system

Abstract

The system according to this embodiment aims to allow people with disabilities to check the accessibility and facilities of tourist destinations before traveling, and to prepare to enjoy their trip with peace of mind. [Solution] The system according to the embodiment comprises an input unit, an experience unit, and an information provision unit. The input unit allows the user to input travel information. The experience unit provides a virtual travel experience based on the information entered by the input unit. The information provision unit provides necessary information during the virtual experience provided by the experience unit.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, 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, people with physical disabilities have limited means to check the accessibility and facility conditions of tourist destinations before traveling, and there is a risk of feeling anxious.

[0005] The system according to the embodiment aims to enable people with physical disabilities to check the accessibility and facility conditions of tourist destinations before traveling and make preparations to enjoy the trip with confidence.

Means for Solving the Problems

[0006] The system according to this embodiment comprises an input unit, an experience unit, and an information provision unit. The input unit allows the user to input travel information. The experience unit provides a virtual travel experience based on the information entered by the input unit. The information provision unit provides necessary information during the virtual experience provided by the experience unit. [Effects of the Invention]

[0007] The system according to this embodiment allows people with disabilities to check the accessibility and facilities of tourist destinations before traveling, and to prepare to enjoy their trip with peace of mind. [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, etc. The communication I / F controls communication between multiple 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 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 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 preview travel system according to an embodiment of the present invention is a system that allows people with disabilities to experience a pre-planned travel course using VR technology. This system allows users to check the accessibility and facilities of tourist destinations from their homes, thereby alleviating anxiety about the actual trip. For example, when a user plans a trip, they input information such as the tourist destinations and accommodations they wish to visit. Next, VR technology is used to provide a virtual travel experience based on the input information. In this virtual experience, users can check the accessibility and facilities of tourist destinations in detail. For example, they can check whether wheelchair access is possible and whether there are barrier-free toilets. Furthermore, through the virtual experience, users can make the necessary preparations for the actual trip. For example, they can check necessary items to bring, means of transportation, and on-site support systems. This helps to alleviate anxiety before the trip and allows users to enjoy their trip with peace of mind. This system is beneficial not only for people with disabilities but also for all people who feel anxious about traveling, such as the elderly and first-time travelers. By using virtual preview travel, travel planning becomes smoother and the enjoyment of travel increases. Thus, the virtual preview travel system allows users to check the accessibility and facilities of tourist destinations from their homes, thereby alleviating anxiety about the actual trip.

[0029] The virtual preview travel system according to the embodiment comprises an input unit, an experience unit, and an information provision unit. The input unit allows the user to input travel information. Travel information includes, but is not limited to, destinations, dates, budget, and activities of interest. The input unit can, for example, allow the user to input information about tourist attractions and accommodations they wish to visit. The experience unit provides a virtual travel experience based on the information entered by the input unit. The virtual travel experience includes, but is not limited to, 3D simulations and the use of VR headsets. The experience unit provides a virtual travel experience based on the information entered by the user, for example, using VR technology. The information provision unit provides necessary information during the virtual experience provided by the experience unit. Necessary information includes, but is not limited to, detailed information about tourist attractions, transportation, and accommodations. The information provision unit provides necessary information through, for example, an information panel displayed during the virtual experience. Thus, the virtual preview travel system according to the embodiment allows the user to input travel information and obtain necessary information through a virtual travel experience.

[0030] The experience section includes a video viewing section for viewing footage shot using a 360-degree camera or drone. The video viewing section allows users to view footage shot using a 360-degree camera or drone. 360-degree cameras include, but are not limited to, specific manufacturers and models. Drones include, but are not limited to, specific manufacturers and models. The video viewing section can view footage shot using a 360-degree camera. It can also view footage shot using a drone. This enables a realistic virtual experience through viewing footage from 360-degree cameras and drones.

[0031] The Experience section includes a Customization section that provides customized virtual experiences using AI technology. The Customization section provides customized virtual experiences using AI technology. AI technology includes, but is not limited to, machine learning algorithms and natural language processing techniques. For example, the Customization section can provide user-specific customized virtual experiences using machine learning algorithms. Furthermore, the Customization section can also provide user-specific customized virtual experiences using natural language processing techniques. Thus, by using AI technology, user-specific customized virtual experiences are provided.

[0032] The information provision unit includes an information panel unit that provides necessary information through information panels displayed during the virtual experience. The information panel unit provides necessary information through information panels displayed during the virtual experience. The information panels include, for example, text information, images, and videos, but are not limited to these examples. The information panel unit can provide, for example, an information panel that displays text information. It can also provide an information panel that displays images. Furthermore, it can also provide an information panel that displays videos. In this way, by providing necessary information through the information panels, users can obtain the information they need during the virtual experience.

[0033] The input unit can analyze the user's past travel history and suggest the optimal input method. For example, it can automatically display tourist destinations the user has visited in the past as suggestions. It can also prioritize suggesting input methods the user has used in the past (voice, text, etc.). Furthermore, it can predict and suggest tourist destinations related to specific seasons or events based on the user's past travel history. In this way, by analyzing the user's past travel history, the system can suggest the optimal input method and streamline the input process. Past travel history includes, for example, past travel destinations, dates, and activities. Suggestions for appropriate input methods include, for example, optimizing the input form and suggesting voice input.

[0034] The input section can customize input fields based on the user's current health status and special needs during input. For example, if the user uses a wheelchair, the input section will prioritize displaying barrier-free tourist destinations. It can also suggest allergy-friendly restaurants if the user has specific allergies. Furthermore, if the user is elderly, it can suggest sightseeing routes with minimal movement. This allows for the provision of information tailored to the user by customizing input fields according to their health status and special needs. Health status assessments include, for example, medical data and self-reports. Special needs assessments include, for example, allergy information and physical limitations.

[0035] The input section can prioritize inputting highly relevant travel information based on the user's geographical location. For example, the input section can automatically display tourist destinations near the user's current location as suggestions. Furthermore, if the user is in a specific region, the input section can prioritize displaying tourist information for that region. Also, if the user is in a travel destination region, the input section can provide the latest tourist information for that region. This allows the system to prioritize inputting highly relevant travel information by considering the user's geographical location. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant travel information can include, for example, information on nearby tourist destinations and events.

[0036] The input section can analyze the user's social media activity during input and automatically input relevant travel information. For example, the input section can automatically display travel destinations that the user has shared on social media as suggestions. It can also prioritize displaying information about tourist destinations that the user follows on social media. Furthermore, it can automatically input information about tourist destinations that the user has "liked" on social media. This allows for the automatic input of relevant travel information by analyzing the user's social media activity, thereby streamlining the input process. Social media activity analysis includes, for example, post content, number of likes, and number of followers. Relevant travel information includes, for example, information related to past travel destinations and activities of interest.

[0037] The Experience Department can provide the optimal virtual experience by referencing the user's past travel experiences during the experience. For example, the Experience Department can provide relevant virtual experiences based on tourist destinations the user has visited in the past. It can also suggest preferred tourist spots based on the user's past travel experiences. Furthermore, the Experience Department can analyze the user's past travel experiences and provide the most interesting virtual experience. This allows for the provision of the optimal virtual experience by referencing the user's past travel experiences. Past travel experiences include, for example, destinations, dates, and activities. Providing the optimal virtual experience includes, for example, experience content and customization methods based on the user's interests.

[0038] The Experience Department can customize the experience content based on the user's current interests. For example, if a user is interested in nature, the Experience Department can provide a virtual experience centered on natural landscapes. Alternatively, if a user is interested in history, the Experience Department can provide a virtual experience visiting historical sites. Furthermore, if a user is interested in food culture, the Experience Department can provide a virtual experience introducing local cuisine. This allows for a more engaging experience by customizing the content based on the user's current interests. Current interests can be obtained, for example, from survey results or social media posts. Customizing the experience content can include, for example, adding activities of interest or removing unnecessary content.

[0039] The experience section can prioritize providing highly relevant experiences by considering the user's geographical location during the experience. For example, the experience section can provide a virtual experience of a tourist destination near the user's current location. It can also prioritize tourist attractions in a specific region if the user is in that region. Furthermore, if the user is in a travel destination region, it can provide the latest tourist information for that region. This allows for the prioritization of highly relevant experiences by considering the user's geographical location. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant experiences include, for example, information on nearby tourist attractions and events.

[0040] The Experience Department can analyze a user's social media activity during an experience and suggest relevant experiences. For example, the Experience Department can provide a virtual experience of a tourist destination that the user has shared on social media. It can also provide a virtual experience of a tourist destination that the user follows on social media. Furthermore, it can provide a virtual experience of a tourist destination that the user has "liked" on social media. By analyzing the user's social media activity, it is possible to suggest relevant experiences and improve the quality of the experience. Social media activity analysis includes, for example, the content of posts, the number of likes, and the number of followers. Relevant experiences include, for example, experiences related to past travel destinations or activities of interest.

[0041] The information provision department can provide optimal information by referring to the user's past information usage history when providing information. For example, the information provision department can provide relevant information based on information the user has used in the past. Furthermore, the information provision department can suggest information the user might like based on their past information usage history. It can also analyze the user's past information usage history and provide the information that is most interesting to them. This allows the information provision department to provide optimal information and improve the quality of information provision by referring to the user's past information usage history. Past information usage history includes, for example, previously viewed information and search history. Providing optimal information includes, for example, information based on the user's interests and methods of customization.

[0042] The information provider can customize the information content based on the user's current needs when providing information. For example, if a user needs accessibility information, the information provider can provide information on accessible tourist destinations. Similarly, if a user needs information on restaurants, the information provider can provide information on allergy-friendly restaurants. Furthermore, if a user needs information on transportation, the information provider can provide information on wheelchair-accessible transportation options. This allows for the provision of more relevant information by customizing the content based on the user's current needs. Current needs can be obtained, for example, from survey results or social media posts. Customizing the information content can include, for example, adding information of interest or removing unnecessary information.

[0043] The information provider can prioritize providing highly relevant information by considering the user's geographical location. For example, the information provider can automatically display information about tourist destinations near the user's current location as a suggestion. Furthermore, if the user is in a specific region, the information provider can prioritize displaying tourist information for that region. Also, if the user is in a travel destination region, the information provider can provide the latest tourist information for that region. This allows for the prioritization of highly relevant information by considering the user's geographical location. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant information includes, for example, information about nearby tourist destinations and events.

[0044] The information provision department can analyze users' social media activity and provide relevant information when providing information. For example, the information provision department can provide information on tourist destinations that users have shared on social media. It can also provide information on tourist destinations that users follow on social media. Furthermore, it can provide information on tourist destinations that users have "liked" on social media. By analyzing users' social media activity, the information provision department can provide relevant information and improve the quality of information provision. Social media activity analysis includes, for example, the content of posts, the number of likes, and the number of followers. Relevant information includes, for example, information related to past travel destinations and activities of interest.

[0045] The video playback unit can provide the most suitable video by referring to the user's past viewing history when they are watching a video. For example, the video playback unit can provide relevant videos based on videos the user has watched in the past. It can also suggest videos the user might like based on their past viewing history. Furthermore, the video playback unit can analyze the user's past viewing history and provide the most interesting videos. In this way, by referring to the user's past viewing history, the system can provide the most suitable video and improve the video viewing experience. Past viewing history includes, for example, videos previously watched and viewing time. Providing the most suitable video includes, for example, videos based on the user's interests and customization methods.

[0046] The video viewing section can customize video content based on the user's current interests and preferences during viewing. For example, if the user is interested in nature, the video viewing section can provide videos focusing on natural landscapes. Similarly, if the user is interested in history, the video viewing section can provide videos showcasing historical sites. Furthermore, if the user is interested in food culture, the video viewing section can provide videos introducing local cuisine. By customizing video content based on the user's current interests, a more engaging viewing experience can be provided. Current interests and preferences can be acquired through methods such as survey results and social media posts. Customizing video content can include adding scenes of interest or removing unwanted scenes.

[0047] The video viewing unit can prioritize providing highly relevant videos by considering the user's geographical location information during video viewing. For example, the video viewing unit can provide videos of tourist destinations near the user's current location. Furthermore, if the user is in a specific region, the video viewing unit can prioritize providing videos of tourist attractions in that region. Also, if the user is in a travel destination, the video viewing unit can provide the latest tourist information for that region via video. This allows for the prioritization of highly relevant videos by considering the user's geographical location information. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant videos include, for example, information on nearby tourist destinations and events.

[0048] The video viewing unit can analyze the user's social media activity while they are watching a video and suggest relevant videos. For example, the unit can provide videos of tourist destinations that the user has shared on social media. It can also provide videos of tourist destinations that the user follows on social media. Furthermore, it can provide videos of tourist destinations that the user has "liked" on social media. By analyzing the user's social media activity, it can suggest relevant videos and improve the video viewing experience. Social media activity analysis includes, for example, the content of posts, the number of likes, and the number of followers. Relevant videos include, for example, videos related to past travel destinations or activities of interest.

[0049] The customization section can provide optimal customizations by referring to the user's past customization history during the customization process. For example, the customization section can provide relevant customizations based on the user's past customizations. It can also suggest preferred customizations based on the user's past customization history. Furthermore, the customization section can analyze the user's past customization history and provide the most interesting customizations. This allows for the provision of optimal customizations and an improved customization experience by referring to the user's past customization history. Past customization history includes, for example, the content and frequency of past customizations. Providing optimal customizations includes, for example, customizations based on the user's interests and customization methods.

[0050] The customization section can modify the customization content based on the user's current needs during the customization process. For example, if the user needs accessibility information, the customization section can provide information on accessible tourist destinations. It can also provide information on allergy-friendly restaurants if the user needs dining information, or wheelchair-accessible transportation if the user needs transportation information. This allows for a more appropriate customized experience by modifying the customization content based on the user's current needs. Current needs can be obtained, for example, from survey results or social media posts. Modifications to the customization content can include adding content of interest or removing content that is no longer needed.

[0051] The customization section can prioritize providing highly relevant customizations by considering the user's geographical location during the customization process. For example, the customization section can provide customizations for tourist destinations near the user's current location. It can also prioritize providing customizations for tourist attractions in a specific region if the user is in that region. Furthermore, if the user is in a travel destination region, the customization section can provide the latest tourist information for that region. This allows for the prioritization of highly relevant customizations by considering the user's geographical location. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant customizations include, for example, information on nearby tourist attractions and events.

[0052] The customization department can analyze the user's social media activity during the customization process and suggest relevant customizations. For example, the customization department can provide customizations of tourist destinations that the user has shared on social media. It can also provide customizations of tourist destinations that the user follows on social media. Furthermore, it can provide customizations of tourist destinations that the user has "liked" on social media. By analyzing the user's social media activity, it is possible to suggest relevant customizations and improve the customization experience. Social media activity analysis includes, for example, the content of posts, the number of likes, and the number of followers. Relevant customizations include, for example, customizations related to past travel destinations or activities of interest.

[0053] The information panel can provide optimal information by referring to the user's past information usage history when displaying the information panel. For example, the information panel can provide relevant information based on information the user has used in the past. It can also suggest preferred information based on the user's past information usage history. Furthermore, it can analyze the user's past information usage history and provide the information that is most of interest to the user. This allows for the provision of optimal information and improves the quality of information provision by referring to the user's past information usage history. Past information usage history includes, for example, previously viewed information and search history. Providing optimal information includes, for example, information based on the user's interests and methods for customization.

[0054] The information panel can customize the information content based on the user's current needs when the information panel is displayed. For example, if the user needs accessibility information, the information panel can provide information on accessible tourist destinations. It can also provide information on allergy-friendly restaurants if the user needs dining information, or wheelchair-accessible transportation if the user needs transportation information. This allows for the provision of more appropriate information by customizing the information content based on the user's current needs. Current needs can be obtained, for example, from survey results or social media posts. Customizing the information content can include, for example, adding information of interest or removing unnecessary information.

[0055] The information panel can prioritize providing highly relevant information by considering the user's geographical location when displaying the information panel. For example, the information panel can automatically display information about tourist destinations near the user's current location as suggestions. Furthermore, if the user is in a specific region, the information panel can prioritize displaying tourist information for that region. Also, if the user is in a travel destination region, the information panel can provide the latest tourist information for that region. This allows for the prioritization of highly relevant information by considering the user's geographical location. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant information can include, for example, information about nearby tourist destinations and events.

[0056] The information panel can analyze the user's social media activity and provide relevant information when displaying the information panel. For example, the information panel can provide information on tourist destinations that the user has shared on social media. It can also provide information on tourist destinations that the user follows on social media. Furthermore, it can provide information on tourist destinations that the user has "liked" on social media. By analyzing the user's social media activity, it is possible to provide relevant information and improve the quality of information provision. Social media activity analysis includes, for example, the content of posts, the number of likes, and the number of followers. Relevant information includes, for example, information related to past travel destinations and activities of interest.

[0057] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0058] The input unit can analyze the user's past travel history and suggest the optimal input method. For example, it can automatically display tourist destinations the user has visited in the past as suggestions. The input unit can also prioritize suggesting input methods the user has used in the past (voice, text, etc.). Furthermore, the input unit can predict and suggest tourist destinations related to specific seasons or events based on the user's past travel history. This allows for the suggestion of the optimal input method and streamlines the input process by analyzing the user's past travel history. Past travel history includes, for example, past destinations, dates, and activities. Suggestions for appropriate input methods include, for example, optimizing the input form and suggesting voice input.

[0059] The experience section can customize the content of the experience based on the user's current interests. For example, if the user is interested in nature, a virtual experience centered on natural landscapes can be provided. If the user is interested in history, a virtual experience visiting historical sites can be provided. Furthermore, if the user is interested in food culture, a virtual experience introducing local cuisine can be provided. In this way, a more interesting experience can be provided by customizing the content based on the user's current interests. Current interests can be obtained, for example, from survey results and social media posts. Customizing the experience content can include, for example, adding activities of interest or removing unnecessary content.

[0060] The input section can customize input fields based on the user's current health status and special needs during input. For example, if the user uses a wheelchair, barrier-free tourist destinations will be prioritized. If the user has specific allergies, allergy-friendly restaurants can be suggested. Furthermore, if the user is elderly, sightseeing routes with minimal movement can be suggested. This allows for the provision of information tailored to the user by customizing input fields according to their health status and special needs. Health status assessments include, for example, medical data and self-reports. Special needs acquisition includes, for example, allergy information and physical limitations.

[0061] The experience department can provide the optimal virtual experience by referencing the user's past travel experiences during the experience. For example, it can provide relevant virtual experiences based on tourist destinations the user has visited in the past. It can also suggest tourist spots the user might like based on their past travel experiences. Furthermore, it can analyze the user's past travel experiences and provide the virtual experience that will be most interesting to them. In this way, the optimal virtual experience can be provided by referencing the user's past travel experiences. Past travel experiences include, for example, destinations, dates, and activities. Providing the optimal virtual experience includes, for example, experience content and customization methods based on the user's interests.

[0062] The information provision department can provide the most relevant information by referring to the user's past information usage history. For example, it can provide relevant information based on information the user has used in the past. It can also suggest information the user might like based on their past information usage history. Furthermore, it can analyze the user's past information usage history and provide the information that is most likely to interest them. In this way, by referring to the user's past information usage history, the quality of information provision can be improved by providing the most relevant information. Past information usage history includes, for example, information previously viewed and search history. Providing the most relevant information includes, for example, information based on the user's interests and methods of customization.

[0063] The video viewing unit can provide the most suitable video by referring to the user's past viewing history when they are watching a video. For example, it can provide related videos based on videos the user has watched in the past. It can also suggest videos the user might like based on their past viewing history. Furthermore, it can analyze the user's past viewing history and provide the most interesting videos. In this way, by referring to the user's past viewing history, the system can provide the most suitable video and improve the video viewing experience. Past viewing history includes, for example, videos previously watched and viewing time. Providing the most suitable video includes, for example, videos based on the user's interests and customization methods.

[0064] The customization section can provide optimal customizations by referring to the user's past customization history during the customization process. For example, it can provide relevant customizations based on the user's past customizations. It can also suggest preferred customizations based on the user's past customization history. Furthermore, it can analyze the user's past customization history and provide the customizations that will interest them most. In this way, by referring to the user's past customization history, optimal customizations can be provided, improving the customization experience. Past customization history includes, for example, the content and frequency of past customizations. Providing optimal customizations includes, for example, customizations based on the user's interests and customization methods.

[0065] The following briefly describes the processing flow for example form 1.

[0066] Step 1: The input section allows the user to enter travel information. This information includes, for example, destination, dates, budget, and activities of interest. The user can enter information about tourist attractions and accommodations they wish to visit. Step 2: The experience section provides a virtual travel experience based on the information entered by the input section. The virtual travel experience may include, for example, 3D simulation or the use of a VR headset. The experience section uses VR technology to provide a virtual travel experience based on the information entered by the user. Step 3: The Information Department provides the necessary information during the virtual experience provided by the Experience Department. This necessary information includes, for example, detailed information about tourist attractions, transportation options, and accommodations. The Information Department provides the necessary information through information panels displayed during the virtual experience.

[0067] (Example of form 2) The virtual preview travel system according to an embodiment of the present invention is a system that allows people with disabilities to experience a pre-planned travel course using VR technology. This system allows users to check the accessibility and facilities of tourist destinations from their homes, thereby alleviating anxiety about the actual trip. For example, when a user plans a trip, they input information such as the tourist destinations and accommodations they wish to visit. Next, VR technology is used to provide a virtual travel experience based on the input information. In this virtual experience, users can check the accessibility and facilities of tourist destinations in detail. For example, they can check whether wheelchair access is possible and whether there are barrier-free toilets. Furthermore, through the virtual experience, users can make the necessary preparations for the actual trip. For example, they can check necessary items to bring, means of transportation, and on-site support systems. This helps to alleviate anxiety before the trip and allows users to enjoy their trip with peace of mind. This system is beneficial not only for people with disabilities but also for all people who feel anxious about traveling, such as the elderly and first-time travelers. By using virtual preview travel, travel planning becomes smoother and the enjoyment of travel increases. Thus, the virtual preview travel system allows users to check the accessibility and facilities of tourist destinations from their homes, thereby alleviating anxiety about the actual trip.

[0068] The virtual preview travel system according to the embodiment comprises an input unit, an experience unit, and an information provision unit. The input unit allows the user to input travel information. Travel information includes, but is not limited to, destinations, dates, budget, and activities of interest. The input unit can, for example, allow the user to input information about tourist attractions and accommodations they wish to visit. The experience unit provides a virtual travel experience based on the information entered by the input unit. The virtual travel experience includes, but is not limited to, 3D simulations and the use of VR headsets. The experience unit provides a virtual travel experience based on the information entered by the user, for example, using VR technology. The information provision unit provides necessary information during the virtual experience provided by the experience unit. Necessary information includes, but is not limited to, detailed information about tourist attractions, transportation, and accommodations. The information provision unit provides necessary information through, for example, an information panel displayed during the virtual experience. Thus, the virtual preview travel system according to the embodiment allows the user to input travel information and obtain necessary information through a virtual travel experience.

[0069] The experience section includes a video viewing section for viewing footage shot using a 360-degree camera or drone. The video viewing section allows users to view footage shot using a 360-degree camera or drone. 360-degree cameras include, but are not limited to, specific manufacturers and models. Drones include, but are not limited to, specific manufacturers and models. The video viewing section can view footage shot using a 360-degree camera. It can also view footage shot using a drone. This enables a realistic virtual experience through viewing footage from 360-degree cameras and drones.

[0070] The Experience section includes a Customization section that provides customized virtual experiences using AI technology. The Customization section provides customized virtual experiences using AI technology. AI technology includes, but is not limited to, machine learning algorithms and natural language processing techniques. For example, the Customization section can provide user-specific customized virtual experiences using machine learning algorithms. Furthermore, the Customization section can also provide user-specific customized virtual experiences using natural language processing techniques. Thus, by using AI technology, user-specific customized virtual experiences are provided.

[0071] The information provision unit includes an information panel unit that provides necessary information through information panels displayed during the virtual experience. The information panel unit provides necessary information through information panels displayed during the virtual experience. The information panels include, for example, text information, images, and videos, but are not limited to these examples. The information panel unit can provide, for example, an information panel that displays text information. It can also provide an information panel that displays images. Furthermore, it can also provide an information panel that displays videos. In this way, by providing necessary information through the information panels, users can obtain the information they need during the virtual experience.

[0072] The input unit can estimate the user's emotions and adjust the design of the input interface according to the estimated emotions. For example, if the user is tense, the input unit can provide an interface with calming colors to reduce visual stress. Conversely, if the user is enjoying themselves, for example, the input unit can provide an interface with bright colors to make the input process more enjoyable. Furthermore, if the user is tired, for example, the input unit can provide a simple and highly visible interface to facilitate the input process. In this way, by adjusting the input interface design according to the user's emotions, user stress can be reduced and the input process can be made more enjoyable. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjustments to the input interface design include, for example, changes in color and layout.

[0073] The input unit can analyze the user's past travel history and suggest the optimal input method. For example, it can automatically display tourist destinations the user has visited in the past as suggestions. It can also prioritize suggesting input methods the user has used in the past (voice, text, etc.). Furthermore, it can predict and suggest tourist destinations related to specific seasons or events based on the user's past travel history. In this way, by analyzing the user's past travel history, the system can suggest the optimal input method and streamline the input process. Past travel history includes, for example, past travel destinations, dates, and activities. Suggestions for appropriate input methods include, for example, optimizing the input form and suggesting voice input.

[0074] The input section can customize input fields based on the user's current health status and special needs during input. For example, if the user uses a wheelchair, the input section will prioritize displaying barrier-free tourist destinations. It can also suggest allergy-friendly restaurants if the user has specific allergies. Furthermore, if the user is elderly, it can suggest sightseeing routes with minimal movement. This allows for the provision of information tailored to the user by customizing input fields according to their health status and special needs. Health status assessments include, for example, medical data and self-reports. Special needs assessments include, for example, allergy information and physical limitations.

[0075] The input unit can estimate the user's emotions and prioritize input items based on those emotions. For example, if the user is nervous, the input unit can display important input items first and simplify the process. Alternatively, if the user is relaxed, the input unit can provide detailed input items and suggest customizable input methods. Furthermore, if the user is in a hurry, the input unit can prioritize displaying only the minimum necessary input items. This allows for input tailored to the user's situation by prioritizing input items according to their emotions. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Factors such as importance and urgency are used to determine the priority of input items.

[0076] The input section can prioritize inputting highly relevant travel information based on the user's geographical location. For example, the input section can automatically display tourist destinations near the user's current location as suggestions. Furthermore, if the user is in a specific region, the input section can prioritize displaying tourist information for that region. Also, if the user is in a travel destination region, the input section can provide the latest tourist information for that region. This allows the system to prioritize inputting highly relevant travel information by considering the user's geographical location. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant travel information can include, for example, information on nearby tourist destinations and events.

[0077] The input section can analyze the user's social media activity during input and automatically input relevant travel information. For example, the input section can automatically display travel destinations that the user has shared on social media as suggestions. It can also prioritize displaying information about tourist destinations that the user follows on social media. Furthermore, it can automatically input information about tourist destinations that the user has "liked" on social media. This allows for the automatic input of relevant travel information by analyzing the user's social media activity, thereby streamlining the input process. Social media activity analysis includes, for example, post content, number of likes, and number of followers. Relevant travel information includes, for example, information related to past travel destinations and activities of interest.

[0078] The experience unit can estimate the user's emotions and adjust the virtual experience scenario based on those emotions. For example, if the user is relaxed, the experience unit can provide a virtual experience that progresses at a leisurely pace. Alternatively, if the user is in a hurry, the experience unit can provide a virtual experience that takes them to major tourist spots in a short amount of time. Furthermore, if the user is excited, the experience unit can provide a virtual experience with visually stimulating effects. By adjusting the virtual experience scenario according to the user's emotions, a more appropriate experience can be provided. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjusting the virtual experience scenario includes, for example, scenario branching and event trigger conditions.

[0079] The Experience Department can provide the optimal virtual experience by referencing the user's past travel experiences during the experience. For example, the Experience Department can provide relevant virtual experiences based on tourist destinations the user has visited in the past. It can also suggest preferred tourist spots based on the user's past travel experiences. Furthermore, the Experience Department can analyze the user's past travel experiences and provide the most interesting virtual experience. This allows for the provision of the optimal virtual experience by referencing the user's past travel experiences. Past travel experiences include, for example, destinations, dates, and activities. Providing the optimal virtual experience includes, for example, experience content and customization methods based on the user's interests.

[0080] The Experience Department can customize the experience content based on the user's current interests. For example, if a user is interested in nature, the Experience Department can provide a virtual experience centered on natural landscapes. Alternatively, if a user is interested in history, the Experience Department can provide a virtual experience visiting historical sites. Furthermore, if a user is interested in food culture, the Experience Department can provide a virtual experience introducing local cuisine. This allows for a more engaging experience by customizing the content based on the user's current interests. Current interests can be obtained, for example, from survey results or social media posts. Customizing the experience content can include, for example, adding activities of interest or removing unnecessary content.

[0081] The experience unit can estimate the user's emotions and adjust the order of the experience based on those emotions. For example, if the user is feeling nervous, the unit can start the experience with relaxing attractions. Alternatively, if the user is relaxed, the unit can start with interesting attractions. Furthermore, if the user is in a hurry, the unit can prioritize the main attractions. This allows for a more appropriate experience by adjusting the order of the experience according to the user's emotions. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjusting the order of the experience includes, for example, changing the order based on the user's interests and optimizing the flow of the experience.

[0082] The experience section can prioritize providing highly relevant experiences by considering the user's geographical location during the experience. For example, the experience section can provide a virtual experience of a tourist destination near the user's current location. It can also prioritize tourist attractions in a specific region if the user is in that region. Furthermore, if the user is in a travel destination region, it can provide the latest tourist information for that region. This allows for the prioritization of highly relevant experiences by considering the user's geographical location. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant experiences include, for example, information on nearby tourist attractions and events.

[0083] The Experience Department can analyze a user's social media activity during an experience and suggest relevant experiences. For example, the Experience Department can provide a virtual experience of a tourist destination that the user has shared on social media. It can also provide a virtual experience of a tourist destination that the user follows on social media. Furthermore, it can provide a virtual experience of a tourist destination that the user has "liked" on social media. By analyzing the user's social media activity, it is possible to suggest relevant experiences and improve the quality of the experience. Social media activity analysis includes, for example, the content of posts, the number of likes, and the number of followers. Relevant experiences include, for example, experiences related to past travel destinations or activities of interest.

[0084] The information delivery unit can estimate the user's emotions and adjust the way information is displayed based on those emotions. For example, if the user is stressed, the information delivery unit can provide a simple and highly visible display method. Alternatively, if the user is relaxed, it can provide a display method that includes detailed information. Furthermore, if the user is in a hurry, it can provide a display method that focuses on the essentials. This allows for information to be presented in a way that is easy for the user to understand by adjusting the display method according to the user's emotions. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjustments to the information display method include, for example, changing font size, color, and layout.

[0085] The information provision department can provide optimal information by referring to the user's past information usage history when providing information. For example, the information provision department can provide relevant information based on information the user has used in the past. Furthermore, the information provision department can suggest information the user might like based on their past information usage history. It can also analyze the user's past information usage history and provide the information that is most interesting to them. This allows the information provision department to provide optimal information and improve the quality of information provision by referring to the user's past information usage history. Past information usage history includes, for example, previously viewed information and search history. Providing optimal information includes, for example, information based on the user's interests and methods of customization.

[0086] The information provider can customize the information content based on the user's current needs when providing information. For example, if a user needs accessibility information, the information provider can provide information on accessible tourist destinations. Similarly, if a user needs information on restaurants, the information provider can provide information on allergy-friendly restaurants. Furthermore, if a user needs information on transportation, the information provider can provide information on wheelchair-accessible transportation options. This allows for the provision of more relevant information by customizing the content based on the user's current needs. Current needs can be obtained, for example, from survey results or social media posts. Customizing the information content can include, for example, adding information of interest or removing unnecessary information.

[0087] The information delivery unit can estimate the user's emotions and prioritize information based on those emotions. For example, if the user is stressed, the information delivery unit will display important information first and simplify the process. Alternatively, if the user is relaxed, the information delivery unit can provide detailed information and suggest customizable options. Furthermore, if the user is in a hurry, the information delivery unit can prioritize displaying minimal information. This allows the system to prioritize information important to the user by determining the priority of information according to their emotions. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Prioritizing information may include factors such as importance and urgency.

[0088] The information provider can prioritize providing highly relevant information by considering the user's geographical location. For example, the information provider can automatically display information about tourist destinations near the user's current location as a suggestion. Furthermore, if the user is in a specific region, the information provider can prioritize displaying tourist information for that region. Also, if the user is in a travel destination region, the information provider can provide the latest tourist information for that region. This allows for the prioritization of highly relevant information by considering the user's geographical location. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant information includes, for example, information about nearby tourist destinations and events.

[0089] The information provision department can analyze users' social media activity and provide relevant information when providing information. For example, the information provision department can provide information on tourist destinations that users have shared on social media. It can also provide information on tourist destinations that users follow on social media. Furthermore, it can provide information on tourist destinations that users have "liked" on social media. By analyzing users' social media activity, the information provision department can provide relevant information and improve the quality of information provision. Social media activity analysis includes, for example, the content of posts, the number of likes, and the number of followers. Relevant information includes, for example, information related to past travel destinations and activities of interest.

[0090] The video playback unit can estimate the user's emotions and adjust the video playback method based on the estimated emotions. For example, if the user is relaxed, the video playback unit can provide a video that progresses at a leisurely pace. Alternatively, if the user is in a hurry, the video playback unit can provide a video that takes them to major tourist spots in a short amount of time. Furthermore, if the user is excited, the video playback unit can provide a video with visually stimulating effects. By adjusting the video playback method according to the user's emotions, a more appropriate video viewing experience can be provided. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjustments to the video playback method include, for example, changing the playback speed and adjusting the image quality.

[0091] The video playback unit can provide the most suitable video by referring to the user's past viewing history when they are watching a video. For example, the video playback unit can provide relevant videos based on videos the user has watched in the past. It can also suggest videos the user might like based on their past viewing history. Furthermore, the video playback unit can analyze the user's past viewing history and provide the most interesting videos. In this way, by referring to the user's past viewing history, the system can provide the most suitable video and improve the video viewing experience. Past viewing history includes, for example, videos previously watched and viewing time. Providing the most suitable video includes, for example, videos based on the user's interests and customization methods.

[0092] The video viewing section can customize video content based on the user's current interests and preferences during viewing. For example, if the user is interested in nature, the video viewing section can provide videos focusing on natural landscapes. Similarly, if the user is interested in history, the video viewing section can provide videos showcasing historical sites. Furthermore, if the user is interested in food culture, the video viewing section can provide videos introducing local cuisine. By customizing video content based on the user's current interests, a more engaging viewing experience can be provided. Current interests and preferences can be acquired through methods such as survey results and social media posts. Customizing video content can include adding scenes of interest or removing unwanted scenes.

[0093] The video playback unit can estimate the user's emotions and adjust the playback order of videos based on those emotions. For example, if the user is tense, the unit can start playback with relaxing videos. Similarly, if the user is relaxed, it can start playback with interesting videos. Furthermore, if the user is in a hurry, it can prioritize playing videos of major tourist attractions. This allows for a more appropriate video viewing experience by adjusting the playback order according to the user's emotions. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjusting the video playback order includes, for example, changing the order based on the user's interests and optimizing the flow of the videos.

[0094] The video viewing unit can prioritize providing highly relevant videos by considering the user's geographical location information during video viewing. For example, the video viewing unit can provide videos of tourist destinations near the user's current location. Furthermore, if the user is in a specific region, the video viewing unit can prioritize providing videos of tourist attractions in that region. Also, if the user is in a travel destination, the video viewing unit can provide the latest tourist information for that region via video. This allows for the prioritization of highly relevant videos by considering the user's geographical location information. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant videos include, for example, information on nearby tourist destinations and events.

[0095] The video viewing unit can analyze the user's social media activity while they are watching a video and suggest relevant videos. For example, the unit can provide videos of tourist destinations that the user has shared on social media. It can also provide videos of tourist destinations that the user follows on social media. Furthermore, it can provide videos of tourist destinations that the user has "liked" on social media. By analyzing the user's social media activity, it can suggest relevant videos and improve the video viewing experience. Social media activity analysis includes, for example, the content of posts, the number of likes, and the number of followers. Relevant videos include, for example, videos related to past travel destinations or activities of interest.

[0096] The customization function can estimate the user's emotions and adjust the customization content based on those emotions. For example, if the user is relaxed, the customization function can provide a relaxed pace. If the user is in a hurry, the customization function can provide a quick tour of major tourist spots. If the user is excited, the customization function can provide a visually stimulating experience. By adjusting the customization content according to the user's emotions, a more appropriate customization experience can be provided. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjustments to the customization content include, for example, customization based on the user's interests and preferences, and customization based on past usage history.

[0097] The customization section can provide optimal customizations by referring to the user's past customization history during the customization process. For example, the customization section can provide relevant customizations based on the user's past customizations. It can also suggest preferred customizations based on the user's past customization history. Furthermore, the customization section can analyze the user's past customization history and provide the most interesting customizations. This allows for the provision of optimal customizations and an improved customization experience by referring to the user's past customization history. Past customization history includes, for example, the content and frequency of past customizations. Providing optimal customizations includes, for example, customizations based on the user's interests and customization methods.

[0098] The customization section can modify the customization content based on the user's current needs during the customization process. For example, if the user needs accessibility information, the customization section can provide information on accessible tourist destinations. It can also provide information on allergy-friendly restaurants if the user needs dining information, or wheelchair-accessible transportation if the user needs transportation information. This allows for a more appropriate customized experience by modifying the customization content based on the user's current needs. Current needs can be obtained, for example, from survey results or social media posts. Modifications to the customization content can include adding content of interest or removing content that is no longer needed.

[0099] The customization section can estimate the user's emotions and prioritize customizations based on those emotions. For example, if the user is stressed, the customization section will display important customizations first and simplify the process. Alternatively, if the user is relaxed, the customization section can offer more detailed customizations and suggest customizable options. Furthermore, if the user is in a hurry, the customization section can prioritize displaying minimal customizations. This allows the system to prioritize customizations based on the user's emotions, ensuring that the most important customizations are provided to the user. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Factors such as importance and urgency are used to determine customization priorities.

[0100] The customization section can prioritize providing highly relevant customizations by considering the user's geographical location during the customization process. For example, the customization section can provide customizations for tourist destinations near the user's current location. It can also prioritize providing customizations for tourist attractions in a specific region if the user is in that region. Furthermore, if the user is in a travel destination region, the customization section can provide the latest tourist information for that region. This allows for the prioritization of highly relevant customizations by considering the user's geographical location. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant customizations include, for example, information on nearby tourist attractions and events.

[0101] The customization department can analyze the user's social media activity during the customization process and suggest relevant customizations. For example, the customization department can provide customizations of tourist destinations that the user has shared on social media. It can also provide customizations of tourist destinations that the user follows on social media. Furthermore, it can provide customizations of tourist destinations that the user has "liked" on social media. By analyzing the user's social media activity, it is possible to suggest relevant customizations and improve the customization experience. Social media activity analysis includes, for example, the content of posts, the number of likes, and the number of followers. Relevant customizations include, for example, customizations related to past travel destinations or activities of interest.

[0102] The information panel can estimate the user's emotions and adjust the display method based on those emotions. For example, if the user is tense, the information panel can provide a simple and highly visible display method. Alternatively, if the user is relaxed, it can provide a display method that includes detailed information. Furthermore, if the user is in a hurry, it can provide a concise display method. By adjusting the information panel display method according to the user's emotions, it becomes possible to provide information that is easy for the user to understand. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjustments to the information panel display method include, for example, changing font size, color, and layout.

[0103] The information panel can provide optimal information by referring to the user's past information usage history when displaying the information panel. For example, the information panel can provide relevant information based on information the user has used in the past. It can also suggest preferred information based on the user's past information usage history. Furthermore, it can analyze the user's past information usage history and provide the information that is most of interest to the user. This allows for the provision of optimal information and improves the quality of information provision by referring to the user's past information usage history. Past information usage history includes, for example, previously viewed information and search history. Providing optimal information includes, for example, information based on the user's interests and methods for customization.

[0104] The information panel can customize the information content based on the user's current needs when the information panel is displayed. For example, if the user needs accessibility information, the information panel can provide information on accessible tourist destinations. It can also provide information on allergy-friendly restaurants if the user needs dining information, or wheelchair-accessible transportation if the user needs transportation information. This allows for the provision of more appropriate information by customizing the information content based on the user's current needs. Current needs can be obtained, for example, from survey results or social media posts. Customizing the information content can include, for example, adding information of interest or removing unnecessary information.

[0105] The information panel can estimate the user's emotions and prioritize the information displayed on the panel based on those emotions. For example, if the user is nervous, the information panel may display important information first and simplify the process. Alternatively, if the user is relaxed, the information panel may provide detailed information and suggest customizable options. Furthermore, if the user is in a hurry, the information panel may prioritize displaying minimal information. This allows the system to prioritize information important to the user by determining the priority of the information panel according to their emotions. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Factors such as importance and urgency may be used to determine the priority of the information panel.

[0106] The information panel can prioritize providing highly relevant information by considering the user's geographical location when displaying the information panel. For example, the information panel can automatically display information about tourist destinations near the user's current location as suggestions. Furthermore, if the user is in a specific region, the information panel can prioritize displaying tourist information for that region. Also, if the user is in a travel destination region, the information panel can provide the latest tourist information for that region. This allows for the prioritization of highly relevant information by considering the user's geographical location. Geographical location information can be obtained, for example, from GPS data or IP addresses. Highly relevant information can include, for example, information about nearby tourist destinations and events.

[0107] The information panel can analyze the user's social media activity and provide relevant information when displaying the information panel. For example, the information panel can provide information on tourist destinations that the user has shared on social media. It can also provide information on tourist destinations that the user follows on social media. Furthermore, it can provide information on tourist destinations that the user has "liked" on social media. By analyzing the user's social media activity, it is possible to provide relevant information and improve the quality of information provision. Social media activity analysis includes, for example, the content of posts, the number of likes, and the number of followers. Relevant information includes, for example, information related to past travel destinations and activities of interest. === Hard Collateral 1-1 === Each of the multiple elements described above, including the input unit, experience unit, information provision unit, video viewing unit, customization unit, and information panel unit, is implemented, for example, by at least one of the smart device 14 and the data processing unit 12. For example, the input unit allows the user to input travel information using the reception device 38 of the smart device 14. The experience unit provides a virtual travel experience using the processor 46 of the smart device 14. The information provision unit provides necessary information through the output device 40 of the smart device 14. The video viewing unit allows viewing of videos taken by a 360-degree camera or drone using the display 40A of the smart device 14. The customization unit provides a customized virtual experience using AI technology using the specific processing unit 290 of the data processing unit 12. The information panel unit displays an information panel through the display 40A of the smart device 14. === Hard Collateral 1-2 === Each of the multiple elements described above, including the input unit, experience unit, information provision unit, video viewing unit, customization unit, and information panel unit, is implemented by, for example, at least one of the smart glasses 214 and the data processing unit 12. For example, the input unit allows the user to input travel information using the microphone 238 of the smart glasses 214. The experience unit provides a virtual travel experience using the processor 46 of the smart glasses 214. The information provision unit provides necessary information through the speaker 240 of the smart glasses 214. The video viewing unit allows the user to view videos taken by a 360-degree camera or drone using the display of the smart glasses 214. The customization unit provides a customized virtual experience using AI technology using the specific processing unit 290 of the data processing unit 12. The information panel unit displays an information panel through the display of the smart glasses 214. === Hard Collateral 1-3 === Each of the multiple elements described above, including the input unit, experience unit, information provision unit, video viewing unit, customization unit, and information panel unit, is implemented by, for example, at least one of the headset terminal 314 and the data processing unit 12. For example, the input unit allows the user to input travel information using the microphone 238 of the headset terminal 314. The experience unit provides a virtual travel experience using the processor 46 of the headset terminal 314. The information provision unit provides necessary information through the speaker 240 of the headset terminal 314. The video viewing unit allows viewing of videos taken by a 360-degree camera or drone using the display 343 of the headset terminal 314. The customization unit provides a customized virtual experience using AI technology using the specific processing unit 290 of the data processing unit 12. The information panel unit displays an information panel through the display 343 of the headset terminal 314. === Hard Collateral 1-4 === Each of the multiple elements described above, including the input unit, experience unit, information provision unit, video viewing unit, customization unit, and information panel unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the input unit allows the user to input travel information using the microphone 238 of the robot 414. The experience unit provides a virtual travel experience using the processor 46 of the robot 414. The information provision unit provides necessary information through the speaker 240 of the robot 414. The video viewing unit allows the user to view videos taken by a 360-degree camera or drone using the display of the robot 414. The customization unit provides a customized virtual experience using AI technology using the specific processing unit 290 of the data processing unit 12. The information panel unit displays an information panel through the display of the robot 414.

[0108] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0109] The input unit can analyze the user's past travel history and suggest the optimal input method. For example, it can automatically display tourist destinations the user has visited in the past as suggestions. The input unit can also prioritize suggesting input methods the user has used in the past (voice, text, etc.). Furthermore, the input unit can predict and suggest tourist destinations related to specific seasons or events based on the user's past travel history. This allows for the suggestion of the optimal input method and streamlines the input process by analyzing the user's past travel history. Past travel history includes, for example, past destinations, dates, and activities. Suggestions for appropriate input methods include, for example, optimizing the input form and suggesting voice input.

[0110] The experience section can customize the content of the experience based on the user's current interests. For example, if the user is interested in nature, a virtual experience centered on natural landscapes can be provided. If the user is interested in history, a virtual experience visiting historical sites can be provided. Furthermore, if the user is interested in food culture, a virtual experience introducing local cuisine can be provided. In this way, a more interesting experience can be provided by customizing the content based on the user's current interests. Current interests can be obtained, for example, from survey results and social media posts. Customizing the experience content can include, for example, adding activities of interest or removing unnecessary content.

[0111] The information delivery unit can estimate the user's emotions and adjust the way information is displayed based on those emotions. For example, if the user is stressed, it can provide a simple and highly visible display. If the user is relaxed, it can provide a display that includes detailed information. Furthermore, if the user is in a hurry, it can provide a display that gets straight to the point. By adjusting the way information is displayed according to the user's emotions, it becomes possible to provide information that is easy for the user to understand. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjustments to the way information is displayed include, for example, changing the font size, changing the color, and changing the layout.

[0112] The video playback unit can estimate the user's emotions and adjust the video playback method based on those emotions. For example, if the user is relaxed, it can provide a video that progresses at a leisurely pace. If the user is in a hurry, it can provide a video that takes them to major tourist spots in a short amount of time. Furthermore, if the user is excited, it can provide a video with visually stimulating effects. In this way, by adjusting the video playback method according to the user's emotions, a more appropriate video viewing experience can be provided. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjustments to the video playback method include, for example, changing the playback speed and adjusting the image quality.

[0113] The customization function can estimate the user's emotions and adjust the customization content based on those emotions. For example, if the user is relaxed, it can provide a customization that proceeds at a leisurely pace. If the user is in a hurry, it can provide a customization that visits major tourist spots in a short amount of time. Furthermore, if the user is excited, it can provide a customization that includes visually stimulating effects. In this way, by adjusting the customization content according to the user's emotions, a more appropriate customization experience can be provided. Emotion estimation is performed using technologies such as facial recognition, voice analysis, and biometrics. Adjustments to the customization content include, for example, customization based on the user's interests and preferences, and customization based on past usage history.

[0114] The input section can customize input fields based on the user's current health status and special needs during input. For example, if the user uses a wheelchair, barrier-free tourist destinations will be prioritized. If the user has specific allergies, allergy-friendly restaurants can be suggested. Furthermore, if the user is elderly, sightseeing routes with minimal movement can be suggested. This allows for the provision of information tailored to the user by customizing input fields according to their health status and special needs. Health status assessments include, for example, medical data and self-reports. Special needs acquisition includes, for example, allergy information and physical limitations.

[0115] The experience department can provide the optimal virtual experience by referencing the user's past travel experiences during the experience. For example, it can provide relevant virtual experiences based on tourist destinations the user has visited in the past. It can also suggest tourist spots the user might like based on their past travel experiences. Furthermore, it can analyze the user's past travel experiences and provide the virtual experience that will be most interesting to them. In this way, the optimal virtual experience can be provided by referencing the user's past travel experiences. Past travel experiences include, for example, destinations, dates, and activities. Providing the optimal virtual experience includes, for example, experience content and customization methods based on the user's interests.

[0116] The information provision department can provide the most relevant information by referring to the user's past information usage history. For example, it can provide relevant information based on information the user has used in the past. It can also suggest information the user might like based on their past information usage history. Furthermore, it can analyze the user's past information usage history and provide the information that is most likely to interest them. In this way, by referring to the user's past information usage history, the quality of information provision can be improved by providing the most relevant information. Past information usage history includes, for example, information previously viewed and search history. Providing the most relevant information includes, for example, information based on the user's interests and methods of customization.

[0117] The video viewing unit can provide the most suitable video by referring to the user's past viewing history when they are watching a video. For example, it can provide related videos based on videos the user has watched in the past. It can also suggest videos the user might like based on their past viewing history. Furthermore, it can analyze the user's past viewing history and provide the most interesting videos. In this way, by referring to the user's past viewing history, the system can provide the most suitable video and improve the video viewing experience. Past viewing history includes, for example, videos previously watched and viewing time. Providing the most suitable video includes, for example, videos based on the user's interests and customization methods.

[0118] The customization section can provide optimal customizations by referring to the user's past customization history during the customization process. For example, it can provide relevant customizations based on the user's past customizations. It can also suggest preferred customizations based on the user's past customization history. Furthermore, it can analyze the user's past customization history and provide the customizations that will interest them most. In this way, by referring to the user's past customization history, optimal customizations can be provided, improving the customization experience. Past customization history includes, for example, the content and frequency of past customizations. Providing optimal customizations includes, for example, customizations based on the user's interests and customization methods.

[0119] The following briefly describes the processing flow for example form 2.

[0120] Step 1: The input section allows the user to enter travel information. This information includes, for example, destination, dates, budget, and activities of interest. The user can enter information about tourist attractions and accommodations they wish to visit. Step 2: The experience section provides a virtual travel experience based on the information entered by the input section. The virtual travel experience may include, for example, 3D simulation or the use of a VR headset. The experience section uses VR technology to provide a virtual travel experience based on the information entered by the user. Step 3: The Information Department provides the necessary information during the virtual experience provided by the Experience Department. This necessary information includes, for example, detailed information about tourist attractions, transportation options, and accommodations. The Information Department provides the necessary information through information panels displayed during the virtual experience.

[0121] 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.

[0122] 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 the following. 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 (for example, 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. 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 a variety of operations, but is not limited to these examples. Furthermore, AI may also be an AI agent. Also, when the operations described above are performed by AI, the operations may be performed partially or entirely by AI, but is not limited to these examples. Additionally, operations performed by AI, including generative AI, may be replaced by rule-based operations, and rule-based operations may be replaced by operations performed by AI, including generative AI.

[0123] 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.

[0124] The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0125] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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).

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.).

[0137] 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.

[0138] 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. 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.

[0139] 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.

[0140] The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0141] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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).

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.).

[0153] 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.

[0154] 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. 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.

[0155] 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.

[0156] The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0157] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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).

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.).

[0170] 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.

[0171] 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. 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.

[0172] 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.

[0173] The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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."

[0180] 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.

[0181] 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.

[0182] 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.

[0183] 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.

[0184] 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.

[0185] 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.

[0186] 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.

[0187] 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.

[0188] 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.

[0189] 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.

[0190] 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.

[0191] 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.

[0192] [Explanation of symbols]

[0193] 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. An input section where the user enters travel information, An experience unit that provides a virtual travel experience based on the information entered by the input unit, An information provision unit that provides information necessary during the virtual experience provided by the aforementioned experience unit, Equipped with A system characterized by the following features.

2. The aforementioned experience section is, It includes a video viewing unit for viewing footage captured using a 360-degree camera or drone. The system according to feature 1.

3. The aforementioned experience section is, It features a customization department that provides customized virtual experiences using AI technology. The system according to feature 1.

4. The aforementioned information provision unit, It features an information panel that provides necessary information through an information panel displayed during the virtual experience. The system according to feature 1.

5. The aforementioned input unit is It estimates the user's emotions and adjusts the input interface design according to the estimated emotions. The system according to feature 1.

6. The aforementioned input unit is It analyzes the user's past travel history and suggests the appropriate input method. The system according to feature 1.

7. The aforementioned input unit is When users enter data, the input fields are customized based on their current health status and special needs. The system according to feature 1.

8. The aforementioned input unit is The system estimates the user's emotions and prioritizes input fields based on those emotions. The system according to feature 1.

9. The aforementioned input unit is When users input data, the system prioritizes providing travel information that is highly relevant to their geographical location. The system according to feature 1.

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