system

Abstract

An object of a system according to an embodiment is to enable an inbound foreigner to easily find a sightseeing spot or a shop that suits his / her hobbies and preferences.SOLUTION: A system includes a proposal unit, a display unit, and a guide unit. The suggestion unit suggests a sightseeing spot or a shop based on the user's hobbies and preferences. The display unit displays the origin of the highlight spot or the famous place of the sightseeing spot in the native language in conjunction with the GPS. The guide part teaches how to order a popular dish in the store.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] Conventional technology makes it difficult for inbound foreign tourists to find tourist spots and shops that suit their interests and preferences, which could result in a decline in the quality of their tourism experience.

[0005] The system according to the embodiment aims to enable inbound foreign tourists to easily find tourist spots and shops that suit their interests and preferences. [Means for solving the problem]

[0006] The system according to the embodiment includes a suggestion unit, a display unit, and a guidance unit. The suggestion unit suggests tourist spots and shops based on the user's hobbies and preferences. The display unit works in conjunction with GPS to display the highlights of tourist spots and the origins of famous places in the user's native language. The guidance unit teaches how to order popular dishes at restaurants. [Effects of the Invention]

[0007] The system according to the embodiment can enable inbound foreign tourists to easily find tourist spots and shops that suit their interests and preferences. [Brief explanation of the drawings]

[0008] [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. DETAILED DESCRIPTION OF THE INVENTION

[0009] 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.

[0010] First, the terms used in the following description will be explained.

[0011] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] 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.

[0013] 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.

[0014] 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), and Bluetooth (registered trademark).

[0015] 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."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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).

[0019] 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.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. 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 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. 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.

[0022] 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.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) A tourism support system according to an embodiment of the present invention is a system that suggests tourist spots and restaurants based on a user's preferences, displays information about tourist spots in the user's native language in conjunction with a GPS, and teaches how to order popular dishes at restaurants. This enables the tourism support system to suggest tourist spots and restaurants based on the user's preferences, provide information about tourist spots, and guide the user on how to order at restaurants.

[0029] A tourism support system according to an embodiment includes a suggestion unit, a display unit, and a guidance unit. The suggestion unit suggests tourist spots and shops based on the user's hobbies and preferences. For example, the generation AI analyzes information about the user's hobbies and preferences and suggests optimal tourist spots and shops based on the analysis. The generation AI receives input from the user in the form of prompts containing instructions on what the user wants the generation AI to do, and the generation AI makes suggestions based on the prompts. The display unit works in conjunction with GPS to display the highlights of tourist spots and the origins of famous landmarks in the user's native language. For example, when the user arrives at a famous Japanese temple, the display unit displays the temple's history and highlights in the user's native language. This allows the user to enjoy sightseeing more deeply. The guidance unit teaches the user how to order popular dishes at a restaurant. For example, when ordering sushi at a Japanese restaurant, the generation AI may provide guidance such as, "This restaurant's recommendation is tuna nigiri sushi. To order, please say, 'Tuna nigiri, please.'" This allows the user to order smoothly without experiencing language barriers. This enables the tourism support system to suggest tourist spots and shops based on the user's hobbies and preferences, provide information on tourist spots, and guide users on how to order at shops.

[0030] The suggestion unit analyzes a user's past travel history and social media posts to make more accurate suggestions. For example, the suggestion unit uses a generation AI to analyze a user's past travel history and suggest the next travel destination based on the places visited and the length of stay. For example, the suggestion unit suggests new tourist spots with similar characteristics based on data on cities the user has previously visited. The suggestion unit also analyzes social media posts to identify themes and activities that the user is interested in. For example, it may discover that the user is interested in natural landscapes or art from frequently posted photos and comments, and suggest tourist spots based on that. The suggestion unit also integrates the user's travel history with social media data to make more accurate suggestions. For example, it may analyze the length of stay and type of activity at past travel destinations to suggest recommended spots at the next travel destination. This enables more accurate suggestions by analyzing a user's past travel history and social media posts.

[0031] The suggestion unit can display other users' reviews and ratings for the suggested tourist spots and shops in real time. For example, the suggestion unit builds a system that displays other users' reviews and ratings for the tourist spots and shops suggested by the generation AI in real time. For example, the latest reviews and ratings for the suggested spots can be displayed for users' reference. The suggestion unit also displays the popularity and satisfaction of the suggested tourist spots and shops based on other users' reviews and ratings. For example, it can display star ratings and the number of comments to make it easier for users to make selections. The suggestion unit also develops a system that dynamically adjusts the content of suggestions based on reviews and ratings that are updated in real time. For example, it can exclude spots with low ratings from the suggestion list and prioritize displaying spots with high ratings. This allows users to refer to other users' reviews and ratings by displaying them in real time.

[0032] The suggestion unit can take into account the user's health condition and physical condition and suggest tourist spots and shops that are appropriate for their physical strength. For example, the suggestion unit will build a system in which a generation AI analyzes the user's health condition and physical condition data and suggests tourist spots and shops that are appropriate for their physical strength. For example, the suggestion unit will suggest a reasonable sightseeing route based on the user's number of steps and heart rate. The suggestion unit will also monitor the user's health condition in real time and dynamically adjust the suggestions based on that data. For example, it will suggest places to rest when the user is tired, and suggest active spots when the user is energetic. The suggestion unit will also develop a system that makes customized suggestions based on the user's physical strength based on the health data. For example, it will suggest nearby tourist spots when the user is feeling unwell, and suggest a trip further away when the user is in good physical condition. This makes it possible to suggest tourist spots and shops that are appropriate for the user's physical strength, taking into account the user's health condition and physical condition.

[0033] The suggestion unit can expand suggestions based on the user's hobbies and preferences to include not only tourist spots but also events and activities. For example, the suggestion unit builds a system in which a generation AI suggests not only tourist spots but also events and activities based on the user's hobbies and preferences. For example, if the user is interested in music, the suggestion unit suggests concerts and live events held in the area. The suggestion unit also analyzes the user's hobbies and preferences and suggests events and activities related to tourist spots based on the analysis. For example, if the user is interested in history, the suggestion unit suggests tours and workshops at historical places. The suggestion unit also develops a system that expands suggestions based on the user's hobbies and preferences to include not only tourist spots but also activities that can be experienced locally. For example, if the user is interested in the outdoors, the suggestion unit suggests hiking and camping activities. This allows suggestions based on the user's hobbies and preferences to be expanded to include not only tourist spots but also events and activities.

[0034] The display unit can work in conjunction with GPS data to automatically display past photos and videos of places the user has visited. For example, the display unit uses GPS data to build a system that automatically displays past photos and videos of places the user has visited. For example, when the user arrives at a historical site, past photos and videos of that site are displayed. The display unit also displays past photos and videos of places the user has visited in real time, enriching the tourist experience. For example, when the user arrives at a tourist spot, historical footage and photos of that site are displayed. The display unit also works in conjunction with GPS data to develop a system that automatically displays past photos and videos of places the user has visited. For example, when the user arrives at a tourist spot, past events and happenings at that site are introduced through video. This enriches the tourist experience by automatically displaying past photos and videos of places the user has visited.

[0035] The display unit can provide the user with the historical background and cultural significance of places visited in an interactive storytelling format. The display unit, for example, uses GPS data to build a system that provides the user with the historical background and cultural significance of places visited in an interactive storytelling format. For example, when a user arrives at a historical landmark, the history of the place is introduced in a narrative format. The display unit also enables the user to interactively learn about the historical background and cultural significance of places visited. For example, when a user arrives at a tourist spot, the history and culture of the place are introduced in a quiz format. The display unit also works in conjunction with GPS data to develop a system that provides the user with the historical background and cultural significance of places visited in an interactive storytelling format. For example, when a user arrives at a tourist spot, the history of the place is introduced using animation and audio. This enriches the tourist experience by providing the user with the historical background and cultural significance of places visited in an interactive storytelling format.

[0036] The display unit can work in conjunction with GPS to provide real-time information about events being held near places visited by the user. For example, the display unit uses GPS data to build a system that provides real-time information about events being held near places visited by the user. For example, when the user arrives at a tourist spot, it displays information about events being held in the vicinity. The display unit also displays real-time information about events being held near places visited by the user, enriching the tourist experience. For example, when the user arrives at a tourist spot, it provides information about festivals and concerts being held in the vicinity. The display unit also works in conjunction with GPS data to develop a system that provides real-time information about events being held near places visited by the user. For example, when the user arrives at a tourist spot, it displays a schedule of events being held in the vicinity. This enriches the tourist experience by providing real-time information about events being held near places visited by the user.

[0037] The guidance unit can analyze the user's dietary history and allergy information to suggest the most suitable dishes. For example, the guidance unit will build a system in which a generating AI analyzes the user's past dietary history and suggests the most suitable dishes based on preferences and allergy information. For example, the guidance unit will suggest recommended dishes at a new restaurant based on dishes the user has liked in the past. The guidance unit will also analyze the user's allergy information in real time and suggest safe dishes based on that data. For example, the guidance unit will suggest dishes that avoid ingredients that the user is allergic to. The guidance unit will also develop a system that integrates dietary history and allergy information to suggest the most suitable dishes for the user. For example, the guidance unit will suggest recommended dishes at a new restaurant based on data on dishes the user has eaten in the past. In this way, the guidance unit can suggest the most suitable dishes by analyzing the user's dietary history and allergy information.

[0038] The guidance unit can support health management by displaying the nutritional information and calories of the dishes ordered by the user in real time. For example, the guidance unit constructs a system in which a generation AI displays the nutritional information and calories of the dishes ordered by the user in real time. For example, the guidance unit displays the calories and nutritional components of the dishes ordered by the user to support health management. The guidance unit also analyzes the nutritional information and calories of the dishes ordered by the user in real time and provides health management advice based on that data. For example, it displays the nutrients and calories that the user should consume. The guidance unit also develops a system that supports health management for the user based on the nutritional information and calories. For example, it displays the nutritional balance of the dishes ordered by the user and suggests healthy meals. This makes it possible to support health management by displaying the nutritional information and calories of the dishes ordered by the user in real time.

[0039] The guidance unit can provide visual guidance in video format on how to order popular dishes at a restaurant. The guidance unit, for example, builds a system in which a generation AI provides visual guidance to a user in video format on how to order popular dishes at a restaurant. For example, the guidance unit may provide a video showing the steps a user takes to order, making it visually easy to understand. The guidance unit may also provide a video showing the names and pronunciations of the dishes the user will order. The guidance unit may also develop a system that provides visual guidance in video format to enable a user to order smoothly. For example, the guidance unit may provide a video showing the steps a user takes to order, making it visually easy to understand. In this way, the guidance unit may provide visual guidance in video format on how to order popular dishes at a restaurant, making it visually easy for a user to order.

[0040] The guidance unit can display other users' reviews and ratings of the food ordered by the user in real time. The guidance unit, for example, builds a system in which a generation AI displays other users' reviews and ratings of the food ordered by the user in real time. For example, the latest reviews and ratings of the food ordered by the user can be displayed for reference. The guidance unit also displays the popularity and satisfaction level of the ordered food based on other users' reviews and ratings. For example, it can display star ratings and the number of comments to make it easier for the user to make a selection. The guidance unit also develops a system that dynamically adjusts the order contents based on reviews and ratings that are updated in real time. For example, it can exclude dishes with low ratings from the suggestion list and prioritize displaying dishes with high ratings. This allows the user to refer to other users' reviews and ratings of the food ordered by displaying them in real time.

[0041] Furthermore, the tourism support system offers a set sale with PoketWi-Fi Prepaid. The tourism support system offers a set sale with PoketWi-Fi Prepaid. This allows users to enjoy sightseeing while ensuring internet connection. For example, a set sale with PoketWi-Fi Prepaid is offered to app users. This allows users to enjoy sightseeing while ensuring internet connection. For example, a message encouraging users who have downloaded the app to purchase PoketWi-Fi Prepaid is displayed. This allows users to enjoy sightseeing while ensuring internet connection by offering a set sale with PoketWi-Fi Prepaid.

[0042] The tourism support system can analyze PoketWi-Fi usage data and propose the optimal plan based on the user's internet usage trends. For example, the tourism support system builds a system that analyzes PoketWi-Fi usage data and proposes the optimal plan based on the user's internet usage trends. For example, the optimal plan is proposed based on the amount of data and time of day that the user frequently uses. The tourism support system also analyzes the user's internet usage trends in real time and proposes the optimal plan based on that data. For example, a high-capacity plan is proposed if the user uses a lot of data. The tourism support system also develops a system that proposes the optimal internet plan to the user based on usage data. For example, the optimal plan is proposed based on the amount of data used by the user and time of day. In this way, convenience for the user is improved by analyzing PoketWi-Fi usage data and proposing the optimal plan based on the user's internet usage trends.

[0043] The tourism support system can monitor PocketWi-Fi usage status in real time and automatically suggest the optimal connection method if the connection is unstable. For example, the tourism support system builds a system that monitors PocketWi-Fi usage status in real time and automatically suggests the optimal connection method if the connection is unstable. For example, it suggests another Wi-Fi network when the connection is unstable. The tourism support system also analyzes the user's connection status in real time and suggests the optimal connection method based on that data. For example, it suggests the optimal connection point when the connection is unstable. The tourism support system also develops a system that suggests the optimal connection method to the user based on usage status. For example, it suggests an alternative connection method when the connection is unstable. In this way, the tourism support system can monitor PocketWi-Fi usage status in real time and automatically suggest the optimal connection method if the connection is unstable, improving user convenience.

[0044] The tourism support system can provide local tourist information and discount coupons to PoketWi-Fi users. For example, a tourism support system is constructed that provides local tourist information and discount coupons to PoketWi-Fi users. For example, when a user arrives at a tourist spot, tourist information and coupons for the surrounding area are provided. The tourism support system also provides local tourist information and discount coupons when a user uses PoketWi-Fi. For example, when a user arrives at a tourist spot, coupons for restaurants and shops in the surrounding area are provided. The tourism support system also develops a system that enriches the tourism experience by providing local tourist information and discount coupons to PoketWi-Fi users. For example, when a user arrives at a tourist spot, tourist information and coupons for the surrounding area are provided. This enriches the tourism experience by providing local tourist information and discount coupons to PoketWi-Fi users.

[0045] The tourism support system can use generative AI to analyze a user's hobbies, preferences, and behavioral history, and display optimal advertisements. For example, the tourism support system will build a system in which generative AI analyzes a user's hobbies, preferences, and behavioral history, and displays optimal advertisements based on that data. For example, advertisements for products and services in which the user is interested are displayed. The tourism support system will also analyze a user's behavioral history in real time, and display optimal advertisements based on the results. For example, advertisements related to places the user has visited or products the user has purchased in the past are displayed. The tourism support system will also develop a system that displays optimal advertisements for users based on their hobbies, preferences, and behavioral history. For example, advertisements for products and services in which the user is interested are displayed. In this way, the effectiveness of advertising can be maximized by using generative AI to analyze a user's hobbies, preferences, and behavioral history and displaying optimal advertisements.

[0046] The tourism support system can analyze the behavioral history of users when they click on an advertisement and reflect this in the next advertisement display. For example, the tourism support system will build a system in which a generation AI analyzes the behavioral history of users when they click on an advertisement and reflects this data in the next advertisement display. For example, it will display advertisements for products and services that the user is interested in. The tourism support system will also analyze the user's behavioral history in real time and reflect the results in the next advertisement display. For example, it will display advertisements for products and services related to advertisements that the user has previously clicked. The tourism support system will also develop a system that displays advertisements that are optimal for the user based on the behavioral history. For example, it will display advertisements for products and services that the user is interested in. This will maximize the effectiveness of advertising by analyzing the behavioral history of users when they click on an advertisement and reflecting this in the next advertisement display.

[0047] In order to earn advertising revenue, the tourism support system can not only display advertisements within the app but also provide local advertisements based on the user's location information. For example, in order to earn advertising revenue, the tourism support system builds a system that not only displays advertisements within the app but also provides local advertisements based on the user's location information. For example, when a user arrives at a tourist destination, advertisements for nearby stores and services are displayed. The tourism support system also earns advertising revenue by providing local advertisements based on the user's location information. For example, when a user arrives at a tourist spot, advertisements for nearby restaurants and shops are displayed. The tourism support system also develops a system that provides the most suitable local advertisements to the user based on the location information. For example, when a user arrives at a tourist destination, advertisements for nearby stores and services are displayed. In this way, advertising revenue is increased by not only displaying advertisements within the app but also providing local advertisements based on the user's location information.

[0048] The tourism support system can provide advertisers with user behavioral data and emotional response data to support analysis of advertising effectiveness. The tourism support system, for example, builds a system that provides advertisers with user behavioral data and emotional response data to support analysis of advertising effectiveness. For example, it provides behavioral data and emotional response data when a user clicks on an advertisement. The tourism support system also supports analysis of advertising effectiveness based on the user behavioral data and emotional response data. For example, it provides behavioral data and emotional response data when a user clicks on an advertisement. The tourism support system also develops a system that supports advertisers in analyzing advertising effectiveness based on the behavioral data and emotional response data. For example, it provides behavioral data and emotional response data when a user clicks on an advertisement. In this way, by providing advertisers with user behavioral data and emotional response data and supporting analysis of advertising effectiveness, it is possible to maximize the effectiveness of advertising.

[0049] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0050] The suggestion unit can take into account the user's health condition and physical condition and suggest tourist spots and shops that are appropriate for their physical strength. For example, we will build a system in which the generation AI analyzes the user's health condition and physical condition data and suggests tourist spots and shops that are appropriate for their physical strength. For example, we will suggest a reasonable sightseeing route based on the user's number of steps and heart rate. The suggestion unit will also monitor the user's health condition in real time and dynamically adjust the suggestions based on that data. For example, when the user is tired, it will suggest places to rest, and when they are energetic, it will suggest active spots. The suggestion unit will also develop a system that makes customized suggestions based on the user's physical strength based on the health data. For example, when the user is feeling unwell, it will suggest nearby tourist spots, and when they are in good physical condition, it will suggest a trip further away. This will allow us to take into account the user's health condition and physical condition and suggest tourist spots and shops that are appropriate for their physical strength.

[0051] The suggestion unit can expand suggestions based on a user's hobbies and preferences to include not only tourist spots but also events and activities. For example, we will build a system in which the generation AI suggests not only tourist spots but also events and activities based on the user's hobbies and preferences. For example, if the user is interested in music, the suggestion unit will suggest concerts and live events held in the area. The suggestion unit will also analyze the user's hobbies and preferences and, based on that, suggest events and activities related to tourist spots. For example, if the user is interested in history, the suggestion unit will suggest tours and workshops at historical places. The suggestion unit will also develop a system that expands suggestions based on a user's hobbies and preferences to include not only tourist spots but also activities that can be experienced locally. For example, if the user is interested in the outdoors, the suggestion unit will suggest hiking and camping activities. This allows suggestions based on a user's hobbies and preferences to be expanded to include not only tourist spots but also events and activities.

[0052] The display unit can work in conjunction with GPS data to automatically display past photos and videos of places the user has visited. For example, we develop a system that uses GPS data to automatically display past photos and videos of places the user has visited. For example, when the user arrives at a historical site, past photos and videos of that site are displayed. The display unit also displays past photos and videos of places the user has visited in real time, enriching the tourist experience. For example, when the user arrives at a tourist spot, historical footage and photos of that site are displayed. We also develop a system that works in conjunction with GPS data to automatically display past photos and videos of places the user has visited. For example, when the user arrives at a tourist spot, past events and happenings at that site are introduced in video. This enriches the tourist experience by automatically displaying past photos and videos of places the user has visited.

[0053] The guidance unit can analyze the user's dietary history and allergy information to suggest the most suitable dishes. For example, we will build a system in which the generative AI analyzes the user's past dietary history and suggests the most suitable dishes based on their preferences and allergy information. For example, we will suggest recommended dishes at a new restaurant based on the dishes the user has liked in the past. The guidance unit will also analyze the user's allergy information in real time and suggest safe dishes based on that data. For example, we will suggest dishes that avoid ingredients that the user is allergic to. The guidance unit will also develop a system that integrates dietary history and allergy information to suggest the most suitable dishes for the user. For example, we will suggest recommended dishes at a new restaurant based on data on dishes the user has eaten in the past. In this way, we will be able to suggest the most suitable dishes by analyzing the user's dietary history and allergy information.

[0054] The guidance unit can support health management by displaying the nutritional information and calories of the dishes ordered by the user in real time. For example, a system can be constructed in which the generative AI displays the nutritional information and calories of the dishes ordered by the user in real time. For example, the system displays the calories and nutritional components of the dishes ordered by the user to support health management. The guidance unit can also analyze the nutritional information and calories of the dishes ordered by the user in real time and provide health management advice based on that data. For example, it displays the nutrients and calories that the user should consume. The guidance unit can also develop a system that supports health management for the user based on the nutritional information and calories. For example, it displays the nutritional balance of the dishes ordered by the user and suggests healthy meals. This can support health management by displaying the nutritional information and calories of the dishes ordered by the user in real time.

[0055] The tourism support system offers a set sale with PoketWi-Fi Prepaid. This allows users to enjoy sightseeing while ensuring internet connection. For example, a set sale with PoketWi-Fi Prepaid is offered to app users. This allows users to enjoy sightseeing while ensuring internet connection. For example, a message encouraging users who have downloaded the app to purchase PoketWi-Fi Prepaid is displayed. By offering a set sale with PoketWi-Fi Prepaid, users can enjoy sightseeing while ensuring internet connection.

[0056] The processing flow of the first embodiment will be briefly explained below.

[0057] Step 1: The suggestion unit suggests tourist spots and shops based on the user's hobbies and preferences. For example, the generation AI analyzes information about the user's hobbies and preferences and suggests the most suitable tourist spots and shops based on that information. The input to the generation AI is a prompt containing instructions on what the user wants the generation AI to do, and the generation AI makes suggestions based on that prompt. Step 2: The display unit works in conjunction with GPS to display the highlights of tourist spots and the origins of famous places in the user's native language. For example, if the user arrives at a famous temple in Japan, the display will show the temple's history and highlights in the user's native language. This allows the user to enjoy sightseeing more deeply. Step 3: The guidance section teaches the user how to order the restaurant's popular dishes. For example, when ordering sushi at a Japanese restaurant, the AI ​​generation system will guide the user by saying, "This restaurant's recommendation is tuna nigiri sushi. To order, please say, 'I'd like tuna nigiri, please.'" This allows the user to order smoothly without experiencing language barriers.

[0058] (Example 2) A tourism support system according to an embodiment of the present invention is a system that suggests tourist spots and restaurants based on a user's preferences, displays information about tourist spots in the user's native language in conjunction with a GPS, and teaches how to order popular dishes at restaurants. This enables the tourism support system to suggest tourist spots and restaurants based on the user's preferences, provide information about tourist spots, and guide the user on how to order at restaurants.

[0059] A tourism support system according to an embodiment includes a suggestion unit, a display unit, and a guidance unit. The suggestion unit suggests tourist spots and shops based on the user's hobbies and preferences. For example, the generation AI analyzes information about the user's hobbies and preferences and suggests optimal tourist spots and shops based on the analysis. The generation AI receives input from the user in the form of prompts containing instructions on what the user wants the generation AI to do, and the generation AI makes suggestions based on the prompts. The display unit works in conjunction with GPS to display the highlights of tourist spots and the origins of famous landmarks in the user's native language. For example, when the user arrives at a famous Japanese temple, the display unit displays the temple's history and highlights in the user's native language. This allows the user to enjoy sightseeing more deeply. The guidance unit teaches the user how to order popular dishes at a restaurant. For example, when ordering sushi at a Japanese restaurant, the generation AI may provide guidance such as, "This restaurant's recommendation is tuna nigiri sushi. To order, please say, 'Tuna nigiri, please.'" This allows the user to order smoothly without experiencing language barriers. This enables the tourism support system to suggest tourist spots and shops based on the user's hobbies and preferences, provide information on tourist spots, and guide users on how to order at shops.

[0060] The suggestion unit analyzes a user's past travel history and social media posts to make more accurate suggestions. For example, the suggestion unit uses a generation AI to analyze a user's past travel history and suggest the next travel destination based on the places visited and the length of stay. For example, the suggestion unit suggests new tourist spots with similar characteristics based on data on cities the user has previously visited. The suggestion unit also analyzes social media posts to identify themes and activities that the user is interested in. For example, it may discover that the user is interested in natural landscapes or art from frequently posted photos and comments, and suggest tourist spots based on that. The suggestion unit also integrates the user's travel history with social media data to make more accurate suggestions. For example, it may analyze the length of stay and type of activity at past travel destinations to suggest recommended spots at the next travel destination. This enables more accurate suggestions by analyzing a user's past travel history and social media posts.

[0061] The suggestion unit can display other users' reviews and ratings for the suggested tourist spots and shops in real time. For example, the suggestion unit builds a system that displays other users' reviews and ratings for the tourist spots and shops suggested by the generation AI in real time. For example, the latest reviews and ratings for the suggested spots can be displayed for users' reference. The suggestion unit also displays the popularity and satisfaction of the suggested tourist spots and shops based on other users' reviews and ratings. For example, it can display star ratings and the number of comments to make it easier for users to make selections. The suggestion unit also develops a system that dynamically adjusts the content of suggestions based on reviews and ratings that are updated in real time. For example, it can exclude spots with low ratings from the suggestion list and prioritize displaying spots with high ratings. This allows users to refer to other users' reviews and ratings by displaying them in real time.

[0062] The suggestion unit can use the emotion estimation function to record the user's emotional reactions at places visited and reflect them in the next suggestion. The suggestion unit, for example, uses the emotion estimation function to build a system that records the user's emotional reactions at places visited. For example, it analyzes the user's facial expressions and voice and reflects places with strong positive emotions in the next suggestion. The suggestion unit also customizes the next suggestion content based on the user's emotional reactions at places visited. For example, it prioritizes suggestions of places and activities that the user enjoyed. The suggestion unit also develops a system that collects emotion estimation data in real time and dynamically adjusts the suggestion content based on the user's emotional reactions. For example, it suggests the next travel destination based on the emotion score of places visited by the user. In this way, by recording the user's emotional reactions and reflecting them in the next suggestion, more personalized suggestions become possible.

[0063] The suggestion unit can analyze the user's real-time emotional state using the emotion estimation function and suggest tourist spots and shops that match the user's mood at that time. The suggestion unit, for example, uses the emotion estimation function to analyze the user's real-time emotional state and build a system that suggests tourist spots and shops that match the user's mood at that time. For example, when the user feels like relaxing, the suggestion unit suggests a quiet cafe or park. The suggestion unit also monitors the user's emotional state in real time and dynamically adjusts the suggestions based on the data. For example, when the user is excited, the suggestion unit suggests an active activity, and when the user wants to calm down, the suggestion unit suggests a relaxing place. The suggestion unit also develops a system that makes customized suggestions based on the user's mood based on the emotion estimation data. For example, when the user is stressed, the suggestion unit suggests a relaxation spot, and when the user wants to have fun, the suggestion unit suggests an entertainment spot. This makes it possible to suggest tourist spots and shops that match the user's mood based on the user's real-time emotional state.

[0064] The suggestion unit can take into account the user's health condition and physical condition and suggest tourist spots and shops that are appropriate for their physical strength. For example, the suggestion unit will build a system in which a generation AI analyzes the user's health condition and physical condition data and suggests tourist spots and shops that are appropriate for their physical strength. For example, the suggestion unit will suggest a reasonable sightseeing route based on the user's number of steps and heart rate. The suggestion unit will also monitor the user's health condition in real time and dynamically adjust the suggestions based on that data. For example, it will suggest places to rest when the user is tired, and suggest active spots when the user is energetic. The suggestion unit will also develop a system that makes customized suggestions based on the user's physical strength based on the health data. For example, it will suggest nearby tourist spots when the user is feeling unwell, and suggest a trip further away when the user is in good physical condition. This makes it possible to suggest tourist spots and shops that are appropriate for the user's physical strength, taking into account the user's health condition and physical condition.

[0065] The suggestion unit can expand suggestions based on the user's hobbies and preferences to include not only tourist spots but also events and activities. For example, the suggestion unit builds a system in which a generation AI suggests not only tourist spots but also events and activities based on the user's hobbies and preferences. For example, if the user is interested in music, the suggestion unit suggests concerts and live events held in the area. The suggestion unit also analyzes the user's hobbies and preferences and suggests events and activities related to tourist spots based on the analysis. For example, if the user is interested in history, the suggestion unit suggests tours and workshops at historical places. The suggestion unit also develops a system that expands suggestions based on the user's hobbies and preferences to include not only tourist spots but also activities that can be experienced locally. For example, if the user is interested in the outdoors, the suggestion unit suggests hiking and camping activities. This allows suggestions based on the user's hobbies and preferences to be expanded to include not only tourist spots but also events and activities.

[0066] The display unit can work in conjunction with GPS data to automatically display past photos and videos of places the user has visited. For example, the display unit uses GPS data to build a system that automatically displays past photos and videos of places the user has visited. For example, when the user arrives at a historical site, past photos and videos of that site are displayed. The display unit also displays past photos and videos of places the user has visited in real time, enriching the tourist experience. For example, when the user arrives at a tourist spot, historical footage and photos of that site are displayed. The display unit also works in conjunction with GPS data to develop a system that automatically displays past photos and videos of places the user has visited. For example, when the user arrives at a tourist spot, past events and happenings at that site are introduced through video. This enriches the tourist experience by automatically displaying past photos and videos of places the user has visited.

[0067] The display unit can use the emotion estimation function to analyze the emotional reactions of the user at places visited and provide information based on the emotions. For example, the display unit uses the emotion estimation function to analyze the emotional reactions of the user at places visited and builds a system that provides emotion-based information based on the data. For example, it provides information related to places that moved the user. The display unit also analyzes the user's emotional reactions in real time and provides emotion-based information based on the results. For example, it suggests activities and events related to places that the user enjoys. The display unit also develops a system that provides information customized to the user's emotions based on the emotion estimation data. For example, it suggests relaxation spots related to places where the user relaxes. This allows for information to be provided based on the user's emotional reactions, enabling a more personalized sightseeing experience.

[0068] The display unit can provide the user with the historical background and cultural significance of places visited in an interactive storytelling format. The display unit, for example, uses GPS data to build a system that provides the user with the historical background and cultural significance of places visited in an interactive storytelling format. For example, when a user arrives at a historical landmark, the history of the place is introduced in a narrative format. The display unit also enables the user to interactively learn about the historical background and cultural significance of places visited. For example, when a user arrives at a tourist spot, the history and culture of the place are introduced in a quiz format. The display unit also works in conjunction with GPS data to develop a system that provides the user with the historical background and cultural significance of places visited in an interactive storytelling format. For example, when a user arrives at a tourist spot, the history of the place is introduced using animation and audio. This enriches the tourist experience by providing the user with the historical background and cultural significance of places visited in an interactive storytelling format.

[0069] The display unit can work in conjunction with GPS to provide real-time information about events being held near places visited by the user. For example, the display unit uses GPS data to build a system that provides real-time information about events being held near places visited by the user. For example, when the user arrives at a tourist spot, it displays information about events being held in the vicinity. The display unit also displays real-time information about events being held near places visited by the user, enriching the tourist experience. For example, when the user arrives at a tourist spot, it provides information about festivals and concerts being held in the vicinity. The display unit also works in conjunction with GPS data to develop a system that provides real-time information about events being held near places visited by the user. For example, when the user arrives at a tourist spot, it displays a schedule of events being held in the vicinity. This enriches the tourist experience by providing real-time information about events being held near places visited by the user.

[0070] The display unit can use the emotion estimation function to suggest the next place to visit based on the user's emotional reaction to places they have visited. For example, the display unit uses the emotion estimation function to analyze the user's emotional reaction to places they have visited, and builds a system that suggests the next place to visit based on that data. For example, it suggests the next tourist spot related to a place the user enjoyed. The display unit also analyzes the user's emotional reaction in real time and customizes the next place to visit based on the results. For example, it suggests a quiet place when the user wants to relax, or a place with plenty of activities when the user wants to be active. The display unit also develops a system that suggests the next tourist spot based on the user's emotions based on the emotion estimation data. For example, it suggests the next tourist spot related to a place that impressed the user. This enables a more personalized sightseeing experience by suggesting the next place to visit based on the user's emotional reaction.

[0071] The guidance unit can analyze the user's dietary history and allergy information to suggest the most suitable dishes. For example, the guidance unit will build a system in which a generating AI analyzes the user's past dietary history and suggests the most suitable dishes based on preferences and allergy information. For example, the guidance unit will suggest recommended dishes at a new restaurant based on dishes the user has liked in the past. The guidance unit will also analyze the user's allergy information in real time and suggest safe dishes based on that data. For example, the guidance unit will suggest dishes that avoid ingredients that the user is allergic to. The guidance unit will also develop a system that integrates dietary history and allergy information to suggest the most suitable dishes for the user. For example, the guidance unit will suggest recommended dishes at a new restaurant based on data on dishes the user has eaten in the past. In this way, the guidance unit can suggest the most suitable dishes by analyzing the user's dietary history and allergy information.

[0072] The guidance unit can use the emotion estimation function to analyze the emotional state of a user when ordering food and provide advice to reduce stress. For example, the guidance unit uses the emotion estimation function to analyze the emotional state of a user when ordering food and builds a system that provides advice to reduce stress based on the data. For example, when the user is nervous, the guidance unit provides advice to relax. The guidance unit also analyzes the user's emotional state in real time and provides specific advice to reduce stress based on the results. For example, when the user is feeling anxious, the guidance unit displays a message that gives a sense of security. The guidance unit also develops a system that provides customized advice tailored to the user's emotional state based on the emotion estimation data. For example, when the user is feeling stressed, the guidance unit suggests breathing techniques to help relax. In this way, the system analyzes the user's emotional state when ordering food and provides advice to reduce stress, thereby improving the user's ordering experience.

[0073] The guidance unit can support health management by displaying the nutritional information and calories of the dishes ordered by the user in real time. For example, the guidance unit constructs a system in which a generation AI displays the nutritional information and calories of the dishes ordered by the user in real time. For example, the guidance unit displays the calories and nutritional components of the dishes ordered by the user to support health management. The guidance unit also analyzes the nutritional information and calories of the dishes ordered by the user in real time and provides health management advice based on that data. For example, it displays the nutrients and calories that the user should consume. The guidance unit also develops a system that supports health management for the user based on the nutritional information and calories. For example, it displays the nutritional balance of the dishes ordered by the user and suggests healthy meals. This makes it possible to support health management by displaying the nutritional information and calories of the dishes ordered by the user in real time.

[0074] The guidance unit can provide visual guidance in video format on how to order popular dishes at a restaurant. The guidance unit, for example, builds a system in which a generation AI provides visual guidance to a user in video format on how to order popular dishes at a restaurant. For example, the guidance unit may provide a video showing the steps a user takes to order, making it visually easy to understand. The guidance unit may also provide a video showing the names and pronunciations of the dishes the user will order. The guidance unit may also develop a system that provides visual guidance in video format to enable a user to order smoothly. For example, the guidance unit may provide a video showing the steps a user takes to order, making it visually easy to understand. In this way, the guidance unit may provide visual guidance in video format on how to order popular dishes at a restaurant, making it visually easy for a user to order.

[0075] The guidance unit can display other users' reviews and ratings of the food ordered by the user in real time. The guidance unit, for example, builds a system in which a generation AI displays other users' reviews and ratings of the food ordered by the user in real time. For example, the latest reviews and ratings of the food ordered by the user can be displayed for reference. The guidance unit also displays the popularity and satisfaction level of the ordered food based on other users' reviews and ratings. For example, it can display star ratings and the number of comments to make it easier for the user to make a selection. The guidance unit also develops a system that dynamically adjusts the order contents based on reviews and ratings that are updated in real time. For example, it can exclude dishes with low ratings from the suggestion list and prioritize displaying dishes with high ratings. This allows the user to refer to other users' reviews and ratings of the food ordered by displaying them in real time.

[0076] The guidance unit uses the emotion estimation function to record the emotional response of the user when ordering food and can reflect it in the next order. The guidance unit, for example, uses the emotion estimation function to build a system that records the emotional response of the user when ordering food. For example, the emotional response of the user to the food ordered by the user is analyzed and reflected in the next order. The guidance unit also analyzes the user's emotional response in real time and customizes the next order based on the results. For example, dishes that the user enjoyed are prioritized. The guidance unit also develops a system that suggests the next order based on the emotion estimation data, tailored to the user's emotional response. For example, the system suggests the next dish related to a dish that impressed the user. In this way, the user's emotional response is recorded and reflected in the next order, enabling a more personalized ordering experience.

[0077] Furthermore, the tourism support system offers a set sale with PoketWi-Fi Prepaid. The tourism support system offers a set sale with PoketWi-Fi Prepaid. This allows users to enjoy sightseeing while ensuring internet connection. For example, a set sale with PoketWi-Fi Prepaid is offered to app users. This allows users to enjoy sightseeing while ensuring internet connection. For example, a message encouraging users who have downloaded the app to purchase PoketWi-Fi Prepaid is displayed. This allows users to enjoy sightseeing while ensuring internet connection by offering a set sale with PoketWi-Fi Prepaid.

[0078] The tourism support system can analyze PoketWi-Fi usage data and propose the optimal plan based on the user's internet usage trends. For example, the tourism support system builds a system that analyzes PoketWi-Fi usage data and proposes the optimal plan based on the user's internet usage trends. For example, the optimal plan is proposed based on the amount of data and time of day that the user frequently uses. The tourism support system also analyzes the user's internet usage trends in real time and proposes the optimal plan based on that data. For example, a high-capacity plan is proposed if the user uses a lot of data. The tourism support system also develops a system that proposes the optimal internet plan to the user based on usage data. For example, the optimal plan is proposed based on the amount of data used by the user and time of day. In this way, convenience for the user is improved by analyzing PoketWi-Fi usage data and proposing the optimal plan based on the user's internet usage trends.

[0079] The tourism support system can use the emotion estimation function to provide advice to reduce the stress a user feels about their internet connection. For example, the tourism support system uses the emotion estimation function to analyze the stress a user feels about their internet connection and builds a system that provides advice to reduce stress based on the data. For example, when a user is dissatisfied with their connection, the system suggests improvement measures. The tourism support system also analyzes the user's emotional state in real time and provides specific advice to reduce stress based on the results. For example, when a user is dissatisfied with their connection, the system suggests changing the connection method. The tourism support system also develops a system that provides customized advice tailored to the user's emotional state based on the emotion estimation data. For example, when a user is stressed, the system suggests ways to relax. This improves user convenience by providing advice to reduce the stress a user feels about their internet connection.

[0080] The tourism support system can monitor PocketWi-Fi usage status in real time and automatically suggest the optimal connection method if the connection is unstable. For example, the tourism support system builds a system that monitors PocketWi-Fi usage status in real time and automatically suggests the optimal connection method if the connection is unstable. For example, it suggests another Wi-Fi network when the connection is unstable. The tourism support system also analyzes the user's connection status in real time and suggests the optimal connection method based on that data. For example, it suggests the optimal connection point when the connection is unstable. The tourism support system also develops a system that suggests the optimal connection method to the user based on usage status. For example, it suggests an alternative connection method when the connection is unstable. In this way, the tourism support system can monitor PocketWi-Fi usage status in real time and automatically suggest the optimal connection method if the connection is unstable, improving user convenience.

[0081] The tourism support system can provide local tourist information and discount coupons to PoketWi-Fi users. For example, a tourism support system is constructed that provides local tourist information and discount coupons to PoketWi-Fi users. For example, when a user arrives at a tourist spot, tourist information and coupons for the surrounding area are provided. The tourism support system also provides local tourist information and discount coupons when a user uses PoketWi-Fi. For example, when a user arrives at a tourist spot, coupons for restaurants and shops in the surrounding area are provided. The tourism support system also develops a system that enriches the tourism experience by providing local tourist information and discount coupons to PoketWi-Fi users. For example, when a user arrives at a tourist spot, tourist information and coupons for the surrounding area are provided. This enriches the tourism experience by providing local tourist information and discount coupons to PoketWi-Fi users.

[0082] The tourism support system can use the emotion estimation function to analyze the emotional reactions a user has to an Internet connection and provide information that will be useful for the next trip. For example, the tourism support system uses the emotion estimation function to analyze the emotional reactions a user has to an Internet connection and builds a system that provides information that will be useful for the next trip based on that data. For example, if the user is satisfied with the connection, the system will suggest the same connection method for the next time. The tourism support system also analyzes the user's emotional reactions in real time and provides information that will be useful for the next trip based on the results. For example, if the user is dissatisfied with the connection, the system will suggest improvements. The tourism support system also develops a system that provides information that will be useful for the next trip, tailored to the user's emotional reactions, based on the emotion estimation data. For example, if the user is satisfied with the connection, the system will suggest the same connection method for the next time. In this way, the tourism support system analyzes the emotional reactions a user has to an Internet connection and provides information that will be useful for the next trip, thereby improving user convenience.

[0083] The tourism support system can use generative AI to analyze a user's hobbies, preferences, and behavioral history, and display optimal advertisements. For example, the tourism support system will build a system in which generative AI analyzes a user's hobbies, preferences, and behavioral history, and displays optimal advertisements based on that data. For example, advertisements for products and services in which the user is interested are displayed. The tourism support system will also analyze a user's behavioral history in real time, and display optimal advertisements based on the results. For example, advertisements related to places the user has visited or products the user has purchased in the past are displayed. The tourism support system will also develop a system that displays optimal advertisements for users based on their hobbies, preferences, and behavioral history. For example, advertisements for products and services in which the user is interested are displayed. In this way, the effectiveness of advertising can be maximized by using generative AI to analyze a user's hobbies, preferences, and behavioral history and displaying optimal advertisements.

[0084] The tourism support system can use the emotion estimation function to analyze the emotional reactions users have to advertisements and maximize the effectiveness of the advertisements. For example, the tourism support system uses the emotion estimation function to analyze the emotional reactions users have to advertisements and builds a system that maximizes the effectiveness of advertisements based on that data. For example, advertisements that users have positive emotions towards are preferentially displayed. The tourism support system also analyzes users' emotional reactions in real time and maximizes the effectiveness of advertisements based on the results. For example, advertisements that users are interested in are preferentially displayed. The tourism support system also develops a system that displays advertisements that match the user's emotional reactions based on the emotion estimation data. For example, advertisements that users have positive emotions towards are preferentially displayed. In this way, the emotional reactions users have to advertisements are analyzed and the effectiveness of advertisements is maximized, thereby increasing advertising revenue.

[0085] The tourism support system can analyze the behavioral history of users when they click on an advertisement and reflect this in the next advertisement display. For example, the tourism support system will build a system in which a generation AI analyzes the behavioral history of users when they click on an advertisement and reflects this data in the next advertisement display. For example, it will display advertisements for products and services that the user is interested in. The tourism support system will also analyze the user's behavioral history in real time and reflect the results in the next advertisement display. For example, it will display advertisements for products and services related to advertisements that the user has previously clicked. The tourism support system will also develop a system that displays advertisements that are optimal for the user based on the behavioral history. For example, it will display advertisements for products and services that the user is interested in. This will maximize the effectiveness of advertising by analyzing the behavioral history of users when they click on an advertisement and reflecting this in the next advertisement display.

[0086] In order to earn advertising revenue, the tourism support system can not only display advertisements within the app but also provide local advertisements based on the user's location information. For example, in order to earn advertising revenue, the tourism support system builds a system that not only displays advertisements within the app but also provides local advertisements based on the user's location information. For example, when a user arrives at a tourist destination, advertisements for nearby stores and services are displayed. The tourism support system also earns advertising revenue by providing local advertisements based on the user's location information. For example, when a user arrives at a tourist spot, advertisements for nearby restaurants and shops are displayed. The tourism support system also develops a system that provides the most suitable local advertisements to the user based on the location information. For example, when a user arrives at a tourist destination, advertisements for nearby stores and services are displayed. In this way, advertising revenue is increased by not only displaying advertisements within the app but also providing local advertisements based on the user's location information.

[0087] The tourism support system can provide advertisers with user behavioral data and emotional response data to support analysis of advertising effectiveness. The tourism support system, for example, builds a system that provides advertisers with user behavioral data and emotional response data to support analysis of advertising effectiveness. For example, it provides behavioral data and emotional response data when a user clicks on an advertisement. The tourism support system also supports analysis of advertising effectiveness based on the user behavioral data and emotional response data. For example, it provides behavioral data and emotional response data when a user clicks on an advertisement. The tourism support system also develops a system that supports advertisers in analyzing advertising effectiveness based on the behavioral data and emotional response data. For example, it provides behavioral data and emotional response data when a user clicks on an advertisement. In this way, by providing advertisers with user behavioral data and emotional response data and supporting analysis of advertising effectiveness, it is possible to maximize the effectiveness of advertising.

[0088] The tourism support system can use the emotion estimation function to optimize the content and display timing of advertisements based on the emotional response that the user feels to the advertisements. For example, the tourism support system uses the emotion estimation function to analyze the emotional response that the user feels to the advertisements, and builds a system that optimizes the content and display timing of advertisements based on that data. For example, advertisements that the user feels positive about are displayed preferentially. The tourism support system also analyzes the user's emotional response in real time, and optimizes the content and display timing of advertisements based on the results. For example, advertisements that the user is interested in are displayed preferentially. The tourism support system also develops a system that displays advertisements that match the user's emotional response based on the emotion estimation data. For example, advertisements that the user feels positive about are displayed preferentially. This makes it possible to maximize the effectiveness of advertisements by optimizing the content and display timing of advertisements based on the emotional response that the user feels to the advertisements.

[0089] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0090] The suggestion unit analyzes the user's real-time emotional state using the emotion estimation function and can suggest tourist spots and shops that match the user's mood at that time. For example, when the user feels like relaxing, it can suggest a quiet cafe or park. The suggestion unit also monitors the user's emotional state in real time and dynamically adjusts the suggestions based on that data. For example, when the user is excited, it can suggest active activities, and when the user wants to calm down, it can suggest places to relax. The suggestion unit will also develop a system that makes customized suggestions based on the emotion estimation data, tailored to the user's mood. For example, when the user is stressed, it can suggest relaxation spots, and when the user wants to have fun, it can suggest entertainment spots. This makes it possible to suggest tourist spots and shops that match the user's mood based on the user's real-time emotional state.

[0091] The suggestion unit can take into account the user's health condition and physical condition and suggest tourist spots and shops that are appropriate for their physical strength. For example, we will build a system in which the generation AI analyzes the user's health condition and physical condition data and suggests tourist spots and shops that are appropriate for their physical strength. For example, we will suggest a reasonable sightseeing route based on the user's number of steps and heart rate. The suggestion unit will also monitor the user's health condition in real time and dynamically adjust the suggestions based on that data. For example, when the user is tired, it will suggest places to rest, and when they are energetic, it will suggest active spots. The suggestion unit will also develop a system that makes customized suggestions based on the user's physical strength based on the health data. For example, when the user is feeling unwell, it will suggest nearby tourist spots, and when they are in good physical condition, it will suggest a trip further away. This will allow us to take into account the user's health condition and physical condition and suggest tourist spots and shops that are appropriate for their physical strength.

[0092] The suggestion unit can expand suggestions based on a user's hobbies and preferences to include not only tourist spots but also events and activities. For example, we will build a system in which the generation AI suggests not only tourist spots but also events and activities based on the user's hobbies and preferences. For example, if the user is interested in music, the suggestion unit will suggest concerts and live events held in the area. The suggestion unit will also analyze the user's hobbies and preferences and, based on that, suggest events and activities related to tourist spots. For example, if the user is interested in history, the suggestion unit will suggest tours and workshops at historical places. The suggestion unit will also develop a system that expands suggestions based on a user's hobbies and preferences to include not only tourist spots but also activities that can be experienced locally. For example, if the user is interested in the outdoors, the suggestion unit will suggest hiking and camping activities. This allows suggestions based on a user's hobbies and preferences to be expanded to include not only tourist spots but also events and activities.

[0093] The display unit can work in conjunction with GPS data to automatically display past photos and videos of places the user has visited. For example, we develop a system that uses GPS data to automatically display past photos and videos of places the user has visited. For example, when the user arrives at a historical site, past photos and videos of that site are displayed. The display unit also displays past photos and videos of places the user has visited in real time, enriching the tourist experience. For example, when the user arrives at a tourist spot, historical footage and photos of that site are displayed. We also develop a system that works in conjunction with GPS data to automatically display past photos and videos of places the user has visited. For example, when the user arrives at a tourist spot, past events and happenings at that site are introduced in video. This enriches the tourist experience by automatically displaying past photos and videos of places the user has visited.

[0094] The display unit can use the emotion estimation function to analyze the emotional reactions of the user at places they have visited and provide information based on their emotions. For example, a system can be constructed that uses the emotion estimation function to analyze the emotional reactions of the user at places they have visited and provide information based on their emotions based on that data. For example, information related to places that have moved the user can be provided. The display unit can also analyze the user's emotional reactions in real time and provide information based on their emotions based on the results. For example, activities and events related to places the user enjoys can be suggested. The display unit can also develop a system that provides information customized to the user's emotions based on the emotion estimation data. For example, relaxation spots related to places where the user relaxes can be suggested. This allows for a more personalized sightseeing experience by providing information based on the user's emotional reactions.

[0095] The guidance unit can analyze the user's dietary history and allergy information to suggest the most suitable dishes. For example, we will build a system in which the generative AI analyzes the user's past dietary history and suggests the most suitable dishes based on their preferences and allergy information. For example, we will suggest recommended dishes at a new restaurant based on the dishes the user has liked in the past. The guidance unit will also analyze the user's allergy information in real time and suggest safe dishes based on that data. For example, we will suggest dishes that avoid ingredients that the user is allergic to. The guidance unit will also develop a system that integrates dietary history and allergy information to suggest the most suitable dishes for the user. For example, we will suggest recommended dishes at a new restaurant based on data on dishes the user has eaten in the past. In this way, we will be able to suggest the most suitable dishes by analyzing the user's dietary history and allergy information.

[0096] The guidance unit can use the emotion estimation function to analyze the emotional state of a user when ordering food and provide advice to reduce stress. For example, a system is constructed that uses the emotion estimation function to analyze the emotional state of a user when ordering food and provides advice to reduce stress based on the data. For example, when the user is nervous, advice to relax is provided. The guidance unit also analyzes the user's emotional state in real time and provides specific advice to reduce stress based on the results. For example, when the user is feeling anxious, a message that gives a sense of security is displayed. The guidance unit also develops a system that provides customized advice tailored to the user's emotional state based on the emotion estimation data. For example, when the user is feeling stressed, a breathing technique to relax is suggested. In this way, the emotional state of a user when ordering food is analyzed and advice to reduce stress is provided, improving the user's ordering experience.

[0097] The guidance unit can support health management by displaying the nutritional information and calories of the dishes ordered by the user in real time. For example, a system can be constructed in which the generative AI displays the nutritional information and calories of the dishes ordered by the user in real time. For example, the system displays the calories and nutritional components of the dishes ordered by the user to support health management. The guidance unit can also analyze the nutritional information and calories of the dishes ordered by the user in real time and provide health management advice based on that data. For example, it displays the nutrients and calories that the user should consume. The guidance unit can also develop a system that supports health management for the user based on the nutritional information and calories. For example, it displays the nutritional balance of the dishes ordered by the user and suggests healthy meals. This can support health management by displaying the nutritional information and calories of the dishes ordered by the user in real time.

[0098] The guidance unit can use the emotion estimation function to record the emotional response of a user when ordering food and reflect it in the next order. For example, a system is constructed that uses the emotion estimation function to record the emotional response of a user when ordering food. For example, the emotional response of a user to a food order is analyzed and reflected in the next order. The guidance unit also analyzes the user's emotional response in real time and customizes the next order based on the results. For example, dishes that the user enjoyed are prioritized. The guidance unit also develops a system that suggests the next order based on the emotion estimation data, tailored to the user's emotional response. For example, the system suggests the next dish related to a dish that impressed the user. In this way, a more personalized ordering experience is possible by recording the user's emotional response and reflecting it in the next order.

[0099] The tourism support system offers a set sale with PoketWi-Fi Prepaid. This allows users to enjoy sightseeing while ensuring internet connection. For example, a set sale with PoketWi-Fi Prepaid is offered to app users. This allows users to enjoy sightseeing while ensuring internet connection. For example, a message encouraging users who have downloaded the app to purchase PoketWi-Fi Prepaid is displayed. By offering a set sale with PoketWi-Fi Prepaid, users can enjoy sightseeing while ensuring internet connection.

[0100] The processing flow of the second embodiment will be briefly explained below.

[0101] Step 1: The suggestion unit suggests tourist spots and shops based on the user's hobbies and preferences. For example, the generation AI analyzes information about the user's hobbies and preferences and suggests the most suitable tourist spots and shops based on that information. The input to the generation AI is a prompt containing instructions on what the user wants the generation AI to do, and the generation AI makes suggestions based on that prompt. Step 2: The display unit works in conjunction with GPS to display the highlights of tourist spots and the origins of famous places in the user's native language. For example, if the user arrives at a famous temple in Japan, the display will show the temple's history and highlights in the user's native language. This allows the user to enjoy sightseeing more deeply. Step 3: The guidance section teaches the user how to order the restaurant's popular dishes. For example, when ordering sushi at a Japanese restaurant, the AI ​​generation system will guide the user by saying, "This restaurant's recommendation is tuna nigiri sushi. To order, please say, 'I'd like tuna nigiri, please.'" This allows the user to order smoothly without experiencing language barriers.

[0102] 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.

[0103] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). 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 speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. 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. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0104] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0105] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0106] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0107] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0108] 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.

[0109] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0110] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0115] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0116] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0117] 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.

[0118] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0119] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0120] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0121] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0122] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0123] 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.

[0124] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0125] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0126] 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.

[0127] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset 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.

[0128] 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.

[0129] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0130] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0131] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0132] 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.

[0133] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0134] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0135] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0136] 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.

[0137] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0138] 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.

[0139] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0140] 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 image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0141] 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.

[0142] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the 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.

[0143] 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.

[0144] 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.

[0145] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0146] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0147] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0148] 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.

[0149] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0150] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0151] 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.

[0152] FIG. 9 illustrates 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 behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions 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.

[0153] 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.

[0154] 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).

[0155] 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 expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, 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 expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0156] 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."

[0157] 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.

[0158] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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. A processor also includes 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.

[0163] The hardware resource that executes the specific process 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 process may be a single processor.

[0164] 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.

[0165] 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.

[0166] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0167] 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, in order to avoid confusion and to 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.

[0168] 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. [Explanation of symbols]

[0169] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a suggestion unit that suggests tourist spots and shops based on the user's hobbies and preferences; A display that works in conjunction with GPS to show tourist spots and the origins of famous places in your native language. It also has a guide section that shows how to order popular dishes at the restaurant. A system characterized by:

2. The proposal unit Analyze the user's past travel history and social media posts to make more accurate suggestions 2. The system of claim 1.

3. The proposal unit Displays other users' reviews and ratings in real time for the tourist spots and shops you suggest.

2. The system of claim 1.

4. The proposal unit Record the user's emotional response to the places they visit and reflect it in their next suggestions.

2. The system of claim 1.

5. The proposal unit The emotion estimation function analyzes the user's real-time emotional state and suggests tourist spots and shops that match their mood at that time.

2. The system of claim 1.

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