system

Abstract

We provide a system that offers personalized travel plans to tourists, and can provide multilingual support and real-time information. [Solution] The system comprises a suggestion unit, a guide unit, a game provision unit, a multilingual support unit, an information provision unit, a translation support unit, and a collaboration unit. The suggestion unit proposes the optimal sightseeing plan based on the user's past travel history, interests, and preferences. The guide unit provides explanations and guidance of tourist destinations in voice or text based on the suggested sightseeing plan. The game provision unit provides an interactive game based on the provided information. The multilingual support unit provides multilingual support based on the suggested sightseeing plan. The information provision unit provides real-time information based on the suggested sightseeing plan. The translation support unit provides translation and interpretation based on the suggested sightseeing plan. The collaboration unit collaborates with local businesses to provide special discounts based on the suggested plan.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, it is difficult to provide a personalized tourism plan for travelers, and there are also problems that multilingual support and real-time information provision are not sufficiently carried out.

[0005] The system according to the embodiment aims to provide a personalized tourism plan for travelers and perform multilingual support and real-time information provision.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a proposal unit, a guide unit, a game provision unit, a multilingual support unit, an information provision unit, a translation support unit, and a collaboration unit. The proposal unit proposes an optimal sightseeing plan based on the user's past travel history, interests, and preferences. The guide unit provides explanations and guidance of tourist destinations in voice or text based on the sightseeing plan proposed by the proposal unit. The game provision unit provides an interactive game based on the information provided by the guide unit. The multilingual support unit provides multilingual support based on the sightseeing plan proposed by the proposal unit. The information provision unit provides real-time information based on the sightseeing plan proposed by the proposal unit. The translation support unit provides translation and interpretation based on the sightseeing plan proposed by the proposal unit. The collaboration unit collaborates with local businesses to provide special discounts based on the sightseeing plan proposed by the proposal unit. [Effects of the Invention]

[0007] The system according to this embodiment can provide travelers with personalized sightseeing plans, and can also provide multilingual support and real-time information. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7]This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the tagged storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the tagged communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

[0017] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[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, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are 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. Also, the reception device 38, the output device 40, and the camera 42 are connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by the contact of an indicator (e.g., a pen or a finger, etc.) by detecting the contact of the indicator. The microphone 38B receives user input by voice by detecting the voice of the user. 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, a specific processing unit 290 (see FIG. 2) acquires data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0024] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0025] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction 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 a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also 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 processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The traveler service system according to an embodiment of the present invention is an application that utilizes generative AI to provide travelers with a "WOW!" experience. Based on the user's past travel history, interests, and preferences, the generative AI proposes the optimal sightseeing plan and content. Next, it provides explanations and guides of tourist destinations in voice or text, and offers interactive games, enabling travelers to learn about history, culture, and environmental protection while having fun. Furthermore, it supports safe and comfortable travel through multilingual support, real-time information provision, and translation / interpretation support. For example, let's describe the personalized service provided by the generative AI. Based on the user's past travel history, interests, and preferences, the generative AI proposes the optimal sightseeing plan and content. For example, for a user who likes anime, it provides content that guides them through famous scenes, behind-the-scenes stories, and history from anime. Also, because there is no fixed schedule, travelers can enjoy their trip in their own way. Next, let's describe the provision of interactive experiences. The generative AI provides explanations and guides of tourist destinations in voice or text. For example, it provides interactive games such as historical exploration, mystery-solving tours, and environmental protection missions, enabling travelers to learn while having fun. Finally, let's describe how safety is ensured. The generating AI supports safe and comfortable travel through multilingual support, real-time information provision, and translation / interpretation support. For example, it provides weather, traffic, and safety information in real time, allowing travelers to enjoy their trip with peace of mind. Finally, let's explain the business model. The application of this invention adopts a subscription model and collaborates with local businesses to offer special discounts. This enables the provision of user-centric experiences, leading to improved customer satisfaction, revitalization of the local economy, and promotion of sustainable tourism. As a result, the traveler service system can provide travelers with a "WOW!" experience, realizing an interactive, personalized, and safe journey.

[0029] The traveler service system according to this embodiment comprises a suggestion unit, a guide unit, a game provision unit, a multilingual support unit, an information provision unit, a translation support unit, and a collaboration unit. The suggestion unit proposes an optimal sightseeing plan based on the user's past travel history and interests / preferences. The suggestion unit proposes an optimal sightseeing plan based on the user's past travel history and interests / preferences, for example, by using a generation AI. The suggestion unit analyzes the user's past travel history and generates a sightseeing plan based on their interests and preferences, for example. The suggestion unit creates a list of tourist destinations based on the user's interests and proposes an optimal plan, for example. The guide unit provides explanations and guides of tourist destinations in voice or text. The guide unit provides, for example, an audio guide explaining the history and culture of the tourist destination. The guide unit provides, for example, a text guide introducing the highlights of the tourist destination. The guide unit provides a guide using a combination of both voice and text, for example. The game provision unit provides interactive games. The game provision unit provides, for example, interactive games such as historical exploration, mystery-solving tours, and environmental protection missions. The game provision unit provides, for example, quizzes and adventure games in which users can participate. The Game Provision Department provides, for example, educational games that allow users to learn while having fun. The Multilingual Support Department provides explanations in multiple languages. For example, the Multilingual Support Department provides explanations of tourist destinations in multiple languages. For example, the Multilingual Support Department provides real-time translations to users. For example, the Multilingual Support Department provides explanations in the most suitable language based on the user's language settings. The Information Provision Department provides real-time weather, traffic, and safety information. For example, the Information Provision Department provides current weather information to help travelers choose appropriate clothing. For example, the Information Provision Department provides traffic information to help travelers move efficiently. For example, the Information Provision Department provides safety information to support travelers in enjoying their trip safely. The Translation Support Department provides translation and interpretation services. For example, the Translation Support Department provides translations into the language the user needs. For example, the Translation Support Department provides real-time interpretation to help users communicate. For example, the Translation Support Department provides the most suitable translation based on the user's language settings. The Partnership Department partners with local businesses to offer special discounts.The partnership department can, for example, collaborate with local restaurants and shops to offer special discounts. It can also, for example, collaborate with local tourist facilities to offer discounted tickets. Furthermore, it can collaborate with local events to offer special discounts. This allows the traveler service system according to the embodiment to propose optimal travel plans based on the user's past travel history, interests, and preferences, enabling an interactive, personalized, and safe travel experience.

[0030] The suggestion department proposes the optimal sightseeing plan based on the user's past travel history, interests, and preferences. Specifically, the suggestion department uses generative AI to propose the optimal sightseeing plan based on the user's past travel history, interests, and preferences. The generative AI retrieves the user's past travel history from a database and analyzes information such as destinations, visited tourist spots, and activities participated in. Furthermore, it considers feedback on tourist spots and activities that the user has previously rated to identify the user's interests and preferences. Based on this information, the generative AI generates the optimal sightseeing plan for the user. For example, if the user is interested in historical tourist spots, the generative AI will propose a plan that includes historical landmarks and museums in that area. Also, if the user prefers to enjoy nature, the generative AI will propose a plan that includes nature parks and hiking trails. The suggestion department creates a list of tourist spots based on the user's interests and proposes the optimal plan. Furthermore, the suggestion department also considers the user's current travel destination, length of stay, budget, and other conditions to provide a realistic and feasible plan. In this way, the suggestion department can provide the optimal sightseeing plan for the user, making travel planning efficient and enjoyable.

[0031] The guide department provides explanations and guides about tourist destinations through audio or text. For example, the guide department provides audio guides that explain the history and culture of tourist destinations. Specifically, the guide department prepares detailed audio guides for each tourist destination and plays them on smartphones or dedicated devices when users visit the destination. The audio guides explain the historical background, cultural significance, and architectural features of the tourist destination in detail, helping users to gain a deeper understanding of the destination. The guide department also provides text guides that introduce the highlights of the tourist destinations. The text guides are provided in a format that users can view on smartphones and tablets and include photos, maps, and descriptions of the tourist destinations. This allows users to enjoy the tourist destinations visually. Furthermore, the guide department combines both audio and text in its guiding. For example, users can listen to the audio guide while simultaneously viewing the text guide to provide a richer tourist experience. The guide department allows users to select the most suitable guide format according to their preferences and circumstances. This enables the guide department to provide users with a comprehensive and personalized tourist guide, maximizing the appeal of the tourist destinations.

[0032] The game provider offers interactive games. These include interactive games such as historical explorations, mystery-solving tours, and environmental protection missions. Specifically, users can participate in games using their smartphones or tablets while visiting tourist destinations. In historical exploration games, users tour tourist destinations while completing quizzes and missions related to historical events and figures. In mystery-solving tours, users search for clues hidden within the tourist destination and solve mysteries to advance to the next destination. In environmental protection missions, users participate in activities to protect the natural environment of tourist destinations and earn points. The game provider also offers quizzes and adventure games that users can participate in. In quiz games, users answer questions about tourist destinations and earn points for correct answers. In adventure games, users complete missions following a story set in the tourist destination and enjoy an adventure. Furthermore, the game provider offers educational games that allow users to learn while having fun. In educational games, users can learn about the history, culture, and natural environment of tourist destinations as they progress through the game. This allows the game provider to offer users an enjoyable and educational experience while visiting tourist destinations, thereby enhancing the appeal of tourism.

[0033] The multilingual support unit provides explanations in multiple languages. For example, it provides explanations of tourist attractions in multiple languages. Specifically, the multilingual support unit prepares audio and text guides in multiple languages ​​for each tourist attraction and provides the guide in the language selected by the user. This makes it easier for users who speak different languages ​​to understand information about tourist attractions. The multilingual support unit also provides real-time translations to users. By using the real-time translation function, users can understand explanations at tourist attractions on the spot. For example, if a user takes a picture of a tourist attraction explanation with their smartphone camera, the multilingual support unit will translate the explanation in real time and display it to the user. In addition, the multilingual support unit provides explanations in the most appropriate language based on the user's language settings. When a user sets the language settings of the application or device, the multilingual support unit automatically provides the guide in the appropriate language based on those settings. In this way, the multilingual support unit can remove language barriers for users and provide a smooth tourist experience. Furthermore, the multilingual support unit collects user feedback and continuously improves the accuracy of translations and the content of guides. This allows the multilingual support department to consistently provide the latest and highest-quality multilingual guides, thereby improving user satisfaction.

[0034] The Information Service provides real-time weather, traffic, and safety information. For example, it provides current weather information to help travelers choose appropriate clothing. Specifically, it acquires weather data in real time and provides weather information for the user's current location and destination. This makes it easier for users to adapt to weather changes during their trip. The Information Service also provides traffic information to help travelers move efficiently. This traffic information includes public transport status, road congestion, and optimal travel routes. Users can use this information to plan their trips. Furthermore, the Information Service provides safety information to support travelers in enjoying their trips safely. This safety information includes local security conditions, emergency contact information, and evacuation locations. This allows users to travel with peace of mind. The Information Service centrally manages this information and provides it to users in real time. For example, when a user opens the application, current weather, traffic, and safety information is automatically updated and displayed. This allows the Information Service to provide users with the latest information and support them in planning and executing their trips.

[0035] The Translation Support Department provides translation and interpretation services. For example, it provides translations into the language the user needs. Specifically, it translates text or audio entered by the user into the specified language and displays or plays it back. This allows users to communicate smoothly with locals without feeling a language barrier. The Translation Support Department also assists users in communication by providing real-time interpretation. By using the real-time interpretation function, it provides instant interpretation when users converse directly with locals. For example, when a user speaks into their smartphone's microphone, the Translation Support Department translates the audio in real time and conveys it to the other party. It also translates the other party's response and conveys it to the user. This allows users to communicate smoothly with locals. Furthermore, the Translation Support Department provides optimal translations based on the user's language settings. When a user sets the language settings for an application or device, the Translation Support Department automatically provides translations in the appropriate language based on those settings. This allows the Translation Support Department to provide users with personalized translation services and support communication during travel.

[0036] The Partnership Department collaborates with local businesses to offer special discounts. For example, it partners with local restaurants and shops to offer special discounts. Specifically, the Partnership Department partners with local restaurants and shops to provide users with discount coupons that can be used at specific stores. Users can obtain coupons through the application and receive discounts by presenting them at the stores. The Partnership Department also partners with local tourist attractions to offer discount tickets. Users can purchase discount tickets for tourist attractions through the application and receive discounts by presenting them on-site. Furthermore, the Partnership Department collaborates with local events to offer special discounts. Users can obtain information about local events through the application and receive special discounts. In this way, the Partnership Department can provide users with special experiences that maximize the appeal of the local area and improve travel satisfaction. In addition, the Partnership Department strengthens collaboration with local businesses and contributes to the revitalization of the local economy. For example, by partnering with local small and medium-sized enterprises and startups to plan special promotions and events, it can boost the tourism industry throughout the region. In this way, the Partnership Department can provide users with attractive travel experiences while also contributing to the local community.

[0037] The suggestion unit can use generative AI to propose the optimal sightseeing plan based on the user's past travel history, interests, and preferences. For example, the suggestion unit uses generative AI to analyze the user's past travel history and generate a sightseeing plan based on their interests and preferences. For example, the suggestion unit uses generative AI to create a list of tourist destinations based on the user's interests and proposes the optimal plan. For example, the suggestion unit uses generative AI to propose a sightseeing plan based on the user's past travel history, interests, and preferences. This allows for the proposal of the optimal sightseeing plan based on the user's past travel history and interests and preferences. For example, the generative AI takes the user's past travel history, interests, and preferences as input and outputs the optimal sightseeing plan. For example, the generative AI creates a list of tourist destinations based on the user's interests and proposes the optimal plan. For example, the generative AI analyzes the user's past travel history and generates a sightseeing plan based on their interests and preferences.

[0038] The guide unit can provide explanations and guides about tourist destinations in audio or text. For example, the guide unit can provide an audio guide explaining the history and culture of the tourist destination. For example, the guide unit can provide a text guide introducing the highlights of the tourist destination. For example, the guide unit can provide a guide using both audio and text. This makes it possible to provide information that is easy for users to understand by providing explanations and guides about tourist destinations in audio or text. Some or all of the above processing in the guide unit may be performed using generative AI, or it may be performed without generative AI. For example, the guide unit can use generative AI to generate an audio guide explaining the history and culture of the tourist destination. The guide unit can use generative AI to generate a text guide introducing the highlights of the tourist destination. The guide unit can use generative AI to provide a guide using both audio and text.

[0039] The game provider can offer interactive games such as historical exploration, mystery-solving tours, and environmental protection missions. For example, the game provider can offer a historical exploration game, allowing users to learn while exploring historical sites. For example, the game provider can offer a mystery-solving tour, allowing users to visit tourist destinations while solving mysteries. For example, the game provider can offer environmental protection missions, allowing users to enjoy learning about environmental protection. In this way, by offering interactive games, the game provider can realize an experience where users can learn while having fun. Some or all of the above processing in the game provider may be performed using generative AI, or not using generative AI. For example, the game provider can use generative AI to generate a historical exploration game, allowing users to learn while exploring historical sites. The game provider can use generative AI to generate a mystery-solving tour, allowing users to visit tourist destinations while solving mysteries. The game provider can use generative AI to generate an environmental protection mission, allowing users to enjoy learning about environmental protection.

[0040] The multilingual support unit can provide explanations in multiple languages. For example, the multilingual support unit can provide explanations of tourist destinations in multiple languages. For example, the multilingual support unit can perform real-time translations and provide them to the user. For example, the multilingual support unit can provide explanations in the most suitable language based on the user's language settings. This allows the unit to accommodate users who speak different languages ​​by providing explanations in multiple languages. Some or all of the above-described processes in the multilingual support unit may be performed using generative AI, or they may not be performed using generative AI. For example, the multilingual support unit can use generative AI to generate explanations of tourist destinations in multiple languages ​​and provide them to the user. The multilingual support unit can use generative AI to perform real-time translations and provide them to the user. The multilingual support unit can use generative AI to provide explanations in the most suitable language based on the user's language settings.

[0041] The information provision unit can provide weather information, traffic information, and safety information in real time. For example, the information provision unit can provide current weather information to help travelers choose appropriate clothing. For example, the information provision unit can provide traffic information to help travelers travel efficiently. For example, the information provision unit can provide safety information to support travelers in enjoying their trip safely. By providing information in real time, users can enjoy their trip with peace of mind. Some or all of the above processing in the information provision unit may be performed using generative AI, or it may be performed without generative AI. For example, the information provision unit can use generative AI to collect weather information and provide it to users in real time. The information provision unit can use generative AI to collect traffic information and provide it to users in real time. The information provision unit can use generative AI to collect safety information and provide it to users in real time.

[0042] The translation support unit can perform translation and interpretation. For example, the translation support unit can provide translations into the language the user needs. For example, the translation support unit can provide real-time interpretation to help users communicate. For example, the translation support unit can provide optimal translations based on the user's language settings. This allows the unit to support users who speak different languages ​​through translation and interpretation. Some or all of the above-described processes in the translation support unit may be performed using or without generative AI. For example, the translation support unit can use generative AI to provide translations into the language the user needs. The translation support unit can use generative AI to provide real-time interpretation to help users communicate. The translation support unit can use generative AI to provide optimal translations based on the user's language settings.

[0043] The collaboration department can partner with local businesses to offer special discounts. For example, the collaboration department can partner with local restaurants and shops to offer special discounts. For example, the collaboration department can partner with local tourist facilities to offer discounted tickets. For example, the collaboration department can partner with local events to offer special discounts. By partnering with local businesses to offer special discounts, a user-centric experience can be provided, and the local economy can be stimulated. Some or all of the above processing in the collaboration department may be performed using generative AI, or not. For example, the collaboration department can use generative AI to partner with local restaurants and shops to offer special discounts. The collaboration department can use generative AI to partner with local tourist facilities to offer discounted tickets. The collaboration department can use generative AI to partner with local events to offer special discounts.

[0044] The suggestion unit can analyze the user's past travel history and select the optimal sightseeing plan. For example, the suggestion unit can suggest new sightseeing destinations based on the user's past visits. For example, the suggestion unit can suggest a sightseeing plan that includes the user's preferred activities based on the user's past travel history. For example, the suggestion unit can analyze the user's past travel history and suggest a sightseeing plan that avoids crowds. In this way, by analyzing the user's past travel history, a more suitable sightseeing plan can be suggested. Some or all of the above processing in the suggestion unit may be performed using generative AI, or not. For example, the suggestion unit can use generative AI to analyze the user's past travel history and select the optimal sightseeing plan. The suggestion unit can use generative AI to analyze the user's past travel history and suggest a sightseeing plan that includes the user's preferred activities. The suggestion unit can use generative AI to analyze the user's past travel history and suggest a sightseeing plan that avoids crowds.

[0045] The suggestion unit can filter suggestions based on the user's current living situation and areas of interest. For example, the suggestion unit can suggest a family-friendly sightseeing plan based on the user's current living situation. For example, the suggestion unit can suggest a cultural sightseeing plan based on the user's areas of interest. For example, the suggestion unit can suggest a sightseeing plan that fits the user's budget, taking into account the user's current living situation. This allows for the suggestion of a more suitable sightseeing plan by filtering suggestions based on the user's current living situation and areas of interest. Some or all of the above processing in the suggestion unit may be performed using generative AI, or without generative AI. For example, the suggestion unit can use generative AI to filter suggestions based on the user's current living situation and areas of interest and then suggest a sightseeing plan. The suggestion unit can use generative AI to suggest a family-friendly sightseeing plan based on the user's current living situation. The suggestion unit can use generative AI to suggest a cultural sightseeing plan based on the user's areas of interest.

[0046] The suggestion unit can prioritize suggesting highly relevant sightseeing plans by considering the user's geographical location information when making suggestions. For example, the suggestion unit can prioritize suggesting sightseeing destinations close to the user's current location. For example, the suggestion unit can suggest easily accessible sightseeing plans based on the user's geographical location information. For example, the suggestion unit can suggest sightseeing plans with convenient transportation options by considering the user's geographical location information. In this way, by considering the user's geographical location information, it is possible to suggest more relevant sightseeing plans. Some or all of the above processing in the suggestion unit may be performed using generative AI, or without generative AI. For example, the suggestion unit can use generative AI to consider the user's geographical location information and suggest highly relevant sightseeing plans. The suggestion unit can use generative AI to suggest easily accessible sightseeing plans based on the user's geographical location information. The suggestion unit can use generative AI to consider the user's geographical location information and suggest sightseeing plans with convenient transportation options.

[0047] The suggestion unit can analyze the user's social media activity and propose relevant travel plans when making suggestions. For example, the suggestion unit can propose travel plans based on the user's interests shared on social media. For example, the suggestion unit can propose popular tourist destinations based on the user's social media activity. For example, the suggestion unit can analyze the user's social media activity and propose travel plans that are in line with current trends. By analyzing the user's social media activity, it is possible to propose more relevant travel plans. Some or all of the above processing in the suggestion unit may be performed using generative AI, or not. For example, the suggestion unit can use generative AI to analyze the user's social media activity and propose relevant travel plans. The suggestion unit can use generative AI to propose travel plans based on the user's interests shared on social media. The suggestion unit can use generative AI to propose popular tourist destinations based on the user's social media activity.

[0048] The guide unit can adjust the level of detail in the guide based on the importance of the tourist destination. For example, the guide unit provides a detailed guide for important tourist destinations. For example, the guide unit provides a concise guide for less important tourist destinations. The guide unit adjusts the content of the guide according to the importance of the tourist destination. This allows the user to receive important information by adjusting the level of detail in the guide based on the importance of the tourist destination. Some or all of the above processing in the guide unit may be performed using generative AI, or it may be performed without generative AI. For example, the guide unit can use generative AI to evaluate the importance of tourist destinations and adjust the level of detail in the guide. The guide unit can use generative AI to provide a detailed guide for important tourist destinations. The guide unit can use generative AI to provide a concise guide for less important tourist destinations.

[0049] The guide unit can apply different guide algorithms depending on the category of the tourist destination during guiding. For example, the guide unit can provide detailed historical information for historical tourist destinations. For example, the guide unit can provide information about the natural environment for natural tourist destinations. For example, the guide unit can provide information about the city's attractions for urban tourist destinations. By applying different guide algorithms depending on the category of the tourist destination, a more appropriate guide can be provided. Some or all of the above processing in the guide unit may be performed using generative AI, or it may be performed without generative AI. For example, the guide unit can classify the category of tourist destinations using generative AI and apply an appropriate guide algorithm. The guide unit can use generative AI to provide detailed historical information for historical tourist destinations. The guide unit can use generative AI to provide information about the natural environment for natural tourist destinations.

[0050] The guiding unit can determine the priority of guides based on the time of year the tourist destination is visited. For example, the guiding unit may prioritize guiding to seasonal tourist destinations. For example, the guiding unit may prioritize guiding to tourist destinations where specific events are being held. For example, the guiding unit may adjust the priority of guides according to the time of year the tourist destination is visited. This allows the guiding unit to provide the user with the most optimal information by determining the priority of guides based on the time of year the tourist destination is visited. Some or all of the above processing in the guiding unit may be performed using or without generative AI. For example, the guiding unit may use generative AI to evaluate the time of year the tourist destination is visited and determine the priority of guides. The guiding unit may use generative AI to prioritize guiding to seasonal tourist destinations. The guiding unit may use generative AI to prioritize guiding to tourist destinations where specific events are being held.

[0051] The guide unit can adjust the order of the guide based on the relevance of the tourist destinations during the guide process. For example, the guide unit may guide users to nearby tourist destinations in succession. For example, the guide unit may guide users to highly relevant tourist destinations in succession. The guide unit adjusts the order of the guide based on the relevance of the tourist destinations. This allows the guide unit to provide information to the user in the most optimal order by adjusting the order of the guide based on the relevance of the tourist destinations. Some or all of the above processing in the guide unit may be performed using generative AI, or not. For example, the guide unit may use generative AI to evaluate the relevance of tourist destinations and adjust the order of the guide. The guide unit may use generative AI to guide users to nearby tourist destinations in succession. The guide unit may use generative AI to guide users to highly relevant tourist destinations in succession.

[0052] The game provider can analyze a user's past gaming history to select the most suitable game when providing a game. For example, the game provider can suggest a new game based on games the user has enjoyed in the past. For example, the game provider can suggest a game of a preferred genre based on the user's past gaming history. For example, the game provider can analyze a user's past gaming history and suggest a game with adjusted difficulty. In this way, by analyzing a user's past gaming history, a more suitable game can be provided. Some or all of the above processing in the game provider may be performed using generative AI, or not. For example, the game provider can use generative AI to analyze a user's past gaming history and select the most suitable game. The game provider can use generative AI to analyze a user's past gaming history and suggest a game of a preferred genre. The game provider can use generative AI to analyze a user's past gaming history and suggest a game with adjusted difficulty.

[0053] The game provider can customize the game content based on the user's current interests when providing the game. For example, the game provider can customize the game based on themes the user is currently interested in. For example, the game provider can customize the game's story based on the user's current areas of interest. For example, the game provider can customize the game's characters considering the user's current interests. By customizing the game content based on the user's current interests, a more personalized gaming experience can be provided. Some or all of the above processing in the game provider may be performed using generative AI, or not. For example, the game provider can use generative AI to customize the game content based on the user's current interests. The game provider can use generative AI to customize the game based on themes the user is currently interested in. The game provider can use generative AI to customize the game's story based on the user's current areas of interest.

[0054] The game provider can provide the most suitable game by considering the user's geographical location information when providing a game. For example, the game provider can provide a game themed around a tourist destination near the user's current location. For example, the game provider can provide a game themed around an easily accessible tourist destination based on the user's geographical location information. For example, the game provider can provide a game themed around a tourist destination with convenient transportation options, taking the user's geographical location information into consideration. This allows for the provision of more relevant games by considering the user's geographical location information. Some or all of the above processing in the game provider may be performed using or without generative AI. For example, the game provider can use generative AI to consider the user's geographical location information and provide the most suitable game. The game provider can use generative AI to provide a game themed around a tourist destination near the user's current location. The game provider can use generative AI to provide a game themed around an easily accessible tourist destination based on the user's geographical location information.

[0055] The game provider can analyze users' social media activity and suggest game content when providing games. For example, the game provider can suggest games based on the interests users have shared on social media. For example, the game provider can suggest popular games based on users' social media activity. For example, the game provider can analyze users' social media activity and suggest games that are in line with current trends. This allows for the provision of more relevant games by analyzing users' social media activity. Some or all of the above processing in the game provider may be performed using generative AI, or not. For example, the game provider can use generative AI to analyze users' social media activity and suggest game content. The game provider can use generative AI to suggest games based on the interests users have shared on social media. The game provider can use generative AI to suggest popular games based on users' social media activity.

[0056] The multilingual support unit can select the optimal language by referring to the user's past language usage history when providing multilingual support. For example, the multilingual support unit can prioritize selecting languages ​​the user has used in the past. For example, the multilingual support unit can suggest frequently used languages ​​from the user's past language usage history. For example, the multilingual support unit can analyze the user's past language usage history and select the most suitable language. This allows the system to provide a more suitable language by referring to the user's past language usage history. Some or all of the above processing in the multilingual support unit may be performed using generative AI, or not. For example, the multilingual support unit can use generative AI to refer to the user's past language usage history and select the optimal language. The multilingual support unit can use generative AI to prioritize selecting languages ​​the user has used in the past. The multilingual support unit can use generative AI to suggest frequently used languages ​​from the user's past language usage history.

[0057] The multilingual support unit can provide the optimal language when providing multilingual support, taking into account the user's current language settings. For example, the multilingual support unit can provide the optimal language based on the language settings of the user's device. For example, the multilingual support unit can prioritize providing the language the user is currently using. For example, the multilingual support unit can provide the most suitable language by considering the user's current language settings. This allows for the provision of a more suitable language by considering the user's current language settings. Some or all of the above-described processes in the multilingual support unit may be performed using or without generative AI. For example, the multilingual support unit can use generative AI to consider the user's current language settings and provide the optimal language. The multilingual support unit can provide the optimal language based on the language settings of the user's device using generative AI. The multilingual support unit can prioritize providing the language the user is currently using using generative AI.

[0058] The multilingual support unit can provide the most suitable language when providing multilingual support, taking into account the user's geographical location information. For example, the multilingual support unit can prioritize providing the language of a region close to the user's current location. For example, the multilingual support unit can provide the language of a region that is easily accessible based on the user's geographical location information. For example, the multilingual support unit can provide the language of a region with convenient transportation, taking into account the user's geographical location information. In this way, a more suitable language can be provided by taking into account the user's geographical location information. Some or all of the above processing in the multilingual support unit may be performed using generative AI, or not. For example, the multilingual support unit can use generative AI to consider the user's geographical location information and provide the most suitable language. The multilingual support unit can use generative AI to prioritize providing the language of a region close to the user's current location. The multilingual support unit can use generative AI to provide the language of a region that is easily accessible based on the user's geographical location information.

[0059] The multilingual support unit can analyze the user's social media activity and suggest the optimal language when providing multilingual support. For example, the multilingual support unit can suggest the optimal language based on the language the user has shared on social media. For example, the multilingual support unit can suggest frequently used languages ​​from the user's social media activity. For example, the multilingual support unit can analyze the user's social media activity and suggest languages ​​that are in line with trends. In this way, by analyzing the user's social media activity, a more suitable language can be provided. Some or all of the above processing in the multilingual support unit may be performed using generative AI, or it may be performed without generative AI. For example, the multilingual support unit can use generative AI to analyze the user's social media activity and suggest the optimal language. The multilingual support unit can use generative AI to suggest the optimal language based on the language the user has shared on social media. The multilingual support unit can use generative AI to suggest frequently used languages ​​from the user's social media activity.

[0060] The information provision unit can select the most suitable information by referring to the user's past information usage history when providing information. For example, the information provision unit can provide the most suitable information based on the information the user has used in the past. For example, the information provision unit can provide frequently used information from the user's past information usage history. For example, the information provision unit can analyze the user's past information usage history and provide the most suitable information. This allows for the provision of more suitable information by referring to the user's past information usage history. Some or all of the above processing in the information provision unit may be performed using or without a generation AI. For example, the information provision unit can use a generation AI to refer to the user's past information usage history and select the most suitable information. The information provision unit can use a generation AI to provide the most suitable information based on the information the user has used in the past. The information provision unit can use a generation AI to provide frequently used information from the user's past information usage history.

[0061] The information provision unit can customize the content of the information based on the user's current situation when providing information. For example, the information provision unit can provide the information the user needs according to their current situation. For example, the information provision unit can provide the optimal information based on the user's current situation. For example, the information provision unit can customize the content of the information considering the user's current situation. By customizing the content of the information based on the user's current situation, more suitable information can be provided. Some or all of the above processing in the information provision unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the information provision unit can customize the content of the information based on the user's current situation using a generation AI. The information provision unit can provide the information the user needs according to their current situation using a generation AI. The information provision unit can provide the optimal information based on the user's current situation using a generation AI.

[0062] The information provision unit can provide optimal information by considering the user's geographical location when providing information. For example, the information provision unit can prioritize providing information about areas close to the user's current location. For example, the information provision unit can provide information about easily accessible areas based on the user's geographical location. For example, the information provision unit can provide information about areas with convenient transportation, taking into account the user's geographical location. In this way, more suitable information can be provided by considering the user's geographical location. Some or all of the above processing in the information provision unit may be performed using generative AI, or it may be performed without using generative AI. For example, the information provision unit can use generative AI to consider the user's geographical location and provide optimal information. The information provision unit can use generative AI to prioritize providing information about areas close to the user's current location. The information provision unit can use generative AI to provide information about easily accessible areas based on the user's geographical location.

[0063] The information provision department can analyze the user's social media activity and suggest information content when providing information. For example, the information provision department can provide optimal information based on information shared by the user on social media. For example, the information provision department can provide frequently used information from the user's social media activity. For example, the information provision department can analyze the user's social media activity and provide information that matches trends. In this way, by analyzing the user's social media activity, more suitable information can be provided. Some or all of the above processing in the information provision department may be performed using generative AI, or not. For example, the information provision department can use generative AI to analyze the user's social media activity and suggest information content. The information provision department can use generative AI to provide optimal information based on information shared by the user on social media. The information provision department can use generative AI to provide frequently used information from the user's social media activity.

[0064] The translation support unit can select the optimal translation method by referring to the user's past translation history when providing translation support. For example, the translation support unit can prioritize selecting translation methods that the user has used in the past. For example, the translation support unit can suggest frequently used translation methods based on the user's past translation history. For example, the translation support unit can analyze the user's past translation history and select the most suitable translation method. This allows the unit to provide a more suitable translation method by referring to the user's past translation history. Some or all of the above processing in the translation support unit may be performed using or without generative AI. For example, the translation support unit can use generative AI to refer to the user's past translation history and select the optimal translation method. The translation support unit can use generative AI to prioritize selecting translation methods that the user has used in the past. The translation support unit can use generative AI to suggest frequently used translation methods based on the user's past translation history.

[0065] The translation support unit can provide the optimal translation by considering the user's current language settings during translation support. For example, the translation support unit can provide the optimal translation based on the language settings of the user's device. For example, the translation support unit can prioritize providing the language the user is currently using. For example, the translation support unit considers the user's current language settings and provides the most suitable translation. This allows for the provision of a more suitable translation by considering the user's current language settings. Some or all of the above processing in the translation support unit may be performed using or without generative AI. For example, the translation support unit can use generative AI to consider the user's current language settings and provide the optimal translation. The translation support unit can use generative AI to provide the optimal translation based on the language settings of the user's device. The translation support unit can use generative AI to prioritize providing the language the user is currently using.

[0066] The translation support unit can provide the most suitable translation by considering the user's geographical location during translation support. For example, the translation support unit can prioritize providing the language of a region close to the user's current location. For example, the translation support unit can provide the language of a region that is easily accessible based on the user's geographical location. For example, the translation support unit can provide the language of a region with convenient transportation, taking into account the user's geographical location. This allows for the provision of more suitable translations by considering the user's geographical location. Some or all of the above processing in the translation support unit may be performed using or without generative AI. For example, the translation support unit can use generative AI to consider the user's geographical location and provide the most suitable translation. The translation support unit can use generative AI to prioritize providing the language of a region close to the user's current location. The translation support unit can use generative AI to provide the language of a region that is easily accessible based on the user's geographical location.

[0067] The translation support department can analyze the user's social media activity and suggest the optimal translation during translation support. For example, the translation support department can provide the optimal translation based on the language the user has shared on social media. For example, the translation support department can provide frequently used languages ​​from the user's social media activity. For example, the translation support department can analyze the user's social media activity and provide languages ​​that are in line with trends. This allows for the provision of more appropriate translations by analyzing the user's social media activity. Some or all of the above processing in the translation support department may be performed using generative AI, or not. For example, the translation support department can use generative AI to analyze the user's social media activity and suggest the optimal translation. The translation support department can use generative AI to provide the optimal translation based on the language the user has shared on social media. The translation support department can use generative AI to provide frequently used languages ​​from the user's social media activity.

[0068] The integration unit can select the most suitable company by analyzing the user's past consumption behavior during integration. For example, the integration unit can select the most suitable company based on the company the user has used in the past. For example, the integration unit can select a company that provides preferred services based on the user's past consumption behavior. For example, the integration unit can analyze the user's past consumption behavior and select the most suitable company. In this way, by analyzing the user's past consumption behavior, a more suitable company can be selected. Some or all of the above processing in the integration unit may be performed using generative AI, or it may be performed without generative AI. For example, the integration unit can use generative AI to analyze the user's past consumption behavior and select the most suitable company. The integration unit can use generative AI to select the most suitable company based on the company the user has used in the past. The integration unit can use generative AI to select a company that provides preferred services based on the user's past consumption behavior.

[0069] The integration unit can select the most suitable company based on the user's current interests and preferences during integration. For example, the integration unit can select a company based on themes the user is currently interested in. For example, the integration unit can select a relevant company based on the user's current areas of interest. For example, the integration unit can select the most suitable company by considering the user's current interests and preferences. This allows for more personalized services by selecting a company based on the user's current interests and preferences. Some or all of the above processing in the integration unit may be performed using generative AI, or not. For example, the integration unit can use generative AI to select a company based on the user's current interests and preferences. The integration unit can use generative AI to select a company based on themes the user is currently interested in. The integration unit can use generative AI to select a relevant company based on the user's current areas of interest.

[0070] The integration unit can select the most suitable company by considering the user's geographical location information during integration. For example, the integration unit can prioritize selecting companies that are close to the user's current location. For example, the integration unit can select companies that are easily accessible based on the user's geographical location information. For example, the integration unit can select companies with convenient transportation options by considering the user's geographical location information. In this way, a more suitable company can be selected by considering the user's geographical location information. Some or all of the above processing in the integration unit may be performed using or without generational AI. For example, the integration unit can use generational AI to consider the user's geographical location information and select the most suitable company. The integration unit can use generational AI to prioritize selecting companies that are close to the user's current location. The integration unit can use generational AI to select companies that are easily accessible based on the user's geographical location information.

[0071] The collaboration unit can analyze a user's social media activity during the collaboration process and propose the most suitable companies. For example, the collaboration unit can propose companies based on the interests the user has shared on social media. For example, the collaboration unit can propose popular companies based on the user's social media activity. For example, the collaboration unit can analyze a user's social media activity and propose companies that are in line with current trends. This allows for the selection of more suitable companies by analyzing the user's social media activity. Some or all of the above-described processes in the collaboration unit may be performed using generative AI, or they may not. For example, the collaboration unit can use generative AI to analyze a user's social media activity and propose the most suitable companies. The collaboration unit can use generative AI to propose companies based on the interests the user has shared on social media. The collaboration unit can use generative AI to propose popular companies based on the user's social media activity.

[0072] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0073] The suggestion function can propose sightseeing plans that take into account the user's current health condition. For example, if the user is tired, the suggestion function will propose a relaxing sightseeing plan. For example, if the user is active, the suggestion function will propose an active sightseeing plan. For example, if the user has health problems, the suggestion function will propose a sightseeing plan that includes nearby medical facilities. By proposing sightseeing plans based on the user's health condition, a safer and more comfortable travel experience can be provided.

[0074] The guide function can customize the content of the guide based on the user's interests. For example, if the user is interested in history, the guide function can provide a guide that explains the historical background in detail. For example, if the user is interested in nature, the guide function can provide a guide about the natural environment and flora and fauna. For example, if the user is interested in art, the guide function can provide a guide about artworks and artists. In this way, a more engaging guide experience can be provided by customizing the content of the guide based on the user's interests.

[0075] The game provider can analyze a user's past gameplay data and suggest the most suitable game. For example, the game provider can suggest a new game based on the genre of games the user has enjoyed in the past. For example, the game provider can suggest a game with adjusted difficulty based on the user's past gameplay data. For example, the game provider can analyze the user's past gameplay data and suggest a game with a storyline that the user prefers. In this way, by analyzing the user's past gameplay data, it is possible to provide a more suitable game.

[0076] The multilingual support unit can provide the most suitable language by considering the user's language learning history. For example, the multilingual support unit can prioritize providing the language the user is currently learning. For example, the multilingual support unit can provide a language appropriate to the user's learning progress based on their language learning history. For example, the multilingual support unit can analyze the user's language learning history and provide tourism information related to the language they are learning. In this way, by considering the user's language learning history, a more suitable language can be provided.

[0077] The information service can provide information considering the user's current activity. For example, if the user is walking, it can provide information on nearby tourist attractions and restaurants. If the user is driving, it can provide information on parking and traffic. If the user is taking a break, it can provide information on places to relax and cafes. By providing information based on the user's current activity, it can provide more relevant information.

[0078] The following briefly describes the processing flow for example form 1.

[0079] Step 1: The suggestion section proposes the optimal sightseeing plan based on the user's past travel history, interests, and preferences. For example, it uses a generation AI to generate sightseeing plans based on the user's past travel history, interests, and preferences, and creates a list of tourist destinations based on the user's interests. Step 2: The guide team provides explanations and guidance about the tourist attractions using audio or text. For example, they offer audio guides and text guides that introduce the history, culture, and highlights of the tourist attractions. It is also possible to combine both audio and text for the guide. Step 3: The game provider will offer interactive games. For example, interactive games such as historical exploration, mystery-solving tours, and environmental protection missions, as well as quizzes, adventure games, and educational games that users can participate in. Step 4: The multilingual support unit provides explanations in multiple languages. For example, it provides explanations of tourist destinations in multiple languages, translates them in real time, and provides explanations in the most suitable language based on the user's language settings. Step 5: The information department provides weather, traffic, and safety information in real time. For example, it provides current weather information to help travelers choose appropriate clothing, traffic information to help travelers move efficiently, and safety information to support travelers in enjoying their trip safely. Step 6: The translation support department performs translation and interpretation. For example, it provides translations into the language the user needs, performs real-time interpretation, and provides the best translation based on the user's language settings. Step 7: The Partnership Department collaborates with local businesses to offer special discounts. For example, they partner with local restaurants, shops, and tourist attractions to offer special discounts or discounted tickets, and collaborate with local events to offer special discounts.

[0080] (Example of form 2) The traveler service system according to an embodiment of the present invention is an application that utilizes generative AI to provide travelers with a "WOW!" experience. Based on the user's past travel history, interests, and preferences, the generative AI proposes the optimal sightseeing plan and content. Next, it provides explanations and guides of tourist destinations in voice or text, and offers interactive games, enabling travelers to learn about history, culture, and environmental protection while having fun. Furthermore, it supports safe and comfortable travel through multilingual support, real-time information provision, and translation / interpretation support. For example, let's describe the personalized service provided by the generative AI. Based on the user's past travel history, interests, and preferences, the generative AI proposes the optimal sightseeing plan and content. For example, for a user who likes anime, it provides content that guides them through famous scenes, behind-the-scenes stories, and history from anime. Also, because there is no fixed schedule, travelers can enjoy their trip in their own way. Next, let's describe the provision of interactive experiences. The generative AI provides explanations and guides of tourist destinations in voice or text. For example, it provides interactive games such as historical exploration, mystery-solving tours, and environmental protection missions, enabling travelers to learn while having fun. Finally, let's describe how safety is ensured. The generating AI supports safe and comfortable travel through multilingual support, real-time information provision, and translation / interpretation support. For example, it provides weather, traffic, and safety information in real time, allowing travelers to enjoy their trip with peace of mind. Finally, let's explain the business model. The application of this invention adopts a subscription model and collaborates with local businesses to offer special discounts. This enables the provision of user-centric experiences, leading to improved customer satisfaction, revitalization of the local economy, and promotion of sustainable tourism. As a result, the traveler service system can provide travelers with a "WOW!" experience, realizing an interactive, personalized, and safe journey.

[0081] The traveler service system according to this embodiment comprises a suggestion unit, a guide unit, a game provision unit, a multilingual support unit, an information provision unit, a translation support unit, and a collaboration unit. The suggestion unit proposes an optimal sightseeing plan based on the user's past travel history and interests / preferences. The suggestion unit proposes an optimal sightseeing plan based on the user's past travel history and interests / preferences, for example, by using a generation AI. The suggestion unit analyzes the user's past travel history and generates a sightseeing plan based on their interests and preferences, for example. The suggestion unit creates a list of tourist destinations based on the user's interests and proposes an optimal plan, for example. The guide unit provides explanations and guides of tourist destinations in voice or text. The guide unit provides, for example, an audio guide explaining the history and culture of the tourist destination. The guide unit provides, for example, a text guide introducing the highlights of the tourist destination. The guide unit provides a guide using a combination of both voice and text, for example. The game provision unit provides interactive games. The game provision unit provides, for example, interactive games such as historical exploration, mystery-solving tours, and environmental protection missions. The game provision unit provides, for example, quizzes and adventure games in which users can participate. The Game Provision Department provides, for example, educational games that allow users to learn while having fun. The Multilingual Support Department provides explanations in multiple languages. For example, the Multilingual Support Department provides explanations of tourist destinations in multiple languages. For example, the Multilingual Support Department provides real-time translations to users. For example, the Multilingual Support Department provides explanations in the most suitable language based on the user's language settings. The Information Provision Department provides real-time weather, traffic, and safety information. For example, the Information Provision Department provides current weather information to help travelers choose appropriate clothing. For example, the Information Provision Department provides traffic information to help travelers move efficiently. For example, the Information Provision Department provides safety information to support travelers in enjoying their trip safely. The Translation Support Department provides translation and interpretation services. For example, the Translation Support Department provides translations into the language the user needs. For example, the Translation Support Department provides real-time interpretation to help users communicate. For example, the Translation Support Department provides the most suitable translation based on the user's language settings. The Partnership Department partners with local businesses to offer special discounts.The partnership department can, for example, collaborate with local restaurants and shops to offer special discounts. It can also, for example, collaborate with local tourist facilities to offer discounted tickets. Furthermore, it can collaborate with local events to offer special discounts. This allows the traveler service system according to the embodiment to propose optimal travel plans based on the user's past travel history, interests, and preferences, enabling an interactive, personalized, and safe travel experience.

[0082] The suggestion department proposes the optimal sightseeing plan based on the user's past travel history, interests, and preferences. Specifically, the suggestion department uses generative AI to propose the optimal sightseeing plan based on the user's past travel history, interests, and preferences. The generative AI retrieves the user's past travel history from a database and analyzes information such as destinations, visited tourist spots, and activities participated in. Furthermore, it considers feedback on tourist spots and activities that the user has previously rated to identify the user's interests and preferences. Based on this information, the generative AI generates the optimal sightseeing plan for the user. For example, if the user is interested in historical tourist spots, the generative AI will propose a plan that includes historical landmarks and museums in that area. Also, if the user prefers to enjoy nature, the generative AI will propose a plan that includes nature parks and hiking trails. The suggestion department creates a list of tourist spots based on the user's interests and proposes the optimal plan. Furthermore, the suggestion department also considers the user's current travel destination, length of stay, budget, and other conditions to provide a realistic and feasible plan. In this way, the suggestion department can provide the optimal sightseeing plan for the user, making travel planning efficient and enjoyable.

[0083] The guide department provides explanations and guides about tourist destinations through audio or text. For example, the guide department provides audio guides that explain the history and culture of tourist destinations. Specifically, the guide department prepares detailed audio guides for each tourist destination and plays them on smartphones or dedicated devices when users visit the destination. The audio guides explain the historical background, cultural significance, and architectural features of the tourist destination in detail, helping users to gain a deeper understanding of the destination. The guide department also provides text guides that introduce the highlights of the tourist destinations. The text guides are provided in a format that users can view on smartphones and tablets and include photos, maps, and descriptions of the tourist destinations. This allows users to enjoy the tourist destinations visually. Furthermore, the guide department combines both audio and text in its guiding. For example, users can listen to the audio guide while simultaneously viewing the text guide to provide a richer tourist experience. The guide department allows users to select the most suitable guide format according to their preferences and circumstances. This enables the guide department to provide users with a comprehensive and personalized tourist guide, maximizing the appeal of the tourist destinations.

[0084] The game provider offers interactive games. These include interactive games such as historical explorations, mystery-solving tours, and environmental protection missions. Specifically, users can participate in games using their smartphones or tablets while visiting tourist destinations. In historical exploration games, users tour tourist destinations while completing quizzes and missions related to historical events and figures. In mystery-solving tours, users search for clues hidden within the tourist destination and solve mysteries to advance to the next destination. In environmental protection missions, users participate in activities to protect the natural environment of tourist destinations and earn points. The game provider also offers quizzes and adventure games that users can participate in. In quiz games, users answer questions about tourist destinations and earn points for correct answers. In adventure games, users complete missions following a story set in the tourist destination and enjoy an adventure. Furthermore, the game provider offers educational games that allow users to learn while having fun. In educational games, users can learn about the history, culture, and natural environment of tourist destinations as they progress through the game. This allows the game provider to offer users an enjoyable and educational experience while visiting tourist destinations, thereby enhancing the appeal of tourism.

[0085] The multilingual support unit provides explanations in multiple languages. For example, it provides explanations of tourist attractions in multiple languages. Specifically, the multilingual support unit prepares audio and text guides in multiple languages ​​for each tourist attraction and provides the guide in the language selected by the user. This makes it easier for users who speak different languages ​​to understand information about tourist attractions. The multilingual support unit also provides real-time translations to users. By using the real-time translation function, users can understand explanations at tourist attractions on the spot. For example, if a user takes a picture of a tourist attraction explanation with their smartphone camera, the multilingual support unit will translate the explanation in real time and display it to the user. In addition, the multilingual support unit provides explanations in the most appropriate language based on the user's language settings. When a user sets the language settings of the application or device, the multilingual support unit automatically provides the guide in the appropriate language based on those settings. In this way, the multilingual support unit can remove language barriers for users and provide a smooth tourist experience. Furthermore, the multilingual support unit collects user feedback and continuously improves the accuracy of translations and the content of guides. This allows the multilingual support department to consistently provide the latest and highest-quality multilingual guides, thereby improving user satisfaction.

[0086] The Information Service provides real-time weather, traffic, and safety information. For example, it provides current weather information to help travelers choose appropriate clothing. Specifically, it acquires weather data in real time and provides weather information for the user's current location and destination. This makes it easier for users to adapt to weather changes during their trip. The Information Service also provides traffic information to help travelers move efficiently. This traffic information includes public transport status, road congestion, and optimal travel routes. Users can use this information to plan their trips. Furthermore, the Information Service provides safety information to support travelers in enjoying their trips safely. This safety information includes local security conditions, emergency contact information, and evacuation locations. This allows users to travel with peace of mind. The Information Service centrally manages this information and provides it to users in real time. For example, when a user opens the application, current weather, traffic, and safety information is automatically updated and displayed. This allows the Information Service to provide users with the latest information and support them in planning and executing their trips.

[0087] The Translation Support Department provides translation and interpretation services. For example, it provides translations into the language the user needs. Specifically, it translates text or audio entered by the user into the specified language and displays or plays it back. This allows users to communicate smoothly with locals without feeling a language barrier. The Translation Support Department also assists users in communication by providing real-time interpretation. By using the real-time interpretation function, it provides instant interpretation when users converse directly with locals. For example, when a user speaks into their smartphone's microphone, the Translation Support Department translates the audio in real time and conveys it to the other party. It also translates the other party's response and conveys it to the user. This allows users to communicate smoothly with locals. Furthermore, the Translation Support Department provides optimal translations based on the user's language settings. When a user sets the language settings for an application or device, the Translation Support Department automatically provides translations in the appropriate language based on those settings. This allows the Translation Support Department to provide users with personalized translation services and support communication during travel.

[0088] The Partnership Department collaborates with local businesses to offer special discounts. For example, it partners with local restaurants and shops to offer special discounts. Specifically, the Partnership Department partners with local restaurants and shops to provide users with discount coupons that can be used at specific stores. Users can obtain coupons through the application and receive discounts by presenting them at the stores. The Partnership Department also partners with local tourist attractions to offer discount tickets. Users can purchase discount tickets for tourist attractions through the application and receive discounts by presenting them on-site. Furthermore, the Partnership Department collaborates with local events to offer special discounts. Users can obtain information about local events through the application and receive special discounts. In this way, the Partnership Department can provide users with special experiences that maximize the appeal of the local area and improve travel satisfaction. In addition, the Partnership Department strengthens collaboration with local businesses and contributes to the revitalization of the local economy. For example, by partnering with local small and medium-sized enterprises and startups to plan special promotions and events, it can boost the tourism industry throughout the region. In this way, the Partnership Department can provide users with attractive travel experiences while also contributing to the local community.

[0089] The suggestion unit can use generative AI to propose the optimal sightseeing plan based on the user's past travel history, interests, and preferences. For example, the suggestion unit uses generative AI to analyze the user's past travel history and generate a sightseeing plan based on their interests and preferences. For example, the suggestion unit uses generative AI to create a list of tourist destinations based on the user's interests and proposes the optimal plan. For example, the suggestion unit uses generative AI to propose a sightseeing plan based on the user's past travel history, interests, and preferences. This allows for the proposal of the optimal sightseeing plan based on the user's past travel history and interests and preferences. For example, the generative AI takes the user's past travel history, interests, and preferences as input and outputs the optimal sightseeing plan. For example, the generative AI creates a list of tourist destinations based on the user's interests and proposes the optimal plan. For example, the generative AI analyzes the user's past travel history and generates a sightseeing plan based on their interests and preferences.

[0090] The guide unit can provide explanations and guides about tourist destinations in audio or text. For example, the guide unit can provide an audio guide explaining the history and culture of the tourist destination. For example, the guide unit can provide a text guide introducing the highlights of the tourist destination. For example, the guide unit can provide a guide using both audio and text. This makes it possible to provide information that is easy for users to understand by providing explanations and guides about tourist destinations in audio or text. Some or all of the above processing in the guide unit may be performed using generative AI, or it may be performed without generative AI. For example, the guide unit can use generative AI to generate an audio guide explaining the history and culture of the tourist destination. The guide unit can use generative AI to generate a text guide introducing the highlights of the tourist destination. The guide unit can use generative AI to provide a guide using both audio and text.

[0091] The game provider can offer interactive games such as historical exploration, mystery-solving tours, and environmental protection missions. For example, the game provider can offer a historical exploration game, allowing users to learn while exploring historical sites. For example, the game provider can offer a mystery-solving tour, allowing users to visit tourist destinations while solving mysteries. For example, the game provider can offer environmental protection missions, allowing users to enjoy learning about environmental protection. In this way, by offering interactive games, the game provider can realize an experience where users can learn while having fun. Some or all of the above processing in the game provider may be performed using generative AI, or not using generative AI. For example, the game provider can use generative AI to generate a historical exploration game, allowing users to learn while exploring historical sites. The game provider can use generative AI to generate a mystery-solving tour, allowing users to visit tourist destinations while solving mysteries. The game provider can use generative AI to generate an environmental protection mission, allowing users to enjoy learning about environmental protection.

[0092] The multilingual support unit can provide explanations in multiple languages. For example, the multilingual support unit can provide explanations of tourist destinations in multiple languages. For example, the multilingual support unit can perform real-time translations and provide them to the user. For example, the multilingual support unit can provide explanations in the most suitable language based on the user's language settings. This allows the unit to accommodate users who speak different languages ​​by providing explanations in multiple languages. Some or all of the above-described processes in the multilingual support unit may be performed using generative AI, or they may not be performed using generative AI. For example, the multilingual support unit can use generative AI to generate explanations of tourist destinations in multiple languages ​​and provide them to the user. The multilingual support unit can use generative AI to perform real-time translations and provide them to the user. The multilingual support unit can use generative AI to provide explanations in the most suitable language based on the user's language settings.

[0093] The information provision unit can provide weather information, traffic information, and safety information in real time. For example, the information provision unit can provide current weather information to help travelers choose appropriate clothing. For example, the information provision unit can provide traffic information to help travelers travel efficiently. For example, the information provision unit can provide safety information to support travelers in enjoying their trip safely. By providing information in real time, users can enjoy their trip with peace of mind. Some or all of the above processing in the information provision unit may be performed using generative AI, or it may be performed without generative AI. For example, the information provision unit can use generative AI to collect weather information and provide it to users in real time. The information provision unit can use generative AI to collect traffic information and provide it to users in real time. The information provision unit can use generative AI to collect safety information and provide it to users in real time.

[0094] The translation support unit can perform translation and interpretation. For example, the translation support unit can provide translations into the language the user needs. For example, the translation support unit can provide real-time interpretation to help users communicate. For example, the translation support unit can provide optimal translations based on the user's language settings. This allows the unit to support users who speak different languages ​​through translation and interpretation. Some or all of the above-described processes in the translation support unit may be performed using or without generative AI. For example, the translation support unit can use generative AI to provide translations into the language the user needs. The translation support unit can use generative AI to provide real-time interpretation to help users communicate. The translation support unit can use generative AI to provide optimal translations based on the user's language settings.

[0095] The collaboration department can partner with local businesses to offer special discounts. For example, the collaboration department can partner with local restaurants and shops to offer special discounts. For example, the collaboration department can partner with local tourist facilities to offer discounted tickets. For example, the collaboration department can partner with local events to offer special discounts. By partnering with local businesses to offer special discounts, a user-centric experience can be provided, and the local economy can be stimulated. Some or all of the above processing in the collaboration department may be performed using generative AI, or not. For example, the collaboration department can use generative AI to partner with local restaurants and shops to offer special discounts. The collaboration department can use generative AI to partner with local tourist facilities to offer discounted tickets. The collaboration department can use generative AI to partner with local events to offer special discounts.

[0096] The suggestion unit can estimate the user's emotions and adjust the suggested sightseeing plan based on those emotions. For example, if the user is feeling stressed, the suggestion unit will suggest a relaxing sightseeing plan. For example, if the user is excited, the suggestion unit will suggest an active sightseeing plan. For example, if the user is tired, the suggestion unit will suggest a sightseeing plan that emphasizes rest. By adjusting the suggested sightseeing plan based on the user's emotions, a more personalized experience can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the processing described above in the suggestion unit may be performed using generative AI or not. For example, the suggestion unit can use generative AI to estimate the user's emotions and adjust the suggested sightseeing plan. The suggestion unit can use generative AI to suggest sightseeing plans based on the user's emotions.

[0097] The suggestion unit can analyze the user's past travel history and select the optimal sightseeing plan. For example, the suggestion unit can suggest new sightseeing destinations based on the user's past visits. For example, the suggestion unit can suggest a sightseeing plan that includes the user's preferred activities based on the user's past travel history. For example, the suggestion unit can analyze the user's past travel history and suggest a sightseeing plan that avoids crowds. In this way, by analyzing the user's past travel history, a more suitable sightseeing plan can be suggested. Some or all of the above processing in the suggestion unit may be performed using generative AI, or not. For example, the suggestion unit can use generative AI to analyze the user's past travel history and select the optimal sightseeing plan. The suggestion unit can use generative AI to analyze the user's past travel history and suggest a sightseeing plan that includes the user's preferred activities. The suggestion unit can use generative AI to analyze the user's past travel history and suggest a sightseeing plan that avoids crowds.

[0098] The suggestion unit can filter suggestions based on the user's current living situation and areas of interest. For example, the suggestion unit can suggest a family-friendly sightseeing plan based on the user's current living situation. For example, the suggestion unit can suggest a cultural sightseeing plan based on the user's areas of interest. For example, the suggestion unit can suggest a sightseeing plan that fits the user's budget, taking into account the user's current living situation. This allows for the suggestion of a more suitable sightseeing plan by filtering suggestions based on the user's current living situation and areas of interest. Some or all of the above processing in the suggestion unit may be performed using generative AI, or without generative AI. For example, the suggestion unit can use generative AI to filter suggestions based on the user's current living situation and areas of interest and then suggest a sightseeing plan. The suggestion unit can use generative AI to suggest a family-friendly sightseeing plan based on the user's current living situation. The suggestion unit can use generative AI to suggest a cultural sightseeing plan based on the user's areas of interest.

[0099] The suggestion unit can estimate the user's emotions and determine the priority of suggested sightseeing plans based on those emotions. For example, if the user is relaxed, the suggestion unit will prioritize suggesting relaxing sightseeing plans. If the user is excited, the suggestion unit will prioritize suggesting active sightseeing plans. If the user is tired, the suggestion unit will prioritize suggesting sightseeing plans that emphasize rest. This allows for a more personalized experience by prioritizing sightseeing plans based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the processing described above in the suggestion unit may be performed using generative AI or not. For example, the suggestion unit can use generative AI to estimate the user's emotions and determine the priority of sightseeing plans. The suggestion unit can use generative AI to suggest sightseeing plans based on the user's emotions.

[0100] The suggestion unit can prioritize suggesting highly relevant sightseeing plans by considering the user's geographical location information when making suggestions. For example, the suggestion unit can prioritize suggesting sightseeing destinations close to the user's current location. For example, the suggestion unit can suggest easily accessible sightseeing plans based on the user's geographical location information. For example, the suggestion unit can suggest sightseeing plans with convenient transportation options by considering the user's geographical location information. In this way, by considering the user's geographical location information, it is possible to suggest more relevant sightseeing plans. Some or all of the above processing in the suggestion unit may be performed using generative AI, or without generative AI. For example, the suggestion unit can use generative AI to consider the user's geographical location information and suggest highly relevant sightseeing plans. The suggestion unit can use generative AI to suggest easily accessible sightseeing plans based on the user's geographical location information. The suggestion unit can use generative AI to consider the user's geographical location information and suggest sightseeing plans with convenient transportation options.

[0101] The suggestion unit can analyze the user's social media activity and propose relevant travel plans when making suggestions. For example, the suggestion unit can propose travel plans based on the user's interests shared on social media. For example, the suggestion unit can propose popular tourist destinations based on the user's social media activity. For example, the suggestion unit can analyze the user's social media activity and propose travel plans that are in line with current trends. By analyzing the user's social media activity, it is possible to propose more relevant travel plans. Some or all of the above processing in the suggestion unit may be performed using generative AI, or not. For example, the suggestion unit can use generative AI to analyze the user's social media activity and propose relevant travel plans. The suggestion unit can use generative AI to propose travel plans based on the user's interests shared on social media. The suggestion unit can use generative AI to propose popular tourist destinations based on the user's social media activity.

[0102] The guide unit can estimate the user's emotions and adjust the way the guide is presented based on the estimated emotions. For example, if the user is nervous, the guide unit will provide guidance in a calm tone. For example, if the user is enjoying themselves, the guide unit will provide guidance in a cheerful tone. For example, if the user is tired, the guide unit will provide simple and easy-to-read guidance. This allows for a more personalized guide by adjusting the way the guide is presented based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the guide unit may be performed using generative AI or not. For example, the guide unit can use generative AI to estimate the user's emotions and adjust the way the guide is presented. The guide unit can use generative AI to provide guidance based on the user's emotions.

[0103] The guide unit can adjust the level of detail in the guide based on the importance of the tourist destination. For example, the guide unit provides a detailed guide for important tourist destinations. For example, the guide unit provides a concise guide for less important tourist destinations. The guide unit adjusts the content of the guide according to the importance of the tourist destination. This allows the user to receive important information by adjusting the level of detail in the guide based on the importance of the tourist destination. Some or all of the above processing in the guide unit may be performed using generative AI, or it may be performed without generative AI. For example, the guide unit can use generative AI to evaluate the importance of tourist destinations and adjust the level of detail in the guide. The guide unit can use generative AI to provide a detailed guide for important tourist destinations. The guide unit can use generative AI to provide a concise guide for less important tourist destinations.

[0104] The guide unit can apply different guide algorithms depending on the category of the tourist destination during guiding. For example, the guide unit can provide detailed historical information for historical tourist destinations. For example, the guide unit can provide information about the natural environment for natural tourist destinations. For example, the guide unit can provide information about the city's attractions for urban tourist destinations. By applying different guide algorithms depending on the category of the tourist destination, a more appropriate guide can be provided. Some or all of the above processing in the guide unit may be performed using generative AI, or it may be performed without generative AI. For example, the guide unit can classify the category of tourist destinations using generative AI and apply an appropriate guide algorithm. The guide unit can use generative AI to provide detailed historical information for historical tourist destinations. The guide unit can use generative AI to provide information about the natural environment for natural tourist destinations.

[0105] The guide unit can estimate the user's emotions and adjust the length of the guide based on the estimated emotions. For example, if the user is in a hurry, the guide unit can provide a short, concise guide. For example, if the user is relaxed, the guide unit can provide a detailed guide. For example, if the user is excited, the guide unit can provide a visually stimulating guide. This allows for a more personalized guide by adjusting the length of the guide based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the guide unit may be performed using generative AI or not. For example, the guide unit can use generative AI to estimate the user's emotions and adjust the length of the guide. The guide unit can use generative AI to provide guidance based on the user's emotions.

[0106] The guiding unit can determine the priority of guides based on the time of year the tourist destination is visited. For example, the guiding unit may prioritize guiding to seasonal tourist destinations. For example, the guiding unit may prioritize guiding to tourist destinations where specific events are being held. For example, the guiding unit may adjust the priority of guides according to the time of year the tourist destination is visited. This allows the guiding unit to provide the user with the most optimal information by determining the priority of guides based on the time of year the tourist destination is visited. Some or all of the above processing in the guiding unit may be performed using or without generative AI. For example, the guiding unit may use generative AI to evaluate the time of year the tourist destination is visited and determine the priority of guides. The guiding unit may use generative AI to prioritize guiding to seasonal tourist destinations. The guiding unit may use generative AI to prioritize guiding to tourist destinations where specific events are being held.

[0107] The guide unit can adjust the order of the guide based on the relevance of the tourist destinations during the guide process. For example, the guide unit may guide users to nearby tourist destinations in succession. For example, the guide unit may guide users to highly relevant tourist destinations in succession. The guide unit adjusts the order of the guide based on the relevance of the tourist destinations. This allows the guide unit to provide information to the user in the most optimal order by adjusting the order of the guide based on the relevance of the tourist destinations. Some or all of the above processing in the guide unit may be performed using generative AI, or not. For example, the guide unit may use generative AI to evaluate the relevance of tourist destinations and adjust the order of the guide. The guide unit may use generative AI to guide users to nearby tourist destinations in succession. The guide unit may use generative AI to guide users to highly relevant tourist destinations in succession.

[0108] The game provider can estimate the user's emotions and adjust the game difficulty based on those emotions. For example, if the user is relaxed, the game provider can provide a game with an easy difficulty level. If the user is excited, the game provider can provide a game with a high difficulty level. If the user is tired, the game provider can provide a game with a low difficulty level. By adjusting the game difficulty based on the user's emotions, a more personalized gaming experience can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the game provider may be performed using generative AI or not. For example, the game provider can use generative AI to estimate the user's emotions and adjust the game difficulty level. The game provider can use generative AI to provide games based on the user's emotions.

[0109] The game provider can analyze a user's past gaming history to select the most suitable game when providing a game. For example, the game provider can suggest a new game based on games the user has enjoyed in the past. For example, the game provider can suggest a game of a preferred genre based on the user's past gaming history. For example, the game provider can analyze a user's past gaming history and suggest a game with adjusted difficulty. In this way, by analyzing a user's past gaming history, a more suitable game can be provided. Some or all of the above processing in the game provider may be performed using generative AI, or not. For example, the game provider can use generative AI to analyze a user's past gaming history and select the most suitable game. The game provider can use generative AI to analyze a user's past gaming history and suggest a game of a preferred genre. The game provider can use generative AI to analyze a user's past gaming history and suggest a game with adjusted difficulty.

[0110] The game provider can customize the game content based on the user's current interests when providing the game. For example, the game provider can customize the game based on themes the user is currently interested in. For example, the game provider can customize the game's story based on the user's current areas of interest. For example, the game provider can customize the game's characters considering the user's current interests. By customizing the game content based on the user's current interests, a more personalized gaming experience can be provided. Some or all of the above processing in the game provider may be performed using generative AI, or not. For example, the game provider can use generative AI to customize the game content based on the user's current interests. The game provider can use generative AI to customize the game based on themes the user is currently interested in. The game provider can use generative AI to customize the game's story based on the user's current areas of interest.

[0111] The game provider can estimate the user's emotions and prioritize games based on those emotions. For example, if the user is relaxed, the game provider will prioritize relaxing games. If the user is excited, the game provider will prioritize active games. If the user is tired, the game provider will prioritize restful games. By prioritizing games based on the user's emotions, a more personalized gaming experience can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the game provider may be performed using generative AI or not. For example, the game provider can use generative AI to estimate the user's emotions and determine game priorities. The game provider can use generative AI to provide games based on the user's emotions.

[0112] The game provider can provide the most suitable game by considering the user's geographical location information when providing a game. For example, the game provider can provide a game themed around a tourist destination near the user's current location. For example, the game provider can provide a game themed around an easily accessible tourist destination based on the user's geographical location information. For example, the game provider can provide a game themed around a tourist destination with convenient transportation options, taking the user's geographical location information into consideration. This allows for the provision of more relevant games by considering the user's geographical location information. Some or all of the above processing in the game provider may be performed using or without generative AI. For example, the game provider can use generative AI to consider the user's geographical location information and provide the most suitable game. The game provider can use generative AI to provide a game themed around a tourist destination near the user's current location. The game provider can use generative AI to provide a game themed around an easily accessible tourist destination based on the user's geographical location information.

[0113] The game provider can analyze users' social media activity and suggest game content when providing games. For example, the game provider can suggest games based on the interests users have shared on social media. For example, the game provider can suggest popular games based on users' social media activity. For example, the game provider can analyze users' social media activity and suggest games that are in line with current trends. This allows for the provision of more relevant games by analyzing users' social media activity. Some or all of the above processing in the game provider may be performed using generative AI, or not. For example, the game provider can use generative AI to analyze users' social media activity and suggest game content. The game provider can use generative AI to suggest games based on the interests users have shared on social media. The game provider can use generative AI to suggest popular games based on users' social media activity.

[0114] The multilingual support unit can estimate the user's emotions and adjust its multilingual support methods based on the estimated emotions. For example, if the user is nervous, the multilingual support unit can provide concise and easy-to-understand multilingual support. For example, if the user is relaxed, the multilingual support unit can provide detailed multilingual support. For example, if the user is excited, the multilingual support unit can provide visually stimulating multilingual support. This allows for more personalized multilingual support by adjusting the multilingual support methods based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processing in the multilingual support unit may be performed using generative AI or not. For example, the multilingual support unit can use generative AI to estimate the user's emotions and adjust its multilingual support methods. The multilingual support unit can use generative AI to perform multilingual support based on the user's emotions.

[0115] The multilingual support unit can select the optimal language by referring to the user's past language usage history when providing multilingual support. For example, the multilingual support unit can prioritize selecting languages ​​the user has used in the past. For example, the multilingual support unit can suggest frequently used languages ​​from the user's past language usage history. For example, the multilingual support unit can analyze the user's past language usage history and select the most suitable language. This allows the system to provide a more suitable language by referring to the user's past language usage history. Some or all of the above processing in the multilingual support unit may be performed using generative AI, or not. For example, the multilingual support unit can use generative AI to refer to the user's past language usage history and select the optimal language. The multilingual support unit can use generative AI to prioritize selecting languages ​​the user has used in the past. The multilingual support unit can use generative AI to suggest frequently used languages ​​from the user's past language usage history.

[0116] The multilingual support unit can provide the optimal language when providing multilingual support, taking into account the user's current language settings. For example, the multilingual support unit can provide the optimal language based on the language settings of the user's device. For example, the multilingual support unit can prioritize providing the language the user is currently using. For example, the multilingual support unit can provide the most suitable language by considering the user's current language settings. This allows for the provision of a more suitable language by considering the user's current language settings. Some or all of the above-described processes in the multilingual support unit may be performed using or without generative AI. For example, the multilingual support unit can use generative AI to consider the user's current language settings and provide the optimal language. The multilingual support unit can provide the optimal language based on the language settings of the user's device using generative AI. The multilingual support unit can prioritize providing the language the user is currently using using generative AI.

[0117] The multilingual support unit can estimate the user's emotions and determine the priority of multilingual support based on the estimated user emotions. For example, if the user is nervous, the multilingual support unit will prioritize providing concise and easy-to-understand multilingual support. For example, if the user is relaxed, the multilingual support unit will prioritize providing detailed multilingual support. For example, if the user is excited, the multilingual support unit will prioritize providing visually stimulating multilingual support. In this way, by determining the priority of multilingual support based on the user's emotions, a more personalized multilingual support can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the multilingual support unit may be performed using generative AI or not. For example, the multilingual support unit can use generative AI to estimate the user's emotions and determine the priority of multilingual support. The multilingual support unit can perform multilingual support based on the user's emotions using generative AI.

[0118] The multilingual support unit can provide the most suitable language when providing multilingual support, taking into account the user's geographical location information. For example, the multilingual support unit can prioritize providing the language of a region close to the user's current location. For example, the multilingual support unit can provide the language of a region that is easily accessible based on the user's geographical location information. For example, the multilingual support unit can provide the language of a region with convenient transportation, taking into account the user's geographical location information. In this way, a more suitable language can be provided by taking into account the user's geographical location information. Some or all of the above processing in the multilingual support unit may be performed using generative AI, or not. For example, the multilingual support unit can use generative AI to consider the user's geographical location information and provide the most suitable language. The multilingual support unit can use generative AI to prioritize providing the language of a region close to the user's current location. The multilingual support unit can use generative AI to provide the language of a region that is easily accessible based on the user's geographical location information.

[0119] The multilingual support unit can analyze the user's social media activity and suggest the optimal language when providing multilingual support. For example, the multilingual support unit can suggest the optimal language based on the language the user has shared on social media. For example, the multilingual support unit can suggest frequently used languages ​​from the user's social media activity. For example, the multilingual support unit can analyze the user's social media activity and suggest languages ​​that are in line with trends. In this way, by analyzing the user's social media activity, a more suitable language can be provided. Some or all of the above processing in the multilingual support unit may be performed using generative AI, or it may be performed without generative AI. For example, the multilingual support unit can use generative AI to analyze the user's social media activity and suggest the optimal language. The multilingual support unit can use generative AI to suggest the optimal language based on the language the user has shared on social media. The multilingual support unit can use generative AI to suggest frequently used languages ​​from the user's social media activity.

[0120] The information delivery unit can estimate the user's emotions and adjust the method of information delivery based on the estimated emotions. For example, if the user is nervous, the information delivery unit will provide concise and easy-to-understand information. For example, if the user is relaxed, the information delivery unit will provide detailed information. For example, if the user is excited, the information delivery unit will provide visually stimulating information. By adjusting the method of information delivery based on the user's emotions, more personalized information delivery becomes possible. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the information delivery unit may be performed using generative AI or not. For example, the information delivery unit can use generative AI to estimate the user's emotions and adjust the method of information delivery. The information delivery unit can use generative AI to provide information based on the user's emotions.

[0121] The information provision unit can select the most suitable information by referring to the user's past information usage history when providing information. For example, the information provision unit can provide the most suitable information based on the information the user has used in the past. For example, the information provision unit can provide frequently used information from the user's past information usage history. For example, the information provision unit can analyze the user's past information usage history and provide the most suitable information. This allows for the provision of more suitable information by referring to the user's past information usage history. Some or all of the above processing in the information provision unit may be performed using or without a generation AI. For example, the information provision unit can use a generation AI to refer to the user's past information usage history and select the most suitable information. The information provision unit can use a generation AI to provide the most suitable information based on the information the user has used in the past. The information provision unit can use a generation AI to provide frequently used information from the user's past information usage history.

[0122] The information provision unit can customize the content of the information based on the user's current situation when providing information. For example, the information provision unit can provide the information the user needs according to their current situation. For example, the information provision unit can provide the optimal information based on the user's current situation. For example, the information provision unit can customize the content of the information considering the user's current situation. By customizing the content of the information based on the user's current situation, more suitable information can be provided. Some or all of the above processing in the information provision unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the information provision unit can customize the content of the information based on the user's current situation using a generation AI. The information provision unit can provide the information the user needs according to their current situation using a generation AI. The information provision unit can provide the optimal information based on the user's current situation using a generation AI.

[0123] The information delivery unit can estimate the user's emotions and determine the priority of information delivery based on the estimated emotions. For example, if the user is nervous, the information delivery unit will prioritize providing concise and easy-to-understand information. For example, if the user is relaxed, the information delivery unit will prioritize providing detailed information. For example, if the user is excited, the information delivery unit will prioritize providing visually stimulating information. This allows for more personalized information delivery by determining the priority of information delivery based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the information delivery unit may be performed using generative AI or not. For example, the information delivery unit can use generative AI to estimate the user's emotions and determine the priority of information delivery. The information delivery unit can use generative AI to provide information based on the user's emotions.

[0124] The information provision unit can provide optimal information by considering the user's geographical location when providing information. For example, the information provision unit can prioritize providing information about areas close to the user's current location. For example, the information provision unit can provide information about easily accessible areas based on the user's geographical location. For example, the information provision unit can provide information about areas with convenient transportation, taking into account the user's geographical location. In this way, more suitable information can be provided by considering the user's geographical location. Some or all of the above processing in the information provision unit may be performed using generative AI, or it may be performed without using generative AI. For example, the information provision unit can use generative AI to consider the user's geographical location and provide optimal information. The information provision unit can use generative AI to prioritize providing information about areas close to the user's current location. The information provision unit can use generative AI to provide information about easily accessible areas based on the user's geographical location.

[0125] The information provision department can analyze the user's social media activity and suggest information content when providing information. For example, the information provision department can provide optimal information based on information shared by the user on social media. For example, the information provision department can provide frequently used information from the user's social media activity. For example, the information provision department can analyze the user's social media activity and provide information that matches trends. In this way, by analyzing the user's social media activity, more suitable information can be provided. Some or all of the above processing in the information provision department may be performed using generative AI, or not. For example, the information provision department can use generative AI to analyze the user's social media activity and suggest information content. The information provision department can use generative AI to provide optimal information based on information shared by the user on social media. The information provision department can use generative AI to provide frequently used information from the user's social media activity.

[0126] The translation support unit can estimate the user's emotions and adjust the translation method based on the estimated emotions. For example, if the user is nervous, the translation support unit will provide a concise and easy-to-understand translation. For example, if the user is relaxed, the translation support unit will provide a detailed translation. For example, if the user is excited, the translation support unit will provide a visually stimulating translation. This allows for more personalized translation support by adjusting the translation method based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the translation support unit may be performed using generative AI or not. For example, the translation support unit can use generative AI to estimate the user's emotions and adjust the translation method. The translation support unit can use generative AI to perform translations based on the user's emotions.

[0127] The translation support unit can select the optimal translation method by referring to the user's past translation history when providing translation support. For example, the translation support unit can prioritize selecting translation methods that the user has used in the past. For example, the translation support unit can suggest frequently used translation methods based on the user's past translation history. For example, the translation support unit can analyze the user's past translation history and select the most suitable translation method. This allows the unit to provide a more suitable translation method by referring to the user's past translation history. Some or all of the above processing in the translation support unit may be performed using or without generative AI. For example, the translation support unit can use generative AI to refer to the user's past translation history and select the optimal translation method. The translation support unit can use generative AI to prioritize selecting translation methods that the user has used in the past. The translation support unit can use generative AI to suggest frequently used translation methods based on the user's past translation history.

[0128] The translation support unit can provide the optimal translation by considering the user's current language settings during translation support. For example, the translation support unit can provide the optimal translation based on the language settings of the user's device. For example, the translation support unit can prioritize providing the language the user is currently using. For example, the translation support unit considers the user's current language settings and provides the most suitable translation. This allows for the provision of a more suitable translation by considering the user's current language settings. Some or all of the above processing in the translation support unit may be performed using or without generative AI. For example, the translation support unit can use generative AI to consider the user's current language settings and provide the optimal translation. The translation support unit can use generative AI to provide the optimal translation based on the language settings of the user's device. The translation support unit can use generative AI to prioritize providing the language the user is currently using.

[0129] The translation support unit can estimate the user's emotions and determine translation priorities based on those emotions. For example, if the user is nervous, the translation support unit will prioritize providing concise and easy-to-understand translations. For example, if the user is relaxed, the translation support unit will prioritize providing detailed translations. For example, if the user is excited, the translation support unit will prioritize providing visually stimulating translations. This allows for more personalized translation support by prioritizing translations based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the translation support unit may be performed using generative AI or not. For example, the translation support unit can use generative AI to estimate the user's emotions and determine translation priorities. The translation support unit can use generative AI to perform translations based on the user's emotions.

[0130] The translation support unit can provide the most suitable translation by considering the user's geographical location during translation support. For example, the translation support unit can prioritize providing the language of a region close to the user's current location. For example, the translation support unit can provide the language of a region that is easily accessible based on the user's geographical location. For example, the translation support unit can provide the language of a region with convenient transportation, taking into account the user's geographical location. This allows for the provision of more suitable translations by considering the user's geographical location. Some or all of the above processing in the translation support unit may be performed using or without generative AI. For example, the translation support unit can use generative AI to consider the user's geographical location and provide the most suitable translation. The translation support unit can use generative AI to prioritize providing the language of a region close to the user's current location. The translation support unit can use generative AI to provide the language of a region that is easily accessible based on the user's geographical location.

[0131] The translation support department can analyze the user's social media activity and suggest the optimal translation during translation support. For example, the translation support department can provide the optimal translation based on the language the user has shared on social media. For example, the translation support department can provide frequently used languages ​​from the user's social media activity. For example, the translation support department can analyze the user's social media activity and provide languages ​​that are in line with trends. This allows for the provision of more appropriate translations by analyzing the user's social media activity. Some or all of the above processing in the translation support department may be performed using generative AI, or not. For example, the translation support department can use generative AI to analyze the user's social media activity and suggest the optimal translation. The translation support department can use generative AI to provide the optimal translation based on the language the user has shared on social media. The translation support department can use generative AI to provide frequently used languages ​​from the user's social media activity.

[0132] The collaboration unit can estimate the user's emotions and select collaborating companies based on the estimated emotions. For example, if the user is relaxed, the collaboration unit will select companies that provide relaxing services. For example, if the user is excited, the collaboration unit will select companies that provide active services. For example, if the user is tired, the collaboration unit will select companies that provide services that prioritize rest. This allows for more personalized services by selecting collaborating companies based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the collaboration unit may be performed using generative AI or not. For example, the collaboration unit can use generative AI to estimate the user's emotions and select collaborating companies. The collaboration unit can use generative AI to select companies based on the user's emotions.

[0133] The integration unit can select the most suitable company by analyzing the user's past consumption behavior during integration. For example, the integration unit can select the most suitable company based on the company the user has used in the past. For example, the integration unit can select a company that provides preferred services based on the user's past consumption behavior. For example, the integration unit can analyze the user's past consumption behavior and select the most suitable company. In this way, by analyzing the user's past consumption behavior, a more suitable company can be selected. Some or all of the above processing in the integration unit may be performed using generative AI, or it may be performed without generative AI. For example, the integration unit can use generative AI to analyze the user's past consumption behavior and select the most suitable company. The integration unit can use generative AI to select the most suitable company based on the company the user has used in the past. The integration unit can use generative AI to select a company that provides preferred services based on the user's past consumption behavior.

[0134] The integration unit can select the most suitable company based on the user's current interests and preferences during integration. For example, the integration unit can select a company based on themes the user is currently interested in. For example, the integration unit can select a relevant company based on the user's current areas of interest. For example, the integration unit can select the most suitable company by considering the user's current interests and preferences. This allows for more personalized services by selecting a company based on the user's current interests and preferences. Some or all of the above processing in the integration unit may be performed using generative AI, or not. For example, the integration unit can use generative AI to select a company based on the user's current interests and preferences. The integration unit can use generative AI to select a company based on themes the user is currently interested in. The integration unit can use generative AI to select a relevant company based on the user's current areas of interest.

[0135] The collaboration unit can estimate the user's emotions and determine the priority of collaborations based on the estimated user emotions. For example, if the user is relaxed, the collaboration unit will prioritize collaborations with companies that provide relaxing services. For example, if the user is excited, the collaboration unit will prioritize collaborations with companies that provide active services. For example, if the user is tired, the collaboration unit will prioritize collaborations with companies that provide services that prioritize rest. This allows for more personalized services by determining the priority of collaborations based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the collaboration unit may be performed using generative AI or not. For example, the collaboration unit can use generative AI to estimate the user's emotions and determine the priority of collaborations. The collaboration unit can use generative AI to select companies based on the user's emotions.

[0136] The integration unit can select the most suitable company by considering the user's geographical location information during integration. For example, the integration unit can prioritize selecting companies that are close to the user's current location. For example, the integration unit can select companies that are easily accessible based on the user's geographical location information. For example, the integration unit can select companies with convenient transportation options by considering the user's geographical location information. In this way, a more suitable company can be selected by considering the user's geographical location information. Some or all of the above processing in the integration unit may be performed using or without generational AI. For example, the integration unit can use generational AI to consider the user's geographical location information and select the most suitable company. The integration unit can use generational AI to prioritize selecting companies that are close to the user's current location. The integration unit can use generational AI to select companies that are easily accessible based on the user's geographical location information.

[0137] The collaboration unit can analyze a user's social media activity during the collaboration process and propose the most suitable companies. For example, the collaboration unit can propose companies based on the interests the user has shared on social media. For example, the collaboration unit can propose popular companies based on the user's social media activity. For example, the collaboration unit can analyze a user's social media activity and propose companies that are in line with current trends. This allows for the selection of more suitable companies by analyzing the user's social media activity. Some or all of the above-described processes in the collaboration unit may be performed using generative AI, or they may not. For example, the collaboration unit can use generative AI to analyze a user's social media activity and propose the most suitable companies. The collaboration unit can use generative AI to propose companies based on the interests the user has shared on social media. The collaboration unit can use generative AI to propose popular companies based on the user's social media activity.

[0138] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0139] The suggestion function can propose sightseeing plans that take into account the user's current health condition. For example, if the user is tired, the suggestion function will propose a relaxing sightseeing plan. For example, if the user is active, the suggestion function will propose an active sightseeing plan. For example, if the user has health problems, the suggestion function will propose a sightseeing plan that includes nearby medical facilities. By proposing sightseeing plans based on the user's health condition, a safer and more comfortable travel experience can be provided.

[0140] The guide function can customize the content of the guide based on the user's interests. For example, if the user is interested in history, the guide function can provide a guide that explains the historical background in detail. For example, if the user is interested in nature, the guide function can provide a guide about the natural environment and flora and fauna. For example, if the user is interested in art, the guide function can provide a guide about artworks and artists. In this way, a more engaging guide experience can be provided by customizing the content of the guide based on the user's interests.

[0141] The game provider can analyze a user's past gameplay data and suggest the most suitable game. For example, the game provider can suggest a new game based on the genre of games the user has enjoyed in the past. For example, the game provider can suggest a game with adjusted difficulty based on the user's past gameplay data. For example, the game provider can analyze the user's past gameplay data and suggest a game with a storyline that the user prefers. In this way, by analyzing the user's past gameplay data, it is possible to provide a more suitable game.

[0142] The multilingual support unit can provide the most suitable language by considering the user's language learning history. For example, the multilingual support unit can prioritize providing the language the user is currently learning. For example, the multilingual support unit can provide a language appropriate to the user's learning progress based on their language learning history. For example, the multilingual support unit can analyze the user's language learning history and provide tourism information related to the language they are learning. In this way, by considering the user's language learning history, a more suitable language can be provided.

[0143] The information service can provide information considering the user's current activity. For example, if the user is walking, it can provide information on nearby tourist attractions and restaurants. If the user is driving, it can provide information on parking and traffic. If the user is taking a break, it can provide information on places to relax and cafes. By providing information based on the user's current activity, it can provide more relevant information.

[0144] The suggestion function can estimate the user's emotions and adjust the suggested sightseeing plan based on those emotions. For example, if the user is feeling stressed, the suggestion function will suggest a relaxing sightseeing plan. If the user is excited, for example, the suggestion function will suggest an active sightseeing plan. If the user is tired, for example, the suggestion function will suggest a sightseeing plan that emphasizes rest. In this way, by adjusting the suggested sightseeing plan based on the user's emotions, a more personalized experience can be provided.

[0145] The guide unit can estimate the user's emotions and adjust the way it presents the guide based on those emotions. For example, if the user is nervous, the guide unit will use a calm tone. If the user is enjoying themselves, the guide unit will use a cheerful tone. If the user is tired, the guide unit will use a simple and easy-to-read style. This allows for a more personalized guide by adjusting the presentation based on the user's emotions.

[0146] The game provider can estimate the user's emotions and adjust the game's difficulty based on those emotions. For example, if the user is relaxed, the game provider can provide an easy game. If the user is excited, the game provider can provide a more difficult game. If the user is tired, the game provider can provide a game with a lower difficulty level. By adjusting the game's difficulty based on the user's emotions, a more personalized gaming experience can be provided.

[0147] The multilingual support unit can estimate the user's emotions and adjust its multilingual support methods based on those emotions. For example, if the user is nervous, the unit provides concise and easy-to-understand multilingual support. If the user is relaxed, the unit provides detailed multilingual support. If the user is excited, the unit provides visually stimulating multilingual support. By adjusting the multilingual support methods based on the user's emotions, a more personalized multilingual support can be provided.

[0148] The information delivery unit can estimate the user's emotions and adjust the method of information delivery based on those emotions. For example, if the user is nervous, the information delivery unit will provide concise and easy-to-understand information. For example, if the user is relaxed, the information delivery unit will provide detailed information. For example, if the user is excited, the information delivery unit will provide visually stimulating information. By adjusting the method of information delivery based on the user's emotions, it becomes possible to provide more personalized information.

[0149] The following briefly describes the processing flow for example form 2.

[0150] Step 1: The suggestion section proposes the optimal sightseeing plan based on the user's past travel history, interests, and preferences. For example, it uses a generation AI to generate sightseeing plans based on the user's past travel history, interests, and preferences, and creates a list of tourist destinations based on the user's interests. Step 2: The guide team provides explanations and guidance about the tourist attractions using audio or text. For example, they offer audio guides and text guides that introduce the history, culture, and highlights of the tourist attractions. It is also possible to combine both audio and text for the guide. Step 3: The game provider will offer interactive games. For example, interactive games such as historical exploration, mystery-solving tours, and environmental protection missions, as well as quizzes, adventure games, and educational games that users can participate in. Step 4: The multilingual support unit provides explanations in multiple languages. For example, it provides explanations of tourist destinations in multiple languages, translates them in real time, and provides explanations in the most suitable language based on the user's language settings. Step 5: The information department provides weather, traffic, and safety information in real time. For example, it provides current weather information to help travelers choose appropriate clothing, traffic information to help travelers move efficiently, and safety information to support travelers in enjoying their trip safely. Step 6: The translation support department performs translation and interpretation. For example, it provides translations into the language the user needs, performs real-time interpretation, and provides the best translation based on the user's language settings. Step 7: The Partnership Department collaborates with local businesses to offer special discounts. For example, they partner with local restaurants, shops, and tourist attractions to offer special discounts or discounted tickets, and collaborate with local events to offer special discounts.

[0151] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0152] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0153] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, 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.

[0154] Each of the multiple elements described above, including the proposal unit, guide unit, game provision unit, multilingual support unit, information provision unit, translation support unit, and collaboration unit, is implemented by at least one of the smart device 14 and the data processing unit 12. For example, the proposal unit is implemented by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing unit 12. The guide unit is implemented by the output device 40 of the smart device 14 or the specific processing unit 290 of the data processing unit 12. The game provision unit is implemented by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing unit 12. The multilingual support unit is implemented by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing unit 12. The information provision unit is implemented by the communication I / F 44 of the smart device 14 or the communication I / F 26 of the data processing unit 12. The translation support unit is implemented by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing unit 12. The coordinating unit is realized by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing device 12. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0155] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0156] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0157] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0158] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0159] The microphone 238 receives voice commands and other instructions from the user by receiving voice signals. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0160] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0161] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0162] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0163] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0164] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0165] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. 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 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0166] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0167] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0168] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0169] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0170] Each of the multiple elements described above, including the proposal unit, guide unit, game provision unit, multilingual support unit, information provision unit, translation support unit, and collaboration unit, is implemented by at least one of the smart glasses 214 and the data processing unit 12. For example, the proposal unit is implemented by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing unit 12. The guide unit is implemented by the speaker 240 of the smart glasses 214 or the specific processing unit 290 of the data processing unit 12. The game provision unit is implemented by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing unit 12. The multilingual support unit is implemented by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing unit 12. The information provision unit is implemented by the communication I / F 44 of the smart glasses 214 or the communication I / F 26 of the data processing unit 12. The translation support unit is implemented by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing unit 12. The coordinating unit is realized by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing device 12. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0171] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0172] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0173] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0174] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0175] The microphone 238 receives voice commands and other instructions from the user by receiving voice signals. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0176] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0177] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0178] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0179] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0180] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0181] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0182] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0183] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0184] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0185] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0186] Each of the multiple elements described above, including the proposal unit, guide unit, game provision unit, multilingual support unit, information provision unit, translation support unit, and collaboration unit, is implemented by at least one of the headset terminal 314 and the data processing unit 12. For example, the proposal unit is implemented by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing unit 12. The guide unit is implemented by the speaker 240 of the headset terminal 314 or the specific processing unit 290 of the data processing unit 12. The game provision unit is implemented by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing unit 12. The multilingual support unit is implemented by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing unit 12. The information provision unit is implemented by the communication I / F 44 of the headset terminal 314 or the communication I / F 26 of the data processing unit 12. The translation support unit is implemented by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing device 12. The coordination unit is implemented by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing device 12. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0187] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0188] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0189] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0190] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0191] The microphone 238 receives voice commands and other instructions from the user by receiving voice signals. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0192] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0193] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0194] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0195] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0196] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0197] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0198] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0199] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0200] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0201] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0202] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0203] Each of the multiple elements described above, including the proposal unit, guide unit, game provision unit, multilingual support unit, information provision unit, translation support unit, and collaboration unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the proposal unit is implemented by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing unit 12. The guide unit is implemented by the speaker 240 of the robot 414 or the specific processing unit 290 of the data processing unit 12. The game provision unit is implemented by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing unit 12. The multilingual support unit is implemented by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing unit 12. The information provision unit is implemented by the communication I / F 44 of the robot 414 or the communication I / F 26 of the data processing unit 12. The translation support unit is implemented by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing unit 12. The coordinating function is implemented by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing device 12. The correspondence between each part and the device or control unit is not limited to the example described above and can be modified in various ways.

[0204] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0205] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0206] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0207] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0208] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0209] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0210] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0211] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0212] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0213] 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.

[0214] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0215] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0216] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0217] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0218] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0219] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0220] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0221] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0222] (Note 1) The proposal department suggests the optimal sightseeing plan based on the user's past travel history, interests, and preferences. A guide unit provides explanations and guides of tourist destinations in audio or text based on the tourist plan proposed by the aforementioned proposal unit. A game provision unit that provides an interactive game based on the information provided by the aforementioned guide unit, A multilingual support unit that provides multilingual support based on the tourism plan proposed by the aforementioned proposal unit, An information provision unit that provides real-time information based on the tourism plan proposed by the aforementioned proposal unit, The Translation Support Department provides translation and interpretation services based on the tourism plans proposed by the aforementioned Proposal Department, The system comprises a collaboration department that provides special discounts in cooperation with local businesses based on the tourism plans proposed by the aforementioned proposal department. A system characterized by the following features. (Note 2) The aforementioned proposal section is, Using generative AI, we propose the optimal travel plan based on the user's past travel history, interests, and preferences. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned guide section is Provide explanations and guides about tourist attractions via audio or text. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned game provision unit, We offer interactive games such as historical exploration, mystery-solving tours, and environmental protection missions. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned multilingual support unit is Provide explanations in multiple languages. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned information provision unit, Provides real-time weather, traffic, and safety information. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned translation support department, Translator and interpreter The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned linkage unit is, We offer special discounts in collaboration with local businesses. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned proposal section is, The system estimates the user's emotions and adjusts the suggested sightseeing plans based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned proposal section is, Analyze the user's past travel history to select the optimal sightseeing plan. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned proposal section is, When making suggestions, filtering is performed based on the user's current lifestyle and areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned proposal section is, It estimates the user's emotions and determines the priority of suggested sightseeing plans based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned proposal section is, When making suggestions, the system prioritizes suggesting highly relevant travel plans, taking into account the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned proposal section is, When making a proposal, we analyze the user's social media activity and suggest relevant travel plans. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned guide section is The system estimates the user's emotions and adjusts the way the guide is presented based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned guide section is During the tour, we adjust the level of detail based on the importance of the tourist attractions. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned guide section is When guiding, different guiding algorithms are applied depending on the category of the tourist destination. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned guide section is It estimates the user's emotions and adjusts the length of the guide based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned guide section is When guiding, we determine the priority of guides based on the timing of visits to tourist destinations. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned guide section is During the tour, we adjust the order of the sightseeing locations based on their relevance. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned game provision unit, The system estimates the user's emotions and adjusts the game's difficulty based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned game provision unit, When providing a game, the system analyzes the user's past gaming history to select the most suitable game. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned game provision unit, When providing a game, the game content is customized based on the user's current interests and preferences. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned game provision unit, It estimates the user's emotions and determines the priority of games based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned game provision unit, When providing games, we take the user's geographical location into consideration to deliver the most suitable game. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned game provision unit, When providing a game, we analyze users' social media activity to suggest game content. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned multilingual support unit is It estimates the user's emotions and adjusts the multilingual support method based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned multilingual support unit is When supporting multiple languages, the system selects the most suitable language by referring to the user's past language usage history. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned multilingual support unit is When supporting multiple languages, the system will provide the optimal language considering the user's current language settings. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned multilingual support unit is It estimates user sentiment and determines the priority of multilingual support based on the estimated user sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned multilingual support unit is When providing multilingual support, the system will provide the optimal language considering the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned multilingual support unit is When providing multilingual support, the system analyzes users' social media activity to suggest the most suitable language. The system described in Appendix 1, characterized by the features described herein. (Note 33) The aforementioned information provision unit, It estimates the user's emotions and adjusts the way information is provided based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 34) The aforementioned information provision unit, When providing information, the system selects the most relevant information by referring to the user's past information usage history. The system described in Appendix 1, characterized by the features described herein. (Note 35) The aforementioned information provision unit, When providing information, customize the content of the information based on the user's current situation. The system described in Appendix 1, characterized by the features described herein. (Note 36) The aforementioned information provision unit, The system estimates the user's emotions and prioritizes information provision based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 37) The aforementioned information provision unit, When providing information, we will consider the user's geographical location to provide the most relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 38) The aforementioned information provision unit, When providing information, we analyze users' social media activity to suggest content. The system described in Appendix 1, characterized by the features described herein. (Note 39) The aforementioned translation support department, It estimates the user's emotions and adjusts the translation method based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Supplementary Note 40) The translation support unit selects an optimal translation method by referring to the user's past translation history during translation support. The system according to Supplementary Note 1, characterized by this. (Supplementary Note 41) The translation support unit provides an optimal translation considering the user's current language settings during translation support. The system according to Supplementary Note 1, characterized by this. (Supplementary Note 42) The translation support unit estimates the user's sentiment and determines the priority order of translation based on the estimated user sentiment. The system according to Supplementary Note 1, characterized by this. (Supplementary Note 43) The translation support unit provides an optimal translation considering the user's geographical location information during translation support. The system according to Supplementary Note 1, characterized by this. (Supplementary Note 44) The translation support unit proposes an optimal translation by analyzing the user's social media activities during translation support. The system according to Supplementary Note 1, characterized by this. (Supplementary Note 45) The cooperation unit estimates the user's sentiment and selects a company to cooperate with based on the estimated user sentiment. The system according to Supplementary Note 1, characterized by this. (Supplementary Note 46) The cooperation unit selects an optimal company by analyzing the user's past consumption behavior during cooperation. The system according to Supplementary Note 1, characterized by this. (Supplementary Note 47) The cooperation unit selects an optimal company based on the user's current interests and concerns during cooperation. The system according to Supplementary Note 1, characterized by this. (Supplementary Note 48) The aforementioned linkage unit is, It estimates the user's emotions and determines the priority of collaborations based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 49) The aforementioned linkage unit is, When integrating, the system selects the most suitable company by considering the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 50) The aforementioned linkage unit is, During the integration process, we analyze the user's social media activity and suggest the most suitable companies. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0223] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The proposal department suggests the optimal sightseeing plan based on the user's past travel history, interests, and preferences. A guide unit provides explanations and guides of tourist destinations in audio or text based on the tourist plan proposed by the aforementioned proposal unit. A game provision unit that provides an interactive game based on the information provided by the aforementioned guide unit, A multilingual support unit that provides multilingual support based on the tourism plan proposed by the aforementioned proposal unit, An information provision unit that provides real-time information based on the tourism plan proposed by the aforementioned proposal unit, The Translation Support Department provides translation and interpretation services based on the tourism plans proposed by the aforementioned Proposal Department, The system comprises a collaboration department that provides special discounts in cooperation with local businesses based on the tourism plans proposed by the aforementioned proposal department. A system characterized by the following features.

2. The aforementioned proposal section is, Using generative AI, we propose the optimal sightseeing plan based on the user's past travel history, interests, and preferences. The system according to feature 1.

3. The aforementioned guide portion is Provide explanations and guides about tourist attractions via audio or text. The system according to feature 1.

4. The aforementioned game provision unit, We offer interactive games such as historical exploration, mystery-solving tours, and environmental protection missions. The system according to feature 1.

5. The aforementioned multilingual support unit is Provide explanations in multiple languages. The system according to feature 1.

6. The aforementioned information provision unit, Provides real-time weather, traffic, and safety information. The system according to feature 1.

7. The aforementioned translation support department, Translator and interpreter The system according to feature 1.

8. The aforementioned linkage unit is, We offer special discounts in collaboration with local businesses. The system according to feature 1.

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