system

Abstract

The system according to the embodiment aims to enable tourists to easily create their own optimal sightseeing plan and receive visual and audio guidance. [Solution] A system according to an embodiment includes a reception unit, an analysis unit, a generation unit, a visual information providing device, and an audio guide device. The reception unit receives information input by tourists. The analysis unit analyzes the information received by the reception unit. The generation unit generates a sightseeing plan based on the information analyzed by the analysis unit. The visual information providing device displays the sightseeing plan generated by the generation unit. The audio guide device provides audio guidance based on the information provided by the visual information providing device.

Description

[Technical Field]

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

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

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

[0004] Conventional technologies have had the problem that it is difficult for tourists to easily create their own optimal sightseeing plans and receive visual and audio guidance.

[0005] The system according to the embodiment aims to enable tourists to easily create their own optimal sightseeing plan and receive visual and audio guidance. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, an analysis unit, a generation unit, a visual information providing device, and an audio guide device. The reception unit receives information input by the tourist. The analysis unit analyzes the information received by the reception unit. The generation unit generates a tour plan based on the information analyzed by the analysis unit. The visual information providing device displays the tour plan generated by the generation unit. The audio guide device provides audio guidance based on the information provided by the visual information providing device. [Effects of the Invention]

[0007] The system according to the embodiment allows tourists to easily create their own optimal sightseeing plan and receive visual and audio guidance. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

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

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

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

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

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

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

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0028] (Example 1) A tourism personal assistant system according to an embodiment of the present invention accepts and analyzes tourist information, generates a sightseeing plan, displays it on a visual information display device, and provides audio guidance through an audio guide device. In this tourism personal assistant system, tourists input information about tourist destinations through a smartphone app, and a multimodal AI analyzes the information to generate a sightseeing plan. The generated sightseeing plan is provided to tourists through smart glasses, which display real-time information about the tourist destinations and assist tourists in navigating from their current location to their destination. Furthermore, a digital human provides tourists with audio and visual guidance. For example, audio explanations of the history and culture of the tourist destination and visual indications of the tourist destination's highlights are provided. Tourists can also ask questions in real time through the smartphone app, and the digital human responds instantly to those questions. This allows tourists to enjoy a personalized sightseeing experience tailored to their interests and needs. Furthermore, the integration of smart glasses and a digital human facilitates smooth navigation and information gathering at tourist destinations, improving the efficiency of sightseeing. This allows the tourism personal assistant system to provide tourists with an optimal sightseeing experience. For example, it can generate sightseeing plans based on the places tourists want to visit and activities they are interested in, providing real-time navigation support. It can also provide audio information about the history and culture of tourist destinations, allowing tourists to have a deeper sightseeing experience. Furthermore, it can improve the efficiency of tourism by allowing tourists to ask questions in real time and receive instant answers.

[0029] A tourism personal assistant system according to an embodiment includes a reception unit, an analysis unit, a generation unit, a visual information providing device, and an audio guide device. The reception unit receives input information from a tourist. The input information from the tourist includes, but is not limited to, places the tourist wants to visit and activities the tourist is interested in. The reception unit receives information input by the tourist via a smartphone app, for example. The reception unit can also receive voice input and image input. The analysis unit analyzes the information received by the reception unit. The analysis can be performed using, for example, natural language processing, image analysis, data mining, or other methods, but is not limited to these examples. The analysis unit extracts data for generating an optimal tour plan based on the tourist's input information. The generation unit generates a tour plan based on the information analyzed by the analysis unit. The tour plan can include, for example, a list of places to visit, a schedule, and activity suggestions, but is not limited to these examples. The generation unit generates a customized tour plan based on, for example, the tourist's interests and preferences. The visual information providing device displays the tour plan generated by the generation unit. Examples of the visual information providing device include, but are not limited to, smartphones, tablets, digital signage, etc. The visual information providing device visually displays, for example, a sightseeing plan and supports tourists in navigating from their current location to their destination. The audio guide device provides audio guidance based on information provided by the visual information providing device. Examples of the audio guide device include, but are not limited to, smartphone apps and dedicated devices. The audio guide device provides audio explanations, for example, of information about the history and culture of tourist destinations. This allows the tourism personal assistant system according to the embodiment to provide tourists with an individually optimized sightseeing experience.

[0030] The reception unit can accept information about places that tourists want to visit and activities that they are interested in. Information about places that tourists want to visit and activities that they are interested in includes, but is not limited to, examples of place names, facility names, and types of activities. For example, the reception unit accepts place names and facility names entered by tourists through a smartphone app. The reception unit can also accept input of types of activities that tourists are interested in. For example, if a tourist simply enters "I want to go to a museum," the reception unit can accept that information. This makes it possible to accept information based on the tourist's specific wishes.

[0031] The analysis unit can analyze the information received by the reception unit and generate a sightseeing plan suitable for the tourist. Specific criteria and generation methods for a sightseeing plan suitable for the tourist include, but are not limited to, a customization method based on individual interests and preferences. The analysis unit can, for example, analyze the information input by the tourist using natural language processing technology to extract the tourist's interests and preferences. The analysis unit can also identify tourist spots of interest from images taken by the tourist using image analysis technology. Furthermore, the analysis unit can analyze the tourist's past visit history and evaluation data using data mining technology to extract data for generating an optimal sightseeing plan. This makes it possible to provide the tourist with an optimal sightseeing plan.

[0032] The generation unit can generate a sightseeing plan based on the information analyzed by the analysis unit. Examples of methods and criteria for generating a sightseeing plan include, but are not limited to, types of algorithms and factors to consider. For example, the generation unit uses a machine learning algorithm to generate a customized sightseeing plan based on the tourist's interests and preferences. The generation unit can also generate a sightseeing plan including a list of places to visit, a schedule, and activity suggestions based on the tourist's input information. Furthermore, the generation unit can generate an optimal sightseeing plan by taking into account the tourist's past visit history and evaluation data. This allows a sightseeing plan to be generated based on the analysis results.

[0033] The visual information providing device can display the sightseeing plan generated by the generation unit. Examples of display methods and standards for the sightseeing plan include, but are not limited to, display formats and interface designs. The visual information providing device visually displays the sightseeing plan using, for example, a smartphone, a tablet, or digital signage. The visual information providing device can also display real-time map information and route guidance to support tourists in navigating from their current location to their destination. Furthermore, the visual information providing device can display real-time information about tourist destinations to help tourists move around and gather information at tourist destinations smoothly. This allows the sightseeing plan to be visually provided.

[0034] The audio guide device can provide audio guidance based on information provided by the visual information providing device. The methods and standards for providing audio guidance include, but are not limited to, the type of audio and selection criteria for the content of the guidance. For example, the audio guide device provides audio explanations of information about the history and culture of a tourist destination using a smartphone app or a dedicated device. The audio guide device can also provide visual information linked to the audio to visually indicate the highlights of the tourist destination. Furthermore, the audio guide device can also provide audio information such as the opening hours and access methods of the tourist destination. This allows audio guidance to be provided based on visual information.

[0035] The visual information providing device can display real-time information about tourist destinations to support tourists in navigating from their current location to their destination. Examples of real-time information about tourist destinations include, but are not limited to, weather information, crowding status, and event information. The visual information providing device can display real-time information about tourist destinations using, for example, a smartphone or tablet. The visual information providing device can also display real-time map information and route guidance to support tourists in navigating from their current location to their destination. Furthermore, the visual information providing device can display real-time crowding status and event information about tourist destinations to support tourists in moving around and gathering information at tourist destinations. This allows for the provision of real-time information about tourist destinations to support navigation.

[0036] The audio guide device can provide audio explanations of information about the history and culture of a tourist destination. Examples of information about the history and culture of a tourist destination include, but are not limited to, historical background and cultural significance. The audio guide device can provide audio explanations of information about the history and culture of a tourist destination using, for example, a smartphone app or a dedicated device. The audio guide device can also provide visual information linked to the audio to visually indicate the highlights of the tourist destination. Furthermore, the audio guide device can also provide audio information such as the opening hours and access methods of the tourist destination. This allows audio provision of information about the history and culture of a tourist destination.

[0037] The audio guide device can visually show the highlights of a tourist destination. Examples of the highlights of a tourist destination include, but are not limited to, tourist spots, famous places, and activities. The audio guide device can visually show the highlights of a tourist destination using, for example, a smartphone app or a dedicated device. The audio guide device can also provide audio information about the history and culture of the tourist destination. Furthermore, the audio guide device can also provide audio information such as the opening hours and access methods of the tourist destination. This makes it possible to visually present the highlights of a tourist destination.

[0038] The reception unit can accept questions from tourists in real time through a smartphone app. Specific methods and standards for accepting questions in real time include, but are not limited to, chatbots and live support. For example, the reception unit accepts questions entered by tourists through a smartphone app in real time. The reception unit can also accept questions entered by tourists via voice. For example, if a tourist asks, "What are the opening hours of this tourist attraction?", the reception unit can accept the question. This allows tourists to ask questions in real time.

[0039] The audio guide device can provide information such as the opening hours and access methods of tourist attractions. Information such as the opening hours and access methods of tourist attractions includes, but is not limited to, the format of the opening hours and details of the access methods. The audio guide device can provide information such as the opening hours and access methods of tourist attractions by voice, for example, using a smartphone app or a dedicated device. The audio guide device can also provide visual information linked to the voice to visually show the highlights of the tourist attractions. Furthermore, the audio guide device can also provide information about the history and culture of the tourist attractions by voice. This makes it possible to provide information such as the opening hours and access methods of tourist attractions.

[0040] The reception unit can analyze the tourist's past visit history and suggest the optimal input method. Specific content and analysis methods of the tourist's past visit history include, but are not limited to, the places visited, the number of visits, and the length of stay. For example, the reception unit can automatically display the places visited by the tourist in the past as candidates. The reception unit can also preferentially suggest input methods (voice, text, etc.) that the tourist has used in the past. Furthermore, the reception unit can predict and suggest places and activities to be used during a specific time period based on the tourist's past visit history. This makes it possible to suggest the optimal input method based on the tourist's past visit history.

[0041] The reception unit can automatically suggest related tourist attraction information based on the tourist's current location information. Specific methods for acquiring and using the tourist's current location information include, but are not limited to, GPS data, location information services, etc. The reception unit, for example, automatically suggests tourist attractions close to the tourist's current location. The reception unit can also suggest the most suitable tourist attraction taking into account the distance from the tourist's current location. Furthermore, the reception unit can update the tourist's current location in real time while the tourist is moving and suggest related tourist attraction information. This makes it possible to suggest related tourist attraction information based on the tourist's current location information.

[0042] The reception unit can select an appropriate input means depending on the tourist's input method. Specific types and selection criteria of the tourist's input method include, but are not limited to, voice input, text input, and image input. For example, the reception unit can provide optimal tourist destination information when the tourist simply inputs "I want to go to the museum" by voice. The reception unit can also provide related tourist destination information based on images taken by the tourist with the smartphone camera. Furthermore, the reception unit can provide optimal tourist destination information based on information entered by the tourist as text. This makes it possible to provide the optimal input means depending on the tourist's input method.

[0043] The reception unit can customize the input method by reflecting the tourists' past feedback. Specific content and reflection methods of the tourists' past feedback include, but are not limited to, survey results, review comments, etc. The reception unit, for example, preferentially suggests input methods that the tourists have previously preferred. The reception unit can also improve the input interface based on the tourists' past feedback. Furthermore, the reception unit can also simplify the input procedure by reflecting the tourists' past feedback. This makes it possible to customize the input method based on the tourists' past feedback.

[0044] The reception unit can prioritize acquiring highly relevant tourist destination information by taking into account the tourist's geographical location information. Specific methods for acquiring and using the tourist's geographical location information include, but are not limited to, GPS data, location information services, etc. For example, the reception unit prioritizes acquiring tourist destination information close to the tourist's current location. The reception unit can also acquire optimal tourist destination information by taking into account the distance from the tourist's current location. Furthermore, the reception unit can update the tourist's current location in real time while the tourist is moving and acquire highly relevant tourist destination information. This makes it possible to acquire highly relevant tourist destination information based on the tourist's geographical location information.

[0045] The reception unit can analyze the tourist's social media activity and automatically suggest related tourist attraction information. Specific content and analysis methods of the tourist's social media activity include, but are not limited to, for example, the content of posts, the number of likes, and the number of followers. The reception unit can also suggest related tourist attraction information based on, for example, the places where the tourist checked in on social media. The reception unit can also analyze the content of the tourist's social media posts and suggest related tourist attraction information. Furthermore, the reception unit can also suggest related tourist attraction information based on the activities of the tourist's friends on social media. In this way, related tourist attraction information can be suggested based on the tourist's social media activity.

[0046] The analysis unit can improve the accuracy of the analysis by referring to the tourist's past visit history. Specific content and analysis methods of the tourist's past visit history include, but are not limited to, the places visited, the number of visits, and the length of stay. For example, the analysis unit can propose an optimal sightseeing plan based on the places the tourist has visited in the past. The analysis unit can also propose a route that avoids crowds based on the tourist's past visit history. Furthermore, the analysis unit can analyze the tourist's past visit history and propose the most efficient sightseeing plan. This can improve the accuracy of the analysis based on the tourist's past visit history.

[0047] The analysis unit can adjust the analysis algorithm based on the tourist's current interests and concerns. Specific methods and criteria for adjusting the analysis algorithm based on the tourist's current interests and concerns include, but are not limited to, machine learning algorithms and statistical analysis methods. For example, the analysis unit can adjust the analysis algorithm based on activities in which the tourist is currently interested. The analysis unit can also adjust the analysis algorithm based on tourist destinations in which the tourist is currently interested. Furthermore, the analysis unit can adjust the analysis algorithm to propose an optimal sightseeing plan based on the tourist's current interests and concerns. This makes it possible to adjust the analysis algorithm based on the tourist's current interests and concerns.

[0048] The analysis unit can apply different analysis methods depending on the category of the information input by the tourist. Specific types and application criteria of analysis methods include, but are not limited to, text analysis, image analysis, data mining, etc. For example, if the information input by the tourist is related to an activity, the analysis unit applies an analysis method specialized for activities. Furthermore, if the information input by the tourist is related to a tourist destination, the analysis unit can also apply an analysis method specialized for tourist destinations. Furthermore, if the information input by the tourist is related to an event, the analysis unit can also apply an analysis method specialized for events. This makes it possible to apply an appropriate analysis method depending on the category of the information input by the tourist.

[0049] The analysis unit can analyze the social media activities of tourists and reflect related information in the analysis. Specific content and acquisition methods of the related information include, but are not limited to, tourist attraction information, event information, and review information. For example, the analysis unit analyzes related tourist attraction information based on the locations where tourists check in on social media. The analysis unit can also analyze the content of tourists' social media posts and analyze related tourist attraction information. Furthermore, the analysis unit can analyze related tourist attraction information by referring to the activities of the tourists' friends on social media. This makes it possible to reflect related information based on the tourists' social media activities in the analysis.

[0050] The analysis unit can improve the accuracy of the analysis by taking into account the tourist's geographical location information. Specific methods and criteria for improving the accuracy of the analysis include, but are not limited to, data quality and algorithm improvements. For example, the analysis unit prioritizes analyzing tourist destination information close to the tourist's current location. The analysis unit can also analyze optimal tourist destination information by taking into account the distance from the tourist's current location. Furthermore, the analysis unit can update the tourist's current location in real time while the tourist is moving and analyze related tourist destination information. This can improve the accuracy of the analysis based on the tourist's geographical location information.

[0051] The analysis unit can optimize the analysis algorithm by reflecting the tourists' past feedback. Specific types and optimization methods of the analysis algorithm include, but are not limited to, machine learning algorithms and statistical analysis methods, for example. The analysis unit optimizes the analysis algorithm based on sightseeing plans that tourists have previously preferred, for example. The analysis unit can also improve the analysis algorithm based on the tourists' past feedback. Furthermore, the analysis unit can adjust the analysis method by reflecting the tourists' past feedback. This makes it possible to optimize the analysis algorithm based on the tourists' past feedback.

[0052] The generation unit can improve the accuracy of the sightseeing plan by referring to the tourist's past visit history. Specific methods and criteria for improving the accuracy of the sightseeing plan include, but are not limited to, for example, data quality and algorithm improvements. For example, the generation unit can propose an optimal sightseeing plan based on the tourist's past visit history. The generation unit can also propose a route that avoids crowds based on the tourist's past visit history. Furthermore, the generation unit can analyze the tourist's past visit history and propose the most efficient sightseeing plan. This makes it possible to improve the accuracy of the sightseeing plan based on the tourist's past visit history.

[0053] The generation unit can customize the sightseeing plan based on the tourist's current interests and concerns. Specific methods and criteria for customizing the sightseeing plan include, but are not limited to, customization methods based on individual interests and preferences. For example, the generation unit customizes the sightseeing plan based on activities in which the tourist is currently interested. The generation unit can also customize the sightseeing plan based on tourist destinations in which the tourist is currently interested. Furthermore, the generation unit can customize the sightseeing plan to propose an optimal sightseeing plan based on the tourist's current interests and concerns. This makes it possible to customize the sightseeing plan based on the tourist's current interests and concerns.

[0054] The generation unit can apply different tour plan generation methods depending on the category of the tourist's input information. Specific types and application criteria of tour plan generation methods include, for example, types of algorithms and factors to be considered, but are not limited to these examples. For example, if the information input by the tourist is related to an activity, the generation unit can apply a tour plan generation method specialized for activities. Furthermore, if the information input by the tourist is related to a tourist destination, the generation unit can also apply a tour plan generation method specialized for tourist destinations. Furthermore, if the information input by the tourist is related to an event, the generation unit can also apply a tour plan generation method specialized for events. This makes it possible to apply an appropriate tour plan generation method depending on the category of the tourist's input information.

[0055] The generation unit can analyze the tourist's social media activities and reflect related information in the tour plan. Specific content and acquisition methods of the related information include, but are not limited to, tourist attraction information, event information, and review information. For example, the generation unit can reflect related tourist attraction information in the tour plan based on the places where the tourist checks in on social media. The generation unit can also analyze the content of the tourist's social media posts and reflect related tourist attraction information in the tour plan. Furthermore, the generation unit can also reflect related tourist attraction information in the tour plan based on the activities of the tourist's friends on social media. In this way, related information based on the tourist's social media activities can be reflected in the tour plan.

[0056] The generation unit can improve the accuracy of the sightseeing plan by taking into account the tourist's geographical location information. Specific methods and criteria for improving the accuracy of the sightseeing plan include, but are not limited to, data quality and algorithm improvements. For example, the generation unit preferentially reflects tourist destination information close to the tourist's current location in the sightseeing plan. The generation unit can also reflect optimal tourist destination information in the sightseeing plan by taking into account the tourist's distance from the current location. Furthermore, the generation unit can update the tourist's current location in real time while the tourist is moving and reflect related tourist destination information in the sightseeing plan. This can improve the accuracy of the sightseeing plan based on the tourist's geographical location information.

[0057] The generation unit can optimize the tour plan generation algorithm by reflecting the tourists' past feedback. Specific types and optimization methods of the tour plan generation algorithm include, but are not limited to, machine learning algorithms and statistical analysis methods. For example, the generation unit optimizes the tour plan generation algorithm based on tour plans that tourists have previously preferred. The generation unit can also improve the tour plan generation algorithm based on the tourists' past feedback. Furthermore, the generation unit can adjust the tour plan generation method by reflecting the tourists' past feedback. This makes it possible to optimize the tour plan generation algorithm based on the tourists' past feedback.

[0058] The visual information providing device can customize the display content of the visual information by referring to the tourist's past visit history. Specific customization methods and criteria for the display content of the visual information include, but are not limited to, customization methods based on individual interests and preferences, for example. The visual information providing device can display related visual information based on, for example, places that the tourist has visited in the past. The visual information providing device can also display visual information that is likely to be of interest to the tourist based on the tourist's past visit history. Furthermore, the visual information providing device can analyze the tourist's past visit history and display the most appropriate visual information. This makes it possible to customize the display content of the visual information based on the tourist's past visit history.

[0059] The visual information providing device can provide real-time visual information based on the tourist's current location information. Specific content and acquisition methods of the real-time visual information include, but are not limited to, weather information, congestion status, and event information. For example, the visual information providing device can provide the tourist with real-time information about tourist spots close to the tourist's current location. The visual information providing device can also provide the tourist with optimal real-time information taking into account the distance from the tourist's current location. Furthermore, the visual information providing device can update the tourist's current location in real time while the tourist is moving and provide related visual information. This makes it possible to provide real-time visual information based on the tourist's current location information.

[0060] The visual information providing device can apply different visual information display methods depending on the category of information input by the tourist. Specific types and application criteria of visual information display methods include, but are not limited to, graph display, text display, interactive display, etc. For example, if the information input by the tourist is related to an activity, the visual information providing device can apply a visual information display method specialized for the activity. Furthermore, if the information input by the tourist is related to a tourist destination, the visual information providing device can also apply a visual information display method specialized for the tourist destination. Furthermore, if the information input by the tourist is related to an event, the visual information providing device can also apply a visual information display method specialized for the event. This makes it possible to apply an appropriate visual information display method depending on the category of information input by the tourist.

[0061] The visual information providing device can analyze the social media activities of tourists and provide related visual information. Specific content and acquisition methods of the related visual information include, but are not limited to, tourist attraction information, event information, and review information. For example, the visual information providing device can provide related visual information based on the locations where tourists check in on social media. The visual information providing device can also analyze the content posted by tourists on social media and provide related visual information. Furthermore, the visual information providing device can provide related visual information by referring to the activities of the tourists' friends on social media. This makes it possible to provide related visual information based on the tourists' social media activities.

[0062] The visual information providing device can improve the accuracy of visual information by taking into account the tourist's geographical location information. Specific methods and criteria for improving the accuracy of visual information include, but are not limited to, data quality and algorithm improvements. For example, the visual information providing device can provide tourist information that is close to the tourist's current location as visual information. The visual information providing device can also provide optimal visual information by taking into account the distance from the tourist's current location. Furthermore, the visual information providing device can update the tourist's current location in real time while the tourist is moving and provide related visual information. This can improve the accuracy of visual information based on the tourist's geographical location information.

[0063] The visual information providing device can optimize the visual information display algorithm by reflecting the tourists' past feedback. Specific types and optimization methods of the visual information display algorithm include, but are not limited to, machine learning algorithms and statistical analysis methods, for example. The visual information providing device can optimize the visual information display algorithm based on the visual information that the tourists have previously preferred. The visual information providing device can also improve the visual information display algorithm based on the tourists' past feedback. Furthermore, the visual information providing device can adjust the visual information display method by reflecting the tourists' past feedback. This makes it possible to optimize the visual information display algorithm based on the tourists' past feedback.

[0064] The audio guide device can customize the content of the audio guide by referring to the tourist's past visit history. Specific customization methods and criteria for the content of the audio guide include, but are not limited to, customization methods based on individual interests and preferences. For example, the audio guide device can provide a relevant audio guide based on places the tourist has visited in the past. The audio guide device can also provide an audio guide that is likely to be of interest to the tourist based on the tourist's past visit history. Furthermore, the audio guide device can analyze the tourist's past visit history and provide the most appropriate audio guide. This makes it possible to customize the content of the audio guide based on the tourist's past visit history.

[0065] The audio guide device can provide real-time audio guidance based on the tourist's current location information. Specific content and provision methods of the real-time audio guidance include, but are not limited to, guidance content based on current location information. For example, the audio guide device can provide the tourist with real-time information about tourist spots close to the tourist's current location by voice. The audio guide device can also provide the tourist with optimal real-time audio guidance taking into account the distance from the tourist's current location. Furthermore, the audio guide device can update the tourist's current location in real time while the tourist is moving and provide related audio guidance. This makes it possible to provide real-time audio guidance based on the tourist's current location information.

[0066] The audio guide device can apply different audio guide methods depending on the category of information input by the tourist. Specific types and application criteria of audio guide methods include, but are not limited to, narration, dialogue, and interactive guide. For example, if the information input by the tourist is related to an activity, the audio guide device can apply an audio guide method specialized for the activity. Furthermore, if the information input by the tourist is related to a tourist destination, the audio guide device can also apply an audio guide method specialized for the tourist destination. Furthermore, if the information input by the tourist is related to an event, the audio guide device can also apply an audio guide method specialized for the event. This makes it possible to apply an appropriate audio guide method depending on the category of information input by the tourist.

[0067] The audio guide device can analyze the social media activities of tourists and provide relevant audio guides. Specific content and methods of providing the relevant audio guides include, but are not limited to, tourist attraction information, event information, and review information. For example, the audio guide device can provide relevant audio guides based on places where tourists have checked in on social media. The audio guide device can also analyze the content posted by tourists on social media and provide relevant tourist attraction information as an audio guide. Furthermore, the audio guide device can provide audio guides for related places and events based on the activities of the tourists' friends on social media. This makes it possible to provide relevant audio guides based on the tourists' social media activities.

[0068] The audio guide device can improve the accuracy of the audio guide by taking into account the tourist's geographical location information. Specific methods and criteria for improving the accuracy of the audio guide include, but are not limited to, data quality and algorithm improvements. For example, the audio guide device can prioritize information about tourist spots close to the tourist's current location as audio guide information. The audio guide device can also provide the optimal audio guide by taking into account the distance from the tourist's current location. Furthermore, the audio guide device can update the tourist's current location in real time while the tourist is moving and provide related audio guide information. This can improve the accuracy of the audio guide based on the tourist's geographical location information.

[0069] The audio guide device can optimize the audio guide algorithm by reflecting tourists' past feedback. Specific types and optimization methods of the audio guide algorithm include, but are not limited to, machine learning algorithms and statistical analysis methods. For example, the audio guide device optimizes the audio guide algorithm based on audio guides that tourists have preferred in the past. The audio guide device can also improve the audio guide algorithm based on tourists' past feedback. Furthermore, the audio guide device can adjust the audio guide method by reflecting tourists' past feedback. This makes it possible to optimize the audio guide algorithm based on tourists' past feedback.

[0070] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0071] The reception unit can obtain the congestion status of tourist spots in real time based on the tourist's input information and provide it to the analysis unit. For example, when a tourist inputs a place they want to visit, the reception unit obtains the current congestion status of that place and provides it to the analysis unit. The reception unit can also obtain the congestion status of activities in which the tourist is interested in in real time and provide it to the analysis unit. Furthermore, the reception unit can update the congestion status in real time while the tourist is traveling and provide it to the analysis unit. This allows the tourist to obtain a sightseeing plan that avoids crowds.

[0072] The analysis unit can analyze safety information for tourist destinations based on the tourist's input information and provide it to the generation unit. For example, when a tourist inputs a place they want to visit, the analysis unit analyzes the current safety information for that place and provides it to the generation unit. The analysis unit can also analyze safety information for activities in which the tourist is interested and provide it to the generation unit. Furthermore, the analysis unit can update the safety information in real time while the tourist is traveling and provide it to the generation unit. This allows tourists to obtain a safe sightseeing plan.

[0073] The generation unit can generate a sightseeing plan that takes into account environmental information about tourist destinations based on the tourist's input information. For example, when a tourist inputs a place they want to visit, the generation unit generates a sightseeing plan that takes into account environmental information about that place (weather, temperature, air quality, etc.). The generation unit can also generate a sightseeing plan that takes into account environmental information about activities in which the tourist is interested. Furthermore, the generation unit can update the environmental information in real time while the tourist is traveling and adjust the sightseeing plan. This allows the tourist to obtain a comfortable sightseeing plan.

[0074] The visual information providing device can display cultural event information for tourist destinations based on tourist input information. For example, when a tourist inputs a place they would like to visit, the visual information providing device displays cultural event information held at that location. The visual information providing device can also display cultural event information related to activities in which the tourist is interested. Furthermore, the visual information providing device can update and display cultural event information in real time while the tourist is moving, allowing the tourist to enjoy cultural events.

[0075] The audio guide device can provide audio information about local specialties of tourist destinations based on information input by tourists. For example, when a tourist inputs a place they would like to visit, the audio guide device will explain audio information about local specialties of that place. The audio guide device can also provide audio information about local specialties related to activities in which the tourist is interested. Furthermore, the audio guide device can update the local specialties information in real time while the tourist is traveling and provide it audio information. This allows tourists to enjoy local specialties.

[0076] The processing flow of the first embodiment will be briefly explained below.

[0077] Step 1: The reception unit accepts tourist information. This information includes places the tourist wants to visit and activities they are interested in. The reception unit accepts information entered by the tourist through a smartphone app, as well as voice and image input. Step 2: The analysis unit analyzes the information received by the reception unit. The analysis is performed using methods such as natural language processing, image analysis, and data mining. The analysis unit extracts data to generate the optimal sightseeing plan based on the tourist's input information. Step 3: The generator generates a sightseeing plan based on the information analyzed by the analyzer. The sightseeing plan includes a list of places to visit, a schedule, and activity suggestions. The generator generates a customized sightseeing plan based on the tourist's interests and preferences. Step 4: The visual information providing device displays the sightseeing plan generated by the generation unit. The visual information providing device may be a smartphone, tablet, digital signage, etc. The visual information providing device visually displays the sightseeing plan and supports tourists in navigating from their current location to their destination. Step 5: The audio guide device provides an audio guide based on the information provided by the visual information device. The audio guide device can be a smartphone app or a dedicated device. The audio guide device provides audio explanations about the history and culture of the tourist destination.

[0078] (Example 2) A tourism personal assistant system according to an embodiment of the present invention accepts and analyzes tourist information, generates a sightseeing plan, displays it on a visual information display device, and provides audio guidance through an audio guide device. In this tourism personal assistant system, tourists input information about tourist destinations through a smartphone app, and a multimodal AI analyzes the information to generate a sightseeing plan. The generated sightseeing plan is provided to tourists through smart glasses, which display real-time information about the tourist destinations and assist tourists in navigating from their current location to their destination. Furthermore, a digital human provides tourists with audio and visual guidance. For example, audio explanations of the history and culture of the tourist destination and visual indications of the tourist destination's highlights are provided. Tourists can also ask questions in real time through the smartphone app, and the digital human responds instantly to those questions. This allows tourists to enjoy a personalized sightseeing experience tailored to their interests and needs. Furthermore, the integration of smart glasses and a digital human facilitates smooth navigation and information gathering at tourist destinations, improving the efficiency of sightseeing. This allows the tourism personal assistant system to provide tourists with an optimal sightseeing experience. For example, it can generate sightseeing plans based on the places tourists want to visit and activities they are interested in, providing real-time navigation support. It can also provide audio information about the history and culture of tourist destinations, allowing tourists to have a deeper sightseeing experience. Furthermore, it can improve the efficiency of tourism by allowing tourists to ask questions in real time and receive instant answers.

[0079] A tourism personal assistant system according to an embodiment includes a reception unit, an analysis unit, a generation unit, a visual information providing device, and an audio guide device. The reception unit receives input information from a tourist. The input information from the tourist includes, but is not limited to, places the tourist wants to visit and activities the tourist is interested in. The reception unit receives information input by the tourist via a smartphone app, for example. The reception unit can also receive voice input and image input. The analysis unit analyzes the information received by the reception unit. The analysis can be performed using, for example, natural language processing, image analysis, data mining, or other methods, but is not limited to these examples. The analysis unit extracts data for generating an optimal tour plan based on the tourist's input information. The generation unit generates a tour plan based on the information analyzed by the analysis unit. The tour plan can include, for example, a list of places to visit, a schedule, and activity suggestions, but is not limited to these examples. The generation unit generates a customized tour plan based on, for example, the tourist's interests and preferences. The visual information providing device displays the tour plan generated by the generation unit. Examples of the visual information providing device include, but are not limited to, smartphones, tablets, digital signage, etc. The visual information providing device visually displays, for example, a sightseeing plan and supports tourists in navigating from their current location to their destination. The audio guide device provides audio guidance based on information provided by the visual information providing device. Examples of the audio guide device include, but are not limited to, smartphone apps and dedicated devices. The audio guide device provides audio explanations, for example, of information about the history and culture of tourist destinations. This allows the tourism personal assistant system according to the embodiment to provide tourists with an individually optimized sightseeing experience.

[0080] The reception unit can accept information about places that tourists want to visit and activities that they are interested in. Information about places that tourists want to visit and activities that they are interested in includes, but is not limited to, examples of place names, facility names, and types of activities. For example, the reception unit accepts place names and facility names entered by tourists through a smartphone app. The reception unit can also accept input of types of activities that tourists are interested in. For example, if a tourist simply enters "I want to go to a museum," the reception unit can accept that information. This makes it possible to accept information based on the tourist's specific wishes.

[0081] The analysis unit can analyze the information received by the reception unit and generate a sightseeing plan suitable for the tourist. Specific criteria and generation methods for a sightseeing plan suitable for the tourist include, but are not limited to, a customization method based on individual interests and preferences. The analysis unit can, for example, analyze the information input by the tourist using natural language processing technology to extract the tourist's interests and preferences. The analysis unit can also identify tourist spots of interest from images taken by the tourist using image analysis technology. Furthermore, the analysis unit can analyze the tourist's past visit history and evaluation data using data mining technology to extract data for generating an optimal sightseeing plan. This makes it possible to provide the tourist with an optimal sightseeing plan.

[0082] The generation unit can generate a sightseeing plan based on the information analyzed by the analysis unit. Examples of methods and criteria for generating a sightseeing plan include, but are not limited to, types of algorithms and factors to consider. For example, the generation unit uses a machine learning algorithm to generate a customized sightseeing plan based on the tourist's interests and preferences. The generation unit can also generate a sightseeing plan including a list of places to visit, a schedule, and activity suggestions based on the tourist's input information. Furthermore, the generation unit can generate an optimal sightseeing plan by taking into account the tourist's past visit history and evaluation data. This allows a sightseeing plan to be generated based on the analysis results.

[0083] The visual information providing device can display the sightseeing plan generated by the generation unit. Examples of display methods and standards for the sightseeing plan include, but are not limited to, display formats and interface designs. The visual information providing device visually displays the sightseeing plan using, for example, a smartphone, a tablet, or digital signage. The visual information providing device can also display real-time map information and route guidance to support tourists in navigating from their current location to their destination. Furthermore, the visual information providing device can display real-time information about tourist destinations to help tourists move around and gather information at tourist destinations smoothly. This allows the sightseeing plan to be visually provided.

[0084] The audio guide device can provide audio guidance based on information provided by the visual information providing device. The methods and standards for providing audio guidance include, but are not limited to, the type of audio and selection criteria for the content of the guidance. For example, the audio guide device provides audio explanations of information about the history and culture of a tourist destination using a smartphone app or a dedicated device. The audio guide device can also provide visual information linked to the audio to visually indicate the highlights of the tourist destination. Furthermore, the audio guide device can also provide audio information such as the opening hours and access methods of the tourist destination. This allows audio guidance to be provided based on visual information.

[0085] The visual information providing device can display real-time information about tourist destinations to support tourists in navigating from their current location to their destination. Examples of real-time information about tourist destinations include, but are not limited to, weather information, crowding status, and event information. The visual information providing device can display real-time information about tourist destinations using, for example, a smartphone or tablet. The visual information providing device can also display real-time map information and route guidance to support tourists in navigating from their current location to their destination. Furthermore, the visual information providing device can display real-time crowding status and event information about tourist destinations to support tourists in moving around and gathering information at tourist destinations. This allows for the provision of real-time information about tourist destinations to support navigation.

[0086] The audio guide device can provide audio explanations of information about the history and culture of a tourist destination. Examples of information about the history and culture of a tourist destination include, but are not limited to, historical background and cultural significance. The audio guide device can provide audio explanations of information about the history and culture of a tourist destination using, for example, a smartphone app or a dedicated device. The audio guide device can also provide visual information linked to the audio to visually indicate the highlights of the tourist destination. Furthermore, the audio guide device can also provide audio information such as the opening hours and access methods of the tourist destination. This allows audio provision of information about the history and culture of a tourist destination.

[0087] The audio guide device can visually show the highlights of a tourist destination. Examples of the highlights of a tourist destination include, but are not limited to, tourist spots, famous places, and activities. The audio guide device can visually show the highlights of a tourist destination using, for example, a smartphone app or a dedicated device. The audio guide device can also provide audio information about the history and culture of the tourist destination. Furthermore, the audio guide device can also provide audio information such as the opening hours and access methods of the tourist destination. This makes it possible to visually present the highlights of a tourist destination.

[0088] The reception unit can accept questions from tourists in real time through a smartphone app. Specific methods and standards for accepting questions in real time include, but are not limited to, chatbots and live support. For example, the reception unit accepts questions entered by tourists through a smartphone app in real time. The reception unit can also accept questions entered by tourists via voice. For example, if a tourist asks, "What are the opening hours of this tourist attraction?", the reception unit can accept the question. This allows tourists to ask questions in real time.

[0089] The audio guide device can provide information such as the opening hours and access methods of tourist attractions. Information such as the opening hours and access methods of tourist attractions includes, but is not limited to, the format of the opening hours and details of the access methods. The audio guide device can provide information such as the opening hours and access methods of tourist attractions by voice, for example, using a smartphone app or a dedicated device. The audio guide device can also provide visual information linked to the voice to visually show the highlights of the tourist attractions. Furthermore, the audio guide device can also provide information about the history and culture of the tourist attractions by voice. This makes it possible to provide information such as the opening hours and access methods of tourist attractions.

[0090] The reception unit can estimate the tourist's emotions and prioritize input information based on the estimated tourist's emotions. Specific methods and criteria for estimating the tourist's emotions include, but are not limited to, facial expression recognition, voice analysis, and text analysis. For example, the reception unit can capture the tourist's facial expressions with a camera and estimate the emotion using an emotion estimation algorithm. The reception unit can also record the tourist's voice and estimate the emotion using voice analysis technology. The reception unit can also analyze the tourist's text input and estimate the emotion. For example, if the tourist is excited, the reception unit can prioritize displaying information about activities that the tourist is interested in. Also, if the tourist is tired, the reception unit can prioritize displaying information about places and activities where the tourist can relax. This makes it possible to prioritize input information based on the tourist's emotions.

[0091] The reception unit can analyze the tourist's past visit history and suggest the optimal input method. Specific content and analysis methods of the tourist's past visit history include, but are not limited to, the places visited, the number of visits, and the length of stay. For example, the reception unit can automatically display the places visited by the tourist in the past as candidates. The reception unit can also preferentially suggest input methods (voice, text, etc.) that the tourist has used in the past. Furthermore, the reception unit can predict and suggest places and activities to be used during a specific time period based on the tourist's past visit history. This makes it possible to suggest the optimal input method based on the tourist's past visit history.

[0092] The reception unit can automatically suggest related tourist attraction information based on the tourist's current location information. Specific methods for acquiring and using the tourist's current location information include, but are not limited to, GPS data, location information services, etc. The reception unit, for example, automatically suggests tourist attractions close to the tourist's current location. The reception unit can also suggest the most suitable tourist attraction taking into account the distance from the tourist's current location. Furthermore, the reception unit can update the tourist's current location in real time while the tourist is moving and suggest related tourist attraction information. This makes it possible to suggest related tourist attraction information based on the tourist's current location information.

[0093] The reception unit can select an appropriate input means depending on the tourist's input method. Specific types and selection criteria of the tourist's input method include, but are not limited to, voice input, text input, and image input. For example, the reception unit can provide optimal tourist destination information when the tourist simply inputs "I want to go to the museum" by voice. The reception unit can also provide related tourist destination information based on images taken by the tourist with the smartphone camera. Furthermore, the reception unit can provide optimal tourist destination information based on information entered by the tourist as text. This makes it possible to provide the optimal input means depending on the tourist's input method.

[0094] The reception unit can estimate the tourist's emotions and adjust the design of the input interface based on the estimated tourist's emotions. Specific methods and standards for estimating the tourist's emotions include, but are not limited to, facial expression recognition, voice analysis, and text analysis. For example, the reception unit can capture the tourist's facial expressions with a camera and estimate the emotion using an emotion estimation algorithm. The reception unit can also record the tourist's voice and estimate the emotion using voice analysis technology. The reception unit can also analyze the tourist's text input to estimate the emotion. For example, if the tourist is nervous, the reception unit can provide an interface with calm colors to reduce visual stress. If the tourist is having fun, the reception unit can provide an interface with bright colors to make the input task more enjoyable. This makes it possible to adjust the design of the input interface based on the tourist's emotions.

[0095] The reception unit can customize the input method by reflecting the tourists' past feedback. Specific content and reflection methods of the tourists' past feedback include, but are not limited to, survey results, review comments, etc. The reception unit, for example, preferentially suggests input methods that the tourists have previously preferred. The reception unit can also improve the input interface based on the tourists' past feedback. Furthermore, the reception unit can also simplify the input procedure by reflecting the tourists' past feedback. This makes it possible to customize the input method based on the tourists' past feedback.

[0096] The reception unit can prioritize acquiring highly relevant tourist destination information by taking into account the tourist's geographical location information. Specific methods for acquiring and using the tourist's geographical location information include, but are not limited to, GPS data, location information services, etc. For example, the reception unit prioritizes acquiring tourist destination information close to the tourist's current location. The reception unit can also acquire optimal tourist destination information by taking into account the distance from the tourist's current location. Furthermore, the reception unit can update the tourist's current location in real time while the tourist is moving and acquire highly relevant tourist destination information. This makes it possible to acquire highly relevant tourist destination information based on the tourist's geographical location information.

[0097] The reception unit can analyze the tourist's social media activity and automatically suggest related tourist attraction information. Specific content and analysis methods of the tourist's social media activity include, but are not limited to, for example, the content of posts, the number of likes, and the number of followers. The reception unit can also suggest related tourist attraction information based on, for example, the places where the tourist checked in on social media. The reception unit can also analyze the content of the tourist's social media posts and suggest related tourist attraction information. Furthermore, the reception unit can also suggest related tourist attraction information based on the activities of the tourist's friends on social media. In this way, related tourist attraction information can be suggested based on the tourist's social media activity.

[0098] The analysis unit can estimate the tourist's emotions and determine the analysis priority based on the estimated tourist's emotions. Specific methods and criteria for estimating the tourist's emotions include, but are not limited to, facial expression recognition, voice analysis, and text analysis. For example, the analysis unit can capture the tourist's facial expressions with a camera and estimate the emotion using an emotion estimation algorithm. The analysis unit can also record the tourist's voice and estimate the emotion using voice analysis technology. The analysis unit can also analyze the tourist's text input and estimate the emotion. For example, if the tourist is excited, the analysis unit can prioritize analyzing information about activities that interest the tourist. Also, if the tourist is tired, the analysis unit can prioritize analyzing information about places and activities where the tourist can relax. This makes it possible to determine the analysis priority based on the tourist's emotions.

[0099] The analysis unit can improve the accuracy of the analysis by referring to the tourist's past visit history. Specific content and analysis methods of the tourist's past visit history include, but are not limited to, the places visited, the number of visits, and the length of stay. For example, the analysis unit can propose an optimal sightseeing plan based on the places the tourist has visited in the past. The analysis unit can also propose a route that avoids crowds based on the tourist's past visit history. Furthermore, the analysis unit can analyze the tourist's past visit history and propose the most efficient sightseeing plan. This can improve the accuracy of the analysis based on the tourist's past visit history.

[0100] The analysis unit can adjust the analysis algorithm based on the tourist's current interests and concerns. Specific methods and criteria for adjusting the analysis algorithm based on the tourist's current interests and concerns include, but are not limited to, machine learning algorithms and statistical analysis methods. For example, the analysis unit can adjust the analysis algorithm based on activities in which the tourist is currently interested. The analysis unit can also adjust the analysis algorithm based on tourist destinations in which the tourist is currently interested. Furthermore, the analysis unit can adjust the analysis algorithm to propose an optimal sightseeing plan based on the tourist's current interests and concerns. This makes it possible to adjust the analysis algorithm based on the tourist's current interests and concerns.

[0101] The analysis unit can apply different analysis methods depending on the category of the information input by the tourist. Specific types and application criteria of analysis methods include, but are not limited to, text analysis, image analysis, data mining, etc. For example, if the information input by the tourist is related to an activity, the analysis unit applies an analysis method specialized for activities. Furthermore, if the information input by the tourist is related to a tourist destination, the analysis unit can also apply an analysis method specialized for tourist destinations. Furthermore, if the information input by the tourist is related to an event, the analysis unit can also apply an analysis method specialized for events. This makes it possible to apply an appropriate analysis method depending on the category of the information input by the tourist.

[0102] The analysis unit can estimate the tourist's emotions and adjust the display method of the analysis results based on the estimated tourist's emotions. Specific methods and standards for estimating the tourist's emotions include, but are not limited to, facial expression recognition, voice analysis, and text analysis. For example, the analysis unit can capture the tourist's facial expressions with a camera and estimate the emotion using an emotion estimation algorithm. The analysis unit can also record the tourist's voice and estimate the emotion using voice analysis technology. The analysis unit can also analyze the tourist's text input and estimate the emotion. For example, if the tourist is nervous, the analysis unit can provide a simple and highly visible display method. If the tourist is relaxed, the analysis unit can provide a display method including detailed information. This makes it possible to adjust the display method of the analysis results based on the tourist's emotions.

[0103] The analysis unit can analyze the social media activities of tourists and reflect related information in the analysis. Specific content and acquisition methods of the related information include, but are not limited to, tourist attraction information, event information, and review information. For example, the analysis unit analyzes related tourist attraction information based on the locations where tourists check in on social media. The analysis unit can also analyze the content of tourists' social media posts and analyze related tourist attraction information. Furthermore, the analysis unit can analyze related tourist attraction information by referring to the activities of the tourists' friends on social media. This makes it possible to reflect related information based on the tourists' social media activities in the analysis.

[0104] The analysis unit can improve the accuracy of the analysis by taking into account the tourist's geographical location information. Specific methods and criteria for improving the accuracy of the analysis include, but are not limited to, data quality and algorithm improvements. For example, the analysis unit prioritizes analyzing tourist destination information close to the tourist's current location. The analysis unit can also analyze optimal tourist destination information by taking into account the distance from the tourist's current location. Furthermore, the analysis unit can update the tourist's current location in real time while the tourist is moving and analyze related tourist destination information. This can improve the accuracy of the analysis based on the tourist's geographical location information.

[0105] The analysis unit can optimize the analysis algorithm by reflecting the tourists' past feedback. Specific types and optimization methods of the analysis algorithm include, but are not limited to, machine learning algorithms and statistical analysis methods, for example. The analysis unit optimizes the analysis algorithm based on sightseeing plans that tourists have previously preferred, for example. The analysis unit can also improve the analysis algorithm based on the tourists' past feedback. Furthermore, the analysis unit can adjust the analysis method by reflecting the tourists' past feedback. This makes it possible to optimize the analysis algorithm based on the tourists' past feedback.

[0106] The generation unit can estimate the tourist's emotions and prioritize the sightseeing plans based on the estimated tourist's emotions. Specific criteria and methods for prioritizing the sightseeing plans include, but are not limited to, importance, urgency, and relevance. For example, the generation unit can use techniques such as facial expression recognition, voice analysis, and text analysis to estimate the tourist's emotions. The generation unit can also use a machine learning algorithm to prioritize the sightseeing plans based on the tourist's emotions. For example, if the tourist is excited, the generation unit can prioritize displaying information about activities that the tourist is interested in. Also, if the tourist is tired, the generation unit can prioritize displaying information about places and activities where the tourist can relax. This makes it possible to prioritize the sightseeing plans based on the tourist's emotions.

[0107] The generation unit can improve the accuracy of the sightseeing plan by referring to the tourist's past visit history. Specific methods and criteria for improving the accuracy of the sightseeing plan include, but are not limited to, for example, data quality and algorithm improvements. For example, the generation unit can propose an optimal sightseeing plan based on the tourist's past visit history. The generation unit can also propose a route that avoids crowds based on the tourist's past visit history. Furthermore, the generation unit can analyze the tourist's past visit history and propose the most efficient sightseeing plan. This makes it possible to improve the accuracy of the sightseeing plan based on the tourist's past visit history.

[0108] The generation unit can customize the sightseeing plan based on the tourist's current interests and concerns. Specific methods and criteria for customizing the sightseeing plan include, but are not limited to, customization methods based on individual interests and preferences. For example, the generation unit customizes the sightseeing plan based on activities in which the tourist is currently interested. The generation unit can also customize the sightseeing plan based on tourist destinations in which the tourist is currently interested. Furthermore, the generation unit can customize the sightseeing plan to propose an optimal sightseeing plan based on the tourist's current interests and concerns. This makes it possible to customize the sightseeing plan based on the tourist's current interests and concerns.

[0109] The generation unit can apply different tour plan generation methods depending on the category of the tourist's input information. Specific types and application criteria of tour plan generation methods include, for example, types of algorithms and factors to be considered, but are not limited to these examples. For example, if the information input by the tourist is related to an activity, the generation unit can apply a tour plan generation method specialized for activities. Furthermore, if the information input by the tourist is related to a tourist destination, the generation unit can also apply a tour plan generation method specialized for tourist destinations. Furthermore, if the information input by the tourist is related to an event, the generation unit can also apply a tour plan generation method specialized for events. This makes it possible to apply an appropriate tour plan generation method depending on the category of the tourist's input information.

[0110] The generation unit can estimate the tourist's emotions and adjust the display method of the tour plan based on the estimated tourist's emotions. Specific content and adjustment methods of the display method of the tour plan include, but are not limited to, display format, interface design, etc. The generation unit can use technologies such as facial expression recognition, voice analysis, and text analysis to estimate the tourist's emotions. The generation unit can also use machine learning algorithms to adjust the display method of the tour plan based on the tourist's emotions. For example, if the tourist is nervous, the generation unit can provide a simple, highly visible display method. Alternatively, if the tourist is relaxed, the generation unit can provide a display method that includes detailed information. This makes it possible to adjust the display method of the tour plan based on the tourist's emotions.

[0111] The generation unit can analyze the tourist's social media activities and reflect related information in the tour plan. Specific content and acquisition methods of the related information include, but are not limited to, tourist attraction information, event information, and review information. For example, the generation unit can reflect related tourist attraction information in the tour plan based on the places where the tourist checks in on social media. The generation unit can also analyze the content of the tourist's social media posts and reflect related tourist attraction information in the tour plan. Furthermore, the generation unit can also reflect related tourist attraction information in the tour plan based on the activities of the tourist's friends on social media. In this way, related information based on the tourist's social media activities can be reflected in the tour plan.

[0112] The generation unit can improve the accuracy of the sightseeing plan by taking into account the tourist's geographical location information. Specific methods and criteria for improving the accuracy of the sightseeing plan include, but are not limited to, data quality and algorithm improvements. For example, the generation unit preferentially reflects tourist destination information close to the tourist's current location in the sightseeing plan. The generation unit can also reflect optimal tourist destination information in the sightseeing plan by taking into account the tourist's distance from the current location. Furthermore, the generation unit can update the tourist's current location in real time while the tourist is moving and reflect related tourist destination information in the sightseeing plan. This can improve the accuracy of the sightseeing plan based on the tourist's geographical location information.

[0113] The generation unit can optimize the tour plan generation algorithm by reflecting the tourists' past feedback. Specific types and optimization methods of the tour plan generation algorithm include, but are not limited to, machine learning algorithms and statistical analysis methods. For example, the generation unit optimizes the tour plan generation algorithm based on tour plans that tourists have previously preferred. The generation unit can also improve the tour plan generation algorithm based on the tourists' past feedback. Furthermore, the generation unit can adjust the tour plan generation method by reflecting the tourists' past feedback. This makes it possible to optimize the tour plan generation algorithm based on the tourists' past feedback.

[0114] The visual information providing device can estimate the tourist's emotions and adjust the visual information display method based on the estimated tourist's emotions. Specific content and adjustment methods of the visual information display method include, but are not limited to, display format, interface design, etc. The visual information providing device can use technologies such as facial expression recognition, voice analysis, and text analysis to estimate the tourist's emotions. The visual information providing device can also use machine learning algorithms to adjust the visual information display method based on the tourist's emotions. For example, if the tourist is nervous, the visual information providing device can provide visual information in calm colors to reduce visual stress. Alternatively, if the tourist is enjoying themselves, the visual information providing device can provide visual information in bright colors to make the tourist experience more enjoyable. This allows the visual information display method to be adjusted based on the tourist's emotions.

[0115] The visual information providing device can customize the display content of the visual information by referring to the tourist's past visit history. Specific customization methods and criteria for the display content of the visual information include, but are not limited to, customization methods based on individual interests and preferences, for example. The visual information providing device can display related visual information based on, for example, places that the tourist has visited in the past. The visual information providing device can also display visual information that is likely to be of interest to the tourist based on the tourist's past visit history. Furthermore, the visual information providing device can analyze the tourist's past visit history and display the most appropriate visual information. This makes it possible to customize the display content of the visual information based on the tourist's past visit history.

[0116] The visual information providing device can provide real-time visual information based on the tourist's current location information. Specific content and acquisition methods of the real-time visual information include, but are not limited to, weather information, congestion status, and event information. For example, the visual information providing device can provide the tourist with real-time information about tourist spots close to the tourist's current location. The visual information providing device can also provide the tourist with optimal real-time information taking into account the distance from the tourist's current location. Furthermore, the visual information providing device can update the tourist's current location in real time while the tourist is moving and provide related visual information. This makes it possible to provide real-time visual information based on the tourist's current location information.

[0117] The visual information providing device can apply different visual information display methods depending on the category of information input by the tourist. Specific types and application criteria of visual information display methods include, but are not limited to, graph display, text display, interactive display, etc. For example, if the information input by the tourist is related to an activity, the visual information providing device can apply a visual information display method specialized for the activity. Furthermore, if the information input by the tourist is related to a tourist destination, the visual information providing device can also apply a visual information display method specialized for the tourist destination. Furthermore, if the information input by the tourist is related to an event, the visual information providing device can also apply a visual information display method specialized for the event. This makes it possible to apply an appropriate visual information display method depending on the category of information input by the tourist.

[0118] The visual information providing device can estimate the tourist's emotions and prioritize the visual information based on the estimated tourist's emotions. Specific criteria and methods for prioritizing the visual information include, but are not limited to, importance, urgency, and relevance. For example, the visual information providing device can use technologies such as facial expression recognition, voice analysis, and text analysis to estimate the tourist's emotions. The visual information providing device can also use a machine learning algorithm to prioritize the visual information based on the tourist's emotions. For example, if the tourist is excited, the visual information providing device can prioritize displaying visual information related to activities that interest the tourist. Also, if the tourist is tired, the visual information providing device can prioritize displaying visual information related to places and activities where the tourist can relax. This allows the priority of the visual information to be determined based on the tourist's emotions.

[0119] The visual information providing device can analyze the social media activities of tourists and provide related visual information. Specific content and acquisition methods of the related visual information include, but are not limited to, tourist attraction information, event information, and review information. For example, the visual information providing device can provide related visual information based on the locations where tourists check in on social media. The visual information providing device can also analyze the content posted by tourists on social media and provide related visual information. Furthermore, the visual information providing device can provide related visual information by referring to the activities of the tourists' friends on social media. This makes it possible to provide related visual information based on the tourists' social media activities.

[0120] The visual information providing device can improve the accuracy of visual information by taking into account the tourist's geographical location information. Specific methods and criteria for improving the accuracy of visual information include, but are not limited to, data quality and algorithm improvements. For example, the visual information providing device can provide tourist information that is close to the tourist's current location as visual information. The visual information providing device can also provide optimal visual information by taking into account the distance from the tourist's current location. Furthermore, the visual information providing device can update the tourist's current location in real time while the tourist is moving and provide related visual information. This can improve the accuracy of visual information based on the tourist's geographical location information.

[0121] The visual information providing device can optimize the visual information display algorithm by reflecting the tourists' past feedback. Specific types and optimization methods of the visual information display algorithm include, but are not limited to, machine learning algorithms and statistical analysis methods, for example. The visual information providing device can optimize the visual information display algorithm based on the visual information that the tourists have previously preferred. The visual information providing device can also improve the visual information display algorithm based on the tourists' past feedback. Furthermore, the visual information providing device can adjust the visual information display method by reflecting the tourists' past feedback. This makes it possible to optimize the visual information display algorithm based on the tourists' past feedback.

[0122] The audio guide device can estimate the tourist's emotions and adjust the content of the audio guide based on the estimated tourist's emotions. Specific methods and criteria for adjusting the content of the audio guide include, but are not limited to, selection criteria for the content of the audio guide and the type of audio. For example, the audio guide device uses technologies such as facial expression recognition, voice analysis, and text analysis to estimate the tourist's emotions. The audio guide device can also use machine learning algorithms to adjust the content of the audio guide based on the tourist's emotions. For example, if the tourist is nervous, the audio guide device can provide guidance in a calm voice. On the other hand, if the tourist is relaxed, the audio guide device can provide guidance in a cheerful voice. This makes it possible to adjust the content of the audio guide based on the tourist's emotions.

[0123] The audio guide device can customize the content of the audio guide by referring to the tourist's past visit history. Specific customization methods and criteria for the content of the audio guide include, but are not limited to, customization methods based on individual interests and preferences. For example, the audio guide device can provide a relevant audio guide based on places the tourist has visited in the past. The audio guide device can also provide an audio guide that is likely to be of interest to the tourist based on the tourist's past visit history. Furthermore, the audio guide device can analyze the tourist's past visit history and provide the most appropriate audio guide. This makes it possible to customize the content of the audio guide based on the tourist's past visit history.

[0124] The audio guide device can provide real-time audio guidance based on the tourist's current location information. Specific content and provision methods of the real-time audio guidance include, but are not limited to, guidance content based on current location information. For example, the audio guide device can provide the tourist with real-time information about tourist spots close to the tourist's current location by voice. The audio guide device can also provide the tourist with optimal real-time audio guidance taking into account the distance from the tourist's current location. Furthermore, the audio guide device can update the tourist's current location in real time while the tourist is moving and provide related audio guidance. This makes it possible to provide real-time audio guidance based on the tourist's current location information.

[0125] The audio guide device can apply different audio guide methods depending on the category of information input by the tourist. Specific types and application criteria of audio guide methods include, but are not limited to, narration, dialogue, and interactive guide. For example, if the information input by the tourist is related to an activity, the audio guide device can apply an audio guide method specialized for the activity. Furthermore, if the information input by the tourist is related to a tourist destination, the audio guide device can also apply an audio guide method specialized for the tourist destination. Furthermore, if the information input by the tourist is related to an event, the audio guide device can also apply an audio guide method specialized for the event. This makes it possible to apply an appropriate audio guide method depending on the category of information input by the tourist.

[0126] The audio guide device can estimate the tourist's emotions and determine the priority of audio guides based on the estimated tourist's emotions. Specific criteria and methods for determining the priority of audio guides include, but are not limited to, importance, urgency, and relevance. For example, the audio guide device can use technologies such as facial expression recognition, voice analysis, and text analysis to estimate the tourist's emotions. The audio guide device can also use machine learning algorithms to determine the priority of audio guides based on the tourist's emotions. For example, if the tourist is excited, the audio guide device can prioritize providing audio guides for activities that interest the tourist. Also, if the tourist is tired, the audio guide device can prioritize providing audio guides for places and activities that help the tourist relax. This allows the priority of audio guides to be determined based on the tourist's emotions.

[0127] The audio guide device can analyze the social media activities of tourists and provide relevant audio guides. Specific content and methods of providing the relevant audio guides include, but are not limited to, tourist attraction information, event information, and review information. For example, the audio guide device can provide relevant audio guides based on places where tourists have checked in on social media. The audio guide device can also analyze the content posted by tourists on social media and provide relevant tourist attraction information as an audio guide. Furthermore, the audio guide device can provide audio guides for related places and events based on the activities of the tourists' friends on social media. This makes it possible to provide relevant audio guides based on the tourists' social media activities.

[0128] The audio guide device can improve the accuracy of the audio guide by taking into account the tourist's geographical location information. Specific methods and criteria for improving the accuracy of the audio guide include, but are not limited to, data quality and algorithm improvements. For example, the audio guide device can prioritize information about tourist spots close to the tourist's current location as audio guide information. The audio guide device can also provide the optimal audio guide by taking into account the distance from the tourist's current location. Furthermore, the audio guide device can update the tourist's current location in real time while the tourist is moving and provide related audio guide information. This can improve the accuracy of the audio guide based on the tourist's geographical location information.

[0129] The audio guide device can optimize the audio guide algorithm by reflecting tourists' past feedback. Specific types and optimization methods of the audio guide algorithm include, but are not limited to, machine learning algorithms and statistical analysis methods. For example, the audio guide device optimizes the audio guide algorithm based on audio guides that tourists have preferred in the past. The audio guide device can also improve the audio guide algorithm based on tourists' past feedback. Furthermore, the audio guide device can adjust the audio guide method by reflecting tourists' past feedback. This makes it possible to optimize the audio guide algorithm based on tourists' past feedback. === Hard Collateral 1-1 === Each of the above-mentioned elements, including the reception unit, analysis unit, generation unit, visual information providing device, and audio guide device, is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart device 14 and receives input information from tourists. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the information received by the reception unit. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates a tour plan based on the analyzed information. The visual information providing device is realized by the output device 40 of the smart device 14 and displays the generated tour plan. The audio guide device is realized by the output device 40B of the smart device 14 and provides information about tourist spots by audio. === Hard Collateral 1-2 === Each of the multiple elements, including the above-mentioned reception unit, analysis unit, generation unit, visual information providing device, and audio guide device, is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart glasses 214 and receives input information from the tourist. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the information received by the reception unit. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates a sightseeing plan based on the analyzed information. The visual information providing device is realized by the display of the smart glasses 214 and displays the generated sightseeing plan. The audio guide device is realized by the speaker 240 of the smart glasses 214 and provides information about tourist destinations by voice. === Hard Collateral 1-3 === Each of the multiple elements, including the above-mentioned reception unit, analysis unit, generation unit, visual information providing device, and audio guide device, is realized, for example, by at least one of the headset terminal 314 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the headset terminal 314 and receives information input by the tourist. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the information received by the reception unit. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates a tour plan based on the analyzed information. The visual information providing device is realized by the display 343 of the headset terminal 314 and displays the generated tour plan. The audio guide device is realized by the speaker 240 of the headset terminal 314 and provides information about tourist spots by voice. === Hard Collateral 1-4 === Each of the multiple elements including the above-mentioned reception unit, analysis unit, generation unit, visual information providing device, and audio guide device is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the robot 414 and receives input information from tourists. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the information received by the reception unit. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates a tour plan based on the analyzed information. The visual information providing device is realized by the display device of the robot 414 and displays the generated tour plan. The audio guide device is realized by the speaker 240 of the robot 414 and provides information about tourist spots by voice.

[0130] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0131] The reception unit can obtain the congestion status of tourist spots in real time based on the tourist's input information and provide it to the analysis unit. For example, when a tourist inputs a place they want to visit, the reception unit obtains the current congestion status of that place and provides it to the analysis unit. The reception unit can also obtain the congestion status of activities in which the tourist is interested in in real time and provide it to the analysis unit. Furthermore, the reception unit can update the congestion status in real time while the tourist is traveling and provide it to the analysis unit. This allows the tourist to obtain a sightseeing plan that avoids crowds.

[0132] The analysis unit can analyze safety information for tourist destinations based on the tourist's input information and provide it to the generation unit. For example, when a tourist inputs a place they want to visit, the analysis unit analyzes the current safety information for that place and provides it to the generation unit. The analysis unit can also analyze safety information for activities in which the tourist is interested and provide it to the generation unit. Furthermore, the analysis unit can update the safety information in real time while the tourist is traveling and provide it to the generation unit. This allows tourists to obtain a safe sightseeing plan.

[0133] The generation unit can generate a sightseeing plan that takes into account environmental information about tourist destinations based on the tourist's input information. For example, when a tourist inputs a place they want to visit, the generation unit generates a sightseeing plan that takes into account environmental information about that place (weather, temperature, air quality, etc.). The generation unit can also generate a sightseeing plan that takes into account environmental information about activities in which the tourist is interested. Furthermore, the generation unit can update the environmental information in real time while the tourist is traveling and adjust the sightseeing plan. This allows the tourist to obtain a comfortable sightseeing plan.

[0134] The visual information providing device can display cultural event information for tourist destinations based on tourist input information. For example, when a tourist inputs a place they would like to visit, the visual information providing device displays cultural event information held at that location. The visual information providing device can also display cultural event information related to activities in which the tourist is interested. Furthermore, the visual information providing device can update and display cultural event information in real time while the tourist is moving, allowing the tourist to enjoy cultural events.

[0135] The audio guide device can provide audio information about local specialties of tourist destinations based on information input by tourists. For example, when a tourist inputs a place they would like to visit, the audio guide device will explain audio information about local specialties of that place. The audio guide device can also provide audio information about local specialties related to activities in which the tourist is interested. Furthermore, the audio guide device can update the local specialties information in real time while the tourist is traveling and provide it audio information. This allows tourists to enjoy local specialties.

[0136] The reception unit can estimate the tourist's emotions and provide recommended information about tourist spots based on the estimated emotions. For example, if the tourist is excited, the reception unit can prioritize suggesting active activities. Also, if the tourist is relaxed, the reception unit can prioritize suggesting places and activities where the tourist can relax. Furthermore, if the tourist is tired, the reception unit can prioritize suggesting places and activities where the tourist can rest. In this way, optimal tourist spot information can be provided based on the tourist's emotions.

[0137] The analysis unit can estimate the tourist's emotions, analyze the congestion status of tourist spots based on the estimated emotions, and provide the analysis results to the generation unit. For example, if the tourist is excited, the analysis unit can prioritize analyzing the congestion status of active activities. Also, if the tourist is relaxed, the analysis unit can prioritize analyzing the congestion status of relaxation areas. Furthermore, if the tourist is tired, the analysis unit can prioritize analyzing the congestion status of rest areas. This makes it possible to provide an optimal sightseeing plan based on the tourist's emotions.

[0138] The generation unit can estimate the tourist's emotions and adjust the display method of the sightseeing plan based on the estimated emotions. For example, if the tourist is nervous, the generation unit can provide a simple, highly visible display method. If the tourist is relaxed, the generation unit can also provide a display method including detailed information. Furthermore, if the tourist is having fun, the generation unit can also provide a display method with bright colors. In this way, the display method of the sightseeing plan can be adjusted based on the tourist's emotions.

[0139] The visual information providing device can estimate the tourist's emotions and adjust the way visual information is displayed based on the estimated emotions. For example, if the tourist is nervous, the visual information providing device can provide visual information in calm colors to reduce visual stress. If the tourist is having fun, the visual information providing device can provide visual information in bright colors to make the tourist experience more enjoyable. Furthermore, if the tourist is tired, the visual information providing device can provide visual information that helps them relax. In this way, the way visual information is displayed can be adjusted based on the tourist's emotions.

[0140] The audio guide device can estimate the tourist's emotions and adjust the content of the audio guide based on the estimated emotions. For example, if the tourist is nervous, the audio guide device can provide guidance in a calm voice. If the tourist is relaxed, the audio guide device can provide guidance in a cheerful voice. Furthermore, if the tourist is having fun, the audio guide device can provide guidance in a cheerful voice. In this way, the content of the audio guide can be adjusted based on the tourist's emotions.

[0141] The processing flow of the second embodiment will be briefly explained below.

[0142] Step 1: The reception unit accepts tourist information. This information includes places the tourist wants to visit and activities they are interested in. The reception unit accepts information entered by the tourist through a smartphone app, as well as voice and image input. Step 2: The analysis unit analyzes the information received by the reception unit. The analysis is performed using methods such as natural language processing, image analysis, and data mining. The analysis unit extracts data to generate the optimal sightseeing plan based on the tourist's input information. Step 3: The generator generates a sightseeing plan based on the information analyzed by the analyzer. The sightseeing plan includes a list of places to visit, a schedule, and activity suggestions. The generator generates a customized sightseeing plan based on the tourist's interests and preferences. Step 4: The visual information providing device displays the sightseeing plan generated by the generation unit. The visual information providing device may be a smartphone, tablet, digital signage, etc. The visual information providing device visually displays the sightseeing plan and supports tourists in navigating from their current location to their destination. Step 5: The audio guide device provides an audio guide based on the information provided by the visual information device. The audio guide device can be a smartphone app or a dedicated device. The audio guide device provides audio explanations about the history and culture of the tourist destination.

[0143] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0144] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0145] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0146] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0147] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0148] 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.

[0149] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0150] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0151] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0152] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0153] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0154] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0155] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0156] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0157] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0158] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0159] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0160] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0161] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0162] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0163] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0164] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0165] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0166] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0167] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0168] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0169] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0170] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0171] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0172] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0173] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0174] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0175] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0176] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0177] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0178] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0179] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0180] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0181] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0182] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0183] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0184] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0185] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0186] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0187] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0188] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0189] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0190] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0191] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0192] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0193] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0194] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0195] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0196] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0197] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0198] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0199] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0200] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0201] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0202] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0203] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0204] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0205] 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.

[0206] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0207] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0208] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0209] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0210] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0211] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0212] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0213] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0214] [Explanation of symbols]

[0215] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a reception unit that receives input information of tourists; an analysis unit that analyzes the information received by the reception unit; a generation unit that generates a sightseeing plan based on the information analyzed by the analysis unit; a visual information providing device that displays the sightseeing plan generated by the generation unit; and a voice guide device that provides voice guidance based on the information provided by the visual information providing device. A system characterized by:

2. The reception unit Accepting information about places tourists want to visit and activities they are interested in 2. The system of claim 1.

3. The analysis unit Analyzing the information received by the reception unit and generating a sightseeing plan suitable for the tourist.

2. The system of claim 1.

4. The generation unit A sightseeing plan is generated based on the information analyzed by the analysis unit.

2. The system of claim 1.

5. The visual information providing device is Displaying the sightseeing plan generated by the generation unit 2. The system of claim 1.

6. The voice guide device Providing audio guidance based on the information provided by the visual information providing device 2. The system of claim 1.

7. The visual information providing device is Displays real-time information about tourist spots and helps tourists navigate from their current location to their destination.

2. The system of claim 1.

8. The voice guide device Audio explanations of historical and cultural information about tourist destinations 2. The system of claim 1.

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