refine the system

[0408] After leaving the house, the user enters feedback into the application and sends it to the server. The server receives this feedback and uses it to improve the accuracy of the system. The feedback also includes the user's emotional information, which is reflected in future suggestions.

[0409] Input data: User feedback and emotional information

[0410] Processing content: Analysis of feedback, updating system improvement algorithms

[0411] Output data: Proposed algorithm for updated system

[0412] Through the above processing steps, optimal destinations and activities are suggested to the user, and the accuracy of the system is continuously improved based on feedback.

[0413] (Application example 2)

[0414] 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."

[0415] Conventional food delivery services have had the challenge of being unable to recommend the best restaurant or meal based on a user's profile information. Furthermore, there are no systems that consider a user's emotional information when proposing recommended meals or restaurants. This has left users unable to choose the best delivery service that best suits their mood and needs at the time.

[0416] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information on the child's age, interests, budget, and mode of transportation input by the user, means for searching for related spot and activity information from various information sources, means for generating a plan suited to the child's interests based on the search results, means for providing the generated plan to the user, means for receiving feedback from the user and improving the accuracy of the system, and means for analyzing the user's emotional information and adjusting suggestions according to the user's emotional state. This enables the user to receive recommendations of restaurants and menus that are optimal for their current emotions and situation.

[0417] "User" means any person who uses the System and enters information.

[0418] "Child's age" is information that refers to the actual age of the child targeted by the system.

[0419] "Interests" refers to specific interests or hobbies that a child has.

[0420] "Budget" refers to information that indicates the upper limit of the amount of money that a user sets when using the system.

[0421] "Transportation" is information that indicates the transportation that the user uses to travel to the destination.

[0422] "Profile information" refers to comprehensive information entered by the user, such as the child's age, interests, budget, and mode of transportation, as well as the user's own emotional information.

[0423] "Emotion information" is information input by the user that indicates their current emotional state.

[0424] "Feedback" refers to information such as impressions and evaluations that users provide to the system after going out or making suggestions.

[0425] "Spot" refers to a specific destination or tourist spot that the system will suggest.

[0426] "Activity information" refers to information that indicates the activities that can be carried out at various spots provided by the system.

[0427] "Plan" refers to a system-generated plan that includes specific proposals and schedules.

[0428] "Search Tool" refers to the functionality for searching for relevant spot and activity information from external and internal databases.

[0429] "Analysis means" refers to a function for analyzing profile information and emotional information entered by a user.

[0430] "Proposal means" refers to the function for generating and providing the optimal plan to the user based on the analysis results.

[0431] "Feedback receiving means" refers to a function for receiving and analyzing feedback information provided by a user.

[0432] The "proposal adjustment means" refers to a function for adjusting the proposal content based on the user's emotional information.

[0433] The present invention relates to a system that proposes optimal food delivery plans based on a user's profile information and emotional information. This system recommends optimal restaurants and menus based on the user's input of information such as the age, interests, budget, mode of transportation, and emotional information about the child.

[0434] Basic system configuration

[0435] Entering your user profile

[0436] A user starts the application on a smartphone or tablet device and then enters user profile information (e.g., family composition, allergy information, budget, emotional information), which is then saved on the device as a profile.

[0437] Profile analysis and database search

[0438] The profile information entered by the user is sent to a server that uses the following hardware and software:

[0439] Hardware: Cloud-based servers (e.g., AWS)

[0440] Software: Database management system (e.g., MySQL, PostgreSQL), Rest API (e.g., Node.js, Express), Sentiment analysis engine (e.g., IBM Watson, Microsoft Azure Sentiment Analysis API)

[0441] The server first analyzes your profile information, filtering restaurant and menu recommendations based on your age and interests.

[0442] Analysis by emotion engine

[0443] The server's built-in emotion engine analyzes the user's emotional information. The results of this analysis are reflected in the plan generation process, and suggestions are made that are appropriate for the user's emotional state. For example, if the user inputs "I'm tired," restaurants and menus that offer a relaxing environment will be prioritized.

[0444] Database search

[0445] The server searches its internal database and internet sources for relevant restaurant and menu information. The search results include details such as restaurant name, address, dish description, price range, and customer reviews.

[0446] Plan Generation

[0447] The server analyzes the search results and generates multiple itineraries, each including specific transportation modes, prices, and meal details, taking into account the user's budget, transportation options, and emotions identified by the emotion engine.

[0448] Providing suggestions

[0449] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and order delivery.

[0450] Gathering feedback and improving the system

[0451] After placing an order, the user enters feedback into the device and sends it to the server. The server analyzes this feedback and uses it to improve the system's accuracy. The feedback is also analyzed for emotional information, further improving the accuracy of the next recommendation.

[0452] Specific examples

[0453] Case study: Relaxed family meal delivery

[0454] 1. A user launches the application and enters the following into their profile: Age: 35, Interests: Pizza, Budget: 3000 yen, Emotion: Tired.

[0455] 2. The device sends the profile to the server.

[0456] 3. The server analyzes the received information and searches for pizza-related restaurants.

[0457] 4. The server retrieves candidates such as "Pizza specialty store A," "Delivery pizza store B," and "Italian restaurant C" from the database, and generates specific plans for each candidate that take into account transportation access and price.

[0458] 5. The server sends the generated plan list to the terminal.

[0459] 6. The device displays the candidate plans to the user.

[0460] Example prompt for a generative AI model:

[0461] plaintext

[0462] Recommend a pizza restaurant within a budget of 3000 yen for a tired 35-year-old user. Please consider name-based information and prioritize restaurants that offer a particularly relaxing environment.

[0463] This system is expected to improve the quality of life by enabling users to easily find the best restaurant and menu that suits their current mood and situation.

[0464] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0465] Step 1:

[0466] The user launches the application and enters their profile information. Specifically, they use a smartphone or tablet to enter their age, interests, budget, mode of transportation, and emotional information. The input data is temporarily stored on the device for use in the next step. The output of the input process is the entire profile information entered by the user.

[0467] Step 2:

[0468] The device sends profile information to the server. This process is performed using an HTTP request, and the data sent is encoded in JSON format. The input is the user's profile information, and the output is the server receiving the profile information.

[0469] Step 3:

[0470] The server analyzes the received profile information. The hardware used by the pros is a cloud-based server, and the software used is, for example, Node.js. The analysis first filters target restaurants and menus based on age information. The input is the profile information, and the output is a list of filtered restaurants and menus.

[0471] Step 4:

[0472] The server uses a sentiment analysis engine to analyze the user's sentiment information. Specifically, it uses a sentiment analysis engine (e.g., IBM Watson, Microsoft Azure sentiment analysis API) to convert the sentiment information entered by the user into a text sentiment score. The input is the user's sentiment information, and the output is the sentiment analysis result. This analysis result is used in the next step.

[0473] Step 5:

[0474] The server searches for relevant restaurant and menu information from an internal database and internet sources. The software used is a database management system (e.g., MySQL, PostgreSQL). The input for the search is the filtered restaurant list and the sentiment analysis results, and the output is a list with detailed restaurant and menu information.

[0475] Step 6:

[0476] Based on the search results, the server generates multiple plans that take into account the user's budget, means of transportation, and emotional state. Plan generation combines information obtained from the database with the results of emotional analysis. Specifically, it selects restaurants and menus that are within the user's budget and sets recommendation levels according to their emotions. The input is a detailed list of restaurant and menu information, and the output is a list of plans to suggest to the user.

[0477] Step 7:

[0478] The server sends the generated plan list to the terminal. This process is again performed using an HTTP request, and the sent data is encoded in JSON format. The input is the generated plan list, and the output is the completion of sending it to the terminal.

[0479] Step 8:

[0480] The terminal displays the proposed plans to the user, and the user selects the most suitable one from the displayed plans. The input is the plan list sent from the server, and the output is the plan selected by the user.

[0481] Step 9:

[0482] After the user completes the trip or delivery, they input their feedback into the application. The feedback includes emotional information. The input is the user's feedback information and is saved on the device.

[0483] Step 10:

[0484] The device sends the feedback information to the server. The transmission is again performed using an HTTP request, and the transmitted data is encoded in JSON format. The input is the user's feedback information, and the output is the receipt of the feedback information by the server.

[0485] Step 11:

[0486] The server analyzes the feedback information to improve the accuracy of the system. The feedback also contains emotional information, which is reflected in the next suggestion. The input is the user's feedback information, and the output is an updated suggestion algorithm and database.

[0487] This processing flow allows users to easily find the best restaurant and menu that suits their current mood and situation, and the system's accuracy is continuously improved based on user feedback.

[0488] 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.

[0489] 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.

[0490] 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.

[0491] [Second embodiment]

[0492] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0493] 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.

[0494] 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).

[0495] 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.

[0496] 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.

[0497] 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).

[0498] 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.

[0499] 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.

[0500] 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.

[0501] 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.

[0502] 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.

[0503] 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."

[0504] The system of the present invention suggests optimal outings and activities for children based on information entered by the user. The system includes a terminal that receives the user's input information, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[0505] 1. Basic configuration

[0506] Entering your user profile

[0507] The user activates the system and enters the child's age, interests, budget, and mode of transportation into a terminal, which then transmits this information to the server.

[0508] Profile analysis and database search

[0509] The server analyzes the received user profile, narrowing it down based on age, interests, budget, and mode of transportation, and then searches for relevant spots and activities from databases and internet sources.

[0510] Plan Generation

[0511] The server analyzes the search results and generates an optimal plan that takes into account budget and transportation options, including the names of specific spots, directions, travel time, financial costs, and details of activities that can be enjoyed within the spots.

[0512] Providing suggestions

[0513] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[0514] Gathering feedback and improving the system

[0515] After leaving the house, users input their feedback into their device and send it to the server, which analyzes it and uses it as data to improve the accuracy of future suggestions.

[0516] 2. Program Processing Overview

[0517] When the device sends the user profile to the server, the server first filters the target activities based on age information, lists spots and activities that are appropriate for the user's age, and then prioritizes the selected spots using interest information.

[0518] For example, if the user is targeting a 3-year-old child who loves trains, the server will search for railway museums, local train ride experiences, railway parks, etc. Among these spots, it will further narrow down the search to those that are reachable within the budget.

[0519] The generated plan includes specific directions (e.g., 30 minutes by train, 10 minutes by bus), admission fees (e.g., 1,000 yen for adults, free for children), and details of activities within the spot (e.g., mini train, driving simulator). This information is sent from the server to the terminal and displayed to the user.

[0520] The feedback provided by users after going out is an important factor in improving the system. The server receives this feedback and uses it to improve the accuracy of the database and the proposed algorithm.

[0521] 3. Specific Examples

[0522] Case study: Going out with a 3-year-old who loves trains

[0523] 1. The user launches the application and enters the following information into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," and "Method of transportation: Train."

[0524] 2. The device sends the profile to the server.

[0525] 3. The server parses the received information and searches for rail-related activity.

[0526] 4. The server retrieves candidates such as "Railway Museum," "Local Railway Ride Experience," and "Railway Park" from the database, and generates a specific plan for each candidate that takes into account transportation access and admission fees.

[0527] 5. The server sends the generated plan list to the terminal.

[0528] 6. The device displays the candidate plans to the user.

[0529] Example: "Railway Museum Plan"

[0530] Directions: 30 minutes by train, 10 minutes by bus

[0531] Admission fee: 1000 yen for adults, free for children

[0532] Activities: Mini train, driving simulator

[0533] 7. The user selects one of the proposed plans and plans their outing.

[0534] 8. After leaving the home, the user enters feedback into the application and sends it to the server.

[0535] 9. The server analyzes the feedback and uses it to improve the accuracy of future plan generation.

[0536] This invention allows parents to efficiently find suitable outings and plan trips that fit their children's interests, and also uses feedback to improve the accuracy of the system's suggestions.

[0537] The processing flow will be explained below.

[0538] Step 1:

[0539] The user launches the application and enters information such as the child's age, interests, budget, and mode of transportation into the input screen. This information is then saved on the device as a profile.

[0540] Step 2:

[0541] The terminal transmits the saved profile information to the server, where it is converted into a data format and transmitted.

[0542] Step 3:

[0543] The server analyzes the received profile information, which then filters recommended activities and places based on age and interests.

[0544] Step 4:

[0545] The server searches for relevant spot and activity information from internal databases and internet sources. The search results include details such as the spot name, address, directions, admission fees, and activity details.

[0546] Step 5:

[0547] The server generates multiple itineraries based on the search results, taking into account the user's budget and transportation options, with each itinerary including specific travel times, costs, and details of activities to enjoy.

[0548] Step 6:

[0549] The server sends the generated plans to the terminal, where the information is converted into a display format and sent.

[0550] Step 7:

[0551] The terminal displays the received plans to the user, who can then select the most suitable one from the presented plans.

[0552] Step 8:

[0553] After the trip, the user enters feedback into the application, including satisfaction with the trip, areas for improvement, and activities that were enjoyed.

[0554] Step 9:

[0555] The terminal transmits the collected feedback information to the server, which also converts the feedback information into a data format before transmitting it.

[0556] Step 10:

[0557] The server receives and analyzes the feedback information, and the results of the analysis are used to update the database and improve the plan generation algorithm.

[0558] This series of steps allows users to efficiently find outings that match their children's interests, and allows the server to continuously improve the accuracy of its suggestions.

[0559] Example 1

[0560] 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."

[0561] Conventional systems that suggest destinations and activities do not adequately consider the user's various information (age, interests, budget, mode of transportation), and therefore may not provide optimal suggestions. Furthermore, feedback functions to improve the accuracy of suggestions are often insufficient. Therefore, there is a need for a system that can analyze the user's input information in detail and provide specific and optimal plans.

[0562] 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.

[0563] In this invention, the server includes means for receiving information input by the user such as the user's age, interests, budget, and mode of transportation, means for searching for related place and activity information from various sources, and means for generating a plan suited to the user's interests based on the search results, thereby enabling the server to suggest destinations and activities optimized for the user's individual needs.

[0564] "User" refers to an individual who uses the system to input information to receive suggestions for destinations and activities.

[0565] "User age" refers to the age information of a child entered by a user as a basis for recommending specific destinations or activities.

[0566] "Interests" refers to the preferences and areas of interest of a user or their child that are taken into account when recommending a particular destination or activity.

[0567] A "budget" refers to a monetary limit that a user sets for a destination or activity.

[0568] "Transportation" refers to the transportation method (e.g., train, car, bus, etc.) that the user will use to reach the suggested destination or activity.

[0569] "Source" refers to a database or Internet resource that the server accesses to obtain relevant location or activity information.

[0570] "Place" refers to a specific geographic location or facility that is suggested as a destination.

[0571] "Activities" refers to specific activities and events that can be done while out and about.

[0572] "Plans" refers to detailed suggestions of destinations and activities generated based on the user's profile information.

[0573] "Feedback" refers to the experiences and opinions that users input into the system after actually going out.

[0574] "Accuracy" refers to a performance indicator that indicates how appropriate the destinations and activities provided by the system are in relation to the user's expectations and needs.

[0575] The system of the present invention aims to suggest optimal destinations and activities for children based on detailed information (age, interests, budget, and mode of transportation) entered by the user. The system is mainly composed of three elements: a terminal that receives user input, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[0576] Entering your user profile

[0577] The user launches the application and enters their child's age (e.g., 3 years old), interest (e.g., railways), budget (e.g., 5,000 yen), and mode of transportation (e.g., train) into the device. This information is sent from the device to the server. The input screen has a user-friendly UI design, providing easy-to-enter forms and drop-down menus.

[0578] Profile analysis and database search

[0579] The server analyzes the received profile information. The analytical tool used here is a generative AI model. Based on the analyzed profile information, a database of related places and activities is searched. For example, for a profile of a "3-year-old child who loves trains," the server retrieves information such as "railway museums" and "local train ride experiences" from the database.

[0580] Plan Generation

[0581] Based on the information acquired by the server, the optimal plan is generated, taking into account budget and means of transportation. This generation process also uses a generative AI model to build proposals optimized for the user profile. As a specific example, a "Railway Museum Plan" is generated. A specific example is shown below:

[0582] Railway Museum Plan

[0583] Directions: 30 minutes by train, 10 minutes by bus

[0584] Admission fee: 1000 yen for adults, free for children

[0585] Activities: Mini train, driving simulator

[0586] View Suggestions

[0587] The generated plan is sent from the server to the terminal, which then displays the plan to the user. A screen has been developed that displays the plan details in a visually easy-to-understand design.

[0588] Gathering feedback and improving the system

[0589] After leaving the facility, users enter their feedback into the device and send it to the server. Feedback is collected using evaluation forms and free-form comment fields. For example, users can enter specific impressions such as, "I had a lot of fun riding the miniature trains at the railway museum, but the driving simulator was out of order." This feedback is analyzed by the server and used as training data for the generative AI model, improving the accuracy of the system's suggestions.

[0590] Example prompt

[0591] Specific examples of prompts include:

[0592] "Age: 3 years old" "Interest: Trains" "Budget: 5,000 yen" "Method of transportation: Train"

[0593] In this way, the system receives and analyzes information from the user in a series of steps, and proposes the optimal outing plan. Subsequent feedback is collected and analyzed to continuously improve the accuracy of the system.

[0594] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0595] Step 1:

[0596] The user starts the application and enters detailed information about their child (age, interests, budget, and mode of transportation). Specifically, they enter age "3 years old," interest "railway," budget "5,000 yen," and mode of transportation "train." This input is collected by the device and processed in the next step.

[0597] Input: Age, interests, budget, transportation information

[0598] Output: User profile data

[0599] Step 2:

[0600] The device sends the collected user profile data to the server. The data is encrypted and sent securely. Specifically, the device transfers the data using the HTTPS protocol.

[0601] Input: User profile data

[0602] Output: User profile data sent to the server

[0603] Step 3:

[0604] The server analyzes the received user profile data. A generative AI model is used here. The server analyzes each item in the profile (age, interests, budget, mode of transportation) and classifies it into a specific category. For example, an age of "3 years old" would be classified as "Toddlers," and an interest of "Railways" would be classified as "Transportation."

[0605] Input: User profile data

[0606] Output: Analyzed profile data (data classified by category)

[0607] Step 4:

[0608] The server searches the database based on the parsed profile data. During this search process, it retrieves information about related places and activities (e.g., railway museums, local train ride experiences). The server uses SQL queries to retrieve relevant entries from the database.

[0609] Input: Analyzed profile data

[0610] Output: Search results data (list of related places and activities)

[0611] Step 5:

[0612] The server generates the optimal plan based on the search results, taking into account budget and means of transportation. This generation process again uses the generative AI model to build a plan optimized for the user profile. As a specific example, a "Railway Museum Plan" is generated, which includes directions (30 minutes by train, 10 minutes by bus), admission fees (1,000 yen for adults, free for children), and activities (mini train, driving simulator).

[0613] Input: Search result data, generative AI model

[0614] Output: Optimal plan data

[0615] Step 6:

[0616] The server sends the generated plan to the device. During this process, the data is formatted and sent in a format that is easy for the user to view. The device uses responsive design to display the plan in a visually easy-to-understand layout for the user.

[0617] Input: Optimal plan data

[0618] Output: Plan data sent to the device

[0619] Step 7:

[0620] The user checks the generated plan and makes specific plans for the trip. After the trip, the user enters feedback into the application. The feedback input screen includes an evaluation form and a free-form comment field, where the user can enter their specific experiences and opinions.

[0621] Input: Feedback based on the user's actual experience

[0622] Output: Feedback data

[0623] Step 8:

[0624] The server analyzes the received feedback data. This analysis uses a generative AI model to evaluate the feedback data and use it to improve the accuracy of the next proposal. The server also updates the database and uses it for the next search and plan generation.

[0625] Input: Feedback data

[0626] Output: Updated database, training data for accuracy improvement

[0627] (Application example 1)

[0628] 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."

[0629] Modern parents face the challenge of finding the right destinations and activities for their children based on their interests, age, budget, and transportation. Particularly when planning activities in physical stores, it can be difficult to find the best options from the vast amount of information available, making it difficult to quickly obtain the right information. To solve this problem, a system is needed that automatically suggests the best physical store activities based on user-entered information.

[0630] 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.

[0631] In this invention, the server includes means for receiving information on the child's age, interests, budget, and transportation method input by the user, means for searching for related spot and activity information from various information sources, and means for generating a plan suited to the child's interests based on the search results. This makes it possible to suggest optimal activities at physical stores based on the profile information input by the user, and to generate and provide a detailed plan to the user.

[0632] "Means for receiving user-entered information on a child's age, interests, budget, and mode of transportation" refers to an interface that allows parents to use an application or device to enter their child's basic data and interests, the daily budget, and the mode of transportation they will use.

[0633] "Means for searching for relevant spot and activity information from various sources" refers to a function that utilizes the Internet, databases, and other information providing services to collect appropriate spot and activity information based on the profile entered by the user.

[0634] The "means of generating a plan suited to the child's interests based on the search results" refers to an algorithm that uses the collected information to select destinations and activities that are best suited to the child's age and interests, and creates a specific visiting plan.

[0635] The "means for providing the generated plan to the user" is a function for displaying the generated visiting plan and activity proposals on the user's terminal.

[0636] "Means for receiving feedback from users and improving the accuracy of the system" refers to a function that receives users' impressions and ratings of the activities they have actually undertaken and the spots they have visited, and uses this information to improve the system's suggestion algorithm.

[0637] The "means for suggesting activities at physical stores" is a function that selects activities that can be carried out at physical stores that can actually be visited from the collected activity information and suggests them to the user.

[0638] The "means for generating detailed plans for activities at physical stores and providing them to users" is a function for creating plans for selected physical store activities, including details such as specific visit schedules, access methods, and costs, and presenting these plans to users.

[0639] A system embodying the present invention is described in detail below.

[0640] Basic system configuration

[0641] 1. Enter your user profile

[0642] Users launch a smartphone application and enter information about their child's age, interests, budget, and mode of transportation, which is then sent from the device to the server.

[0643] 2. Profile analysis and database search

[0644] The server then parses the received user profile using a web framework called Flask, then searches an SQLite database and relevant sources on the internet to gather activity information based on age, interests, budget, and mode of transportation.

[0645] 3. Plan Generation

[0646] The server then generates a plan that best suits the user's profile based on the search results. This plan takes into account budget and transportation options, and focuses on activities at physical stores. The plan includes the names of destinations, directions, travel time, financial costs, and details of activities.

[0647] 4. Providing Proposals

[0648] The generated plan is sent to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[0649] 5. Gathering feedback and improving the system

[0650] After leaving the house, users input their feedback into their devices and send it to the server, which analyzes the feedback and uses the data to improve the system's suggestion algorithm.

[0651] Specific processing details

[0652] 1. Data Receipt and Analysis

[0653] The server receives user-submitted profile information using the Flask API, stores it in JSON format, and filters relevant activities based on a SQLite database.

[0654] 2. Searching and filtering information

[0655] The server queries an SQLite database to find activities appropriate for the child's age and interests, while also taking into account budget and transportation options. For example, it searches for activities that fit the criteria, such as "places within a bicycle ride for a 5-year-old child who loves animals and has a budget of under 3,000 yen."

[0656] 3. Plan Generation and Delivery

[0657] Based on the extracted activity information, a detailed itinerary is generated, including specific directions to the locations, costs, travel times, and details of the activities you can enjoy. The generated itinerary is then sent to the user's device in JSON format.

[0658] 4. Feedback Analysis

[0659] After going out based on the provided plan, the user provides feedback through the application, which is analyzed by the server to improve the accuracy of future recommendation algorithms.

[0660] Examples and prompts

[0661] For example, if a 5-year-old child loves animals, has a budget of 3,000 yen, and can travel within a cycling distance, the following information would be entered:

[0662] example:

[0663] UserProfile:

[0664] Age: 5

[0665] Interest: Animals

[0666] Budget: 3000

[0667] Transport: Bicycle

[0668] Proposed plan:

[0669] 1. Name: Zoo

[0670] Description: Animal interaction corner, penguin show

[0671] Cost: Admission - 500 yen for adults, 300 yen for children

[0672] Transportation: 15 minutes by bicycle

[0673] This allows users to quickly plan optimal outings and provide children with a fun experience that suits their interests.

[0674] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0675] Step 1:

[0676] The user launches a smartphone application and enters information about the child's age, interests, budget, and transportation method.

[0677] Input: Children's ages, interests, budget, transportation

[0678] Output: JSON format of the input data

[0679] What it does: A user uses a form in the application to enter details about their child, which are then sent to the server in JSON format.

[0680] Step 2:

[0681] The terminal transmits user data to the server.

[0682] Input: JSON data entered by the user

[0683] Output: Send data to the server

[0684] How it works: The smartphone sends user input information to an API endpoint over the Internet, using the Flask framework.

[0685] Step 3:

[0686] The server parses the received user data and retrieves the appropriate activity information from the SQLite database.

[0687] Input: User data in JSON format

[0688] Output: A list of activity information based on the user profile.

[0689] What it does: The server uses Flask to receive the JSON data and queries an SQLite database to filter activities based on age, interests, budget, and mode of transportation.

[0690] Step 4:

[0691] The server generates an appropriate plan.

[0692] Input: Filtered activity information

[0693] Output: A list of detailed visit plans

[0694] Specific Actions: The server creates a specific itinerary based on the search results, including location names, directions, travel time, costs, and activity details.

[0695] Step 5:

[0696] The server sends the generated plan to the terminal.

[0697] Input: List of detailed visit plans

[0698] Output: Send data to the user's terminal

[0699] Specific operation: The generated visit plan is sent from the server to the user's smartphone in JSON format. The Flask framework and REST API are used.

[0700] Step 6:

[0701] The terminal displays the proposed plan to the user.

[0702] Input: JSON data of detailed visit plan

[0703] Output: Plan information displayed on screen

[0704] Specific operation: The smartphone application extracts the visit plan from the received JSON data and displays it on the user interface.

[0705] Step 7:

[0706] Go out based on the plan selected by the user.

[0707] Input: Selected plan information

[0708] Output: Real-world outing experience

[0709] Specific behavior: Visit designated physical stores and activities according to the plan selected by the user.

[0710] Step 8:

[0711] Users provide feedback after their trip.

[0712] Input: Feedback information

[0713] Output: Send feedback data to the server

[0714] What happens: The user uses the feedback form within the application to enter and submit their thoughts and ratings about the activity they visited.

[0715] Step 9:

[0716] The server receives the feedback, stores it in a database and analyzes it.

[0717] Input: Feedback data

[0718] Output: Analysis results and system improvement data

[0719] How it works: The server receives the feedback data, analyzes it, and stores the results in a database to improve the accuracy of future activity suggestions.

[0720] 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.

[0721] The system of the present invention suggests optimal destinations and activities for children based on information entered by the user, and also has the ability to recognize the user's emotions and adjust suggestions based on those emotions. The system includes a terminal that receives the user's input information, a server that analyzes the information and recognizes emotions, and a network that exchanges information between the server and the terminal.

[0722] 1. Basic configuration

[0723] Entering your user profile

[0724] The user starts the system and enters information about their child's age, interests, budget, mode of transportation, and their own emotional state on the input screen. This information is then saved on the device as a profile.

[0725] Profile analysis and database search

[0726] The server then analyzes the received profile information, filtering recommended activities and places based on the child's age and interests.

[0727] Analysis by emotion engine

[0728] Furthermore, the server is equipped with an emotion engine that analyzes the user's emotion information and adjusts the proposed plan based on the emotion data entered by the user.

[0729] Database search

[0730] The server searches its internal database and internet sources for relevant spot and activity information, and the search results include details such as the spot name, address, directions, admission fees, and activity details.

[0731] Plan Generation

[0732] The server analyzes the search results and generates multiple itineraries, each including specific travel times, costs, and details of activities to enjoy, taking into account the user's budget, transportation options, and emotions identified by the emotion engine.

[0733] Providing suggestions

[0734] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[0735] Gathering feedback and improving the system

[0736] After leaving the house, the user inputs feedback into the device and sends it to the server. The server analyzes this feedback and uses it to improve the accuracy of the system. The feedback is also analyzed as emotional information to further improve the accuracy of the next suggestion.

[0737] 2. Program Processing Overview

[0738] When a device sends a user profile to the server, the server first analyzes the profile information, filters the target activities based on age information, and then prioritizes the selected spots using interest information.

[0739] In parallel, the emotion engine analyzes the emotion data entered by the user. The analysis results are reflected in the plan generation process, and suggestions appropriate to the user's emotional state are made.

[0740] For example, if the user is targeting a 3-year-old child who loves trains, the server will search for railway museums, local train ride experiences, railway parks, etc. Among these spots, it will further narrow down the search to those that are reachable within the budget.

[0741] The generated plan includes specific directions (e.g., 30 minutes by train, 10 minutes by bus), admission fees (e.g., 1,000 yen for adults, free for children), and details of activities within the spot (e.g., mini train, driving simulator). This information is sent from the server to the terminal and displayed to the user.

[0742] The feedback provided by users after going out is an important factor in improving the system. The server receives this feedback and uses it to improve the accuracy of the database and the proposal algorithm. The feedback also includes emotional information, which is reflected in the next proposal.

[0743] 3. Specific Examples

[0744] Case study: Going out with a 3-year-old who loves trains

[0745] 1. The user launches the application and enters the following into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," "Method of transportation: Train," and "Emotion: Feeling excited."

[0746] 2. The device sends the profile to the server.

[0747] 3. The server parses the received information and searches for rail-related activity.

[0748] 4. The server retrieves candidates such as "Railway Museum," "Local Railway Ride Experience," and "Railway Park" from the database, and generates a specific plan for each candidate that takes into account transportation access and admission fees.

[0749] 5. The server sends the generated plan list to the terminal.

[0750] 6. The device displays the candidate plans to the user.

[0751] Example: "Railway Museum Plan"

[0752] Directions: 30 minutes by train, 10 minutes by bus

[0753] Admission fee: 1000 yen for adults, free for children

[0754] Activities: Mini train, driving simulator

[0755] 7. The user selects one of the proposed plans and plans their outing.

[0756] 8. After leaving the home, the user inputs feedback into the application and sends it to the server. The feedback includes emotional information.

[0757] 9. The server analyzes the feedback and improves the accuracy of future suggestions.

[0758] This invention allows parents to efficiently find suitable outing destinations and plan trips that fit their children's interests. In addition, the introduction of an emotion engine allows for more appropriate suggestions based on the user's emotions.

[0759] The processing flow will be explained below.

[0760] Step 1:

[0761] The user launches the application and enters information about their child's age, interests, budget, mode of transportation, and current emotions (e.g., excited, tired, excited, etc.). This information is stored on the device as a profile.

[0762] Step 2:

[0763] The device sends the saved profile information to the server, which converts the profile information into a data format and sends it to the server via secure communication.

[0764] Step 3:

[0765] The server analyzes the received profile information, filtering recommended activities based on the child's age and using interest information to prioritize relevant activities and places.

[0766] Step 4:

[0767] The server uses an emotion engine to analyze the emotion data entered by the user. For example, if the user enters "fun," the server will prioritize plans that correspond to that emotion.

[0768] Step 5:

[0769] The server searches for relevant spot and activity information from internal databases and internet sources. The search results include details such as the spot name, address, directions, admission fees, and activity details.

[0770] Step 6:

[0771] The server generates multiple itineraries based on the search results, taking into account the user's budget, transportation options, and emotional information. Each itinerary includes specific travel times, costs, and details of activities that can be enjoyed.

[0772] Step 7:

[0773] The server sends the generated plans to the terminal, where the information is converted into a display format and sent in a format that is easy for the user to understand.

[0774] Step 8:

[0775] The terminal displays the received plans to the user, who can then select the most suitable one from the presented plans and plan their outing.

[0776] Step 9:

[0777] After the trip, users enter feedback into the application, including specific experiences, satisfaction, areas for improvement, and emotional information during the trip.

[0778] Step 10:

[0779] The terminal transmits the collected feedback information to the server, which also converts the feedback information into a data format before transmitting it.

[0780] Step 11:

[0781] The server receives and analyzes the feedback information. The analysis results are reflected in updating the database and improving the plan generation algorithm. In addition, the user's emotional information is used in the next proposal.

[0782] This series of steps allows users to efficiently find outings that match their child's interests and current emotions, and allows the server to continuously improve the accuracy of its suggestions.

[0783] Example 2

[0784] 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."

[0785] Conventional systems could suggest suitable outings and activities for children based on information entered by the user, but they did not provide suggestions that took into account the user's emotional information. As a result, they were unable to suggest optimal outings based on the user's emotions, making it difficult to improve the quality of the user experience. Furthermore, there was a lack of effort to collect feedback and use it to improve the accuracy of the system. This made it difficult to improve the accuracy of suggestions and user satisfaction.

[0786] 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.

[0787] In this invention, the server includes means for receiving information on the child's age, interests, budget, and mode of transportation input by the user, means for receiving user emotion information, means for analyzing the profile information and emotion information and prioritizing recommended activities and spots, means for searching for related spot and activity information from various information sources, means for generating a plan suited to the child's interests and the user's emotions based on the search results, means for providing the generated plan to the user, and means for receiving user feedback and improving the accuracy of the system. This makes it possible to suggest optimal destinations and activities taking the user's emotions into consideration, and realizes continuous improvement of the system's accuracy based on the feedback.

[0788] "User" refers to an individual who uses the system and enters information to find out about their child's outings and activities.

[0789] "Profile Information" refers to information entered by the user regarding their child's age, interests, budget, and transportation.

[0790] "Emotion information" refers to information input by the user about their own emotions and mental state.

[0791] "Server" refers to a computer system that receives profile information and emotion information, analyzes them, searches various information sources, generates an optimal plan, and provides it to the user.

[0792] "Filtering" refers to the process of selecting recommended activities and places based on profile information and sentiment information.

[0793] "Various sources" refers to internal databases and internet sources, including information on travel destinations and activities.

[0794] "Plan" refers to suggestions for destinations and activities generated based on the user's and children's interests, budget, emotions, and transportation options.

[0795] "Generation" refers to the server analyzing profile information and emotional information and creating plans for outings and activities based on that information.

[0796] "Feedback" refers to evaluations, impressions, and information for improvement of the system provided by users after going out.

[0797] "Improved accuracy" refers to using feedback to improve the system's suggestions and analytical capabilities, thereby increasing the quality of suggestions from the next time onwards.

[0798] The present invention is a system that suggests optimal destinations and activities for children based on information input by the user, such as their age, interests, budget, mode of transportation, and emotional state. The system includes a terminal that receives the information input by the user, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[0799] The user launches the application and enters the following information into the profile entry screen:

[0800] Child's age (e.g., 3 years old)

[0801] Interests (e.g., railways)

[0802] Budget (e.g. 5,000 yen)

[0803] Transportation (e.g. train)

[0804] Your (user's) emotional information (e.g., feeling excited)

[0805] The device receives this profile information and sends it to the server, which then performs the necessary analysis. Specifically, the server is equipped with a data analysis engine and an emotion engine, which perform detailed analysis of the profile information and emotion information.

[0806] Hardware and Software Used

[0807] Device: Input device such as smartphone, tablet, PC, etc.

[0808] Servers: Cloud computers and local servers

[0809] Analysis engine: Database management system, sentiment analysis model

[0810] Communication networks: Internet and local networks

[0811] Data processing and calculation

[0812] The server processes and calculates data in the following steps.

[0813] 1. Profile Analysis: A data analysis engine filters suitable activity suggestions based on age, interests, budget and mode of transportation.

[0814] 2. Emotion data analysis: The emotion engine analyzes the user's emotional information and reflects it in the proposed plan.

[0815] 3. Database Search: The server searches its internal database and internet sources for relevant spot and activity information, including spot names, addresses, directions, admission fees, and activity details.

[0816] 4. Plan Generation: Based on the search results, multiple plans are generated taking into account the user's budget, means of transportation, and emotions.

[0817] 5. Providing proposals: The generated plan is sent from the server to the terminal and displayed to the user.

[0818] 6. Collect feedback and improve the system's accuracy: After going out, users enter feedback, which is used to improve the accuracy of the next suggestion.

[0819] Specific examples

[0820] For example, if a user is looking for a place to go for their 3-year-old child who loves trains, the following process will be executed:

[0821] 1. The user launches the application and enters the following into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," "Method of transportation: Train," and "Emotion: Feeling excited."

[0822] 2. The device sends the profile information to the server.

[0823] 3. The server analyzes the profile and emotional information and searches a database for related spots and activities (e.g., railway museums, local railway ride experiences, railway parks).

[0824] 4. The server generates a specific plan (e.g., Railway Museum Plan - Directions: 30 minutes by train, 10 minutes by bus / Admission fee: 1,000 yen for adults, free for children / Activities: mini train, driving simulator).

[0825] 5. The device displays the proposed plan to the user.

[0826] 6. After the user leaves the house, they enter their feedback into the application and send it to the server, which improves the accuracy of suggestions for the next trip.

[0827] Prompt Sentence Examples

[0828] Below is an example of a prompt that the user can enter.

[0829] "Age: 3, Interests: Trains, Budget: 5,000 yen, Transportation: Train, Emotions: Feeling excited"

[0830] This allows users to efficiently find the perfect outing destination that matches their child's interests and their own emotions. The server uses the feedback to improve the accuracy of the system, and future suggestions will be more accurate.

[0831] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0832] Processing Steps

[0833] Step 1: Fill in your user profile

[0834] The user launches the application and enters their child's age, interests, budget, mode of transportation, and their own emotional information into the profile entry screen. The information entered is as follows:

[0835] Child's age: 3 years old

[0836] Interests: Railways

[0837] Budget: 5,000 yen

[0838] Means of transportation: train

[0839] Emotional information: Feeling excited

[0840] Input data: Child's age, interests, budget, transportation, emotional information

[0841] Output data: User profile information

[0842] Step 2: Sending the profile to the server

[0843] The device sends the user's profile information to the server via an HTTP request. The data includes the child's age, interests, budget, mode of transportation, and emotional information.

[0844] Input data: User profile information

[0845] Output data: Profile information sent to the server

[0846] Step 3: Parse the profile information

[0847] The server analyzes the received profile information, and a data analysis engine filters suitable activity suggestions based on age, interests, budget, and mode of transportation, generating a filtered list of activities as a result of the analysis.

[0848] Input data: Profile information sent to the server

[0849] Processing: Analyzes profile information and filters activity candidates

[0850] Output data: Filtered activity list

[0851] Step 4: Analyze the sentiment data

[0852] The emotion engine installed on the server analyzes the emotion data entered by the user, and the analysis results are taken into consideration when generating a plan based on the user's emotion.

[0853] Input data: User's emotional information

[0854] Processing content: Emotion data analysis

[0855] Output data: Sentiment analysis results

[0856] Step 5: Database Search

[0857] The server retrieves relevant spot and activity information from an internal database and various external sources, including spot names, addresses, directions, admission fees, and activity details.

[0858] Input data: filtered activity list, sentiment analysis results

[0859] Processing content: Database search, acquisition of related information

[0860] Output data: Detailed information about spots and activities

[0861] Step 6: Generate a plan

[0862] The server generates multiple plans based on the search results, taking into account the user's budget, transportation means, and emotions. Each plan includes details of specific transportation means, travel time, expenses, and activities that can be enjoyed.

[0863] Input data: detailed information on spots and activities, user budget and transportation method, sentiment analysis results

[0864] Process: Generate plan, create plan details

[0865] Output data: List of generated plans

[0866] Step 7: Provide a proposal

[0867] The server sends the generated plan list to the terminal, which receives it and displays it to the user. The user can then select the most suitable plan from the proposed plans.

[0868] Input data: List of generated plans

[0869] Output data: Plan list sent to the device, plans displayed to the user

[0870] Step 8: Gather feedback and refine the system

[0871] After leaving the house, the user enters feedback into the application and sends it to the server. The server receives this feedback and uses it to improve the accuracy of the system. The feedback also includes the user's emotional information, which is reflected in future suggestions.

[0872] Input data: User feedback and emotional information

[0873] Processing content: Analysis of feedback, updating system improvement algorithms

[0874] Output data: Proposed algorithm for updated system

[0875] Through the above processing steps, optimal destinations and activities are suggested to the user, and the accuracy of the system is continuously improved based on feedback.

[0876] (Application example 2)

[0877] 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."

[0878] Conventional food delivery services have had the challenge of being unable to recommend the best restaurant or meal based on a user's profile information. Furthermore, there are no systems that consider a user's emotional information when proposing recommended meals or restaurants. This has left users unable to choose the best delivery service that best suits their mood and needs at the time.

[0879] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information on the child's age, interests, budget, and mode of transportation input by the user, means for searching for related spot and activity information from various information sources, means for generating a plan suited to the child's interests based on the search results, means for providing the generated plan to the user, means for receiving feedback from the user and improving the accuracy of the system, and means for analyzing the user's emotional information and adjusting suggestions according to the user's emotional state. This enables the user to receive recommendations of restaurants and menus that are optimal for their current emotions and situation.

[0880] "User" means any person who uses the System and enters information.

[0881] "Child's age" is information that refers to the actual age of the child targeted by the system.

[0882] "Interests" refers to specific interests or hobbies that a child has.

[0883] "Budget" refers to information that indicates the upper limit of the amount of money that a user sets when using the system.

[0884] "Transportation" is information that indicates the transportation that the user uses to travel to the destination.

[0885] "Profile information" refers to comprehensive information entered by the user, such as the child's age, interests, budget, and mode of transportation, as well as the user's own emotional information.

[0886] "Emotion information" is information input by the user that indicates their current emotional state.

[0887] "Feedback" refers to information such as impressions and evaluations that users provide to the system after going out or making suggestions.

[0888] "Spot" refers to a specific destination or tourist spot that the system will suggest.

[0889] "Activity information" refers to information that indicates the activities that can be carried out at various spots provided by the system.

[0890] "Plan" refers to a system-generated plan that includes specific proposals and schedules.

[0891] "Search Tool" refers to the functionality for searching for relevant spot and activity information from external and internal databases.

[0892] "Analysis means" refers to a function for analyzing profile information and emotional information entered by a user.

[0893] "Proposal means" refers to the function for generating and providing the optimal plan to the user based on the analysis results.

[0894] "Feedback receiving means" refers to a function for receiving and analyzing feedback information provided by a user.

[0895] The "proposal adjustment means" refers to a function for adjusting the proposal content based on the user's emotional information.

[0896] The present invention relates to a system that proposes optimal food delivery plans based on a user's profile information and emotional information. This system recommends optimal restaurants and menus based on the user's input of information such as the age, interests, budget, mode of transportation, and emotional information about the child.

[0897] Basic system configuration

[0898] Entering your user profile

[0899] A user starts the application on a smartphone or tablet device and then enters user profile information (e.g., family composition, allergy information, budget, emotional information), which is then saved on the device as a profile.

[0900] Profile analysis and database search

[0901] The profile information entered by the user is sent to a server that uses the following hardware and software:

[0902] Hardware: Cloud-based servers (e.g., AWS)

[0903] Software: Database management system (e.g., MySQL, PostgreSQL), Rest API (e.g., Node.js, Express), Sentiment analysis engine (e.g., IBM Watson, Microsoft Azure Sentiment Analysis API)

[0904] The server first analyzes your profile information, filtering restaurant and menu recommendations based on your age and interests.

[0905] Analysis by emotion engine

[0906] The server's built-in emotion engine analyzes the user's emotional information. The results of this analysis are reflected in the plan generation process, and suggestions are made that are appropriate for the user's emotional state. For example, if the user inputs "I'm tired," restaurants and menus that offer a relaxing environment will be prioritized.

[0907] Database search

[0908] The server searches its internal database and internet sources for relevant restaurant and menu information. The search results include details such as restaurant name, address, dish description, price range, and customer reviews.

[0909] Plan Generation

[0910] The server analyzes the search results and generates multiple itineraries, each including specific transportation modes, prices, and meal details, taking into account the user's budget, transportation options, and emotions identified by the emotion engine.

[0911] Providing suggestions

[0912] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and order delivery.

[0913] Gathering feedback and improving the system

[0914] After placing an order, the user enters feedback into the device and sends it to the server. The server analyzes this feedback and uses it to improve the system's accuracy. The feedback is also analyzed for emotional information, further improving the accuracy of the next recommendation.

[0915] Specific examples

[0916] Case study: Relaxed family meal delivery

[0917] 1. A user launches the application and enters the following into their profile: Age: 35, Interests: Pizza, Budget: 3000 yen, Emotion: Tired.

[0918] 2. The device sends the profile to the server.

[0919] 3. The server analyzes the received information and searches for pizza-related restaurants.

[0920] 4. The server retrieves candidates such as "Pizza specialty store A," "Delivery pizza store B," and "Italian restaurant C" from the database, and generates specific plans for each candidate that take into account transportation access and price.

[0921] 5. The server sends the generated plan list to the terminal.

[0922] 6. The device displays the candidate plans to the user.

[0923] Example prompt for a generative AI model:

[0924] plaintext

[0925] Recommend a pizza restaurant within a budget of 3000 yen for a tired 35-year-old user. Please consider name-based information and prioritize restaurants that offer a particularly relaxing environment.

[0926] This system is expected to improve the quality of life by enabling users to easily find the best restaurant and menu that suits their current mood and situation.

[0927] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0928] Step 1:

[0929] The user launches the application and enters their profile information. Specifically, they use a smartphone or tablet to enter their age, interests, budget, mode of transportation, and emotional information. The input data is temporarily stored on the device for use in the next step. The output of the input process is the entire profile information entered by the user.

[0930] Step 2:

[0931] The device sends profile information to the server. This process is performed using an HTTP request, and the data sent is encoded in JSON format. The input is the user's profile information, and the output is the server receiving the profile information.

[0932] Step 3:

[0933] The server analyzes the received profile information. The hardware used by the pros is a cloud-based server, and the software used is, for example, Node.js. The analysis first filters target restaurants and menus based on age information. The input is the profile information, and the output is a list of filtered restaurants and menus.

[0934] Step 4:

[0935] The server uses a sentiment analysis engine to analyze the user's sentiment information. Specifically, it uses a sentiment analysis engine (e.g., IBM Watson, Microsoft Azure sentiment analysis API) to convert the sentiment information entered by the user into a text sentiment score. The input is the user's sentiment information, and the output is the sentiment analysis result. This analysis result is used in the next step.

[0936] Step 5:

[0937] The server searches for relevant restaurant and menu information from an internal database and internet sources. The software used is a database management system (e.g., MySQL, PostgreSQL). The input for the search is the filtered restaurant list and the sentiment analysis results, and the output is a list with detailed restaurant and menu information.

[0938] Step 6:

[0939] Based on the search results, the server generates multiple plans that take into account the user's budget, means of transportation, and emotional state. Plan generation combines information obtained from the database with the results of emotional analysis. Specifically, it selects restaurants and menus that are within the user's budget and sets recommendation levels according to their emotions. The input is a detailed list of restaurant and menu information, and the output is a list of plans to suggest to the user.

[0940] Step 7:

[0941] The server sends the generated plan list to the terminal. This process is again performed using an HTTP request, and the sent data is encoded in JSON format. The input is the generated plan list, and the output is the completion of sending it to the terminal.

[0942] Step 8:

[0943] The terminal displays the proposed plans to the user, and the user selects the most suitable one from the displayed plans. The input is the plan list sent from the server, and the output is the plan selected by the user.

[0944] Step 9:

[0945] After the user completes the trip or delivery, they input their feedback into the application. The feedback includes emotional information. The input is the user's feedback information and is saved on the device.

[0946] Step 10:

[0947] The device sends the feedback information to the server. The transmission is again performed using an HTTP request, and the transmitted data is encoded in JSON format. The input is the user's feedback information, and the output is the receipt of the feedback information by the server.

[0948] Step 11:

[0949] The server analyzes the feedback information to improve the accuracy of the system. The feedback also contains emotional information, which is reflected in the next suggestion. The input is the user's feedback information, and the output is an updated suggestion algorithm and database.

[0950] This processing flow allows users to easily find the best restaurant and menu that suits their current mood and situation, and the system's accuracy is continuously improved based on user feedback.

[0951] 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.

[0952] 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.

[0953] 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.

[0954] [Third embodiment]

[0955] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0956] 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.

[0957] 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).

[0958] 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.

[0959] 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.

[0960] 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).

[0961] 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.

[0962] 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.

[0963] 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.

[0964] 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.

[0965] 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.

[0966] 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."

[0967] The system of the present invention suggests optimal outings and activities for children based on information entered by the user. The system includes a terminal that receives the user's input information, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[0968] 1. Basic configuration

[0969] Entering your user profile

[0970] The user activates the system and enters the child's age, interests, budget, and mode of transportation into a terminal, which then transmits this information to the server.

[0971] Profile analysis and database search

[0972] The server analyzes the received user profile, narrowing it down based on age, interests, budget, and mode of transportation, and then searches for relevant spots and activities from databases and internet sources.

[0973] Plan Generation

[0974] The server analyzes the search results and generates an optimal plan that takes into account budget and transportation options, including the names of specific spots, directions, travel time, financial costs, and details of activities that can be enjoyed within the spots.

[0975] Providing suggestions

[0976] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[0977] Gathering feedback and improving the system

[0978] After leaving the house, users input their feedback into their device and send it to the server, which analyzes it and uses it as data to improve the accuracy of future suggestions.

[0979] 2. Program Processing Overview

[0980] When the device sends the user profile to the server, the server first filters the target activities based on age information, lists spots and activities that are appropriate for the user's age, and then prioritizes the selected spots using interest information.

[0981] For example, if the user is targeting a 3-year-old child who loves trains, the server will search for railway museums, local train ride experiences, railway parks, etc. Among these spots, it will further narrow down the search to those that are reachable within the budget.

[0982] The generated plan includes specific directions (e.g., 30 minutes by train, 10 minutes by bus), admission fees (e.g., 1,000 yen for adults, free for children), and details of activities within the spot (e.g., mini train, driving simulator). This information is sent from the server to the terminal and displayed to the user.

[0983] The feedback provided by users after going out is an important factor in improving the system. The server receives this feedback and uses it to improve the accuracy of the database and the proposed algorithm.

[0984] 3. Specific Examples

[0985] Case study: Going out with a 3-year-old who loves trains

[0986] 1. The user launches the application and enters the following information into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," and "Method of transportation: Train."

[0987] 2. The device sends the profile to the server.

[0988] 3. The server parses the received information and searches for rail-related activity.

[0989] 4. The server retrieves candidates such as "Railway Museum," "Local Railway Ride Experience," and "Railway Park" from the database, and generates a specific plan for each candidate that takes into account transportation access and admission fees.

[0990] 5. The server sends the generated plan list to the terminal.

[0991] 6. The device displays the candidate plans to the user.

[0992] Example: "Railway Museum Plan"

[0993] Directions: 30 minutes by train, 10 minutes by bus

[0994] Admission fee: 1000 yen for adults, free for children

[0995] Activities: Mini train, driving simulator

[0996] 7. The user selects one of the proposed plans and plans their outing.

[0997] 8. After leaving the home, the user enters feedback into the application and sends it to the server.

[0998] 9. The server analyzes the feedback and uses it to improve the accuracy of future plan generation.

[0999] This invention allows parents to efficiently find suitable outings and plan trips that fit their children's interests, and also uses feedback to improve the accuracy of the system's suggestions.

[1000] The processing flow will be explained below.

[1001] Step 1:

[1002] The user launches the application and enters information such as the child's age, interests, budget, and mode of transportation into the input screen. This information is then saved on the device as a profile.

[1003] Step 2:

[1004] The terminal transmits the saved profile information to the server, where it is converted into a data format and transmitted.

[1005] Step 3:

[1006] The server analyzes the received profile information, which then filters recommended activities and places based on age and interests.

[1007] Step 4:

[1008] The server searches for relevant spot and activity information from internal databases and internet sources. The search results include details such as the spot name, address, directions, admission fees, and activity details.

[1009] Step 5:

[1010] The server generates multiple itineraries based on the search results, taking into account the user's budget and transportation options, with each itinerary including specific travel times, costs, and details of activities to enjoy.

[1011] Step 6:

[1012] The server sends the generated plans to the terminal, where the information is converted into a display format and sent.

[1013] Step 7:

[1014] The terminal displays the received plans to the user, who can then select the most suitable one from the presented plans.

[1015] Step 8:

[1016] After the trip, the user enters feedback into the application, including satisfaction with the trip, areas for improvement, and activities that were enjoyed.

[1017] Step 9:

[1018] The terminal transmits the collected feedback information to the server, which also converts the feedback information into a data format before transmitting it.

[1019] Step 10:

[1020] The server receives and analyzes the feedback information, and the results of the analysis are used to update the database and improve the plan generation algorithm.

[1021] This series of steps allows users to efficiently find outings that match their children's interests, and allows the server to continuously improve the accuracy of its suggestions.

[1022] Example 1

[1023] 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."

[1024] Conventional systems that suggest destinations and activities do not adequately consider the user's various information (age, interests, budget, mode of transportation), and therefore may not provide optimal suggestions. Furthermore, feedback functions to improve the accuracy of suggestions are often insufficient. Therefore, there is a need for a system that can analyze the user's input information in detail and provide specific and optimal plans.

[1025] 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.

[1026] In this invention, the server includes means for receiving information input by the user such as the user's age, interests, budget, and mode of transportation, means for searching for related place and activity information from various sources, and means for generating a plan suited to the user's interests based on the search results, thereby enabling the server to suggest destinations and activities optimized for the user's individual needs.

[1027] "User" refers to an individual who uses the system to input information to receive suggestions for destinations and activities.

[1028] "User age" refers to the age information of a child entered by a user as a basis for recommending specific destinations or activities.

[1029] "Interests" refers to the preferences and areas of interest of a user or their child that are taken into account when recommending a particular destination or activity.

[1030] A "budget" refers to a monetary limit that a user sets for a destination or activity.

[1031] "Transportation" refers to the transportation method (e.g., train, car, bus, etc.) that the user will use to reach the suggested destination or activity.

[1032] "Source" refers to a database or Internet resource that the server accesses to obtain relevant location or activity information.

[1033] "Place" refers to a specific geographic location or facility that is suggested as a destination.

[1034] "Activities" refers to specific activities and events that can be done while out and about.

[1035] "Plans" refers to detailed suggestions of destinations and activities generated based on the user's profile information.

[1036] "Feedback" refers to the experiences and opinions that users input into the system after actually going out.

[1037] "Accuracy" refers to a performance indicator that indicates how appropriate the destinations and activities provided by the system are in relation to the user's expectations and needs.

[1038] The system of the present invention aims to suggest optimal destinations and activities for children based on detailed information (age, interests, budget, and mode of transportation) entered by the user. The system is mainly composed of three elements: a terminal that receives user input, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[1039] Entering your user profile

[1040] The user launches the application and enters their child's age (e.g., 3 years old), interest (e.g., railways), budget (e.g., 5,000 yen), and mode of transportation (e.g., train) into the device. This information is sent from the device to the server. The input screen has a user-friendly UI design, providing easy-to-enter forms and drop-down menus.

[1041] Profile analysis and database search

[1042] The server analyzes the received profile information. The analytical tool used here is a generative AI model. Based on the analyzed profile information, a database of related places and activities is searched. For example, for a profile of a "3-year-old child who loves trains," the server retrieves information such as "railway museums" and "local train ride experiences" from the database.

[1043] Plan Generation

[1044] Based on the information acquired by the server, the optimal plan is generated, taking into account budget and means of transportation. This generation process also uses a generative AI model to build proposals optimized for the user profile. As a specific example, a "Railway Museum Plan" is generated. A specific example is shown below:

[1045] Railway Museum Plan

[1046] Directions: 30 minutes by train, 10 minutes by bus

[1047] Admission fee: 1000 yen for adults, free for children

[1048] Activities: Mini train, driving simulator

[1049] View Suggestions

[1050] The generated plan is sent from the server to the terminal, which then displays the plan to the user. A screen has been developed that displays the plan details in a visually easy-to-understand design.

[1051] Gathering feedback and improving the system

[1052] After leaving the facility, users enter their feedback into the device and send it to the server. Feedback is collected using evaluation forms and free-form comment fields. For example, users can enter specific impressions such as, "I had a lot of fun riding the miniature trains at the railway museum, but the driving simulator was out of order." This feedback is analyzed by the server and used as training data for the generative AI model, improving the accuracy of the system's suggestions.

[1053] Example prompt

[1054] Specific examples of prompts include:

[1055] "Age: 3 years old" "Interest: Trains" "Budget: 5,000 yen" "Method of transportation: Train"

[1056] In this way, the system receives and analyzes information from the user in a series of steps, and proposes the optimal outing plan. Subsequent feedback is collected and analyzed to continuously improve the accuracy of the system.

[1057] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1058] Step 1:

[1059] The user starts the application and enters detailed information about their child (age, interests, budget, and mode of transportation). Specifically, they enter age "3 years old," interest "railway," budget "5,000 yen," and mode of transportation "train." This input is collected by the device and processed in the next step.

[1060] Input: Age, interests, budget, transportation information

[1061] Output: User profile data

[1062] Step 2:

[1063] The device sends the collected user profile data to the server. The data is encrypted and sent securely. Specifically, the device transfers the data using the HTTPS protocol.

[1064] Input: User profile data

[1065] Output: User profile data sent to the server

[1066] Step 3:

[1067] The server analyzes the received user profile data. A generative AI model is used here. The server analyzes each item in the profile (age, interests, budget, mode of transportation) and classifies it into a specific category. For example, an age of "3 years old" would be classified as "Toddlers," and an interest of "Railways" would be classified as "Transportation."

[1068] Input: User profile data

[1069] Output: Analyzed profile data (data classified by category)

[1070] Step 4:

[1071] The server searches the database based on the parsed profile data. During this search process, it retrieves information about related places and activities (e.g., railway museums, local train ride experiences). The server uses SQL queries to retrieve relevant entries from the database.

[1072] Input: Analyzed profile data

[1073] Output: Search results data (list of related places and activities)

[1074] Step 5:

[1075] The server generates the optimal plan based on the search results, taking into account budget and means of transportation. This generation process again uses the generative AI model to build a plan optimized for the user profile. As a specific example, a "Railway Museum Plan" is generated, which includes directions (30 minutes by train, 10 minutes by bus), admission fees (1,000 yen for adults, free for children), and activities (mini train, driving simulator).

[1076] Input: Search result data, generative AI model

[1077] Output: Optimal plan data

[1078] Step 6:

[1079] The server sends the generated plan to the device. During this process, the data is formatted and sent in a format that is easy for the user to view. The device uses responsive design to display the plan in a visually easy-to-understand layout for the user.

[1080] Input: Optimal plan data

[1081] Output: Plan data sent to the device

[1082] Step 7:

[1083] The user checks the generated plan and makes specific plans for the trip. After the trip, the user enters feedback into the application. The feedback input screen includes an evaluation form and a free-form comment field, where the user can enter their specific experiences and opinions.

[1084] Input: Feedback based on the user's actual experience

[1085] Output: Feedback data

[1086] Step 8:

[1087] The server analyzes the received feedback data. This analysis uses a generative AI model to evaluate the feedback data and use it to improve the accuracy of the next proposal. The server also updates the database and uses it for the next search and plan generation.

[1088] Input: Feedback data

[1089] Output: Updated database, training data for accuracy improvement

[1090] (Application example 1)

[1091] 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."

[1092] Modern parents face the challenge of finding the right destinations and activities for their children based on their interests, age, budget, and transportation. Particularly when planning activities in physical stores, it can be difficult to find the best options from the vast amount of information available, making it difficult to quickly obtain the right information. To solve this problem, a system is needed that automatically suggests the best physical store activities based on user-entered information.

[1093] 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.

[1094] In this invention, the server includes means for receiving information on the child's age, interests, budget, and transportation method input by the user, means for searching for related spot and activity information from various information sources, and means for generating a plan suited to the child's interests based on the search results. This makes it possible to suggest optimal activities at physical stores based on the profile information input by the user, and to generate and provide a detailed plan to the user.

[1095] "Means for receiving user-entered information on a child's age, interests, budget, and mode of transportation" refers to an interface that allows parents to use an application or device to enter their child's basic data and interests, the daily budget, and the mode of transportation they will use.

[1096] "Means for searching for relevant spot and activity information from various sources" refers to a function that utilizes the Internet, databases, and other information providing services to collect appropriate spot and activity information based on the profile entered by the user.

[1097] The "means of generating a plan suited to the child's interests based on the search results" refers to an algorithm that uses the collected information to select destinations and activities that are best suited to the child's age and interests, and creates a specific visiting plan.

[1098] The "means for providing the generated plan to the user" is a function for displaying the generated visiting plan and activity proposals on the user's terminal.

[1099] "Means for receiving feedback from users and improving the accuracy of the system" refers to a function that receives users' impressions and ratings of the activities they have actually undertaken and the spots they have visited, and uses this information to improve the system's suggestion algorithm.

[1100] The "means for suggesting activities at physical stores" is a function that selects activities that can be carried out at physical stores that can actually be visited from the collected activity information and suggests them to the user.

[1101] The "means for generating detailed plans for activities at physical stores and providing them to users" is a function for creating plans for selected physical store activities, including details such as specific visit schedules, access methods, and costs, and presenting these plans to users.

[1102] A system embodying the present invention is described in detail below.

[1103] Basic system configuration

[1104] 1. Enter your user profile

[1105] Users launch a smartphone application and enter information about their child's age, interests, budget, and mode of transportation, which is then sent from the device to the server.

[1106] 2. Profile analysis and database search

[1107] The server then parses the received user profile using a web framework called Flask, then searches an SQLite database and relevant sources on the internet to gather activity information based on age, interests, budget, and mode of transportation.

[1108] 3. Plan Generation

[1109] The server then generates a plan that best suits the user's profile based on the search results. This plan takes into account budget and transportation options, and focuses on activities at physical stores. The plan includes the names of destinations, directions, travel time, financial costs, and details of activities.

[1110] 4. Providing Proposals

[1111] The generated plan is sent to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[1112] 5. Gathering feedback and improving the system

[1113] After leaving the house, users input their feedback into their devices and send it to the server, which analyzes the feedback and uses the data to improve the system's suggestion algorithm.

[1114] Specific processing details

[1115] 1. Data Receipt and Analysis

[1116] The server receives user-submitted profile information using the Flask API, stores it in JSON format, and filters relevant activities based on a SQLite database.

[1117] 2. Searching and filtering information

[1118] The server queries an SQLite database to find activities appropriate for the child's age and interests, while also taking into account budget and transportation options. For example, it searches for activities that fit the criteria, such as "places within a bicycle ride for a 5-year-old child who loves animals and has a budget of under 3,000 yen."

[1119] 3. Plan Generation and Delivery

[1120] Based on the extracted activity information, a detailed itinerary is generated, including specific directions to the locations, costs, travel times, and details of the activities you can enjoy. The generated itinerary is then sent to the user's device in JSON format.

[1121] 4. Feedback Analysis

[1122] After going out based on the provided plan, the user provides feedback through the application, which is analyzed by the server to improve the accuracy of future recommendation algorithms.

[1123] Examples and prompts

[1124] For example, if a 5-year-old child loves animals, has a budget of 3,000 yen, and can travel within a cycling distance, the following information would be entered:

[1125] example:

[1126] UserProfile:

[1127] Age: 5

[1128] Interest: Animals

[1129] Budget: 3000

[1130] Transport: Bicycle

[1131] Proposed plan:

[1132] 1. Name: Zoo

[1133] Description: Animal interaction corner, penguin show

[1134] Cost: Admission - 500 yen for adults, 300 yen for children

[1135] Transportation: 15 minutes by bicycle

[1136] This allows users to quickly plan optimal outings and provide children with a fun experience that suits their interests.

[1137] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1138] Step 1:

[1139] The user launches a smartphone application and enters information about the child's age, interests, budget, and transportation method.

[1140] Input: Children's ages, interests, budget, transportation

[1141] Output: JSON format of the input data

[1142] What it does: A user uses a form in the application to enter details about their child, which are then sent to the server in JSON format.

[1143] Step 2:

[1144] The terminal transmits user data to the server.

[1145] Input: JSON data entered by the user

[1146] Output: Send data to the server

[1147] How it works: The smartphone sends user input information to an API endpoint over the Internet, using the Flask framework.

[1148] Step 3:

[1149] The server parses the received user data and retrieves the appropriate activity information from the SQLite database.

[1150] Input: User data in JSON format

[1151] Output: A list of activity information based on the user profile.

[1152] What it does: The server uses Flask to receive the JSON data and queries an SQLite database to filter activities based on age, interests, budget, and mode of transportation.

[1153] Step 4:

[1154] The server generates an appropriate plan.

[1155] Input: Filtered activity information

[1156] Output: A list of detailed visit plans

[1157] Specific Actions: The server creates a specific itinerary based on the search results, including location names, directions, travel time, costs, and activity details.

[1158] Step 5:

[1159] The server sends the generated plan to the terminal.

[1160] Input: List of detailed visit plans

[1161] Output: Send data to the user's terminal

[1162] Specific operation: The generated visit plan is sent from the server to the user's smartphone in JSON format. The Flask framework and REST API are used.

[1163] Step 6:

[1164] The terminal displays the proposed plan to the user.

[1165] Input: JSON data of detailed visit plan

[1166] Output: Plan information displayed on screen

[1167] Specific operation: The smartphone application extracts the visit plan from the received JSON data and displays it on the user interface.

[1168] Step 7:

[1169] Go out based on the plan selected by the user.

[1170] Input: Selected plan information

[1171] Output: Real-world outing experience

[1172] Specific behavior: Visit designated physical stores and activities according to the plan selected by the user.

[1173] Step 8:

[1174] Users provide feedback after their trip.

[1175] Input: Feedback information

[1176] Output: Send feedback data to the server

[1177] What happens: The user uses the feedback form within the application to enter and submit their thoughts and ratings about the activity they visited.

[1178] Step 9:

[1179] The server receives the feedback, stores it in a database and analyzes it.

[1180] Input: Feedback data

[1181] Output: Analysis results and system improvement data

[1182] How it works: The server receives the feedback data, analyzes it, and stores the results in a database to improve the accuracy of future activity suggestions.

[1183] 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.

[1184] The system of the present invention suggests optimal destinations and activities for children based on information entered by the user, and also has the ability to recognize the user's emotions and adjust suggestions based on those emotions. The system includes a terminal that receives the user's input information, a server that analyzes the information and recognizes emotions, and a network that exchanges information between the server and the terminal.

[1185] 1. Basic configuration

[1186] Entering your user profile

[1187] The user starts the system and enters information about their child's age, interests, budget, mode of transportation, and their own emotional state on the input screen. This information is then saved on the device as a profile.

[1188] Profile analysis and database search

[1189] The server then analyzes the received profile information, filtering recommended activities and places based on the child's age and interests.

[1190] Analysis by emotion engine

[1191] Furthermore, the server is equipped with an emotion engine that analyzes the user's emotion information and adjusts the proposed plan based on the emotion data entered by the user.

[1192] Database search

[1193] The server searches its internal database and internet sources for relevant spot and activity information, and the search results include details such as the spot name, address, directions, admission fees, and activity details.

[1194] Plan Generation

[1195] The server analyzes the search results and generates multiple itineraries, each including specific travel times, costs, and details of activities to enjoy, taking into account the user's budget, transportation options, and emotions identified by the emotion engine.

[1196] Providing suggestions

[1197] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[1198] Gathering feedback and improving the system

[1199] After leaving the house, the user inputs feedback into the device and sends it to the server. The server analyzes this feedback and uses it to improve the accuracy of the system. The feedback is also analyzed as emotional information to further improve the accuracy of the next suggestion.

[1200] 2. Program Processing Overview

[1201] When a device sends a user profile to the server, the server first analyzes the profile information, filters the target activities based on age information, and then prioritizes the selected spots using interest information.

[1202] In parallel, the emotion engine analyzes the emotion data entered by the user. The analysis results are reflected in the plan generation process, and suggestions appropriate to the user's emotional state are made.

[1203] For example, if the user is targeting a 3-year-old child who loves trains, the server will search for railway museums, local train ride experiences, railway parks, etc. Among these spots, it will further narrow down the search to those that are reachable within the budget.

[1204] The generated plan includes specific directions (e.g., 30 minutes by train, 10 minutes by bus), admission fees (e.g., 1,000 yen for adults, free for children), and details of activities within the spot (e.g., mini train, driving simulator). This information is sent from the server to the terminal and displayed to the user.

[1205] The feedback provided by users after going out is an important factor in improving the system. The server receives this feedback and uses it to improve the accuracy of the database and the proposal algorithm. The feedback also includes emotional information, which is reflected in the next proposal.

[1206] 3. Specific Examples

[1207] Case study: Going out with a 3-year-old who loves trains

[1208] 1. The user launches the application and enters the following into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," "Method of transportation: Train," and "Emotion: Feeling excited."

[1209] 2. The device sends the profile to the server.

[1210] 3. The server parses the received information and searches for rail-related activity.

[1211] 4. The server retrieves candidates such as "Railway Museum," "Local Railway Ride Experience," and "Railway Park" from the database, and generates a specific plan for each candidate that takes into account transportation access and admission fees.

[1212] 5. The server sends the generated plan list to the terminal.

[1213] 6. The device displays the candidate plans to the user.

[1214] Example: "Railway Museum Plan"

[1215] Directions: 30 minutes by train, 10 minutes by bus

[1216] Admission fee: 1000 yen for adults, free for children

[1217] Activities: Mini train, driving simulator

[1218] 7. The user selects one of the proposed plans and plans their outing.

[1219] 8. After leaving the home, the user inputs feedback into the application and sends it to the server. The feedback includes emotional information.

[1220] 9. The server analyzes the feedback and improves the accuracy of future suggestions.

[1221] This invention allows parents to efficiently find suitable outing destinations and plan trips that fit their children's interests. In addition, the introduction of an emotion engine allows for more appropriate suggestions based on the user's emotions.

[1222] The processing flow will be explained below.

[1223] Step 1:

[1224] The user launches the application and enters information about their child's age, interests, budget, mode of transportation, and current emotions (e.g., excited, tired, excited, etc.). This information is stored on the device as a profile.

[1225] Step 2:

[1226] The device sends the saved profile information to the server, which converts the profile information into a data format and sends it to the server via secure communication.

[1227] Step 3:

[1228] The server analyzes the received profile information, filtering recommended activities based on the child's age and using interest information to prioritize relevant activities and places.

[1229] Step 4:

[1230] The server uses an emotion engine to analyze the emotion data entered by the user. For example, if the user enters "fun," the server will prioritize plans that correspond to that emotion.

[1231] Step 5:

[1232] The server searches for relevant spot and activity information from internal databases and internet sources. The search results include details such as the spot name, address, directions, admission fees, and activity details.

[1233] Step 6:

[1234] The server generates multiple itineraries based on the search results, taking into account the user's budget, transportation options, and emotional information. Each itinerary includes specific travel times, costs, and details of activities that can be enjoyed.

[1235] Step 7:

[1236] The server sends the generated plans to the terminal, where the information is converted into a display format and sent in a format that is easy for the user to understand.

[1237] Step 8:

[1238] The terminal displays the received plans to the user, who can then select the most suitable one from the presented plans and plan their outing.

[1239] Step 9:

[1240] After the trip, users enter feedback into the application, including specific experiences, satisfaction, areas for improvement, and emotional information during the trip.

[1241] Step 10:

[1242] The terminal transmits the collected feedback information to the server, which also converts the feedback information into a data format before transmitting it.

[1243] Step 11:

[1244] The server receives and analyzes the feedback information. The analysis results are reflected in updating the database and improving the plan generation algorithm. In addition, the user's emotional information is used in the next proposal.

[1245] This series of steps allows users to efficiently find outings that match their child's interests and current emotions, and allows the server to continuously improve the accuracy of its suggestions.

[1246] Example 2

[1247] 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."

[1248] Conventional systems could suggest suitable outings and activities for children based on information entered by the user, but they did not provide suggestions that took into account the user's emotional information. As a result, they were unable to suggest optimal outings based on the user's emotions, making it difficult to improve the quality of the user experience. Furthermore, there was a lack of effort to collect feedback and use it to improve the accuracy of the system. This made it difficult to improve the accuracy of suggestions and user satisfaction.

[1249] 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.

[1250] In this invention, the server includes means for receiving information on the child's age, interests, budget, and mode of transportation input by the user, means for receiving user emotion information, means for analyzing the profile information and emotion information and prioritizing recommended activities and spots, means for searching for related spot and activity information from various information sources, means for generating a plan suited to the child's interests and the user's emotions based on the search results, means for providing the generated plan to the user, and means for receiving user feedback and improving the accuracy of the system. This makes it possible to suggest optimal destinations and activities taking the user's emotions into consideration, and realizes continuous improvement of the system's accuracy based on the feedback.

[1251] "User" refers to an individual who uses the system and enters information to find out about their child's outings and activities.

[1252] "Profile Information" refers to information entered by the user regarding their child's age, interests, budget, and transportation.

[1253] "Emotion information" refers to information input by the user about their own emotions and mental state.

[1254] "Server" refers to a computer system that receives profile information and emotion information, analyzes them, searches various information sources, generates an optimal plan, and provides it to the user.

[1255] "Filtering" refers to the process of selecting recommended activities and places based on profile information and sentiment information.

[1256] "Various sources" refers to internal databases and internet sources, including information on travel destinations and activities.

[1257] "Plan" refers to suggestions for destinations and activities generated based on the user's and children's interests, budget, emotions, and transportation options.

[1258] "Generation" refers to the server analyzing profile information and emotional information and creating plans for outings and activities based on that information.

[1259] "Feedback" refers to evaluations, impressions, and information for improvement of the system provided by users after going out.

[1260] "Improved accuracy" refers to using feedback to improve the system's suggestions and analytical capabilities, thereby increasing the quality of suggestions from the next time onwards.

[1261] The present invention is a system that suggests optimal destinations and activities for children based on information input by the user, such as their age, interests, budget, mode of transportation, and emotional state. The system includes a terminal that receives the information input by the user, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[1262] The user launches the application and enters the following information into the profile entry screen:

[1263] Child's age (e.g., 3 years old)

[1264] Interests (e.g., railways)

[1265] Budget (e.g. 5,000 yen)

[1266] Transportation (e.g. train)

[1267] Your (user's) emotional information (e.g., feeling excited)

[1268] The device receives this profile information and sends it to the server, which then performs the necessary analysis. Specifically, the server is equipped with a data analysis engine and an emotion engine, which perform detailed analysis of the profile information and emotion information.

[1269] Hardware and Software Used

[1270] Device: Input device such as smartphone, tablet, PC, etc.

[1271] Servers: Cloud computers and local servers

[1272] Analysis engine: Database management system, sentiment analysis model

[1273] Communication networks: Internet and local networks

[1274] Data processing and calculation

[1275] The server processes and calculates data in the following steps.

[1276] 1. Profile Analysis: A data analysis engine filters suitable activity suggestions based on age, interests, budget and mode of transportation.

[1277] 2. Emotion data analysis: The emotion engine analyzes the user's emotional information and reflects it in the proposed plan.

[1278] 3. Database Search: The server searches its internal database and internet sources for relevant spot and activity information, including spot names, addresses, directions, admission fees, and activity details.

[1279] 4. Plan Generation: Based on the search results, multiple plans are generated taking into account the user's budget, means of transportation, and emotions.

[1280] 5. Providing proposals: The generated plan is sent from the server to the terminal and displayed to the user.

[1281] 6. Collect feedback and improve the system's accuracy: After going out, users enter feedback, which is used to improve the accuracy of the next suggestion.

[1282] Specific examples

[1283] For example, if a user is looking for a place to go for their 3-year-old child who loves trains, the following process will be executed:

[1284] 1. The user launches the application and enters the following into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," "Method of transportation: Train," and "Emotion: Feeling excited."

[1285] 2. The device sends the profile information to the server.

[1286] 3. The server analyzes the profile and emotional information and searches a database for related spots and activities (e.g., railway museums, local railway ride experiences, railway parks).

[1287] 4. The server generates a specific plan (e.g., Railway Museum Plan - Directions: 30 minutes by train, 10 minutes by bus / Admission fee: 1,000 yen for adults, free for children / Activities: mini train, driving simulator).

[1288] 5. The device displays the proposed plan to the user.

[1289] 6. After the user leaves the house, they enter their feedback into the application and send it to the server, which improves the accuracy of suggestions for the next trip.

[1290] Prompt Sentence Examples

[1291] Below is an example of a prompt that the user can enter.

[1292] "Age: 3, Interests: Trains, Budget: 5,000 yen, Transportation: Train, Emotions: Feeling excited"

[1293] This allows users to efficiently find the perfect outing destination that matches their child's interests and their own emotions. The server uses the feedback to improve the accuracy of the system, and future suggestions will be more accurate.

[1294] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1295] Processing Steps

[1296] Step 1: Fill in your user profile

[1297] The user launches the application and enters their child's age, interests, budget, mode of transportation, and their own emotional information into the profile entry screen. The information entered is as follows:

[1298] Child's age: 3 years old

[1299] Interests: Railways

[1300] Budget: 5,000 yen

[1301] Means of transportation: train

[1302] Emotional information: Feeling excited

[1303] Input data: Child's age, interests, budget, transportation, emotional information

[1304] Output data: User profile information

[1305] Step 2: Sending the profile to the server

[1306] The device sends the user's profile information to the server via an HTTP request. The data includes the child's age, interests, budget, mode of transportation, and emotional information.

[1307] Input data: User profile information

[1308] Output data: Profile information sent to the server

[1309] Step 3: Parse the profile information

[1310] The server analyzes the received profile information, and a data analysis engine filters suitable activity suggestions based on age, interests, budget, and mode of transportation, generating a filtered list of activities as a result of the analysis.

[1311] Input data: Profile information sent to the server

[1312] Processing: Analyzes profile information and filters activity candidates

[1313] Output data: Filtered activity list

[1314] Step 4: Analyze the sentiment data

[1315] The emotion engine installed on the server analyzes the emotion data entered by the user, and the analysis results are taken into consideration when generating a plan based on the user's emotion.

[1316] Input data: User's emotional information

[1317] Processing content: Emotion data analysis

[1318] Output data: Sentiment analysis results

[1319] Step 5: Database Search

[1320] The server retrieves relevant spot and activity information from an internal database and various external sources, including spot names, addresses, directions, admission fees, and activity details.

[1321] Input data: filtered activity list, sentiment analysis results

[1322] Processing content: Database search, acquisition of related information

[1323] Output data: Detailed information about spots and activities

[1324] Step 6: Generate a plan

[1325] The server generates multiple plans based on the search results, taking into account the user's budget, transportation means, and emotions. Each plan includes details of specific transportation means, travel time, expenses, and activities that can be enjoyed.

[1326] Input data: detailed information on spots and activities, user budget and transportation method, sentiment analysis results

[1327] Process: Generate plan, create plan details

[1328] Output data: List of generated plans

[1329] Step 7: Provide a proposal

[1330] The server sends the generated plan list to the terminal, which receives it and displays it to the user. The user can then select the most suitable plan from the proposed plans.

[1331] Input data: List of generated plans

[1332] Output data: Plan list sent to the device, plans displayed to the user

[1333] Step 8: Gather feedback and refine the system

[1334] After leaving the house, the user enters feedback into the application and sends it to the server. The server receives this feedback and uses it to improve the accuracy of the system. The feedback also includes the user's emotional information, which is reflected in future suggestions.

[1335] Input data: User feedback and emotional information

[1336] Processing content: Analysis of feedback, updating system improvement algorithms

[1337] Output data: Proposed algorithm for updated system

[1338] Through the above processing steps, optimal destinations and activities are suggested to the user, and the accuracy of the system is continuously improved based on feedback.

[1339] (Application example 2)

[1340] 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."

[1341] Conventional food delivery services have had the challenge of being unable to recommend the best restaurant or meal based on a user's profile information. Furthermore, there are no systems that consider a user's emotional information when proposing recommended meals or restaurants. This has left users unable to choose the best delivery service that best suits their mood and needs at the time.

[1342] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information on the child's age, interests, budget, and mode of transportation input by the user, means for searching for related spot and activity information from various information sources, means for generating a plan suited to the child's interests based on the search results, means for providing the generated plan to the user, means for receiving feedback from the user and improving the accuracy of the system, and means for analyzing the user's emotional information and adjusting suggestions according to the user's emotional state. This enables the user to receive recommendations of restaurants and menus that are optimal for their current emotions and situation.

[1343] "User" means any person who uses the System and enters information.

[1344] "Child's age" is information that refers to the actual age of the child targeted by the system.

[1345] "Interests" refers to specific interests or hobbies that a child has.

[1346] "Budget" refers to information that indicates the upper limit of the amount of money that a user sets when using the system.

[1347] "Transportation" is information that indicates the transportation that the user uses to travel to the destination.

[1348] "Profile information" refers to comprehensive information entered by the user, such as the child's age, interests, budget, and mode of transportation, as well as the user's own emotional information.

[1349] "Emotion information" is information input by the user that indicates their current emotional state.

[1350] "Feedback" refers to information such as impressions and evaluations that users provide to the system after going out or making suggestions.

[1351] "Spot" refers to a specific destination or tourist spot that the system will suggest.

[1352] "Activity information" refers to information that indicates the activities that can be carried out at various spots provided by the system.

[1353] "Plan" refers to a system-generated plan that includes specific proposals and schedules.

[1354] "Search Tool" refers to the functionality for searching for relevant spot and activity information from external and internal databases.

[1355] "Analysis means" refers to a function for analyzing profile information and emotional information entered by a user.

[1356] "Proposal means" refers to the function for generating and providing the optimal plan to the user based on the analysis results.

[1357] "Feedback receiving means" refers to a function for receiving and analyzing feedback information provided by a user.

[1358] The "proposal adjustment means" refers to a function for adjusting the proposal content based on the user's emotional information.

[1359] The present invention relates to a system that proposes optimal food delivery plans based on a user's profile information and emotional information. This system recommends optimal restaurants and menus based on the user's input of information such as the age, interests, budget, mode of transportation, and emotional information about the child.

[1360] Basic system configuration

[1361] Entering your user profile

[1362] A user starts the application on a smartphone or tablet device and then enters user profile information (e.g., family composition, allergy information, budget, emotional information), which is then saved on the device as a profile.

[1363] Profile analysis and database search

[1364] The profile information entered by the user is sent to a server that uses the following hardware and software:

[1365] Hardware: Cloud-based servers (e.g., AWS)

[1366] Software: Database management system (e.g., MySQL, PostgreSQL), Rest API (e.g., Node.js, Express), Sentiment analysis engine (e.g., IBM Watson, Microsoft Azure Sentiment Analysis API)

[1367] The server first analyzes your profile information, filtering restaurant and menu recommendations based on your age and interests.

[1368] Analysis by emotion engine

[1369] The server's built-in emotion engine analyzes the user's emotional information. The results of this analysis are reflected in the plan generation process, and suggestions are made that are appropriate for the user's emotional state. For example, if the user inputs "I'm tired," restaurants and menus that offer a relaxing environment will be prioritized.

[1370] Database search

[1371] The server searches its internal database and internet sources for relevant restaurant and menu information. The search results include details such as restaurant name, address, dish description, price range, and customer reviews.

[1372] Plan Generation

[1373] The server analyzes the search results and generates multiple itineraries, each including specific transportation modes, prices, and meal details, taking into account the user's budget, transportation options, and emotions identified by the emotion engine.

[1374] Providing suggestions

[1375] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and order delivery.

[1376] Gathering feedback and improving the system

[1377] After placing an order, the user enters feedback into the device and sends it to the server. The server analyzes this feedback and uses it to improve the system's accuracy. The feedback is also analyzed for emotional information, further improving the accuracy of the next recommendation.

[1378] Specific examples

[1379] Case study: Relaxed family meal delivery

[1380] 1. A user launches the application and enters the following into their profile: Age: 35, Interests: Pizza, Budget: 3000 yen, Emotion: Tired.

[1381] 2. The device sends the profile to the server.

[1382] 3. The server analyzes the received information and searches for pizza-related restaurants.

[1383] 4. The server retrieves candidates such as "Pizza specialty store A," "Delivery pizza store B," and "Italian restaurant C" from the database, and generates specific plans for each candidate that take into account transportation access and price.

[1384] 5. The server sends the generated plan list to the terminal.

[1385] 6. The device displays the candidate plans to the user.

[1386] Example prompt for a generative AI model:

[1387] plaintext

[1388] Recommend a pizza restaurant within a budget of 3000 yen for a tired 35-year-old user. Please consider name-based information and prioritize restaurants that offer a particularly relaxing environment.

[1389] This system is expected to improve the quality of life by enabling users to easily find the best restaurant and menu that suits their current mood and situation.

[1390] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1391] Step 1:

[1392] The user launches the application and enters their profile information. Specifically, they use a smartphone or tablet to enter their age, interests, budget, mode of transportation, and emotional information. The input data is temporarily stored on the device for use in the next step. The output of the input process is the entire profile information entered by the user.

[1393] Step 2:

[1394] The device sends profile information to the server. This process is performed using an HTTP request, and the data sent is encoded in JSON format. The input is the user's profile information, and the output is the server receiving the profile information.

[1395] Step 3:

[1396] The server analyzes the received profile information. The hardware used by the pros is a cloud-based server, and the software used is, for example, Node.js. The analysis first filters target restaurants and menus based on age information. The input is the profile information, and the output is a list of filtered restaurants and menus.

[1397] Step 4:

[1398] The server uses a sentiment analysis engine to analyze the user's sentiment information. Specifically, it uses a sentiment analysis engine (e.g., IBM Watson, Microsoft Azure sentiment analysis API) to convert the sentiment information entered by the user into a text sentiment score. The input is the user's sentiment information, and the output is the sentiment analysis result. This analysis result is used in the next step.

[1399] Step 5:

[1400] The server searches for relevant restaurant and menu information from an internal database and internet sources. The software used is a database management system (e.g., MySQL, PostgreSQL). The input for the search is the filtered restaurant list and the sentiment analysis results, and the output is a list with detailed restaurant and menu information.

[1401] Step 6:

[1402] Based on the search results, the server generates multiple plans that take into account the user's budget, means of transportation, and emotional state. Plan generation combines information obtained from the database with the results of emotional analysis. Specifically, it selects restaurants and menus that are within the user's budget and sets recommendation levels according to their emotions. The input is a detailed list of restaurant and menu information, and the output is a list of plans to suggest to the user.

[1403] Step 7:

[1404] The server sends the generated plan list to the terminal. This process is again performed using an HTTP request, and the sent data is encoded in JSON format. The input is the generated plan list, and the output is the completion of sending it to the terminal.

[1405] Step 8:

[1406] The terminal displays the proposed plans to the user, and the user selects the most suitable one from the displayed plans. The input is the plan list sent from the server, and the output is the plan selected by the user.

[1407] Step 9:

[1408] After the user completes the trip or delivery, they input their feedback into the application. The feedback includes emotional information. The input is the user's feedback information and is saved on the device.

[1409] Step 10:

[1410] The device sends the feedback information to the server. The transmission is again performed using an HTTP request, and the transmitted data is encoded in JSON format. The input is the user's feedback information, and the output is the receipt of the feedback information by the server.

[1411] Step 11:

[1412] The server analyzes the feedback information to improve the accuracy of the system. The feedback also contains emotional information, which is reflected in the next suggestion. The input is the user's feedback information, and the output is an updated suggestion algorithm and database.

[1413] This processing flow allows users to easily find the best restaurant and menu that suits their current mood and situation, and the system's accuracy is continuously improved based on user feedback.

[1414] 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.

[1415] 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.

[1416] 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.

[1417] [Fourth embodiment]

[1418] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1419] 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.

[1420] 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).

[1421] 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.

[1422] 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.

[1423] 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).

[1424] 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.

[1425] 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.

[1426] 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.

[1427] 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.

[1428] 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.

[1429] 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.

[1430] 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."

[1431] The system of the present invention suggests optimal outings and activities for children based on information entered by the user. The system includes a terminal that receives the user's input information, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[1432] 1. Basic configuration

[1433] Entering your user profile

[1434] The user activates the system and enters the child's age, interests, budget, and mode of transportation into a terminal, which then transmits this information to the server.

[1435] Profile analysis and database search

[1436] The server analyzes the received user profile, narrowing it down based on age, interests, budget, and mode of transportation, and then searches for relevant spots and activities from databases and internet sources.

[1437] Plan Generation

[1438] The server analyzes the search results and generates an optimal plan that takes into account budget and transportation options, including the names of specific spots, directions, travel time, financial costs, and details of activities that can be enjoyed within the spots.

[1439] Providing suggestions

[1440] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[1441] Gathering feedback and improving the system

[1442] After leaving the house, users input their feedback into their device and send it to the server, which analyzes it and uses it as data to improve the accuracy of future suggestions.

[1443] 2. Program Processing Overview

[1444] When the device sends the user profile to the server, the server first filters the target activities based on age information, lists spots and activities that are appropriate for the user's age, and then prioritizes the selected spots using interest information.

[1445] For example, if the user is targeting a 3-year-old child who loves trains, the server will search for railway museums, local train ride experiences, railway parks, etc. Among these spots, it will further narrow down the search to those that are reachable within the budget.

[1446] The generated plan includes specific directions (e.g., 30 minutes by train, 10 minutes by bus), admission fees (e.g., 1,000 yen for adults, free for children), and details of activities within the spot (e.g., mini train, driving simulator). This information is sent from the server to the terminal and displayed to the user.

[1447] The feedback provided by users after going out is an important factor in improving the system. The server receives this feedback and uses it to improve the accuracy of the database and the proposed algorithm.

[1448] 3. Specific Examples

[1449] Case study: Going out with a 3-year-old who loves trains

[1450] 1. The user launches the application and enters the following information into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," and "Method of transportation: Train."

[1451] 2. The device sends the profile to the server.

[1452] 3. The server parses the received information and searches for rail-related activity.

[1453] 4. The server retrieves candidates such as "Railway Museum," "Local Railway Ride Experience," and "Railway Park" from the database, and generates a specific plan for each candidate that takes into account transportation access and admission fees.

[1454] 5. The server sends the generated plan list to the terminal.

[1455] 6. The device displays the candidate plans to the user.

[1456] Example: "Railway Museum Plan"

[1457] Directions: 30 minutes by train, 10 minutes by bus

[1458] Admission fee: 1000 yen for adults, free for children

[1459] Activities: Mini train, driving simulator

[1460] 7. The user selects one of the proposed plans and plans their outing.

[1461] 8. After leaving the home, the user enters feedback into the application and sends it to the server.

[1462] 9. The server analyzes the feedback and uses it to improve the accuracy of future plan generation.

[1463] This invention allows parents to efficiently find suitable outings and plan trips that fit their children's interests, and also uses feedback to improve the accuracy of the system's suggestions.

[1464] The processing flow will be explained below.

[1465] Step 1:

[1466] The user launches the application and enters information such as the child's age, interests, budget, and mode of transportation into the input screen. This information is then saved on the device as a profile.

[1467] Step 2:

[1468] The terminal transmits the saved profile information to the server, where it is converted into a data format and transmitted.

[1469] Step 3:

[1470] The server analyzes the received profile information, which then filters recommended activities and places based on age and interests.

[1471] Step 4:

[1472] The server searches for relevant spot and activity information from internal databases and internet sources. The search results include details such as the spot name, address, directions, admission fees, and activity details.

[1473] Step 5:

[1474] The server generates multiple itineraries based on the search results, taking into account the user's budget and transportation options, with each itinerary including specific travel times, costs, and details of activities to enjoy.

[1475] Step 6:

[1476] The server sends the generated plans to the terminal, where the information is converted into a display format and sent.

[1477] Step 7:

[1478] The terminal displays the received plans to the user, who can then select the most suitable one from the presented plans.

[1479] Step 8:

[1480] After the trip, the user enters feedback into the application, including satisfaction with the trip, areas for improvement, and activities that were enjoyed.

[1481] Step 9:

[1482] The terminal transmits the collected feedback information to the server, which also converts the feedback information into a data format before transmitting it.

[1483] Step 10:

[1484] The server receives and analyzes the feedback information, and the results of the analysis are used to update the database and improve the plan generation algorithm.

[1485] This series of steps allows users to efficiently find outings that match their children's interests, and allows the server to continuously improve the accuracy of its suggestions.

[1486] Example 1

[1487] 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."

[1488] Conventional systems that suggest destinations and activities do not adequately consider the user's various information (age, interests, budget, mode of transportation), and therefore may not provide optimal suggestions. Furthermore, feedback functions to improve the accuracy of suggestions are often insufficient. Therefore, there is a need for a system that can analyze the user's input information in detail and provide specific and optimal plans.

[1489] 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.

[1490] In this invention, the server includes means for receiving information input by the user such as the user's age, interests, budget, and mode of transportation, means for searching for related place and activity information from various sources, and means for generating a plan suited to the user's interests based on the search results, thereby enabling the server to suggest destinations and activities optimized for the user's individual needs.

[1491] "User" refers to an individual who uses the system to input information to receive suggestions for destinations and activities.

[1492] "User age" refers to the age information of a child entered by a user as a basis for recommending specific destinations or activities.

[1493] "Interests" refers to the preferences and areas of interest of a user or their child that are taken into account when recommending a particular destination or activity.

[1494] A "budget" refers to a monetary limit that a user sets for a destination or activity.

[1495] "Transportation" refers to the transportation method (e.g., train, car, bus, etc.) that the user will use to reach the suggested destination or activity.

[1496] "Source" refers to a database or Internet resource that the server accesses to obtain relevant location or activity information.

[1497] "Place" refers to a specific geographic location or facility that is suggested as a destination.

[1498] "Activities" refers to specific activities and events that can be done while out and about.

[1499] "Plans" refers to detailed suggestions of destinations and activities generated based on the user's profile information.

[1500] "Feedback" refers to the experiences and opinions that users input into the system after actually going out.

[1501] "Accuracy" refers to a performance indicator that indicates how appropriate the destinations and activities provided by the system are in relation to the user's expectations and needs.

[1502] The system of the present invention aims to suggest optimal destinations and activities for children based on detailed information (age, interests, budget, and mode of transportation) entered by the user. The system is mainly composed of three elements: a terminal that receives user input, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[1503] Entering your user profile

[1504] The user launches the application and enters their child's age (e.g., 3 years old), interest (e.g., railways), budget (e.g., 5,000 yen), and mode of transportation (e.g., train) into the device. This information is sent from the device to the server. The input screen has a user-friendly UI design, providing easy-to-enter forms and drop-down menus.

[1505] Profile analysis and database search

[1506] The server analyzes the received profile information. The analytical tool used here is a generative AI model. Based on the analyzed profile information, a database of related places and activities is searched. For example, for a profile of a "3-year-old child who loves trains," the server retrieves information such as "railway museums" and "local train ride experiences" from the database.

[1507] Plan Generation

[1508] Based on the information acquired by the server, the optimal plan is generated, taking into account budget and means of transportation. This generation process also uses a generative AI model to build proposals optimized for the user profile. As a specific example, a "Railway Museum Plan" is generated. A specific example is shown below:

[1509] Railway Museum Plan

[1510] Directions: 30 minutes by train, 10 minutes by bus

[1511] Admission fee: 1000 yen for adults, free for children

[1512] Activities: Mini train, driving simulator

[1513] View Suggestions

[1514] The generated plan is sent from the server to the terminal, which then displays the plan to the user. A screen has been developed that displays the plan details in a visually easy-to-understand design.

[1515] Gathering feedback and improving the system

[1516] After leaving the facility, users enter their feedback into the device and send it to the server. Feedback is collected using evaluation forms and free-form comment fields. For example, users can enter specific impressions such as, "I had a lot of fun riding the miniature trains at the railway museum, but the driving simulator was out of order." This feedback is analyzed by the server and used as training data for the generative AI model, improving the accuracy of the system's suggestions.

[1517] Example prompt

[1518] Specific examples of prompts include:

[1519] "Age: 3 years old" "Interest: Trains" "Budget: 5,000 yen" "Method of transportation: Train"

[1520] In this way, the system receives and analyzes information from the user in a series of steps, and proposes the optimal outing plan. Subsequent feedback is collected and analyzed to continuously improve the accuracy of the system.

[1521] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1522] Step 1:

[1523] The user starts the application and enters detailed information about their child (age, interests, budget, and mode of transportation). Specifically, they enter age "3 years old," interest "railway," budget "5,000 yen," and mode of transportation "train." This input is collected by the device and processed in the next step.

[1524] Input: Age, interests, budget, transportation information

[1525] Output: User profile data

[1526] Step 2:

[1527] The device sends the collected user profile data to the server. The data is encrypted and sent securely. Specifically, the device transfers the data using the HTTPS protocol.

[1528] Input: User profile data

[1529] Output: User profile data sent to the server

[1530] Step 3:

[1531] The server analyzes the received user profile data. A generative AI model is used here. The server analyzes each item in the profile (age, interests, budget, mode of transportation) and classifies it into a specific category. For example, an age of "3 years old" would be classified as "Toddlers," and an interest of "Railways" would be classified as "Transportation."

[1532] Input: User profile data

[1533] Output: Analyzed profile data (data classified by category)

[1534] Step 4:

[1535] The server searches the database based on the parsed profile data. During this search process, it retrieves information about related places and activities (e.g., railway museums, local train ride experiences). The server uses SQL queries to retrieve relevant entries from the database.

[1536] Input: Analyzed profile data

[1537] Output: Search results data (list of related places and activities)

[1538] Step 5:

[1539] The server generates the optimal plan based on the search results, taking into account budget and means of transportation. This generation process again uses the generative AI model to build a plan optimized for the user profile. As a specific example, a "Railway Museum Plan" is generated, which includes directions (30 minutes by train, 10 minutes by bus), admission fees (1,000 yen for adults, free for children), and activities (mini train, driving simulator).

[1540] Input: Search result data, generative AI model

[1541] Output: Optimal plan data

[1542] Step 6:

[1543] The server sends the generated plan to the device. During this process, the data is formatted and sent in a format that is easy for the user to view. The device uses responsive design to display the plan in a visually easy-to-understand layout for the user.

[1544] Input: Optimal plan data

[1545] Output: Plan data sent to the device

[1546] Step 7:

[1547] The user checks the generated plan and makes specific plans for the trip. After the trip, the user enters feedback into the application. The feedback input screen includes an evaluation form and a free-form comment field, where the user can enter their specific experiences and opinions.

[1548] Input: Feedback based on the user's actual experience

[1549] Output: Feedback data

[1550] Step 8:

[1551] The server analyzes the received feedback data. This analysis uses a generative AI model to evaluate the feedback data and use it to improve the accuracy of the next proposal. The server also updates the database and uses it for the next search and plan generation.

[1552] Input: Feedback data

[1553] Output: Updated database, training data for accuracy improvement

[1554] (Application example 1)

[1555] 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."

[1556] Modern parents face the challenge of finding the right destinations and activities for their children based on their interests, age, budget, and transportation. Particularly when planning activities in physical stores, it can be difficult to find the best options from the vast amount of information available, making it difficult to quickly obtain the right information. To solve this problem, a system is needed that automatically suggests the best physical store activities based on user-entered information.

[1557] 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.

[1558] In this invention, the server includes means for receiving information on the child's age, interests, budget, and transportation method input by the user, means for searching for related spot and activity information from various information sources, and means for generating a plan suited to the child's interests based on the search results. This makes it possible to suggest optimal activities at physical stores based on the profile information input by the user, and to generate and provide a detailed plan to the user.

[1559] "Means for receiving user-entered information on a child's age, interests, budget, and mode of transportation" refers to an interface that allows parents to use an application or device to enter their child's basic data and interests, the daily budget, and the mode of transportation they will use.

[1560] "Means for searching for relevant spot and activity information from various sources" refers to a function that utilizes the Internet, databases, and other information providing services to collect appropriate spot and activity information based on the profile entered by the user.

[1561] The "means of generating a plan suited to the child's interests based on the search results" refers to an algorithm that uses the collected information to select destinations and activities that are best suited to the child's age and interests, and creates a specific visiting plan.

[1562] The "means for providing the generated plan to the user" is a function for displaying the generated visiting plan and activity proposals on the user's terminal.

[1563] "Means for receiving feedback from users and improving the accuracy of the system" refers to a function that receives users' impressions and ratings of the activities they have actually undertaken and the spots they have visited, and uses this information to improve the system's suggestion algorithm.

[1564] The "means for suggesting activities at physical stores" is a function that selects activities that can be carried out at physical stores that can actually be visited from the collected activity information and suggests them to the user.

[1565] The "means for generating detailed plans for activities at physical stores and providing them to users" is a function for creating plans for selected physical store activities, including details such as specific visit schedules, access methods, and costs, and presenting these plans to users.

[1566] A system embodying the present invention is described in detail below.

[1567] Basic system configuration

[1568] 1. Enter your user profile

[1569] Users launch a smartphone application and enter information about their child's age, interests, budget, and mode of transportation, which is then sent from the device to the server.

[1570] 2. Profile analysis and database search

[1571] The server then parses the received user profile using a web framework called Flask, then searches an SQLite database and relevant sources on the internet to gather activity information based on age, interests, budget, and mode of transportation.

[1572] 3. Plan Generation

[1573] The server then generates a plan that best suits the user's profile based on the search results. This plan takes into account budget and transportation options, and focuses on activities at physical stores. The plan includes the names of destinations, directions, travel time, financial costs, and details of activities.

[1574] 4. Providing Proposals

[1575] The generated plan is sent to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[1576] 5. Gathering feedback and improving the system

[1577] After leaving the house, users input their feedback into their devices and send it to the server, which analyzes the feedback and uses the data to improve the system's suggestion algorithm.

[1578] Specific processing details

[1579] 1. Data Receipt and Analysis

[1580] The server receives user-submitted profile information using the Flask API, stores it in JSON format, and filters relevant activities based on a SQLite database.

[1581] 2. Searching and filtering information

[1582] The server queries an SQLite database to find activities appropriate for the child's age and interests, while also taking into account budget and transportation options. For example, it searches for activities that fit the criteria, such as "places within a bicycle ride for a 5-year-old child who loves animals and has a budget of under 3,000 yen."

[1583] 3. Plan Generation and Delivery

[1584] Based on the extracted activity information, a detailed itinerary is generated, including specific directions to the locations, costs, travel times, and details of the activities you can enjoy. The generated itinerary is then sent to the user's device in JSON format.

[1585] 4. Feedback Analysis

[1586] After going out based on the provided plan, the user provides feedback through the application, which is analyzed by the server to improve the accuracy of future recommendation algorithms.

[1587] Examples and prompts

[1588] For example, if a 5-year-old child loves animals, has a budget of 3,000 yen, and can travel within a cycling distance, the following information would be entered:

[1589] example:

[1590] UserProfile:

[1591] Age: 5

[1592] Interest: Animals

[1593] Budget: 3000

[1594] Transport: Bicycle

[1595] Proposed plan:

[1596] 1. Name: Zoo

[1597] Description: Animal interaction corner, penguin show

[1598] Cost: Admission - 500 yen for adults, 300 yen for children

[1599] Transportation: 15 minutes by bicycle

[1600] This allows users to quickly plan optimal outings and provide children with a fun experience that suits their interests.

[1601] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1602] Step 1:

[1603] The user launches a smartphone application and enters information about the child's age, interests, budget, and transportation method.

[1604] Input: Children's ages, interests, budget, transportation

[1605] Output: JSON format of the input data

[1606] What it does: A user uses a form in the application to enter details about their child, which are then sent to the server in JSON format.

[1607] Step 2:

[1608] The terminal transmits user data to the server.

[1609] Input: JSON data entered by the user

[1610] Output: Send data to the server

[1611] How it works: The smartphone sends user input information to an API endpoint over the Internet, using the Flask framework.

[1612] Step 3:

[1613] The server parses the received user data and retrieves the appropriate activity information from the SQLite database.

[1614] Input: User data in JSON format

[1615] Output: A list of activity information based on the user profile.

[1616] What it does: The server uses Flask to receive the JSON data and queries an SQLite database to filter activities based on age, interests, budget, and mode of transportation.

[1617] Step 4:

[1618] The server generates an appropriate plan.

[1619] Input: Filtered activity information

[1620] Output: A list of detailed visit plans

[1621] Specific Actions: The server creates a specific itinerary based on the search results, including location names, directions, travel time, costs, and activity details.

[1622] Step 5:

[1623] The server sends the generated plan to the terminal.

[1624] Input: List of detailed visit plans

[1625] Output: Send data to the user's terminal

[1626] Specific operation: The generated visit plan is sent from the server to the user's smartphone in JSON format. The Flask framework and REST API are used.

[1627] Step 6:

[1628] The terminal displays the proposed plan to the user.

[1629] Input: JSON data of detailed visit plan

[1630] Output: Plan information displayed on screen

[1631] Specific operation: The smartphone application extracts the visit plan from the received JSON data and displays it on the user interface.

[1632] Step 7:

[1633] Go out based on the plan selected by the user.

[1634] Input: Selected plan information

[1635] Output: Real-world outing experience

[1636] Specific behavior: Visit designated physical stores and activities according to the plan selected by the user.

[1637] Step 8:

[1638] Users provide feedback after their trip.

[1639] Input: Feedback information

[1640] Output: Send feedback data to the server

[1641] What happens: The user uses the feedback form within the application to enter and submit their thoughts and ratings about the activity they visited.

[1642] Step 9:

[1643] The server receives the feedback, stores it in a database and analyzes it.

[1644] Input: Feedback data

[1645] Output: Analysis results and system improvement data

[1646] How it works: The server receives the feedback data, analyzes it, and stores the results in a database to improve the accuracy of future activity suggestions.

[1647] 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.

[1648] The system of the present invention suggests optimal destinations and activities for children based on information entered by the user, and also has the ability to recognize the user's emotions and adjust suggestions based on those emotions. The system includes a terminal that receives the user's input information, a server that analyzes the information and recognizes emotions, and a network that exchanges information between the server and the terminal.

[1649] 1. Basic configuration

[1650] Entering your user profile

[1651] The user starts the system and enters information about their child's age, interests, budget, mode of transportation, and their own emotional state on the input screen. This information is then saved on the device as a profile.

[1652] Profile analysis and database search

[1653] The server then analyzes the received profile information, filtering recommended activities and places based on the child's age and interests.

[1654] Analysis by emotion engine

[1655] Furthermore, the server is equipped with an emotion engine that analyzes the user's emotion information and adjusts the proposed plan based on the emotion data entered by the user.

[1656] Database search

[1657] The server searches its internal database and internet sources for relevant spot and activity information, and the search results include details such as the spot name, address, directions, admission fees, and activity details.

[1658] Plan Generation

[1659] The server analyzes the search results and generates multiple itineraries, each including specific travel times, costs, and details of activities to enjoy, taking into account the user's budget, transportation options, and emotions identified by the emotion engine.

[1660] Providing suggestions

[1661] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and plan their outing.

[1662] Gathering feedback and improving the system

[1663] After leaving the house, the user inputs feedback into the device and sends it to the server. The server analyzes this feedback and uses it to improve the accuracy of the system. The feedback is also analyzed as emotional information to further improve the accuracy of the next suggestion.

[1664] 2. Program Processing Overview

[1665] When a device sends a user profile to the server, the server first analyzes the profile information, filters the target activities based on age information, and then prioritizes the selected spots using interest information.

[1666] In parallel, the emotion engine analyzes the emotion data entered by the user. The analysis results are reflected in the plan generation process, and suggestions appropriate to the user's emotional state are made.

[1667] For example, if the user is targeting a 3-year-old child who loves trains, the server will search for railway museums, local train ride experiences, railway parks, etc. Among these spots, it will further narrow down the search to those that are reachable within the budget.

[1668] The generated plan includes specific directions (e.g., 30 minutes by train, 10 minutes by bus), admission fees (e.g., 1,000 yen for adults, free for children), and details of activities within the spot (e.g., mini train, driving simulator). This information is sent from the server to the terminal and displayed to the user.

[1669] The feedback provided by users after going out is an important factor in improving the system. The server receives this feedback and uses it to improve the accuracy of the database and the proposal algorithm. The feedback also includes emotional information, which is reflected in the next proposal.

[1670] 3. Specific Examples

[1671] Case study: Going out with a 3-year-old who loves trains

[1672] 1. The user launches the application and enters the following into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," "Method of transportation: Train," and "Emotion: Feeling excited."

[1673] 2. The device sends the profile to the server.

[1674] 3. The server parses the received information and searches for rail-related activity.

[1675] 4. The server retrieves candidates such as "Railway Museum," "Local Railway Ride Experience," and "Railway Park" from the database, and generates a specific plan for each candidate that takes into account transportation access and admission fees.

[1676] 5. The server sends the generated plan list to the terminal.

[1677] 6. The device displays the candidate plans to the user.

[1678] Example: "Railway Museum Plan"

[1679] Directions: 30 minutes by train, 10 minutes by bus

[1680] Admission fee: 1000 yen for adults, free for children

[1681] Activities: Mini train, driving simulator

[1682] 7. The user selects one of the proposed plans and plans their outing.

[1683] 8. After leaving the home, the user inputs feedback into the application and sends it to the server. The feedback includes emotional information.

[1684] 9. The server analyzes the feedback and improves the accuracy of future suggestions.

[1685] This invention allows parents to efficiently find suitable outing destinations and plan trips that fit their children's interests. In addition, the introduction of an emotion engine allows for more appropriate suggestions based on the user's emotions.

[1686] The processing flow will be explained below.

[1687] Step 1:

[1688] The user launches the application and enters information about their child's age, interests, budget, mode of transportation, and current emotions (e.g., excited, tired, excited, etc.). This information is stored on the device as a profile.

[1689] Step 2:

[1690] The device sends the saved profile information to the server, which converts the profile information into a data format and sends it to the server via secure communication.

[1691] Step 3:

[1692] The server analyzes the received profile information, filtering recommended activities based on the child's age and using interest information to prioritize relevant activities and places.

[1693] Step 4:

[1694] The server uses an emotion engine to analyze the emotion data entered by the user. For example, if the user enters "fun," the server will prioritize plans that correspond to that emotion.

[1695] Step 5:

[1696] The server searches for relevant spot and activity information from internal databases and internet sources. The search results include details such as the spot name, address, directions, admission fees, and activity details.

[1697] Step 6:

[1698] The server generates multiple itineraries based on the search results, taking into account the user's budget, transportation options, and emotional information. Each itinerary includes specific travel times, costs, and details of activities that can be enjoyed.

[1699] Step 7:

[1700] The server sends the generated plans to the terminal, where the information is converted into a display format and sent in a format that is easy for the user to understand.

[1701] Step 8:

[1702] The terminal displays the received plans to the user, who can then select the most suitable one from the presented plans and plan their outing.

[1703] Step 9:

[1704] After the trip, users enter feedback into the application, including specific experiences, satisfaction, areas for improvement, and emotional information during the trip.

[1705] Step 10:

[1706] The terminal transmits the collected feedback information to the server, which also converts the feedback information into a data format before transmitting it.

[1707] Step 11:

[1708] The server receives and analyzes the feedback information. The analysis results are reflected in updating the database and improving the plan generation algorithm. In addition, the user's emotional information is used in the next proposal.

[1709] This series of steps allows users to efficiently find outings that match their child's interests and current emotions, and allows the server to continuously improve the accuracy of its suggestions.

[1710] Example 2

[1711] 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."

[1712] Conventional systems could suggest suitable outings and activities for children based on information entered by the user, but they did not provide suggestions that took into account the user's emotional information. As a result, they were unable to suggest optimal outings based on the user's emotions, making it difficult to improve the quality of the user experience. Furthermore, there was a lack of effort to collect feedback and use it to improve the accuracy of the system. This made it difficult to improve the accuracy of suggestions and user satisfaction.

[1713] 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.

[1714] In this invention, the server includes means for receiving information on the child's age, interests, budget, and mode of transportation input by the user, means for receiving user emotion information, means for analyzing the profile information and emotion information and prioritizing recommended activities and spots, means for searching for related spot and activity information from various information sources, means for generating a plan suited to the child's interests and the user's emotions based on the search results, means for providing the generated plan to the user, and means for receiving user feedback and improving the accuracy of the system. This makes it possible to suggest optimal destinations and activities taking the user's emotions into consideration, and realizes continuous improvement of the system's accuracy based on the feedback.

[1715] "User" refers to an individual who uses the system and enters information to find out about their child's outings and activities.

[1716] "Profile Information" refers to information entered by the user regarding their child's age, interests, budget, and transportation.

[1717] "Emotion information" refers to information input by the user about their own emotions and mental state.

[1718] "Server" refers to a computer system that receives profile information and emotion information, analyzes them, searches various information sources, generates an optimal plan, and provides it to the user.

[1719] "Filtering" refers to the process of selecting recommended activities and places based on profile information and sentiment information.

[1720] "Various sources" refers to internal databases and internet sources, including information on travel destinations and activities.

[1721] "Plan" refers to suggestions for destinations and activities generated based on the user's and children's interests, budget, emotions, and transportation options.

[1722] "Generation" refers to the server analyzing profile information and emotional information and creating plans for outings and activities based on that information.

[1723] "Feedback" refers to evaluations, impressions, and information for improvement of the system provided by users after going out.

[1724] "Improved accuracy" refers to using feedback to improve the system's suggestions and analytical capabilities, thereby increasing the quality of suggestions from the next time onwards.

[1725] The present invention is a system that suggests optimal destinations and activities for children based on information input by the user, such as their age, interests, budget, mode of transportation, and emotional state. The system includes a terminal that receives the information input by the user, a server that analyzes the information and generates suggestions, and a network that exchanges information between the server and the terminal.

[1726] The user launches the application and enters the following information into the profile entry screen:

[1727] Child's age (e.g., 3 years old)

[1728] Interests (e.g., railways)

[1729] Budget (e.g. 5,000 yen)

[1730] Transportation (e.g. train)

[1731] Your (user's) emotional information (e.g., feeling excited)

[1732] The device receives this profile information and sends it to the server, which then performs the necessary analysis. Specifically, the server is equipped with a data analysis engine and an emotion engine, which perform detailed analysis of the profile information and emotion information.

[1733] Hardware and Software Used

[1734] Device: Input device such as smartphone, tablet, PC, etc.

[1735] Servers: Cloud computers and local servers

[1736] Analysis engine: Database management system, sentiment analysis model

[1737] Communication networks: Internet and local networks

[1738] Data processing and calculation

[1739] The server processes and calculates data in the following steps.

[1740] 1. Profile Analysis: A data analysis engine filters suitable activity suggestions based on age, interests, budget and mode of transportation.

[1741] 2. Emotion data analysis: The emotion engine analyzes the user's emotional information and reflects it in the proposed plan.

[1742] 3. Database Search: The server searches its internal database and internet sources for relevant spot and activity information, including spot names, addresses, directions, admission fees, and activity details.

[1743] 4. Plan Generation: Based on the search results, multiple plans are generated taking into account the user's budget, means of transportation, and emotions.

[1744] 5. Providing proposals: The generated plan is sent from the server to the terminal and displayed to the user.

[1745] 6. Collect feedback and improve the system's accuracy: After going out, users enter feedback, which is used to improve the accuracy of the next suggestion.

[1746] Specific examples

[1747] For example, if a user is looking for a place to go for their 3-year-old child who loves trains, the following process will be executed:

[1748] 1. The user launches the application and enters the following into their profile: "Age: 3 years old," "Interest: Railways," "Budget: 5,000 yen," "Method of transportation: Train," and "Emotion: Feeling excited."

[1749] 2. The device sends the profile information to the server.

[1750] 3. The server analyzes the profile and emotional information and searches a database for related spots and activities (e.g., railway museums, local railway ride experiences, railway parks).

[1751] 4. The server generates a specific plan (e.g., Railway Museum Plan - Directions: 30 minutes by train, 10 minutes by bus / Admission fee: 1,000 yen for adults, free for children / Activities: mini train, driving simulator).

[1752] 5. The device displays the proposed plan to the user.

[1753] 6. After the user leaves the house, they enter their feedback into the application and send it to the server, which improves the accuracy of suggestions for the next trip.

[1754] Prompt Sentence Examples

[1755] Below is an example of a prompt that the user can enter.

[1756] "Age: 3, Interests: Trains, Budget: 5,000 yen, Transportation: Train, Emotions: Feeling excited"

[1757] This allows users to efficiently find the perfect outing destination that matches their child's interests and their own emotions. The server uses the feedback to improve the accuracy of the system, and future suggestions will be more accurate.

[1758] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1759] Processing Steps

[1760] Step 1: Fill in your user profile

[1761] The user launches the application and enters their child's age, interests, budget, mode of transportation, and their own emotional information into the profile entry screen. The information entered is as follows:

[1762] Child's age: 3 years old

[1763] Interests: Railways

[1764] Budget: 5,000 yen

[1765] Means of transportation: train

[1766] Emotional information: Feeling excited

[1767] Input data: Child's age, interests, budget, transportation, emotional information

[1768] Output data: User profile information

[1769] Step 2: Sending the profile to the server

[1770] The device sends the user's profile information to the server via an HTTP request. The data includes the child's age, interests, budget, mode of transportation, and emotional information.

[1771] Input data: User profile information

[1772] Output data: Profile information sent to the server

[1773] Step 3: Parse the profile information

[1774] The server analyzes the received profile information, and a data analysis engine filters suitable activity suggestions based on age, interests, budget, and mode of transportation, generating a filtered list of activities as a result of the analysis.

[1775] Input data: Profile information sent to the server

[1776] Processing: Analyzes profile information and filters activity candidates

[1777] Output data: Filtered activity list

[1778] Step 4: Analyze the sentiment data

[1779] The emotion engine installed on the server analyzes the emotion data entered by the user, and the analysis results are taken into consideration when generating a plan based on the user's emotion.

[1780] Input data: User's emotional information

[1781] Processing content: Emotion data analysis

[1782] Output data: Sentiment analysis results

[1783] Step 5: Database Search

[1784] The server retrieves relevant spot and activity information from an internal database and various external sources, including spot names, addresses, directions, admission fees, and activity details.

[1785] Input data: filtered activity list, sentiment analysis results

[1786] Processing content: Database search, acquisition of related information

[1787] Output data: Detailed information about spots and activities

[1788] Step 6: Generate a plan

[1789] The server generates multiple plans based on the search results, taking into account the user's budget, transportation means, and emotions. Each plan includes details of specific transportation means, travel time, expenses, and activities that can be enjoyed.

[1790] Input data: detailed information on spots and activities, user budget and transportation method, sentiment analysis results

[1791] Process: Generate plan, create plan details

[1792] Output data: List of generated plans

[1793] Step 7: Provide a proposal

[1794] The server sends the generated plan list to the terminal, which receives it and displays it to the user. The user can then select the most suitable plan from the proposed plans.

[1795] Input data: List of generated plans

[1796] Output data: Plan list sent to the device, plans displayed to the user

[1797] Step 8: Gather feedback and refine the system

[1798] After leaving the house, the user enters feedback into the application and sends it to the server. The server receives this feedback and uses it to improve the accuracy of the system. The feedback also includes the user's emotional information, which is reflected in future suggestions.

[1799] Input data: User feedback and emotional information

[1800] Processing content: Analysis of feedback, updating system improvement algorithms

[1801] Output data: Proposed algorithm for updated system

[1802] Through the above processing steps, optimal destinations and activities are suggested to the user, and the accuracy of the system is continuously improved based on feedback.

[1803] (Application example 2)

[1804] 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."

[1805] Conventional food delivery services have had the challenge of being unable to recommend the best restaurant or meal based on a user's profile information. Furthermore, there are no systems that consider a user's emotional information when proposing recommended meals or restaurants. This has left users unable to choose the best delivery service that best suits their mood and needs at the time.

[1806] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving information on the child's age, interests, budget, and mode of transportation input by the user, means for searching for related spot and activity information from various information sources, means for generating a plan suited to the child's interests based on the search results, means for providing the generated plan to the user, means for receiving feedback from the user and improving the accuracy of the system, and means for analyzing the user's emotional information and adjusting suggestions according to the user's emotional state. This enables the user to receive recommendations of restaurants and menus that are optimal for their current emotions and situation.

[1807] "User" means any person who uses the System and enters information.

[1808] "Child's age" is information that refers to the actual age of the child targeted by the system.

[1809] "Interests" refers to specific interests or hobbies that a child has.

[1810] "Budget" refers to information that indicates the upper limit of the amount of money that a user sets when using the system.

[1811] "Transportation" is information that indicates the transportation that the user uses to travel to the destination.

[1812] "Profile information" refers to comprehensive information entered by the user, such as the child's age, interests, budget, and mode of transportation, as well as the user's own emotional information.

[1813] "Emotion information" is information input by the user that indicates their current emotional state.

[1814] "Feedback" refers to information such as impressions and evaluations that users provide to the system after going out or making suggestions.

[1815] "Spot" refers to a specific destination or tourist spot that the system will suggest.

[1816] "Activity information" refers to information that indicates the activities that can be carried out at various spots provided by the system.

[1817] "Plan" refers to a system-generated plan that includes specific proposals and schedules.

[1818] "Search Tool" refers to the functionality for searching for relevant spot and activity information from external and internal databases.

[1819] "Analysis means" refers to a function for analyzing profile information and emotional information entered by a user.

[1820] "Proposal means" refers to the function for generating and providing the optimal plan to the user based on the analysis results.

[1821] "Feedback receiving means" refers to a function for receiving and analyzing feedback information provided by a user.

[1822] The "proposal adjustment means" refers to a function for adjusting the proposal content based on the user's emotional information.

[1823] The present invention relates to a system that proposes optimal food delivery plans based on a user's profile information and emotional information. This system recommends optimal restaurants and menus based on the user's input of information such as the age, interests, budget, mode of transportation, and emotional information about the child.

[1824] Basic system configuration

[1825] Entering your user profile

[1826] A user starts the application on a smartphone or tablet device and then enters user profile information (e.g., family composition, allergy information, budget, emotional information), which is then saved on the device as a profile.

[1827] Profile analysis and database search

[1828] The profile information entered by the user is sent to a server that uses the following hardware and software:

[1829] Hardware: Cloud-based servers (e.g., AWS)

[1830] Software: Database management system (e.g., MySQL, PostgreSQL), Rest API (e.g., Node.js, Express), Sentiment analysis engine (e.g., IBM Watson, Microsoft Azure Sentiment Analysis API)

[1831] The server first analyzes your profile information, filtering restaurant and menu recommendations based on your age and interests.

[1832] Analysis by emotion engine

[1833] The server's built-in emotion engine analyzes the user's emotional information. The results of this analysis are reflected in the plan generation process, and suggestions are made that are appropriate for the user's emotional state. For example, if the user inputs "I'm tired," restaurants and menus that offer a relaxing environment will be prioritized.

[1834] Database search

[1835] The server searches its internal database and internet sources for relevant restaurant and menu information. The search results include details such as restaurant name, address, dish description, price range, and customer reviews.

[1836] Plan Generation

[1837] The server analyzes the search results and generates multiple itineraries, each including specific transportation modes, prices, and meal details, taking into account the user's budget, transportation options, and emotions identified by the emotion engine.

[1838] Providing suggestions

[1839] The generated plan is sent from the server to the terminal and displayed to the user, who can then select the most suitable plan from the proposed plans and order delivery.

[1840] Gathering feedback and improving the system

[1841] After placing an order, the user enters feedback into the device and sends it to the server. The server analyzes this feedback and uses it to improve the system's accuracy. The feedback is also analyzed for emotional information, further improving the accuracy of the next recommendation.

[1842] Specific examples

[1843] Case study: Relaxed family meal delivery

[1844] 1. A user launches the application and enters the following into their profile: Age: 35, Interests: Pizza, Budget: 3000 yen, Emotion: Tired.

[1845] 2. The device sends the profile to the server.

[1846] 3. The server analyzes the received information and searches for pizza-related restaurants.

[1847] 4. The server retrieves candidates such as "Pizza specialty store A," "Delivery pizza store B," and "Italian restaurant C" from the database, and generates specific plans for each candidate that take into account transportation access and price.

[1848] 5. The server sends the generated plan list to the terminal.

[1849] 6. The device displays the candidate plans to the user.

[1850] Example prompt for a generative AI model:

[1851] plaintext

[1852] Recommend a pizza restaurant within a budget of 3000 yen for a tired 35-year-old user. Please consider name-based information and prioritize restaurants that offer a particularly relaxing environment.

[1853] This system is expected to improve the quality of life by enabling users to easily find the best restaurant and menu that suits their current mood and situation.

[1854] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1855] Step 1:

[1856] The user launches the application and enters their profile information. Specifically, they use a smartphone or tablet to enter their age, interests, budget, mode of transportation, and emotional information. The input data is temporarily stored on the device for use in the next step. The output of the input process is the entire profile information entered by the user.

[1857] Step 2:

[1858] The device sends profile information to the server. This process is performed using an HTTP request, and the data sent is encoded in JSON format. The input is the user's profile information, and the output is the server receiving the profile information.

[1859] Step 3:

[1860] The server analyzes the received profile information. The hardware used by the pros is a cloud-based server, and the software used is, for example, Node.js. The analysis first filters target restaurants and menus based on age information. The input is the profile information, and the output is a list of filtered restaurants and menus.

[1861] Step 4:

[1862] The server uses a sentiment analysis engine to analyze the user's sentiment information. Specifically, it uses a sentiment analysis engine (e.g., IBM Watson, Microsoft Azure sentiment analysis API) to convert the sentiment information entered by the user into a text sentiment score. The input is the user's sentiment information, and the output is the sentiment analysis result. This analysis result is used in the next step.

[1863] Step 5:

[1864] The server searches for relevant restaurant and menu information from an internal database and internet sources. The software used is a database management system (e.g., MySQL, PostgreSQL). The input for the search is the filtered restaurant list and the sentiment analysis results, and the output is a list with detailed restaurant and menu information.

[1865] Step 6:

[1866] Based on the search results, the server generates multiple plans that take into account the user's budget, means of transportation, and emotional state. Plan generation combines information obtained from the database with the results of emotional analysis. Specifically, it selects restaurants and menus that are within the user's budget and sets recommendation levels according to their emotions. The input is a detailed list of restaurant and menu information, and the output is a list of plans to suggest to the user.

[1867] Step 7:

[1868] The server sends the generated plan list to the terminal. This process is again performed using an HTTP request, and the sent data is encoded in JSON format. The input is the generated plan list, and the output is the completion of sending it to the terminal.

[1869] Step 8:

[1870] The terminal displays the proposed plans to the user, and the user selects the most suitable one from the displayed plans. The input is the plan list sent from the server, and the output is the plan selected by the user.

[1871] Step 9:

[1872] After the user completes the trip or delivery, they input their feedback into the application. The feedback includes emotional information. The input is the user's feedback information and is saved on the device.

[1873] Step 10:

[1874] The device sends the feedback information to the server. The transmission is again performed using an HTTP request, and the transmitted data is encoded in JSON format. The input is the user's feedback information, and the output is the receipt of the feedback information by the server.

[1875] Step 11:

[1876] The server analyzes the feedback information to improve the accuracy of the system. The feedback also contains emotional information, which is reflected in the next suggestion. The input is the user's feedback information, and the output is an updated suggestion algorithm and database.

[1877] This processing flow allows users to easily find the best restaurant and menu that suits their current mood and situation, and the system's accuracy is continuously improved based on user feedback.

[1878] 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.

[1879] 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.

[1880] 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.

[1881] 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.

[1882] 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.

[1883] 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.

[1884] 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).

[1885] 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.

[1886] 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."

[1887] 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.

[1888] 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).

[1889] 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.

[1890] 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.

[1891] 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.

[1892] 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.

[1893] 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.

[1894] 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.

[1895] 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.

[1896] 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.

[1897] 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.

[1898] 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.

[1899] The following is further disclosed regarding the above embodiment.

[1900] (Claim 1)

[1901] a means for receiving user-entered information regarding the child's age, interests, budget, and mode of transportation;

[1902] A means of searching for relevant spot and activity information from various sources;

[1903] A means of generating a plan based on the search results that is suited to the child's interests;

[1904] means for providing the generated plan to a user;

[1905] a means for receiving user feedback to improve the accuracy of the system; and

[1906] A system including:

[1907] (Claim 2)

[1908] 10. The system of claim 1, further comprising means for analyzing profile information entered by a user to filter recommended activities.

[1909] (Claim 3)

[1910] 10. The system according to claim 1, further comprising means for generating an appropriate plan taking into consideration a user's budget and means of transportation.

[1911] "Example 1"

[1912] (Claim 1)

[1913] a means for receiving user input information regarding the user's age, interests, budget, and mode of transportation;

[1914] a means of searching for relevant place and activity information from a variety of sources;

[1915] A means for generating a plan based on the search results that is suited to the user's interests;

[1916] means for providing the generated plan to a user;

[1917] a means for receiving user feedback to improve the accuracy of the system; and

[1918] A system including:

[1919] (Claim 2)

[1920] 10. The system of claim 1, further comprising means for analyzing profile information entered by a user to filter recommended activities.

[1921] (Claim 3)

[1922] 10. The system of claim 1, further comprising means for generating an appropriate plan taking into account a user's budget and means of transportation.

[1923] "Application Example 1"

[1924] (Claim 1)

[1925] a means for receiving user-entered information regarding the child's age, interests, budget, and mode of transportation;

[1926] A means of searching for relevant spot and activity information from various sources;

[1927] A means of generating a plan based on the search results that is suited to the child's interests;

[1928] means for providing the generated plan to a user;

[1929] a means for receiving user feedback to improve the accuracy of the system; and

[1930] A way to suggest in-store activities from search results,

[1931] means for generating and providing a detailed plan of activities at the physical store to a user;

[1932] A system including:

[1933] (Claim 2)

[1934] 10. The system of claim 1, further comprising means for analyzing profile information entered by a user to filter recommended activities.

[1935] (Claim 3)

[1936] 10. The system according to claim 1, further comprising means for generating an appropriate plan taking into consideration a user's budget and means of transportation.

[1937] "Example 2: Combining Emotion Engines"

[1938] (Claim 1)

[1939] a means for receiving user-entered information regarding the child's age, interests, budget, and mode of transportation;

[1940] means for receiving user emotion information;

[1941] a means for analyzing profile information and sentiment information to filter recommended activities;

[1942] A means of searching for relevant spot and activity information from various sources;

[1943] A means for generating a plan suitable for the child's interests and the user's emotions based on the search results;

[1944] means for providing the generated plan to a user;

[1945] a means for receiving user feedback to improve the accuracy of the system; and

[1946] A system including:

[1947] (Claim 2)

[1948] 10. The system of claim 1, further comprising means for analyzing the profile information and the sentiment information and prioritizing the recommended activities and places.

[1949] (Claim 3)

[1950] 10. The system according to claim 1, further comprising means for generating an appropriate plan taking into consideration a user's budget and means of transportation.

[1951] "Application example 2 when combining emotion engines"

[1952] (Claim 1)

[1953] a means for receiving user-entered information regarding the child's age, interests, budget, and mode of transportation;

[1954] A means of searching for relevant spot and activity information from various sources;

[1955] A means of generating a plan based on the search results that is suited to the child's interests;

[1956] means for providing the generated plan to a user;

[1957] a means for receiving user feedback to improve the accuracy of the system; and

[1958] means for analyzing the user's emotional information and tailoring suggestions according to the user's emotional state;

[1959] A system including:

[1960] (Claim 2)

[1961] 10. The system of claim 1, further comprising means for analyzing profile information entered by a user to filter recommended activities.

[1962] (Claim 3)

[1963] 10. The system according to claim 1, further comprising means for generating an appropriate plan taking into consideration a user's budget and means of transportation. [Explanation of symbols]

[1964] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for receiving user-entered information regarding the child's age, interests, budget, and mode of transportation; A means of searching for relevant spot and activity information from various sources; A means of generating a plan based on the search results that is suited to the child's interests; means for providing the generated plan to a user; a means for receiving user feedback to improve the accuracy of the system; and A system including:

2. 2. The system of claim 1, further comprising means for analyzing profile information entered by a user and filtering recommended activities.

3. 2. The system according to claim 1, further comprising means for generating an appropriate plan taking into consideration a user's budget and means of transportation.

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