system

Abstract

The system according to this embodiment aims to allow elderly people to experience tourist destinations around the world and explore new worlds from the comfort of their own homes. [Solution] The system according to the embodiment comprises a reception unit, a generation unit, a provision unit, and a response unit. The reception unit receives the user's travel destination selection. The generation unit generates a travel plan based on the information received by the reception unit. The provision unit provides a VR experience based on the travel plan generated by the generation unit. The response unit responds to the user's questions and requests during the VR experience provided by the provision unit.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including 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, there is a problem that it is difficult for the elderly to experience tourist destinations around the world while staying at home, and it is difficult to explore a new world beyond physical constraints.

[0005] The system according to the embodiment aims to enable the elderly to experience tourist destinations around the world while staying at home and explore a new world.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a reception unit, a generation unit, a provision unit, and a response unit. The reception unit receives the user's travel destination selection. The generation unit generates a travel plan based on the information received by the reception unit. The provision unit provides a VR experience based on the travel plan generated by the generation unit. The response unit responds to the user's questions and requests during the VR experience provided by the provision unit. [Effects of the Invention]

[0007] The system according to this embodiment allows elderly people to experience tourist destinations around the world and explore new worlds from the comfort of their own homes. [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 signed storage is one or more non-volatile storage devices that store various programs and various parameters. 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 labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F manages communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards such as 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 [SP1]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] Note: There seems to be a small error in the original Chinese text where "プロセッサ28" is repeated twice in the English translation part of ID=18. It should be just one "processor 28" as in the original Chinese text. I've translated it as accurately as possible based on the given rules.The smart device 14 comprises a computer 36, a receiving device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the 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 virtual travel service according to an embodiment of the present invention is a system that allows elderly people to experience tourist destinations around the world from the comfort of their homes. This system utilizes generative AI to provide travel plans and guide information tailored to the user's preferences. Based on the tourist destinations and cultures that interest the user, it provides an immersive VR experience, and by adding audio guides and interactive elements, it realizes a more realistic travel experience. Furthermore, the AI ​​responds in real time to questions and requests that the user may have during the trip, providing personalized information. This allows elderly people to explore new worlds beyond physical limitations and feel connected to society. This service aims to provide not only a tourist experience but also opportunities for enrichment of mind and learning. For example, the user selects a travel destination or tourist destination of interest. Next, the generative AI generates a travel plan based on the user's selection and provides a VR experience. For example, if the user selects to visit the Eiffel Tower in Paris, the generative AI generates a travel plan that includes detailed information about the Eiffel Tower, its history, and surrounding tourist spots. Furthermore, the VR experience provides a sense of realism as if the user were actually visiting the Eiffel Tower, and an audio guide explains the history and highlights of the Eiffel Tower. Furthermore, the AI ​​responds in real time to questions and requests that users may have during their trip. For example, if a user asks, "How tall is the Eiffel Tower?", the AI ​​will immediately answer, providing the height of the Eiffel Tower and other relevant information. This allows users to resolve questions they may have during their trip and gain a deeper understanding. In addition, it is possible to enjoy virtual travel with friends and family. Users can share their trip in the same VR space as other users and communicate in real time. This allows them to share an enjoyable travel experience while maintaining social connections. This service aims to provide seniors with opportunities to explore new worlds beyond physical limitations, enriching their minds and providing opportunities for learning. For example, users can gain new knowledge by learning about different cultures and histories. Also, through virtual travel, users can enjoy new experiences and add excitement to their daily lives.This means that virtual travel services can allow seniors to experience tourist destinations around the world from the comfort of their own homes, providing opportunities for enrichment and learning.

[0029] The virtual travel service according to the embodiment comprises a reception unit, a generation unit, a provision unit, and a response unit. The reception unit receives the user's travel destination selection. The user's travel destination selection includes, but is not limited to, the method of presenting options and selection criteria. The reception unit provides, for example, an interface for the user to select a travel destination. The reception unit can also collect travel destination information based on the user's selection. For example, the reception unit provides detailed information about the travel destination selected by the user. The generation unit generates a travel plan based on the information received by the reception unit using a generation AI. The travel plan includes, for example, elements included in the plan and a generation algorithm, but is not limited to, such examples. The generation unit generates a customized travel plan based on the user's selection. The generation unit can also generate a travel plan based on the user's past behavioral data and preference information. For example, the generation unit analyzes the user's past travel history and generates an optimal travel plan. The provision unit provides a VR experience based on the travel plan generated by the generation unit. The VR experience includes, for example, the type of experience and the means of delivery, but is not limited to, such examples. The service provider offers a VR experience that includes, for example, audio guides and interactive elements. The service provider can also provide features for enjoying virtual travel with friends and family. For example, the service provider can provide a function that allows multiple users to share a trip in the same VR space. The response unit responds to user questions and requests during the VR experience provided by the service provider. Responses include, but are not limited to, criteria for response timing and content. The response unit responds to user questions in real time, for example. The response unit can also respond to user questions using natural language processing techniques. For example, the response unit provides appropriate information in response to user questions. This allows the virtual travel service according to the embodiment to consistently handle everything from user destination selection to VR experience provision and response to questions and requests.

[0030] The reception desk accepts the user's travel destination selection. This selection process includes, but is not limited to, the presentation of options and selection criteria. The reception desk provides an interface for the user to select a travel destination. Specifically, it presents the user with a variety of travel destination options through the user interface. This includes information such as geographical location, tourist attractions, cultural background, and seasonal events. Based on this information, the user can select a travel destination that suits their interests and preferences. Furthermore, the reception desk can also collect travel destination information based on the user's selection. For example, to provide detailed information about the travel destination selected by the user, it can collect information from publicly available databases and travel guide websites on the internet and provide it to the user. This allows the user to obtain detailed information about their selected travel destination and form a more concrete image. The reception desk can also record the user's past selection history and preference information, which can be used as a reference when selecting a travel destination in the future. This enables personalized travel destination suggestions tailored to the user's preferences. For example, a user who has previously preferred beach resorts can be given priority in presenting new beach resort options. This allows the reception desk to efficiently and effectively support users in selecting their travel destinations, thereby improving user satisfaction.

[0031] The generation unit uses a generation AI to generate travel plans based on information received by the reception unit. These travel plans may include, but are not limited to, elements and generation algorithms. For example, the generation unit can generate customized travel plans based on user selections. Specifically, the generation AI automatically generates the optimal travel plan based on information about the travel destination selected by the user. The generation AI analyzes the user's past behavioral data and preferences to propose a plan tailored to their tastes. For example, for a user who has previously enjoyed visiting historical tourist destinations, the generation AI will generate a plan centered around historical landmarks in the selected destination. The generation AI can also create an optimal schedule considering the user's travel style, budget, and length of stay. Furthermore, the generation unit can analyze the user's past travel history to generate optimal travel plans. For example, based on data from places visited and activities participated in in the past, it can suggest places and activities the user hasn't yet visited but might be interested in. This allows the generation unit to provide users with new discoveries and experiences. The generation unit also presents the generated travel plan to the user and provides an interface for the user to review and modify the plan. Users can provide feedback on the generated plan and customize it as needed. This allows the generation unit to provide a travel plan that fully meets the user's needs.

[0032] The service provider delivers VR experiences based on travel plans generated by the generation unit. These VR experiences include, but are not limited to, the type of experience and the means of delivery. For example, the service provider may offer VR experiences that include audio guides and interactive elements. Specifically, the service provider may offer virtual tours of user-selected travel destinations, providing users with an experience as if they were actually visiting the location. These VR experiences may include high-resolution video, 3D audio, and haptic feedback, allowing users to enjoy a realistic experience through sight, sound, and touch. Furthermore, the service provider can also provide features for enjoying virtual travel with friends and family. For example, the service provider may offer a feature that allows multiple users to share a trip in the same VR space, enabling them to communicate with each other in real time while enjoying the trip. This allows users to enjoy traveling with friends and family who are far away, deepening their bonds through the shared experience. Additionally, the service provider can continuously improve the content of the VR experience based on user feedback. For example, if a user gives a high rating to a particular location or activity, new content can be added based on that information. This allows the service provider to always provide the latest and most engaging VR experiences, improving user satisfaction.

[0033] The response unit responds to user questions and requests during the VR experience provided by the service provider. Responses include, but are not limited to, criteria for response timing and content. The response unit responds to user questions in real time, for example. Specifically, it can use natural language processing technology to respond to user questions. For example, if a user asks about a specific tourist attraction during the VR experience, the response unit provides detailed information about that attraction. The response unit can also adjust the content of the VR experience according to user requests. For example, if a user wants to see a particular place in more detail, the response unit can provide detailed images and information about that place. Furthermore, the response unit can continuously improve its responses based on user feedback. For example, if a user does not receive a satisfactory answer to a particular question, the response algorithm can be improved based on that feedback, increasing the accuracy of responses in subsequent sessions. This allows the response unit to respond quickly and accurately to user questions and requests, improving the quality of the VR experience. The response unit can also record the user's past question history for reference during subsequent VR experiences. This enables personalized responses tailored to the user's preferences and interests, providing a more satisfying experience.

[0034] The generation unit can generate customized travel plans based on the user's past behavioral data and preference information. For example, the generation unit can collect the user's past behavioral data and reflect it in the travel plan. For instance, it can customize the travel plan based on the user's visit history and purchase history. The generation unit can also collect the user's preference information and reflect it in the travel plan. For example, it can generate a travel plan based on the user's preferred travel style and activities of interest. Furthermore, the generation unit can analyze the user's preference information using natural language processing technology and reflect it in the travel plan. For example, it can analyze the user's past travel history and generate the optimal travel plan. This allows for the provision of more personalized travel plans based on the user's past behavioral data and preference information.

[0035] The service provider can offer VR experiences that include audio guides and interactive elements. For example, the service provider can provide information about tourist destinations using audio guides. For instance, the service provider can provide audio explanations of the history and highlights of the tourist destination. The service provider can also offer VR experiences that include interactive elements. For example, the service provider can allow users to interact with interactive objects as they explore the tourist destination. Furthermore, the service provider can provide a more realistic VR experience through interaction with the user. For example, the service provider can allow users to ask questions about the tourist destination and respond to those questions in real time. This allows for a more realistic VR experience by including audio guides and interactive elements.

[0036] The response unit can respond to user questions in real time. For example, if a user asks a question about a tourist destination, the response unit will answer it immediately. For instance, if a user asks, "How tall is the Eiffel Tower?", the response unit will provide the height of the Eiffel Tower and other relevant information. The response unit can also respond to user requests in real time. For example, if a user requests, "Please tell me which tourist destination I should visit next," the response unit will suggest a suitable destination. By responding to user questions in real time, it can immediately address any questions or requests that arise during travel.

[0037] The service provider can offer features that allow users to enjoy virtual travel with friends and family. For example, it can provide a feature that allows multiple users to share a trip in the same VR space. For instance, it can enable users to explore tourist destinations with friends and family and communicate in real time. The service provider can also provide an interface for users to enjoy virtual travel with other users. For example, it can enable users to share interactive elements when visiting tourist destinations with other users. This allows users to share travel experiences while maintaining social connections by enjoying virtual travel with friends and family.

[0038] The response unit can respond to user questions using natural language processing technology. For example, if a user asks a question about a tourist destination, the response unit will use natural language processing technology to provide appropriate information in response to that question. For instance, if a user asks, "Please tell me about the history of the Eiffel Tower," the response unit will use natural language processing technology to provide information about the history of the Eiffel Tower. The response unit can also respond to user requests using natural language processing technology. For example, if a user requests, "Please tell me what tourist destination I should visit next," the response unit will use natural language processing technology to suggest an appropriate tourist destination. In this way, using natural language processing technology allows for more natural and appropriate responses.

[0039] The reception desk can analyze the user's past travel destination selection history and present the most suitable options. For example, the reception desk can suggest similar tourist destinations based on the tourist destinations the user has visited in the past. For example, the reception desk can suggest highly-rated tourist destinations based on the user's ratings of tourist destinations they have visited in the past. The reception desk can also suggest tourist destinations that should be visited in the same season as the tourist destinations the user has visited in the past. For example, the reception desk can suggest the most suitable tourist destinations based on the seasonal information of tourist destinations the user has visited in the past. In this way, by analyzing the user's past travel destination selection history, more appropriate travel destinations can be suggested. Some or all of the above processing in the reception desk may be performed using AI, for example, or without using AI.

[0040] The reception desk can filter travel destinations based on the user's current health status and interests. For example, if the user is in good health, the reception desk will suggest active tourist destinations. For example, if the user is in poor health, the reception desk will suggest quiet tourist destinations. The reception desk can also suggest tourist destinations that the user might be interested in. For example, the reception desk will suggest the most suitable tourist destination based on the user's interests. This allows for the suggestion of more appropriate travel destinations by filtering based on the user's health status and interests. Some or all of the above processing in the reception desk may be performed using AI, for example, or without AI.

[0041] The reception desk can prioritize presenting highly relevant options when users select a travel destination, taking into account their geographical location. For example, the reception desk can prioritize presenting tourist destinations close to the user's current location. For example, the reception desk can prioritize presenting tourist destinations that are easily accessible from the user's current location. The reception desk can also prioritize presenting the most suitable tourist destination by considering the travel time from the user's current location. For example, the reception desk can suggest the most suitable tourist destination based on the travel time from the user's current location. In this way, by considering the user's geographical location, it is possible to suggest a more appropriate travel destination. Some or all of the above processing in the reception desk may be performed using AI, for example, or without using AI.

[0042] The reception desk can analyze the user's social media activity when selecting a travel destination and present relevant options. For example, the reception desk can prioritize tourist destinations that the user has shown interest in on social media. For example, the reception desk can prioritize tourist destinations that the user's social media friends have visited. The reception desk can also analyze the content of the user's social media posts and prioritize relevant tourist destinations. For example, the reception desk can suggest the most suitable tourist destination based on the content of the user's social media posts. In this way, by analyzing the user's social media activity, it is possible to suggest more appropriate travel destinations. Some or all of the above processing in the reception desk may be performed using AI, for example, or not using AI.

[0043] The generation unit can customize travel plans by considering the user's past travel history and preferences. For example, the generation unit can generate travel plans that include similar tourist destinations based on the user's past visits. For example, the generation unit can generate travel plans that include tourist destinations of interest based on the user's preferences. The generation unit can also analyze the user's past travel history and generate travel plans that include the most suitable tourist destinations. For example, the generation unit can suggest the most suitable tourist destinations based on the user's past travel history. This allows for the provision of more appropriate travel plans by considering the user's past travel history and preferences. Some or all of the above-described processes in the generation unit may be performed using, for example, a generation AI, or without using a generation AI.

[0044] The generation unit can reflect the season and event information of the selected travel destination when generating a travel plan. For example, the generation unit generates a travel plan that includes tourist attractions suited to the season of the selected travel destination. For example, the generation unit generates a travel plan that includes events based on the event information of the selected travel destination. The generation unit can also generate the optimal travel plan by considering the season and event information of the selected travel destination. For example, the generation unit suggests the optimal tourist attractions based on the seasonal information of the selected travel destination. In this way, by reflecting the season and event information of the selected travel destination, a more appropriate travel plan can be provided. Some or all of the above processing in the generation unit may be performed using, for example, a generation AI, or without using a generation AI.

[0045] The generation unit can determine the priority of travel plans based on when the user submits them. For example, if the user submits an early plan, the generation unit will prioritize generating a detailed travel plan. For example, if the user submits a plan at the last minute, the generation unit will prioritize generating a concise travel plan. The generation unit can also prioritize generating the most suitable travel plan based on when the user submits it. For example, the generation unit will suggest the most suitable tourist destinations based on when the user submits it. By prioritizing plans based on when the user submits them, the generation unit can provide more appropriate travel plans. Some or all of the above processing in the generation unit may be performed using, for example, a generation AI, or without using a generation AI.

[0046] The generation unit can create a travel plan by referring to relevant literature and guidebook information for the selected travel destination. For example, the generation unit can generate a detailed travel plan based on relevant literature for the selected travel destination. For example, the generation unit can generate an optimal travel plan based on guidebook information for the selected travel destination. The generation unit can also generate a customized travel plan by referring to relevant literature and guidebook information for the selected travel destination. For example, the generation unit can suggest the best tourist destinations based on relevant literature for the selected travel destination. This allows for the provision of a more appropriate travel plan by referring to relevant literature and guidebook information for the selected travel destination. Some or all of the above processing in the generation unit may be performed using, for example, a generation AI, or without using a generation AI.

[0047] The service provider can provide the optimal VR experience by referring to the user's past experience history when providing a VR experience. For example, the service provider can provide a similar VR experience based on the user's past VR experiences. For example, the service provider can analyze the user's past experience history and provide the optimal VR experience. The service provider can also provide a customized VR experience based on the user's past experience history. For example, the service provider can suggest the optimal tourist destination based on the user's past experience history. In this way, a more appropriate VR experience can be provided by referring to the user's past experience history. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI.

[0048] The service provider can reflect the latest information on the selected travel destination when providing a VR experience. For example, the service provider can provide the latest VR experience based on the latest information on the selected travel destination. For example, the service provider can provide a VR experience that includes events based on the latest event information on the selected travel destination. The service provider can also provide the optimal VR experience by reflecting the latest information on the selected travel destination. For example, the service provider can suggest the best tourist destinations based on the latest information on the selected travel destination. This allows for the provision of a more appropriate VR experience by reflecting the latest information on the selected travel destination. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI.

[0049] The service provider can provide an optimal VR experience by considering the user's geographical location when providing a VR experience. For example, the service provider can provide a VR experience of a tourist destination close to the user's current location. For example, the service provider can provide a VR experience of a tourist destination that is easily accessible from the user's current location. The service provider can also provide an optimal VR experience of a tourist destination by considering the travel time from the user's current location. For example, the service provider can suggest an optimal tourist destination based on the travel time from the user's current location. In this way, a more appropriate VR experience can be provided by considering the user's geographical location. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI.

[0050] The service provider can analyze the user's social media activity when providing a VR experience and offer a relevant experience. For example, the service provider can offer a VR experience of a tourist destination that the user has shown interest in on social media. For example, the service provider can offer a VR experience of a tourist destination visited by the user's social media friends. The service provider can also analyze the content of the user's social media posts and offer a VR experience of a relevant tourist destination. For example, the service provider can suggest the most suitable tourist destination based on the content of the user's social media posts. In this way, by analyzing the user's social media activity, a more appropriate VR experience can be provided. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI.

[0051] The response unit can provide the most appropriate response by referring to the user's past question history when responding. For example, the response unit can provide responses to similar questions based on the content of questions the user has asked in the past. For example, the response unit can analyze the user's past question history and provide the most appropriate response. The response unit can also provide customized responses based on the user's past question history. For example, the response unit can provide information on the most suitable tourist destinations based on the user's past question history. This allows for the provision of more appropriate responses by referring to the user's past question history. Some or all of the above processing in the response unit may be performed using AI, for example, or without using AI.

[0052] The response unit can reflect the latest information on the selected travel destination when responding. For example, the response unit provides the latest response based on the latest information on the selected travel destination. For example, the response unit provides a response regarding an event based on the latest event information on the selected travel destination. The response unit can also provide the most appropriate response by reflecting the latest information on the selected travel destination. For example, the response unit provides information on the most suitable tourist destination based on the latest information on the selected travel destination. This allows for the provision of a more appropriate response by reflecting the latest information on the selected travel destination. Some or all of the above processing in the response unit may be performed using AI, for example, or without using AI.

[0053] The response unit can provide an optimal response by considering the user's geographical location information when responding. For example, the response unit can provide a response regarding tourist destinations close to the user's current location. For example, the response unit can provide a response regarding tourist destinations that are easily accessible from the user's current location. The response unit can also provide a response regarding optimal tourist destinations by considering the travel time from the user's current location. For example, the response unit can provide information about optimal tourist destinations based on the travel time from the user's current location. This allows for the provision of a more appropriate response by considering the user's geographical location information. Some or all of the above processing in the response unit may be performed using AI, for example, or without using AI.

[0054] The response unit can analyze the user's social media activity and provide relevant information when responding. For example, the response unit can provide responses regarding tourist destinations that the user has shown interest in on social media. For example, the response unit can provide responses regarding tourist destinations visited by the user's friends on social media. The response unit can also analyze the content of the user's social media posts and provide responses regarding relevant tourist destinations. For example, the response unit can provide information on the most suitable tourist destinations based on the content of the user's social media posts. This allows for the provision of more appropriate responses by analyzing the user's social media activity. Some or all of the above processing in the response unit may be performed using AI, for example, or without using AI.

[0055] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0056] The reception desk can monitor the user's health status and adjust travel destination suggestions accordingly. For example, it can measure the user's heart rate and blood pressure using sensors and suggest active tourist destinations if the user is in good health. Conversely, if the user is in poor health, it can suggest quieter tourist destinations. Furthermore, the reception desk can adjust the activities at the travel destination based on the user's health status. For example, if the user is in good health, it can suggest travel plans that include hiking and walking tours, while if the user is in poor health, it can suggest relaxing tourist destinations and activities. This allows the system to suggest the most suitable travel destination for the user based on their health condition.

[0057] The service provider can provide a more personalized VR experience by referencing the user's past travel history. For example, based on data from tourist destinations the user has visited in the past, the service provider can offer a VR experience of a similar tourist destination. It can also analyze the user's past travel history and provide a VR experience that includes tourist destinations and activities that the user was particularly interested in. Furthermore, based on the user's past travel history, the service provider can suggest tourist destinations that the user has not yet visited but might be interested in. In this way, the service provider can leverage the user's past travel history to provide a more personalized VR experience.

[0058] The service provider can analyze users' social media activity and provide relevant VR experiences. For example, it can provide VR experiences of tourist destinations that users have shown interest in on social media. It can also provide VR experiences of tourist destinations visited by the user's social media friends. Furthermore, it can analyze the content of users' social media posts and provide VR experiences of relevant tourist destinations. This allows for the provision of more personalized VR experiences by leveraging users' social media activity.

[0059] The generation unit can create more personalized travel plans by considering the user's past travel history and preferences. For example, it can generate travel plans that include similar tourist destinations based on data of tourist destinations the user has visited in the past. It can also generate travel plans that include tourist destinations and activities of interest based on the user's preferences. Furthermore, it can analyze the user's past travel history and suggest tourist destinations that the user has not yet visited but might be interested in. In this way, it can provide more personalized travel plans by utilizing the user's past travel history and preferences.

[0060] The response unit can provide more appropriate responses by referring to the user's past question history. For example, the response unit can provide answers to similar questions based on what the user has asked in the past. It can also analyze the user's past question history and provide information about tourist destinations or activities that the user has been particularly interested in. Furthermore, based on the user's past question history, it can suggest information that the user has not yet asked about but might be interested in. In this way, the system can provide more appropriate responses by utilizing the user's past question history.

[0061] The following briefly describes the processing flow for example form 1.

[0062] Step 1: The reception desk accepts the user's travel destination selection. This selection may include, but is not limited to, the method of presenting options and the selection criteria. The reception desk may also provide an interface for the user to select a travel destination and collect travel destination information based on the user's selection. Step 2: The generation unit uses a generation AI to generate a travel plan based on the information received by the reception unit. The travel plan may include, but is not limited to, elements and generation algorithms included in the plan. The generation unit can also generate a customized travel plan based on user selections, or generate a travel plan based on the user's past behavioral data and preferences. Step 3: The provider delivers the VR experience based on the travel plan generated by the generator. The VR experience may include, but is not limited to, the type of experience and the means of delivery. The provider may also provide a VR experience that includes audio guides and interactive elements, and may offer features to enjoy virtual travel with friends and family. Step 4: The response unit responds to user questions and requests during the VR experience provided by the provider unit. Responses include, but are not limited to, criteria for response timing and content. The response unit can respond to user questions in real time and may also use natural language processing techniques to respond to user questions.

[0063] (Example of form 2) The virtual travel service according to an embodiment of the present invention is a system that allows elderly people to experience tourist destinations around the world from the comfort of their homes. This system utilizes generative AI to provide travel plans and guide information tailored to the user's preferences. Based on the tourist destinations and cultures that interest the user, it provides an immersive VR experience, and by adding audio guides and interactive elements, it realizes a more realistic travel experience. Furthermore, the AI ​​responds in real time to questions and requests that the user may have during the trip, providing personalized information. This allows elderly people to explore new worlds beyond physical limitations and feel connected to society. This service aims to provide not only a tourist experience but also opportunities for enrichment of mind and learning. For example, the user selects a travel destination or tourist destination of interest. Next, the generative AI generates a travel plan based on the user's selection and provides a VR experience. For example, if the user selects to visit the Eiffel Tower in Paris, the generative AI generates a travel plan that includes detailed information about the Eiffel Tower, its history, and surrounding tourist spots. Furthermore, the VR experience provides a sense of realism as if the user were actually visiting the Eiffel Tower, and an audio guide explains the history and highlights of the Eiffel Tower. Furthermore, the AI ​​responds in real time to questions and requests that users may have during their trip. For example, if a user asks, "How tall is the Eiffel Tower?", the AI ​​will immediately answer, providing the height of the Eiffel Tower and other relevant information. This allows users to resolve questions they may have during their trip and gain a deeper understanding. In addition, it is possible to enjoy virtual travel with friends and family. Users can share their trip in the same VR space as other users and communicate in real time. This allows them to share an enjoyable travel experience while maintaining social connections. This service aims to provide seniors with opportunities to explore new worlds beyond physical limitations, enriching their minds and providing opportunities for learning. For example, users can gain new knowledge by learning about different cultures and histories. Also, through virtual travel, users can enjoy new experiences and add excitement to their daily lives.This means that virtual travel services can allow seniors to experience tourist destinations around the world from the comfort of their own homes, providing opportunities for enrichment and learning.

[0064] The virtual travel service according to the embodiment comprises a reception unit, a generation unit, a provision unit, and a response unit. The reception unit receives the user's travel destination selection. The user's travel destination selection includes, but is not limited to, the method of presenting options and selection criteria. The reception unit provides, for example, an interface for the user to select a travel destination. The reception unit can also collect travel destination information based on the user's selection. For example, the reception unit provides detailed information about the travel destination selected by the user. The generation unit generates a travel plan based on the information received by the reception unit using a generation AI. The travel plan includes, for example, elements included in the plan and a generation algorithm, but is not limited to, such examples. The generation unit generates a customized travel plan based on the user's selection. The generation unit can also generate a travel plan based on the user's past behavioral data and preference information. For example, the generation unit analyzes the user's past travel history and generates an optimal travel plan. The provision unit provides a VR experience based on the travel plan generated by the generation unit. The VR experience includes, for example, the type of experience and the means of delivery, but is not limited to, such examples. The service provider offers a VR experience that includes, for example, audio guides and interactive elements. The service provider can also provide features for enjoying virtual travel with friends and family. For example, the service provider can provide a function that allows multiple users to share a trip in the same VR space. The response unit responds to user questions and requests during the VR experience provided by the service provider. Responses include, but are not limited to, criteria for response timing and content. The response unit responds to user questions in real time, for example. The response unit can also respond to user questions using natural language processing techniques. For example, the response unit provides appropriate information in response to user questions. This allows the virtual travel service according to the embodiment to consistently handle everything from user destination selection to VR experience provision and response to questions and requests.

[0065] The reception desk accepts the user's travel destination selection. This selection process includes, but is not limited to, the presentation of options and selection criteria. The reception desk provides an interface for the user to select a travel destination. Specifically, it presents the user with a variety of travel destination options through the user interface. This includes information such as geographical location, tourist attractions, cultural background, and seasonal events. Based on this information, the user can select a travel destination that suits their interests and preferences. Furthermore, the reception desk can also collect travel destination information based on the user's selection. For example, to provide detailed information about the travel destination selected by the user, it can collect information from publicly available databases and travel guide websites on the internet and provide it to the user. This allows the user to obtain detailed information about their selected travel destination and form a more concrete image. The reception desk can also record the user's past selection history and preference information, which can be used as a reference when selecting a travel destination in the future. This enables personalized travel destination suggestions tailored to the user's preferences. For example, a user who has previously preferred beach resorts can be given priority in presenting new beach resort options. This allows the reception desk to efficiently and effectively support users in selecting their travel destinations, thereby improving user satisfaction.

[0066] The generation unit uses a generation AI to generate travel plans based on information received by the reception unit. These travel plans may include, but are not limited to, elements and generation algorithms. For example, the generation unit can generate customized travel plans based on user selections. Specifically, the generation AI automatically generates the optimal travel plan based on information about the travel destination selected by the user. The generation AI analyzes the user's past behavioral data and preferences to propose a plan tailored to their tastes. For example, for a user who has previously enjoyed visiting historical tourist destinations, the generation AI will generate a plan centered around historical landmarks in the selected destination. The generation AI can also create an optimal schedule considering the user's travel style, budget, and length of stay. Furthermore, the generation unit can analyze the user's past travel history to generate optimal travel plans. For example, based on data from places visited and activities participated in in the past, it can suggest places and activities the user hasn't yet visited but might be interested in. This allows the generation unit to provide users with new discoveries and experiences. The generation unit also presents the generated travel plan to the user and provides an interface for the user to review and modify the plan. Users can provide feedback on the generated plan and customize it as needed. This allows the generation unit to provide a travel plan that fully meets the user's needs.

[0067] The service provider delivers VR experiences based on travel plans generated by the generation unit. These VR experiences include, but are not limited to, the type of experience and the means of delivery. For example, the service provider may offer VR experiences that include audio guides and interactive elements. Specifically, the service provider may offer virtual tours of user-selected travel destinations, providing users with an experience as if they were actually visiting the location. These VR experiences may include high-resolution video, 3D audio, and haptic feedback, allowing users to enjoy a realistic experience through sight, sound, and touch. Furthermore, the service provider can also provide features for enjoying virtual travel with friends and family. For example, the service provider may offer a feature that allows multiple users to share a trip in the same VR space, enabling them to communicate with each other in real time while enjoying the trip. This allows users to enjoy traveling with friends and family who are far away, deepening their bonds through the shared experience. Additionally, the service provider can continuously improve the content of the VR experience based on user feedback. For example, if a user gives a high rating to a particular location or activity, new content can be added based on that information. This allows the service provider to always provide the latest and most engaging VR experiences, improving user satisfaction.

[0068] The response unit responds to user questions and requests during the VR experience provided by the service provider. Responses include, but are not limited to, criteria for response timing and content. The response unit responds to user questions in real time, for example. Specifically, it can use natural language processing technology to respond to user questions. For example, if a user asks about a specific tourist attraction during the VR experience, the response unit provides detailed information about that attraction. The response unit can also adjust the content of the VR experience according to user requests. For example, if a user wants to see a particular place in more detail, the response unit can provide detailed images and information about that place. Furthermore, the response unit can continuously improve its responses based on user feedback. For example, if a user does not receive a satisfactory answer to a particular question, the response algorithm can be improved based on that feedback, increasing the accuracy of responses in subsequent sessions. This allows the response unit to respond quickly and accurately to user questions and requests, improving the quality of the VR experience. The response unit can also record the user's past question history for reference during subsequent VR experiences. This enables personalized responses tailored to the user's preferences and interests, providing a more satisfying experience.

[0069] The generation unit can generate customized travel plans based on the user's past behavioral data and preference information. For example, the generation unit can collect the user's past behavioral data and reflect it in the travel plan. For instance, it can customize the travel plan based on the user's visit history and purchase history. The generation unit can also collect the user's preference information and reflect it in the travel plan. For example, it can generate a travel plan based on the user's preferred travel style and activities of interest. Furthermore, the generation unit can analyze the user's preference information using natural language processing technology and reflect it in the travel plan. For example, it can analyze the user's past travel history and generate the optimal travel plan. This allows for the provision of more personalized travel plans based on the user's past behavioral data and preference information.

[0070] The service provider can offer VR experiences that include audio guides and interactive elements. For example, the service provider can provide information about tourist destinations using audio guides. For instance, the service provider can provide audio explanations of the history and highlights of the tourist destination. The service provider can also offer VR experiences that include interactive elements. For example, the service provider can allow users to interact with interactive objects as they explore the tourist destination. Furthermore, the service provider can provide a more realistic VR experience through interaction with the user. For example, the service provider can allow users to ask questions about the tourist destination and respond to those questions in real time. This allows for a more realistic VR experience by including audio guides and interactive elements.

[0071] The response unit can respond to user questions in real time. For example, if a user asks a question about a tourist destination, the response unit will answer it immediately. For instance, if a user asks, "How tall is the Eiffel Tower?", the response unit will provide the height of the Eiffel Tower and other relevant information. The response unit can also respond to user requests in real time. For example, if a user requests, "Please tell me which tourist destination I should visit next," the response unit will suggest a suitable destination. By responding to user questions in real time, it can immediately address any questions or requests that arise during travel.

[0072] The service provider can offer features that allow users to enjoy virtual travel with friends and family. For example, it can provide a feature that allows multiple users to share a trip in the same VR space. For instance, it can enable users to explore tourist destinations with friends and family and communicate in real time. The service provider can also provide an interface for users to enjoy virtual travel with other users. For example, it can enable users to share interactive elements when visiting tourist destinations with other users. This allows users to share travel experiences while maintaining social connections by enjoying virtual travel with friends and family.

[0073] The response unit can respond to user questions using natural language processing technology. For example, if a user asks a question about a tourist destination, the response unit will use natural language processing technology to provide appropriate information in response to that question. For instance, if a user asks, "Please tell me about the history of the Eiffel Tower," the response unit will use natural language processing technology to provide information about the history of the Eiffel Tower. The response unit can also respond to user requests using natural language processing technology. For example, if a user requests, "Please tell me what tourist destination I should visit next," the response unit will use natural language processing technology to suggest an appropriate tourist destination. In this way, using natural language processing technology allows for more natural and appropriate responses.

[0074] The reception desk can estimate the user's emotions and adjust its travel destination suggestions based on those emotions. For example, the reception desk can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For instance, if the user is relaxed, the reception desk will suggest relaxing tourist destinations. The reception desk can also record the user's voice and estimate their emotions using voice analysis technology. For example, if the user is excited, the reception desk will suggest active tourist destinations. Furthermore, the reception desk can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, if the user is tired, the reception desk will suggest quiet tourist destinations. By adjusting travel destination suggestions based on the user's emotions, a more appropriate destination can be suggested. Emotion estimation is achieved using emotion estimation functions, 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.

[0075] The reception desk can analyze the user's past travel destination selection history and present the most suitable options. For example, the reception desk can suggest similar tourist destinations based on the tourist destinations the user has visited in the past. For example, the reception desk can suggest highly-rated tourist destinations based on the user's ratings of tourist destinations they have visited in the past. The reception desk can also suggest tourist destinations that should be visited in the same season as the tourist destinations the user has visited in the past. For example, the reception desk can suggest the most suitable tourist destinations based on the seasonal information of tourist destinations the user has visited in the past. In this way, by analyzing the user's past travel destination selection history, more appropriate travel destinations can be suggested. Some or all of the above processing in the reception desk may be performed using AI, for example, or without using AI.

[0076] The reception desk can filter travel destinations based on the user's current health status and interests. For example, if the user is in good health, the reception desk will suggest active tourist destinations. For example, if the user is in poor health, the reception desk will suggest quiet tourist destinations. The reception desk can also suggest tourist destinations that the user might be interested in. For example, the reception desk will suggest the most suitable tourist destination based on the user's interests. This allows for the suggestion of more appropriate travel destinations by filtering based on the user's health status and interests. Some or all of the above processing in the reception desk may be performed using AI, for example, or without AI.

[0077] The reception desk can estimate the user's emotions and prioritize options based on those emotions. For example, the reception desk can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For instance, if the user is relaxed, the reception desk will prioritize suggesting relaxing tourist destinations. The reception desk can also record the user's voice and estimate their emotions using voice analysis technology. For example, if the user is excited, the reception desk will prioritize suggesting active tourist destinations. Furthermore, the reception desk can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, if the user is tired, the reception desk will prioritize suggesting quiet tourist destinations. This allows for the suggestion of more appropriate travel destinations by prioritizing options based on the user's emotions. Emotion estimation is achieved using emotion estimation functions, 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.

[0078] The reception desk can prioritize presenting highly relevant options when users select a travel destination, taking into account their geographical location. For example, the reception desk can prioritize presenting tourist destinations close to the user's current location. For example, the reception desk can prioritize presenting tourist destinations that are easily accessible from the user's current location. The reception desk can also prioritize presenting the most suitable tourist destination by considering the travel time from the user's current location. For example, the reception desk can suggest the most suitable tourist destination based on the travel time from the user's current location. In this way, by considering the user's geographical location, it is possible to suggest a more appropriate travel destination. Some or all of the above processing in the reception desk may be performed using AI, for example, or without using AI.

[0079] The reception desk can analyze the user's social media activity when selecting a travel destination and present relevant options. For example, the reception desk can prioritize tourist destinations that the user has shown interest in on social media. For example, the reception desk can prioritize tourist destinations that the user's social media friends have visited. The reception desk can also analyze the content of the user's social media posts and prioritize relevant tourist destinations. For example, the reception desk can suggest the most suitable tourist destination based on the content of the user's social media posts. In this way, by analyzing the user's social media activity, it is possible to suggest more appropriate travel destinations. Some or all of the above processing in the reception desk may be performed using AI, for example, or not using AI.

[0080] The generation unit can estimate the user's emotions and adjust the travel plan based on those emotions. For example, the generation unit can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For instance, if the user is relaxed, the generation unit will generate a travel plan that includes relaxing tourist destinations. The generation unit can also record the user's voice and estimate their emotions using voice analysis technology. For example, if the user is excited, the generation unit will generate a travel plan that includes active tourist destinations. Furthermore, the generation unit can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, if the user is tired, the generation unit will generate a travel plan that includes quiet tourist destinations. This allows for the provision of more appropriate travel plans by adjusting the content based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0081] The generation unit can customize travel plans by considering the user's past travel history and preferences. For example, the generation unit can generate travel plans that include similar tourist destinations based on the user's past visits. For example, the generation unit can generate travel plans that include tourist destinations of interest based on the user's preferences. The generation unit can also analyze the user's past travel history and generate travel plans that include the most suitable tourist destinations. For example, the generation unit can suggest the most suitable tourist destinations based on the user's past travel history. This allows for the provision of more appropriate travel plans by considering the user's past travel history and preferences. Some or all of the above-described processes in the generation unit may be performed using, for example, a generation AI, or without using a generation AI.

[0082] The generation unit can reflect the season and event information of the selected travel destination when generating a travel plan. For example, the generation unit generates a travel plan that includes tourist attractions suited to the season of the selected travel destination. For example, the generation unit generates a travel plan that includes events based on the event information of the selected travel destination. The generation unit can also generate the optimal travel plan by considering the season and event information of the selected travel destination. For example, the generation unit suggests the optimal tourist attractions based on the seasonal information of the selected travel destination. In this way, by reflecting the season and event information of the selected travel destination, a more appropriate travel plan can be provided. Some or all of the above processing in the generation unit may be performed using, for example, a generation AI, or without using a generation AI.

[0083] The generation unit can estimate the user's emotions and adjust the level of detail in the travel plan based on the estimated emotions. For example, the generation unit can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For example, if the user is relaxed, the generation unit will generate a detailed travel plan. The generation unit can also record the user's voice and estimate their emotions using voice analysis technology. For example, if the user is excited, the generation unit will generate a concise travel plan. Furthermore, the generation unit can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, if the user is tired, the generation unit will generate a concise travel plan. This allows for the provision of more appropriate travel plans by adjusting the level of detail in the travel plan based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0084] The generation unit can determine the priority of travel plans based on when the user submits them. For example, if the user submits an early plan, the generation unit will prioritize generating a detailed travel plan. For example, if the user submits a plan at the last minute, the generation unit will prioritize generating a concise travel plan. The generation unit can also prioritize generating the most suitable travel plan based on when the user submits it. For example, the generation unit will suggest the most suitable tourist destinations based on when the user submits it. By prioritizing plans based on when the user submits them, the generation unit can provide more appropriate travel plans. Some or all of the above processing in the generation unit may be performed using, for example, a generation AI, or without using a generation AI.

[0085] The generation unit can create a travel plan by referring to relevant literature and guidebook information for the selected travel destination. For example, the generation unit can generate a detailed travel plan based on relevant literature for the selected travel destination. For example, the generation unit can generate an optimal travel plan based on guidebook information for the selected travel destination. The generation unit can also generate a customized travel plan by referring to relevant literature and guidebook information for the selected travel destination. For example, the generation unit can suggest the best tourist destinations based on relevant literature for the selected travel destination. This allows for the provision of a more appropriate travel plan by referring to relevant literature and guidebook information for the selected travel destination. Some or all of the above processing in the generation unit may be performed using, for example, a generation AI, or without using a generation AI.

[0086] The service provider can estimate the user's emotions and adjust the content of the VR experience based on those emotions. For example, the service provider can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For instance, if the user is relaxed, the service provider can provide a relaxing VR experience. The service provider can also record the user's voice and estimate their emotions using voice analysis technology. For example, if the user is excited, the service provider can provide an active VR experience. Furthermore, the service provider can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, if the user is tired, the service provider can provide a quiet VR experience. By adjusting the content of the VR experience based on the user's emotions, a more appropriate VR 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.

[0087] The service provider can provide the optimal VR experience by referring to the user's past experience history when providing a VR experience. For example, the service provider can provide a similar VR experience based on the user's past VR experiences. For example, the service provider can analyze the user's past experience history and provide the optimal VR experience. The service provider can also provide a customized VR experience based on the user's past experience history. For example, the service provider can suggest the optimal tourist destination based on the user's past experience history. In this way, a more appropriate VR experience can be provided by referring to the user's past experience history. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI.

[0088] The service provider can reflect the latest information on the selected travel destination when providing a VR experience. For example, the service provider can provide the latest VR experience based on the latest information on the selected travel destination. For example, the service provider can provide a VR experience that includes events based on the latest event information on the selected travel destination. The service provider can also provide the optimal VR experience by reflecting the latest information on the selected travel destination. For example, the service provider can suggest the best tourist destinations based on the latest information on the selected travel destination. This allows for the provision of a more appropriate VR experience by reflecting the latest information on the selected travel destination. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI.

[0089] The service provider can estimate the user's emotions and prioritize VR experiences based on those emotions. For example, the service provider can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For instance, if the user is relaxed, the service provider will prioritize providing relaxing VR experiences. The service provider can also record the user's voice and estimate their emotions using voice analysis technology. For example, if the user is excited, the service provider will prioritize providing active VR experiences. Furthermore, the service provider can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, if the user is tired, the service provider will prioritize providing calm VR experiences. This allows for the provision of more appropriate VR experiences by prioritizing VR experiences based on the user's emotions. Emotion estimation is achieved using emotion estimation functions, 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.

[0090] The service provider can provide an optimal VR experience by considering the user's geographical location when providing a VR experience. For example, the service provider can provide a VR experience of a tourist destination close to the user's current location. For example, the service provider can provide a VR experience of a tourist destination that is easily accessible from the user's current location. The service provider can also provide an optimal VR experience of a tourist destination by considering the travel time from the user's current location. For example, the service provider can suggest an optimal tourist destination based on the travel time from the user's current location. In this way, a more appropriate VR experience can be provided by considering the user's geographical location. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI.

[0091] The service provider can analyze the user's social media activity when providing a VR experience and offer a relevant experience. For example, the service provider can offer a VR experience of a tourist destination that the user has shown interest in on social media. For example, the service provider can offer a VR experience of a tourist destination visited by the user's social media friends. The service provider can also analyze the content of the user's social media posts and offer a VR experience of a relevant tourist destination. For example, the service provider can suggest the most suitable tourist destination based on the content of the user's social media posts. In this way, by analyzing the user's social media activity, a more appropriate VR experience can be provided. Some or all of the above processing in the service provider may be performed using AI, for example, or without using AI.

[0092] The response unit can estimate the user's emotions and adjust its response based on those emotions. For example, the response unit can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. For instance, if the user is relaxed, the response unit will provide a relaxing response. The response unit can also record the user's voice and estimate their emotions using voice analysis technology. For example, if the user is excited, the response unit will provide an active response. Furthermore, the response unit can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. For example, if the user is tired, the response unit will provide a calm response. This allows for more appropriate responses by adjusting the response 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.

[0093] The response unit can provide the most appropriate response by referring to the user's past question history when responding. For example, the response unit can provide responses to similar questions based on the content of questions the user has asked in the past. For example, the response unit can analyze the user's past question history and provide the most appropriate response. The response unit can also provide customized responses based on the user's past question history. For example, the response unit can provide information on the most suitable tourist destinations based on the user's past question history. This allows for the provision of more appropriate responses by referring to the user's past question history. Some or all of the above processing in the response unit may be performed using AI, for example, or without using AI.

[0094] The response unit can reflect the latest information on the selected travel destination when responding. For example, the response unit provides the latest response based on the latest information on the selected travel destination. For example, the response unit provides a response regarding an event based on the latest event information on the selected travel destination. The response unit can also provide the most appropriate response by reflecting the latest information on the selected travel destination. For example, the response unit provides information on the most suitable tourist destination based on the latest information on the selected travel destination. This allows for the provision of a more appropriate response by reflecting the latest information on the selected travel destination. Some or all of the above processing in the response unit may be performed using AI, for example, or without using AI.

[0095] The response unit can estimate the user's emotions and determine the priority of responses based on the estimated emotions. For example, the response unit can capture the user's facial expressions with a camera and estimate emotions using an emotion estimation algorithm. For example, if the user is relaxed, the response unit will prioritize providing relaxing responses. The response unit can also record the user's voice and estimate emotions using voice analysis technology. For example, if the user is excited, the response unit will prioritize providing active responses. Furthermore, the response unit can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate emotions using an emotion estimation algorithm. For example, if the user is tired, the response unit will prioritize providing calm responses. This allows for the provision of more appropriate responses by determining the priority of responses based on the user's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) and multimodal generation AI.

[0096] The response unit can provide an optimal response by considering the user's geographical location information when responding. For example, the response unit can provide a response regarding tourist destinations close to the user's current location. For example, the response unit can provide a response regarding tourist destinations that are easily accessible from the user's current location. The response unit can also provide a response regarding optimal tourist destinations by considering the travel time from the user's current location. For example, the response unit can provide information about optimal tourist destinations based on the travel time from the user's current location. This allows for the provision of a more appropriate response by considering the user's geographical location information. Some or all of the above processing in the response unit may be performed using AI, for example, or without using AI.

[0097] The response unit can analyze the user's social media activity and provide relevant information when responding. For example, the response unit can provide responses regarding tourist destinations that the user has shown interest in on social media. For example, the response unit can provide responses regarding tourist destinations visited by the user's friends on social media. The response unit can also analyze the content of the user's social media posts and provide responses regarding relevant tourist destinations. For example, the response unit can provide information on the most suitable tourist destinations based on the content of the user's social media posts. This allows for the provision of more appropriate responses by analyzing the user's social media activity. Some or all of the above processing in the response unit may be performed using AI, for example, or without using AI.

[0098] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0099] The reception desk can monitor the user's health status and adjust travel destination suggestions accordingly. For example, it can measure the user's heart rate and blood pressure using sensors and suggest active tourist destinations if the user is in good health. Conversely, if the user is in poor health, it can suggest quieter tourist destinations. Furthermore, the reception desk can adjust the activities at the travel destination based on the user's health status. For example, if the user is in good health, it can suggest travel plans that include hiking and walking tours, while if the user is in poor health, it can suggest relaxing tourist destinations and activities. This allows the system to suggest the most suitable travel destination for the user based on their health condition.

[0100] The generation unit can estimate the user's emotions and adjust the travel plan based on those emotions. For example, the generation unit can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. If the user is relaxed, it generates a travel plan that includes relaxing tourist destinations. It can also record the user's voice and estimate their emotions using voice analysis technology. If the user is excited, it generates a travel plan that includes active tourist destinations. Furthermore, it can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. If the user is tired, it generates a travel plan that includes quiet tourist destinations. This allows for the provision of more appropriate travel plans by adjusting the content based on the user's emotions.

[0101] The service provider can provide a more personalized VR experience by referencing the user's past travel history. For example, based on data from tourist destinations the user has visited in the past, the service provider can offer a VR experience of a similar tourist destination. It can also analyze the user's past travel history and provide a VR experience that includes tourist destinations and activities that the user was particularly interested in. Furthermore, based on the user's past travel history, the service provider can suggest tourist destinations that the user has not yet visited but might be interested in. In this way, the service provider can leverage the user's past travel history to provide a more personalized VR experience.

[0102] The response unit can estimate the user's emotions and adjust its response based on those emotions. For example, the response unit can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. If the user is relaxed, it will provide a relaxing response. It can also record the user's voice and estimate their emotions using voice analysis technology. If the user is excited, it will provide an active response. Furthermore, it can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. If the user is tired, it will provide a calm response. By adjusting the response based on the user's emotions, it can provide a more appropriate response.

[0103] The service provider can analyze users' social media activity and provide relevant VR experiences. For example, it can provide VR experiences of tourist destinations that users have shown interest in on social media. It can also provide VR experiences of tourist destinations visited by the user's social media friends. Furthermore, it can analyze the content of users' social media posts and provide VR experiences of relevant tourist destinations. This allows for the provision of more personalized VR experiences by leveraging users' social media activity.

[0104] The reception desk can estimate the user's emotions and adjust travel destination suggestions based on those estimates. For example, the reception desk can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. If the user is relaxed, it will suggest relaxing tourist destinations. It can also record the user's voice and estimate their emotions using voice analysis technology. If the user is excited, it will suggest active tourist destinations. Furthermore, it can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. If the user is tired, it will suggest quiet tourist destinations. By adjusting travel destination suggestions based on the user's emotions, it can suggest more appropriate destinations.

[0105] The generation unit can create more personalized travel plans by considering the user's past travel history and preferences. For example, it can generate travel plans that include similar tourist destinations based on data of tourist destinations the user has visited in the past. It can also generate travel plans that include tourist destinations and activities of interest based on the user's preferences. Furthermore, it can analyze the user's past travel history and suggest tourist destinations that the user has not yet visited but might be interested in. In this way, it can provide more personalized travel plans by utilizing the user's past travel history and preferences.

[0106] The service provider can estimate the user's emotions and adjust the content of the VR experience based on those emotions. For example, the service provider can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. If the user is relaxed, it will provide a relaxing VR experience. It can also record the user's voice and estimate their emotions using voice analysis technology. If the user is excited, it will provide an active VR experience. Furthermore, it can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. If the user is tired, it will provide a quiet VR experience. In this way, by adjusting the content of the VR experience based on the user's emotions, a more appropriate VR experience can be provided.

[0107] The response unit can provide more appropriate responses by referring to the user's past question history. For example, the response unit can provide answers to similar questions based on what the user has asked in the past. It can also analyze the user's past question history and provide information about tourist destinations or activities that the user has been particularly interested in. Furthermore, based on the user's past question history, it can suggest information that the user has not yet asked about but might be interested in. In this way, the system can provide more appropriate responses by utilizing the user's past question history.

[0108] The service provider can estimate the user's emotions and prioritize VR experiences based on those emotions. For example, the service provider can capture the user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. If the user is relaxed, it will prioritize providing relaxing VR experiences. It can also record the user's voice and estimate their emotions using voice analysis technology. If the user is excited, it will prioritize providing active VR experiences. Furthermore, it can collect the user's biometric data (heart rate and skin electrical activity) with sensors and estimate their emotions using an emotion estimation algorithm. If the user is tired, it will prioritize providing quiet VR experiences. In this way, by prioritizing VR experiences based on the user's emotions, a more appropriate VR experience can be provided.

[0109] The following briefly describes the processing flow for example form 2.

[0110] Step 1: The reception desk accepts the user's travel destination selection. This selection may include, but is not limited to, the method of presenting options and the selection criteria. The reception desk may also provide an interface for the user to select a travel destination and collect travel destination information based on the user's selection. Step 2: The generation unit uses a generation AI to generate a travel plan based on the information received by the reception unit. The travel plan may include, but is not limited to, elements and generation algorithms included in the plan. The generation unit can also generate a customized travel plan based on user selections, or generate a travel plan based on the user's past behavioral data and preferences. Step 3: The provider delivers the VR experience based on the travel plan generated by the generator. The VR experience may include, but is not limited to, the type of experience and the means of delivery. The provider may also provide a VR experience that includes audio guides and interactive elements, and may offer features to enjoy virtual travel with friends and family. Step 4: The response unit responds to user questions and requests during the VR experience provided by the provider unit. Responses include, but are not limited to, criteria for response timing and content. The response unit can respond to user questions in real time and may also use natural language processing techniques to respond to user questions.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] Each of the multiple elements described above, including the reception unit, generation unit, provision unit, and response unit, is implemented in at least one of the smart device 14 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart device 14 and provides an interface for receiving the user's travel destination selection. The generation unit is implemented by the specific processing unit 290 of the data processing unit 12 and generates a travel plan using a generation AI. The provision unit is implemented by the control unit 46A of the smart device 14 and provides a VR experience based on the generated travel plan. The response unit is implemented by the specific processing unit 290 of the data processing unit 12 and responds in real time to the user's questions and requests during the VR experience. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

[0115] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] The microphone 238 receives voice signals from the user and accepts instructions from the user. 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.

[0120] 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).

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] Each of the multiple elements described above, including the reception unit, generation unit, provision unit, and response unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart glasses 214 and provides an interface for receiving the user's travel destination selection. The generation unit is implemented by the specific processing unit 290 of the data processing unit 12 and generates a travel plan using generation AI. The provision unit is implemented by the control unit 46A of the smart glasses 214 and provides a VR experience based on the generated travel plan. The response unit is implemented by the specific processing unit 290 of the data processing unit 12 and responds in real time to the user's questions and requests during the VR experience. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

[0131] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] The microphone 238 receives voice signals from the user and accepts instructions from the user. 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.

[0136] 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).

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.).

[0143] 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.

[0144] 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.

[0145] 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.

[0146] Each of the multiple elements described above, including the reception unit, generation unit, provision unit, and response unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the headset terminal 314 and provides an interface for receiving the user's travel destination selection. The generation unit is implemented by the specific processing unit 290 of the data processing unit 12 and generates a travel plan using a generation AI. The provision unit is implemented by the control unit 46A of the headset terminal 314 and provides a VR experience based on the generated travel plan. The response unit is implemented by the specific processing unit 290 of the data processing unit 12 and responds in real time to the user's questions and requests during the VR experience. 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.

[0147] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] The microphone 238 receives voice signals from the user and accepts instructions from the user. 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.

[0152] 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).

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.).

[0160] 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.

[0161] 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.

[0162] 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.

[0163] Each of the multiple elements described above, including the reception unit, generation unit, provision unit, and response unit, is implemented in at least one of the robot 414 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the robot 414 and provides an interface for receiving the user's travel destination selection. The generation unit is implemented by the specific processing unit 290 of the data processing unit 12 and generates a travel plan using a generation AI. The provision unit is implemented by the control unit 46A of the robot 414 and provides a VR experience based on the generated travel plan. The response unit is implemented by the specific processing unit 290 of the data processing unit 12 and responds in real time to the user's questions and requests during the VR experience. 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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."

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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.

[0182] (Note 1) A reception desk that accepts users' travel destination selections, A generation unit that generates a travel plan based on the information received by the reception unit, A provisioning unit that provides a VR experience based on the travel plan generated by the generation unit, The system includes a response unit that responds to user questions and requests during the VR experience provided by the aforementioned provision unit. A system characterized by the following features. (Note 2) The generating unit is Generate customized travel plans based on the user's past behavioral data and preferences. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned supply unit is, It provides a VR experience that includes audio guides and interactive elements. The system described in Appendix 1, characterized by the features described herein. (Note 4) The response unit is Respond to user questions in real time. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned supply unit is, It provides features for enjoying virtual travel with friends and family. The system described in Appendix 1, characterized by the features described herein. (Note 6) The response unit is Respond to user questions using natural language processing techniques. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned reception unit is It estimates the user's emotions and adjusts destination selection suggestions based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned reception unit is The system analyzes the user's past travel destination selection history and presents the most suitable options. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned reception unit is When selecting a travel destination, filtering is performed based on the user's current health status and interests. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned reception unit is It estimates the user's emotions and determines the priority of choices based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned reception unit is When selecting a travel destination, the system prioritizes and presents highly relevant options by considering the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned reception unit is When users select a travel destination, the system analyzes their social media activity and presents relevant options. The system described in Appendix 1, characterized by the features described herein. (Note 13) The generating unit is The system estimates the user's emotions and adjusts the travel plan based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 14) The generating unit is When generating travel plans, the system customizes them by taking into account the user's past travel history and preferences. The system described in Appendix 1, characterized by the features described herein. (Note 15) The generating unit is When generating a travel plan, the seasonal and event information for the selected travel destination will be reflected. The system described in Appendix 1, characterized by the features described herein. (Note 16) The generating unit is The system estimates the user's emotions and adjusts the level of detail in the travel plan based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 17) The generating unit is When generating travel plans, the priority of the plans is determined based on when the user submitted them. The system described in Appendix 1, characterized by the features described herein. (Note 18) The generating unit is When generating a travel plan, the plan is created by referring to relevant literature and guidebook information for the selected travel destination. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned supply unit is, It estimates the user's emotions and adjusts the VR experience based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned supply unit is, When providing a VR experience, we refer to the user's past experience history to provide the optimal experience. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned supply unit is, When providing a VR experience, the latest information on the selected travel destination will be reflected. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned supply unit is, It estimates the user's emotions and prioritizes the VR experience based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned supply unit is, When providing VR experiences, we take the user's geographical location into consideration to deliver the optimal experience. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned supply unit is, When providing VR experiences, we analyze users' social media activity to deliver relevant experiences. The system described in Appendix 1, characterized by the features described herein. (Note 25) The response unit is It estimates the user's emotions and adjusts the response based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 26) The response unit is When responding, the system refers to the user's past question history to provide the most appropriate response. The system described in Appendix 1, characterized by the features described herein. (Note 27) The response unit is The response will reflect the latest information on the selected travel destination. The system described in Appendix 1, characterized by the features described herein. (Note 28) The response unit is It estimates the user's emotions and determines the priority of responses based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 29) The response unit is When responding, the system provides the optimal response by taking into account the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 30) The response unit is When responding, the system analyzes the user's social media activity and provides relevant information. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0183] 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. A reception desk that accepts users' travel destination selections, A generation unit that generates a travel plan based on the information received by the reception unit, A provisioning unit that provides a VR experience based on the travel plan generated by the generation unit, The system includes a response unit that responds to user questions and requests during the VR experience provided by the aforementioned provision unit. A system characterized by the following features.

2. The generating unit is Generate customized travel plans based on the user's past behavioral data and preferences. The system according to feature 1.

3. The aforementioned supply unit is, It provides a VR experience that includes audio guides and interactive elements. The system according to feature 1.

4. The response unit is Respond to user questions in real time. The system according to feature 1.

5. The aforementioned supply unit is, It provides features for enjoying virtual travel with friends and family. The system according to feature 1.

6. The response unit is Respond to user questions using natural language processing techniques. The system according to feature 1.

7. The aforementioned reception unit is It estimates the user's emotions and adjusts destination selection suggestions based on those estimated emotions. The system according to feature 1.

8. The aforementioned reception unit is The system analyzes the user's past travel destination selection history and presents the most suitable options. The system according to feature 1.

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