system

Abstract

The system of the embodiment aims to enable foreign visitors to Japan to plan their trip with peace of mind and make reservations in one stop. [Solution] The system according to the embodiment comprises a reception unit, an analysis unit, a generation unit, a display unit, an information provision unit, and a reservation unit. The reception unit receives input from the user of budget, period, desired experiences, places to go, and considerations. The analysis unit analyzes the information received by the reception unit. The generation unit generates an optimal travel plan based on the information analyzed by the analysis unit. The display unit displays the travel plan generated by the generation unit. The information provision unit provides real-time information based on the travel plan displayed by the display unit. The reservation unit arranges reservations based on the travel plan displayed by the display unit.

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] With conventional technology, it was difficult for foreign visitors to Japan to alleviate their concerns about using public transportation, preparing for disasters, and observing religious regulations when planning their trips.

[0005] The system of the embodiment aims to enable foreign visitors to Japan to plan their trip with peace of mind and make reservations in one stop. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, an analysis unit, a generation unit, a display unit, an information provision unit, and a reservation unit. The reception unit receives input from the user of budget, time period, desired experiences, places to go, and considerations. The analysis unit analyzes the information received by the reception unit. The generation unit generates an optimal travel plan based on the information analyzed by the analysis unit. The display unit displays the travel plan generated by the generation unit. The information provision unit provides real-time information based on the travel plan displayed by the display unit. The reservation unit arranges reservations based on the travel plan displayed by the display unit. [Effects of the Invention]

[0007] The system according to the embodiment allows foreign visitors to Japan to plan their trip with peace of mind and make all the reservations in one place. [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) The travel plan suggestion system according to an embodiment of the present invention addresses concerns of foreign visitors to Japan (such as transportation, preparations for disasters like earthquakes, and religious observance), proposes optimal travel plans, and allows for one-stop booking. This system allows users to select their budget, travel period, desired experiences, destinations, and other considerations. AI analyzes this information and displays the optimal travel plan. This travel plan also includes information about transportation transfers and evacuation shelters, allowing users to obtain this information in advance. Real-time information can also be provided by using a real-time information providing device. Furthermore, users can make one-stop reservations for the displayed travel plan. For example, users select their budget, travel period, desired experiences, destinations, and other considerations. At this time, users can input detailed requirements tailored to their preferences. For example, a budget of ¥100,000 or less, a travel period of one week, desired experiences including hot springs and Japanese culture, destinations in Tokyo and Kyoto, and considerations such as religious observance. This information is input into the AI. The AI ​​then analyzes the input information and displays the optimal travel plan. AI generates optimal travel plans based on the user's preferences. For example, it selects accommodations and tourist attractions within a user's budget and displays plans that include information on public transport transfers and evacuation shelters. This allows users to easily check travel plans that suit their preferences. Furthermore, by using a real-time information providing device, real-time information can be provided. For example, when a user visits a tourist spot, they can check public transport transfer information and evacuation shelter information in real time through the real-time information providing device. This allows users to enjoy their trip with peace of mind. Finally, users can make one-stop reservations for the displayed travel plan. For example, they can make reservations for accommodations and public transport all at once. This allows users to complete their travel preparations hassle-free. This system alleviates concerns for foreign visitors to Japan and realizes a one-stop service that proposes optimal travel plans and allows them to make reservations.For example, it can alleviate concerns that foreign visitors to Japan have about how to use public transportation, how to prepare for disasters such as earthquakes, and how to observe religious rules. This allows foreign visitors to visit Japan with peace of mind. In this way, the travel plan suggestion system can enable foreign visitors to visit Japan with peace of mind.

[0029] The travel plan proposal system according to the embodiment includes a reception unit, an analysis unit, a generation unit, a display unit, an information provision unit, and a reservation unit. The reception unit receives input from a user of a budget, a travel period, desired experiences, places to visit, and considerations. The information input by the user may include, for example, a budget of less than 100,000 yen, a travel period of one week, desired experiences including hot springs and Japanese culture, places to visit including Tokyo and Kyoto, and considerations including religious observance. The analysis unit analyzes the information received by the reception unit. The analysis unit extracts data for generating an optimal travel plan based on, for example, the information input by the user. The generation unit generates an optimal travel plan based on the information analyzed by the analysis unit. The generation unit selects, for example, accommodations and tourist spots within a budget and generates a plan that also includes information on public transportation transfers and evacuation shelters. The display unit displays the travel plan generated by the generation unit. The display unit displays, for example, the travel plan generated based on conditions selected by the user on a screen. The information provision unit provides real-time information based on the travel plan displayed by the display unit. The information providing unit provides, for example, transportation transfer information and evacuation shelter information using a real-time information providing device. The reservation unit makes reservations based on the travel plan displayed by the display unit. The reservation unit can, for example, make reservations for accommodations and transportation all at once. As a result, the travel plan proposal system according to the embodiment generates an optimal travel plan based on information input by the user and can provide real-time information and make reservations in one stop.

[0030] The information providing unit can provide public transport transfer information and evacuation shelter information using a real-time information providing device. Examples of real-time information providing devices include smartphone apps and wearable devices. For example, the information providing unit can provide the user with optimal transfer information from their current location to their destination using a smartphone app. The information providing unit can also enable the user to check evacuation shelter information in real time using a wearable device. For example, the information providing unit can provide public transport transfer information in real time when the user visits a tourist spot. The information providing unit can also enable the user to check evacuation shelter information in real time when a disaster such as an earthquake occurs. Thus, by using the real-time information providing device, the user can obtain information needed during their trip in real time. Some or all of the above-described processing in the information providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the information providing unit can input data acquired from the real-time information providing device into a generation AI and provide the user with the results of the analysis by the generation AI.

[0031] The reception unit can refer to the user's past travel history and automatically complete the input fields. For example, the reception unit can automatically display candidates for places the user wants to go to based on places the user has visited in the past. The reception unit can also automatically display candidates for experiences the user wants to experience based on experience contents the user has previously selected. Furthermore, the reception unit can automatically display candidates for optimal budgets and periods based on budgets and periods previously set by the user. This can make input work more efficient by referring to the user's past travel history. Some or all of the above-mentioned processing in the reception unit may be performed using, for example, AI, or may be performed without using AI. For example, the reception unit can input the user's past travel history data into a generation AI and automatically complete the input fields based on the analysis results of the generation AI.

[0032] The reception unit can display related additional information in real time based on the user's input. For example, when the user inputs a place they want to go, the reception unit can display the weather forecast for that place in real time. Furthermore, when the user inputs an experience they want to have, the reception unit can display event information related to that experience in real time. Furthermore, when the user inputs a budget, the reception unit can display information about special offers and discounts available within that budget in real time. This can assist the user in making decisions by providing related information in real time based on the user's input. Some or all of the above-described processing in the reception unit may be performed using, for example, AI, or may be performed without AI. For example, the reception unit can input the user's input data into a generation AI and display related information in real time based on the analysis results of the generation AI.

[0033] The reception unit can customize input items to region-specific information by taking into account the user's geographical location information. For example, when the user is in a specific region, the reception unit displays tourist attractions and event information for that region as input items. Furthermore, when the user is in a specific region, the reception unit can also display transportation information for that region as input items. Furthermore, when the user is in a specific region, the reception unit can also display weather forecasts and evacuation shelter information for that region as input items. This allows region-specific information to be provided by customizing input items based on the user's geographical location information. Some or all of the above-described processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit can input the user's geographical location information to a generation AI and customize the input items to region-specific information based on the analysis results of the generation AI.

[0034] The reception unit can analyze the user's social media activity and propose relevant travel plans. For example, the reception unit can propose relevant travel plans based on travel destinations and experiences shared by the user on social media. The reception unit can also propose relevant travel plans based on tourist attractions and event information followed by the user on social media. Furthermore, the reception unit can also propose relevant travel plans based on places and activities in which the user has shown interest on social media. In this way, by proposing travel plans based on the user's social media activity, it is possible to provide plans that match the user's preferences. Some or all of the above-described processing by the reception unit may be performed using, for example, AI, or may be performed without using AI. For example, the reception unit can input the user's social media data into a generation AI and propose a travel plan based on the analysis results of the generation AI.

[0035] During analysis, the analysis unit can improve the accuracy of the analysis by taking into account the user's past travel history and preferences. The analysis unit can, for example, propose a travel plan that matches the user's preferences based on the places the user has visited and the experiences they have had in the past. The analysis unit can also propose an optimal travel plan based on the budget and period set by the user in the past. Furthermore, the analysis unit can propose a travel plan that gives the user a sense of security based on the considerations the user has previously selected. This improves the accuracy of the analysis by taking into account the user's past travel history and preferences. Some or all of the above-mentioned processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can input the user's past travel history data into the generation AI and improve the accuracy of the analysis based on the results of the analysis by the generation AI.

[0036] The analysis unit can optimize the analysis results by incorporating real-time external data during analysis. For example, the analysis unit can propose an optimal travel route based on real-time traffic conditions. The analysis unit can also propose an optimal sightseeing schedule based on real-time weather forecasts. Furthermore, the analysis unit can also propose optimal experience content based on real-time event information. In this way, the analysis results can be optimized by incorporating real-time external data. Some or all of the above-mentioned processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can input real-time external data into the generation AI and optimize the analysis results based on the analysis results of the generation AI.

[0037] During analysis, the analysis unit can customize the analysis results to region-specific information by taking into account the user's geographical location information. For example, when the user is in a specific region, the analysis unit can reflect tourist attractions and event information for that region in the analysis results. Furthermore, when the user is in a specific region, the analysis unit can also reflect transportation information for that region in the analysis results. Furthermore, when the user is in a specific region, the analysis unit can also reflect weather forecasts and evacuation shelter information for that region in the analysis results. This allows region-specific information to be provided by customizing the analysis results based on the user's geographical location information. Some or all of the above-described processing in the analysis unit may be performed, for example, using AI, or may be performed without AI. For example, the analysis unit can input the user's geographical location information into the generation AI and customize the analysis results to region-specific information based on the analysis results of the generation AI.

[0038] During the analysis, the analysis unit can analyze the user's social media activities and provide relevant analysis results. The analysis unit can provide relevant analysis results based on, for example, travel destinations and experiences shared by the user on social media. The analysis unit can also provide relevant analysis results based on tourist spots and event information followed by the user on social media. The analysis unit can also provide relevant analysis results based on places and activities in which the user has shown interest on social media. In this way, by providing analysis results based on the user's social media activities, information tailored to the user's preferences can be provided. Some or all of the above-described processing by the analysis unit can be performed, for example, using AI or without AI. For example, the analysis unit can input the user's social media data into a generation AI and provide analysis results based on the results of the analysis by the generation AI.

[0039] The generation unit can generate an optimal travel plan by taking into account the user's past travel history and preferences. The generation unit generates a travel plan that matches the user's preferences, for example, based on places the user has visited in the past and experiences they have had. The generation unit can also generate an optimal travel plan based on a budget and period previously set by the user. Furthermore, the generation unit can generate a travel plan that gives a sense of security based on considerations previously selected by the user. This makes it possible to generate an optimal travel plan by taking into account the user's past travel history and preferences. Some or all of the above-mentioned processing in the generation unit may be performed, for example, using AI, or may be performed without using AI. For example, the generation unit can input the user's past travel history data into the generation AI and generate an optimal travel plan based on the analysis results of the generation AI.

[0040] The generation unit can optimize the travel plan by incorporating real-time external data during generation. The generation unit can, for example, propose an optimal travel route based on real-time traffic conditions. The generation unit can also propose an optimal sightseeing schedule based on real-time weather forecasts. Furthermore, the generation unit can also propose optimal experience content based on real-time event information. In this way, the travel plan can be optimized by incorporating real-time external data. Some or all of the above-mentioned processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can input real-time external data into the generation AI and optimize the travel plan based on the results of analysis by the generation AI.

[0041] The generation unit can customize the travel plan to include region-specific information by taking into account the user's geographical location information during generation. For example, when the user is in a specific region, the generation unit can reflect tourist attractions and event information for that region in the travel plan. Furthermore, when the user is in a specific region, the generation unit can also reflect transportation information for that region in the travel plan. Furthermore, when the user is in a specific region, the generation unit can also reflect weather forecasts and evacuation shelter information for that region in the travel plan. This allows the travel plan to be customized based on the user's geographical location information, thereby providing region-specific information. Some or all of the above-described processing in the generation unit may be performed, for example, using AI, or may be performed without AI. For example, the generation unit can input the user's geographical location information into the generation AI and customize the travel plan to include region-specific information based on the analysis results of the generation AI.

[0042] The generation unit can analyze the user's social media activity during generation and provide related travel plans. The generation unit can provide related travel plans based on, for example, travel destinations and experiences shared by the user on social media. The generation unit can also provide related travel plans based on tourist attractions and event information that the user follows on social media. The generation unit can also provide related travel plans based on places and activities in which the user has expressed interest on social media. In this way, by providing travel plans based on the user's social media activity, it is possible to provide plans that match the user's preferences. Some or all of the above-described processing in the generation unit can be performed, for example, using AI or without AI. For example, the generation unit can input the user's social media data into the generation AI and provide a travel plan based on the analysis results of the generation AI.

[0043] The display unit can customize the display content by taking into account the user's past travel history and preferences when displaying the content. The display unit can provide display content that matches the user's preferences, for example, based on places the user has visited in the past and experiences they have had. The display unit can also provide optimal display content based on the budget and period the user has set in the past. Furthermore, the display unit can provide display content that gives a sense of security based on considerations the user has selected in the past. This allows the display content to be customized by taking into account the user's past travel history and preferences. Some or all of the above-mentioned processing in the display unit may be performed, for example, using AI, or may be performed without using AI. For example, the display unit can input the user's past travel history data into a generation AI and customize the display content based on the analysis results of the generation AI.

[0044] The display unit can optimize the display content by incorporating real-time external data during display. The display unit can, for example, display an optimal travel route based on real-time traffic conditions. The display unit can also display an optimal sightseeing schedule based on real-time weather forecasts. Furthermore, the display unit can display optimal experience content based on real-time event information. In this way, the display content can be optimized by incorporating real-time external data. Some or all of the above-mentioned processing in the display unit may be performed using, for example, AI, or may be performed without using AI. For example, the display unit can input real-time external data into a generation AI and optimize the display content based on the analysis results of the generation AI.

[0045] The display unit can customize the display content to region-specific information by taking into account the user's geographical location information. For example, when the user is in a specific region, the display unit reflects tourist attractions and event information for that region in the display content. Furthermore, when the user is in a specific region, the display unit can also reflect transportation information for that region in the display content. Furthermore, when the user is in a specific region, the display unit can also reflect weather forecasts and evacuation shelter information for that region in the display content. In this way, region-specific information can be provided by customizing the display content based on the user's geographical location information. Some or all of the above-described processing in the display unit may be performed, for example, using AI, or may be performed without using AI. For example, the display unit can input the user's geographical location information into a generation AI and customize the display content to region-specific information based on the analysis results of the generation AI.

[0046] The display unit can analyze the user's social media activity and provide related display content when displaying the content. The display unit can provide related display content based on, for example, travel destinations and experiences shared by the user on social media. The display unit can also provide related display content based on tourist spots and event information that the user follows on social media. Furthermore, the display unit can also provide related display content based on places and activities in which the user has shown interest on social media. This allows the display content to be provided based on the user's social media activity, thereby providing information that matches the user's preferences. Some or all of the above-described processing in the display unit can be performed, for example, using AI, or can be performed without AI. For example, the display unit can input the user's social media data into a generation AI and provide display content based on the analysis results of the generation AI.

[0047] When providing information, the information providing unit can customize the provided information by taking into account the user's past travel history and preferences. The information providing unit can provide information that matches the user's preferences, for example, based on places the user has visited in the past and experiences they have had. The information providing unit can also provide optimal information based on a budget and period of time previously set by the user. Furthermore, the information providing unit can provide information that gives a sense of security based on considerations previously selected by the user. This makes it possible to customize the provided information by taking into account the user's past travel history and preferences. Some or all of the above-described processing in the information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the information providing unit can input the user's past travel history data into a generation AI and customize the provided information based on the analysis results of the generation AI.

[0048] The information providing unit can optimize the provided information by incorporating real-time external data when providing information. The information providing unit can, for example, provide an optimal travel route based on real-time traffic conditions. The information providing unit can also provide an optimal sightseeing schedule based on real-time weather forecasts. Furthermore, the information providing unit can also provide optimal experience content based on real-time event information. In this way, the provided information can be optimized by incorporating real-time external data. Some or all of the above-mentioned processing in the information providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the information providing unit can input real-time external data to a generation AI and optimize the provided information based on the analysis results of the generation AI.

[0049] When providing information, the information providing unit can customize the provided information to be region-specific, taking into account the user's geographical location information. For example, when the user is in a specific region, the information providing unit can provide information about tourist attractions and events in that region. Furthermore, when the user is in a specific region, the information providing unit can also provide transportation information for that region. Furthermore, when the user is in a specific region, the information providing unit can also provide weather forecasts and evacuation shelter information for that region. In this way, region-specific information can be provided by customizing the provided information based on the user's geographical location information. Some or all of the above-described processing in the information providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the information providing unit can input the user's geographical location information into a generation AI and customize the provided information to be region-specific based on the analysis results of the generation AI.

[0050] The information providing unit can analyze the user's social media activities and provide related information when providing information. The information providing unit can provide related information based on, for example, travel destinations and experiences shared by the user on social media. The information providing unit can also provide related information based on tourist spots and event information that the user follows on social media. Furthermore, the information providing unit can also provide related information based on places and activities in which the user has shown interest on social media. In this way, by providing information based on the user's social media activities, it is possible to provide information that matches the user's preferences. Some or all of the above-described processing by the information providing unit can be performed, for example, using AI or without AI. For example, the information providing unit can input the user's social media data into a generation AI and provide related information based on the analysis results of the generation AI.

[0051] The reservation unit can make optimal reservation arrangements at the time of reservation, taking into account the user's past reservation history and preferences. The reservation unit can make optimal reservation arrangements, for example, based on accommodations and transportation facilities used by the user in the past. The reservation unit can also make optimal reservation arrangements based on the budget and period set by the user in the past. Furthermore, the reservation unit can make reservation arrangements that provide peace of mind based on considerations selected by the user in the past. This makes it possible to provide optimal reservation arrangements by taking into account the user's past reservation history and preferences. Some or all of the above-described processing in the reservation unit may be performed using, for example, AI, or may be performed without using AI. For example, the reservation unit can input the user's past reservation history data into a generation AI and make optimal reservation arrangements based on the analysis results of the generation AI.

[0052] The reservation unit can optimize reservation arrangements by incorporating real-time external data at the time of reservation. The reservation unit can, for example, make optimal travel arrangements based on real-time traffic conditions. The reservation unit can also make optimal accommodation arrangements based on real-time weather forecasts. Furthermore, the reservation unit can also make optimal experience arrangements based on real-time event information. In this way, reservation arrangements can be optimized by incorporating real-time external data. Some or all of the above-mentioned processing in the reservation unit may be performed using, for example, AI, or may be performed without using AI. For example, the reservation unit can input real-time external data into the generation AI and optimize reservation arrangements based on the results of analysis by the generation AI.

[0053] The reservation unit can customize the reservation arrangement to region-specific information by taking into account the user's geographical location information when making a reservation. For example, if the user is in a specific region, the reservation unit reflects accommodations and transportation options in that region in the reservation arrangement. Furthermore, if the user is in a specific region, the reservation unit can also reflect event information for that region in the reservation arrangement. Furthermore, if the user is in a specific region, the reservation unit can also reflect weather forecasts and evacuation shelter information for that region in the reservation arrangement. This allows region-specific information to be provided by customizing the reservation arrangement based on the user's geographical location information. Some or all of the above-described processing in the reservation unit may be performed, for example, using AI, or may be performed without AI. For example, the reservation unit can input the user's geographical location information into a generation AI and customize the reservation arrangement to region-specific information based on the analysis results of the generation AI.

[0054] The reservation unit can analyze the user's social media activity at the time of reservation and provide relevant reservation arrangements. For example, the reservation unit can provide relevant reservation arrangements based on travel destinations and experiences shared by the user on social media. The reservation unit can also provide relevant reservation arrangements based on tourist attractions and event information followed by the user on social media. Furthermore, the reservation unit can provide relevant reservation arrangements based on places and activities the user has expressed interest in on social media. In this way, by providing reservation arrangements based on the user's social media activity, reservation arrangements that match the user's preferences can be provided. Some or all of the above-described processing in the reservation unit may be performed, for example, using AI or without AI. For example, the reservation unit can input the user's social media data into a generation AI and provide relevant reservation arrangements based on the analysis results of the generation AI.

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

[0056] The analysis unit can improve the accuracy of analysis by taking into account the user's past travel history and preferences. For example, it can propose a travel plan that matches the user's preferences based on the places the user has visited and experiences they have had in the past. It can also propose an optimal travel plan based on the budget and period set by the user in the past. It can also propose a travel plan that gives the user a sense of security based on the considerations the user has selected in the past. In this way, the analysis accuracy is improved by taking into account the user's past travel history and preferences.

[0057] The reception unit can customize input items to region-specific information by taking into account the user's geographical location information. For example, when the user is in a specific region, tourist attractions and event information for that region can be displayed as input items. Also, when the user is in a specific region, transportation information for that region can be displayed as input items. Furthermore, when the user is in a specific region, weather forecasts and evacuation shelter information for that region can be displayed as input items. In this way, by customizing input items based on the user's geographical location information, it is possible to provide region-specific information.

[0058] The analysis unit can incorporate real-time external data during analysis to optimize the analysis results. For example, it can suggest optimal travel routes based on real-time traffic conditions. It can also suggest optimal sightseeing schedules based on real-time weather forecasts. It can also suggest optimal experience content based on real-time event information. In this way, incorporating real-time external data can optimize the analysis results.

[0059] The generation unit can generate an optimal travel plan by taking into account the user's past travel history and preferences. For example, a travel plan that matches the user's preferences is generated based on the places the user has visited in the past and the experiences they have had. The optimal travel plan can also be generated based on the budget and period set by the user in the past. Furthermore, a travel plan that gives a sense of security can also be generated based on the considerations selected by the user in the past. In this way, the optimal travel plan can be generated by taking into account the user's past travel history and preferences.

[0060] The display unit can incorporate real-time external data during display to optimize the display content. For example, it can display the optimal travel route based on real-time traffic conditions. It can also display the optimal sightseeing schedule based on real-time weather forecasts. It can also display the optimal experience content based on real-time event information. In this way, the display content can be optimized by incorporating real-time external data.

[0061] The reservation unit can make optimal reservation arrangements by taking into account the user's past reservation history and preferences when making a reservation. For example, optimal reservation arrangements can be made based on accommodations and transportation options used by the user in the past. Optimal reservation arrangements can also be made based on the budget and period set by the user in the past. Furthermore, reservation arrangements that provide a sense of security can also be made based on considerations selected by the user in the past. This makes it possible to provide optimal reservation arrangements by taking into account the user's past reservation history and preferences.

[0062] The processing flow of the first embodiment will be briefly explained below.

[0063] Step 1: The reception unit accepts input from the user of the budget, duration, desired experience, desired destination, and considerations. Information input by the user may include, for example, a budget of 100,000 yen or less, a duration of one week, desired experiences of hot springs and Japanese culture, desired destinations of Tokyo and Kyoto, and considerations such as adherence to religious regulations. Step 2: The analysis unit analyzes the information received by the reception unit. For example, the analysis unit extracts data for generating an optimal travel plan based on the information input by the user. Step 3: The generation unit generates an optimal travel plan based on the information analyzed by the analysis unit. For example, the generation unit selects accommodations and tourist spots within the budget and generates a plan that also includes information on public transportation transfers and evacuation shelters. Step 4: The display unit displays the itinerary generated by the generation unit. The display unit displays, for example, the itinerary generated based on the conditions selected by the user on a screen. Step 5: The information providing unit provides real-time information based on the travel plan displayed by the display unit. For example, the information providing unit provides transportation transfer information and evacuation shelter information using a real-time information providing device. Step 6: The reservation unit makes reservations based on the travel plan displayed by the display unit. The reservation unit can, for example, make reservations for accommodations and transportation all at once.

[0064] (Example 2) The travel plan suggestion system according to an embodiment of the present invention addresses concerns of foreign visitors to Japan (such as transportation, preparations for disasters like earthquakes, and religious observance), proposes optimal travel plans, and allows for one-stop booking. This system allows users to select their budget, travel period, desired experiences, destinations, and other considerations. AI analyzes this information and displays the optimal travel plan. This travel plan also includes information about transportation transfers and evacuation shelters, allowing users to obtain this information in advance. Real-time information can also be provided by using a real-time information providing device. Furthermore, users can make one-stop reservations for the displayed travel plan. For example, users select their budget, travel period, desired experiences, destinations, and other considerations. At this time, users can input detailed requirements tailored to their preferences. For example, a budget of ¥100,000 or less, a travel period of one week, desired experiences including hot springs and Japanese culture, destinations in Tokyo and Kyoto, and considerations such as religious observance. This information is input into the AI. The AI ​​then analyzes the input information and displays the optimal travel plan. AI generates optimal travel plans based on the user's preferences. For example, it selects accommodations and tourist attractions within a user's budget and displays plans that include information on public transport transfers and evacuation shelters. This allows users to easily check travel plans that suit their preferences. Furthermore, by using a real-time information providing device, real-time information can be provided. For example, when a user visits a tourist spot, they can check public transport transfer information and evacuation shelter information in real time through the real-time information providing device. This allows users to enjoy their trip with peace of mind. Finally, users can make one-stop reservations for the displayed travel plan. For example, they can make reservations for accommodations and public transport all at once. This allows users to complete their travel preparations hassle-free. This system alleviates concerns for foreign visitors to Japan and realizes a one-stop service that proposes optimal travel plans and allows them to make reservations.For example, it can alleviate concerns that foreign visitors to Japan have about how to use public transportation, how to prepare for disasters such as earthquakes, and how to observe religious rules. This allows foreign visitors to visit Japan with peace of mind. In this way, the travel plan suggestion system can enable foreign visitors to visit Japan with peace of mind.

[0065] The travel plan proposal system according to the embodiment includes a reception unit, an analysis unit, a generation unit, a display unit, an information provision unit, and a reservation unit. The reception unit receives input from a user of a budget, a travel period, desired experiences, places to visit, and considerations. The information input by the user may include, for example, a budget of less than 100,000 yen, a travel period of one week, desired experiences including hot springs and Japanese culture, places to visit including Tokyo and Kyoto, and considerations including religious observance. The analysis unit analyzes the information received by the reception unit. The analysis unit extracts data for generating an optimal travel plan based on, for example, the information input by the user. The generation unit generates an optimal travel plan based on the information analyzed by the analysis unit. The generation unit selects, for example, accommodations and tourist spots within a budget and generates a plan that also includes information on public transportation transfers and evacuation shelters. The display unit displays the travel plan generated by the generation unit. The display unit displays, for example, the travel plan generated based on conditions selected by the user on a screen. The information provision unit provides real-time information based on the travel plan displayed by the display unit. The information providing unit provides, for example, transportation transfer information and evacuation shelter information using a real-time information providing device. The reservation unit makes reservations based on the travel plan displayed by the display unit. The reservation unit can, for example, make reservations for accommodations and transportation all at once. As a result, the travel plan proposal system according to the embodiment generates an optimal travel plan based on information input by the user and can provide real-time information and make reservations in one stop.

[0066] The information providing unit can provide public transport transfer information and evacuation shelter information using a real-time information providing device. Examples of real-time information providing devices include smartphone apps and wearable devices. For example, the information providing unit can provide the user with optimal transfer information from their current location to their destination using a smartphone app. The information providing unit can also enable the user to check evacuation shelter information in real time using a wearable device. For example, the information providing unit can provide public transport transfer information in real time when the user visits a tourist spot. The information providing unit can also enable the user to check evacuation shelter information in real time when a disaster such as an earthquake occurs. Thus, by using the real-time information providing device, the user can obtain information needed during their trip in real time. Some or all of the above-described processing in the information providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the information providing unit can input data acquired from the real-time information providing device into a generation AI and provide the user with the results of the analysis by the generation AI.

[0067] The reception unit can estimate the user's emotions and dynamically change the design of the input interface based on the estimated user emotions. For example, if the user is nervous, the reception unit can provide an interface with subdued colors to reduce visual stress. Furthermore, if the user is having fun, the reception unit can provide an interface with bright colors to make input work more enjoyable. Furthermore, if the user is tired, the reception unit can provide a simple, highly visible interface to make input work easier. This allows the user's input work to be made more comfortable by changing the design of the input interface according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the reception unit may be performed using AI, or may be performed without AI. For example, the reception unit can input the user's facial expression data into the generation AI and change the interface design based on the analysis results of the generation AI.

[0068] The reception unit can refer to the user's past travel history and automatically complete the input fields. For example, the reception unit can automatically display candidates for places the user wants to go to based on places the user has visited in the past. The reception unit can also automatically display candidates for experiences the user wants to experience based on experience contents the user has previously selected. Furthermore, the reception unit can automatically display candidates for optimal budgets and periods based on budgets and periods previously set by the user. This can make input work more efficient by referring to the user's past travel history. Some or all of the above-mentioned processing in the reception unit may be performed using, for example, AI, or may be performed without using AI. For example, the reception unit can input the user's past travel history data into a generation AI and automatically complete the input fields based on the analysis results of the generation AI.

[0069] The reception unit can display related additional information in real time based on the user's input. For example, when the user inputs a place they want to go, the reception unit can display the weather forecast for that place in real time. Furthermore, when the user inputs an experience they want to have, the reception unit can display event information related to that experience in real time. Furthermore, when the user inputs a budget, the reception unit can display information about special offers and discounts available within that budget in real time. This can assist the user in making decisions by providing related information in real time based on the user's input. Some or all of the above-described processing in the reception unit may be performed using, for example, AI, or may be performed without AI. For example, the reception unit can input the user's input data into a generation AI and display related information in real time based on the analysis results of the generation AI.

[0070] The reception unit can estimate the user's emotions and dynamically change the priority of input items based on the estimated user emotions. For example, when the user is in a hurry, the reception unit can prioritize displaying important input items to enable quick input. Furthermore, when the user is relaxed, the reception unit can display detailed input items and provide a customizable input method. Furthermore, when the user is feeling anxious, the reception unit can prioritize displaying simple and easy-to-understand input items to provide a sense of security. This can improve the efficiency of the user's input work by changing the priority of input items according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the reception unit can be performed using, for example, AI, or without AI. For example, the reception unit can input the user's facial expression data into the generation AI and dynamically change the priority of input items based on the analysis results of the generation AI.

[0071] The reception unit can customize input items to region-specific information by taking into account the user's geographical location information. For example, when the user is in a specific region, the reception unit displays tourist attractions and event information for that region as input items. Furthermore, when the user is in a specific region, the reception unit can also display transportation information for that region as input items. Furthermore, when the user is in a specific region, the reception unit can also display weather forecasts and evacuation shelter information for that region as input items. This allows region-specific information to be provided by customizing input items based on the user's geographical location information. Some or all of the above-described processing in the reception unit may be performed, for example, using AI, or may be performed without using AI. For example, the reception unit can input the user's geographical location information to a generation AI and customize the input items to region-specific information based on the analysis results of the generation AI.

[0072] The reception unit can analyze the user's social media activity and propose relevant travel plans. For example, the reception unit can propose relevant travel plans based on travel destinations and experiences shared by the user on social media. The reception unit can also propose relevant travel plans based on tourist attractions and event information followed by the user on social media. Furthermore, the reception unit can also propose relevant travel plans based on places and activities in which the user has shown interest on social media. In this way, by proposing travel plans based on the user's social media activity, it is possible to provide plans that match the user's preferences. Some or all of the above-described processing by the reception unit may be performed using, for example, AI, or may be performed without using AI. For example, the reception unit can input the user's social media data into a generation AI and propose a travel plan based on the analysis results of the generation AI.

[0073] The analysis unit can estimate the user's emotions and dynamically adjust the parameters of the analysis algorithm based on the estimated user emotions. For example, if the user is relaxed, the analysis unit can perform a detailed analysis and propose an optimal travel plan. Furthermore, if the user is in a hurry, the analysis unit can perform a quick analysis and immediately propose a travel plan. Furthermore, if the user is feeling anxious, the analysis unit can perform an analysis that provides a sense of security and propose a reliable travel plan. This allows optimal analysis results to be provided by adjusting the parameters of the analysis algorithm according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit can be performed using, for example, AI, or without AI. For example, the analysis unit can input the user's emotion data into the generation AI and dynamically adjust the parameters of the analysis algorithm based on the analysis results of the generation AI.

[0074] During analysis, the analysis unit can improve the accuracy of the analysis by taking into account the user's past travel history and preferences. The analysis unit can, for example, propose a travel plan that matches the user's preferences based on the places the user has visited and the experiences they have had in the past. The analysis unit can also propose an optimal travel plan based on the budget and period set by the user in the past. Furthermore, the analysis unit can propose a travel plan that gives the user a sense of security based on the considerations the user has previously selected. This improves the accuracy of the analysis by taking into account the user's past travel history and preferences. Some or all of the above-mentioned processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can input the user's past travel history data into the generation AI and improve the accuracy of the analysis based on the results of the analysis by the generation AI.

[0075] The analysis unit can optimize the analysis results by incorporating real-time external data during analysis. For example, the analysis unit can propose an optimal travel route based on real-time traffic conditions. The analysis unit can also propose an optimal sightseeing schedule based on real-time weather forecasts. Furthermore, the analysis unit can also propose optimal experience content based on real-time event information. In this way, the analysis results can be optimized by incorporating real-time external data. Some or all of the above-mentioned processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can input real-time external data into the generation AI and optimize the analysis results based on the analysis results of the generation AI.

[0076] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the estimated user emotions. For example, if the user is nervous, the analysis unit can provide a simple, highly visible display method. Furthermore, if the user is relaxed, the analysis unit can provide a display method that includes detailed information. Furthermore, if the user is in a hurry, the analysis unit can provide a display method that focuses on the main points. This allows the display method of the analysis results to be adjusted according to the user's emotions, making the display easy for the user to view. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the analysis unit can be performed using, for example, AI, or without AI. For example, the analysis unit can input the user's emotion data into the generation AI and adjust the display method of the analysis results based on the analysis results of the generation AI.

[0077] During analysis, the analysis unit can customize the analysis results to region-specific information by taking into account the user's geographical location information. For example, when the user is in a specific region, the analysis unit can reflect tourist attractions and event information for that region in the analysis results. Furthermore, when the user is in a specific region, the analysis unit can also reflect transportation information for that region in the analysis results. Furthermore, when the user is in a specific region, the analysis unit can also reflect weather forecasts and evacuation shelter information for that region in the analysis results. This allows region-specific information to be provided by customizing the analysis results based on the user's geographical location information. Some or all of the above-described processing in the analysis unit may be performed, for example, using AI, or may be performed without AI. For example, the analysis unit can input the user's geographical location information into the generation AI and customize the analysis results to region-specific information based on the analysis results of the generation AI.

[0078] During the analysis, the analysis unit can analyze the user's social media activities and provide relevant analysis results. The analysis unit can provide relevant analysis results based on, for example, travel destinations and experiences shared by the user on social media. The analysis unit can also provide relevant analysis results based on tourist spots and event information followed by the user on social media. The analysis unit can also provide relevant analysis results based on places and activities in which the user has shown interest on social media. In this way, by providing analysis results based on the user's social media activities, information tailored to the user's preferences can be provided. Some or all of the above-described processing by the analysis unit can be performed, for example, using AI or without AI. For example, the analysis unit can input the user's social media data into a generation AI and provide analysis results based on the results of the analysis by the generation AI.

[0079] The generation unit can estimate the user's emotions and adjust the content of the generated travel plan based on the estimated user emotions. For example, if the user is relaxed, the generation unit can generate a travel plan that proceeds at a leisurely pace. Furthermore, if the user is in a hurry, the generation unit can generate a travel plan that emphasizes efficient travel routes. Furthermore, if the user is excited, the generation unit can generate a travel plan that includes visually stimulating tourist spots. This allows the optimal plan for the user to be provided by adjusting the content of the travel plan according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the generation unit can be performed using, for example, AI, or without AI. For example, the generation unit can input the user's emotion data into the generation AI and adjust the content of the travel plan based on the analysis results of the generation AI.

[0080] The generation unit can generate an optimal travel plan by taking into account the user's past travel history and preferences. The generation unit generates a travel plan that matches the user's preferences, for example, based on places the user has visited in the past and experiences they have had. The generation unit can also generate an optimal travel plan based on a budget and period previously set by the user. Furthermore, the generation unit can generate a travel plan that gives a sense of security based on considerations previously selected by the user. This makes it possible to generate an optimal travel plan by taking into account the user's past travel history and preferences. Some or all of the above-mentioned processing in the generation unit may be performed, for example, using AI, or may be performed without using AI. For example, the generation unit can input the user's past travel history data into the generation AI and generate an optimal travel plan based on the analysis results of the generation AI.

[0081] The generation unit can optimize the travel plan by incorporating real-time external data during generation. The generation unit can, for example, propose an optimal travel route based on real-time traffic conditions. The generation unit can also propose an optimal sightseeing schedule based on real-time weather forecasts. Furthermore, the generation unit can also propose optimal experience content based on real-time event information. In this way, the travel plan can be optimized by incorporating real-time external data. Some or all of the above-mentioned processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can input real-time external data into the generation AI and optimize the travel plan based on the results of analysis by the generation AI.

[0082] The generation unit can estimate the user's emotions and prioritize the generated itinerary based on the estimated user emotions. For example, if the user is in a hurry, the generation unit can generate an itinerary that prioritizes important tourist spots and experiences. Furthermore, if the user is relaxed, the generation unit can generate an itinerary that proceeds at a leisurely pace. Furthermore, if the user is excited, the generation unit can generate an itinerary that prioritizes visually stimulating tourist spots. This allows the user to be provided with an optimal itinerary by prioritizing the itinerary based on the user's emotions. The emotion estimation is realized using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the generation unit can be performed using, for example, AI, or without AI. For example, the generation unit can input the user's emotion data into the generation AI and prioritize the itinerary based on the analysis results of the generation AI.

[0083] The generation unit can customize the travel plan to include region-specific information by taking into account the user's geographical location information during generation. For example, when the user is in a specific region, the generation unit can reflect tourist attractions and event information for that region in the travel plan. Furthermore, when the user is in a specific region, the generation unit can also reflect transportation information for that region in the travel plan. Furthermore, when the user is in a specific region, the generation unit can also reflect weather forecasts and evacuation shelter information for that region in the travel plan. This allows the travel plan to be customized based on the user's geographical location information, thereby providing region-specific information. Some or all of the above-described processing in the generation unit may be performed, for example, using AI, or may be performed without AI. For example, the generation unit can input the user's geographical location information into the generation AI and customize the travel plan to include region-specific information based on the analysis results of the generation AI.

[0084] The generation unit can analyze the user's social media activity during generation and provide related travel plans. The generation unit can provide related travel plans based on, for example, travel destinations and experiences shared by the user on social media. The generation unit can also provide related travel plans based on tourist attractions and event information that the user follows on social media. The generation unit can also provide related travel plans based on places and activities in which the user has expressed interest on social media. In this way, by providing travel plans based on the user's social media activity, it is possible to provide plans that match the user's preferences. Some or all of the above-described processing in the generation unit can be performed, for example, using AI or without AI. For example, the generation unit can input the user's social media data into the generation AI and provide a travel plan based on the analysis results of the generation AI.

[0085] The display unit can estimate the user's emotions and dynamically change the design of the display interface based on the estimated user emotions. For example, if the user is nervous, the display unit can provide an interface with subdued colors to reduce visual stress. Furthermore, if the user is having fun, the display unit can provide an interface with bright colors to make display work more enjoyable. Furthermore, if the user is tired, the display unit can provide a simple, highly visible interface to make display work easier. This allows the user's display work to be made more comfortable by changing the design of the display interface according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the display unit can be performed using, for example, AI, or without AI. For example, the display unit can input the user's emotion data into the generation AI and dynamically change the design of the display interface based on the analysis results of the generation AI.

[0086] The display unit can customize the display content by taking into account the user's past travel history and preferences when displaying the content. The display unit can provide display content that matches the user's preferences, for example, based on places the user has visited in the past and experiences they have had. The display unit can also provide optimal display content based on the budget and period the user has set in the past. Furthermore, the display unit can provide display content that gives a sense of security based on considerations the user has selected in the past. This allows the display content to be customized by taking into account the user's past travel history and preferences. Some or all of the above-mentioned processing in the display unit may be performed, for example, using AI, or may be performed without using AI. For example, the display unit can input the user's past travel history data into a generation AI and customize the display content based on the analysis results of the generation AI.

[0087] The display unit can optimize the display content by incorporating real-time external data during display. The display unit can, for example, display an optimal travel route based on real-time traffic conditions. The display unit can also display an optimal sightseeing schedule based on real-time weather forecasts. Furthermore, the display unit can display optimal experience content based on real-time event information. In this way, the display content can be optimized by incorporating real-time external data. Some or all of the above-mentioned processing in the display unit may be performed using, for example, AI, or may be performed without using AI. For example, the display unit can input real-time external data into a generation AI and optimize the display content based on the analysis results of the generation AI.

[0088] The display unit can estimate the user's emotions and dynamically change the priority of display content based on the estimated user emotions. For example, when the user is in a hurry, the display unit can prioritize displaying important information to allow the user to quickly check it. Furthermore, when the user is relaxed, the display unit can display detailed information and provide a customizable display method. Furthermore, when the user is feeling anxious, the display unit can prioritize displaying concise and easy-to-understand information to provide a sense of security. This allows the user's display work to be streamlined by changing the priority of display content according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the display unit can be performed using, for example, AI, or without AI. For example, the display unit can input the user's emotion data into the generation AI and dynamically change the priority of display content based on the analysis results of the generation AI.

[0089] The display unit can customize the display content to region-specific information by taking into account the user's geographical location information. For example, when the user is in a specific region, the display unit reflects tourist attractions and event information for that region in the display content. Furthermore, when the user is in a specific region, the display unit can also reflect transportation information for that region in the display content. Furthermore, when the user is in a specific region, the display unit can also reflect weather forecasts and evacuation shelter information for that region in the display content. In this way, region-specific information can be provided by customizing the display content based on the user's geographical location information. Some or all of the above-described processing in the display unit may be performed, for example, using AI, or may be performed without using AI. For example, the display unit can input the user's geographical location information into a generation AI and customize the display content to region-specific information based on the analysis results of the generation AI.

[0090] The display unit can analyze the user's social media activity and provide related display content when displaying the content. The display unit can provide related display content based on, for example, travel destinations and experiences shared by the user on social media. The display unit can also provide related display content based on tourist spots and event information that the user follows on social media. Furthermore, the display unit can also provide related display content based on places and activities in which the user has shown interest on social media. This allows the display content to be provided based on the user's social media activity, thereby providing information that matches the user's preferences. Some or all of the above-described processing in the display unit can be performed, for example, using AI, or can be performed without AI. For example, the display unit can input the user's social media data into a generation AI and provide display content based on the analysis results of the generation AI.

[0091] The information providing unit can estimate the user's emotions and adjust the content of the information to be provided based on the estimated user emotions. For example, if the user is nervous, the information providing unit can prioritize providing information that gives a sense of security. Furthermore, if the user is relaxed, the information providing unit can provide detailed information to increase the enjoyment of the trip. Furthermore, if the user is in a hurry, the information providing unit can provide important information concisely. By adjusting the content of the information to be provided according to the user's emotions, optimal information can be provided to the user. Emotion estimation is realized using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the information providing unit can be performed using, for example, AI, or without AI. For example, the information providing unit can input the user's emotion data into the generation AI and adjust the content of the information to be provided based on the analysis results of the generation AI.

[0092] When providing information, the information providing unit can customize the provided information by taking into account the user's past travel history and preferences. The information providing unit can provide information that matches the user's preferences, for example, based on places the user has visited in the past and experiences they have had. The information providing unit can also provide optimal information based on a budget and period of time previously set by the user. Furthermore, the information providing unit can provide information that gives a sense of security based on considerations previously selected by the user. This makes it possible to customize the provided information by taking into account the user's past travel history and preferences. Some or all of the above-described processing in the information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the information providing unit can input the user's past travel history data into a generation AI and customize the provided information based on the analysis results of the generation AI.

[0093] The information providing unit can optimize the provided information by incorporating real-time external data when providing information. The information providing unit can, for example, provide an optimal travel route based on real-time traffic conditions. The information providing unit can also provide an optimal sightseeing schedule based on real-time weather forecasts. Furthermore, the information providing unit can also provide optimal experience content based on real-time event information. In this way, the provided information can be optimized by incorporating real-time external data. Some or all of the above-mentioned processing in the information providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the information providing unit can input real-time external data to a generation AI and optimize the provided information based on the analysis results of the generation AI.

[0094] The information providing unit can estimate the user's emotions and determine the priority of information to be provided based on the estimated user emotions. For example, if the user is in a hurry, the information providing unit can prioritize providing important information so that the user can quickly check it. Furthermore, if the user is relaxed, the information providing unit can provide detailed information to increase the enjoyment of the trip. Furthermore, if the user is feeling anxious, the information providing unit can prioritize providing information that gives the user a sense of security. Thus, by determining the priority of information to be provided according to the user's emotions, optimal information can be provided to the user. Emotion estimation is realized using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the information providing unit can be performed using, for example, AI, or without AI. For example, the information providing unit can input the user's emotion data into the generation AI and determine the priority of information to be provided based on the analysis results of the generation AI.

[0095] When providing information, the information providing unit can customize the provided information to be region-specific, taking into account the user's geographical location information. For example, when the user is in a specific region, the information providing unit can provide information about tourist attractions and events in that region. Furthermore, when the user is in a specific region, the information providing unit can also provide transportation information for that region. Furthermore, when the user is in a specific region, the information providing unit can also provide weather forecasts and evacuation shelter information for that region. In this way, region-specific information can be provided by customizing the provided information based on the user's geographical location information. Some or all of the above-described processing in the information providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the information providing unit can input the user's geographical location information into a generation AI and customize the provided information to be region-specific based on the analysis results of the generation AI.

[0096] The information providing unit can analyze the user's social media activities and provide related information when providing information. The information providing unit can provide related information based on, for example, travel destinations and experiences shared by the user on social media. The information providing unit can also provide related information based on tourist spots and event information that the user follows on social media. Furthermore, the information providing unit can also provide related information based on places and activities in which the user has shown interest on social media. In this way, by providing information based on the user's social media activities, it is possible to provide information that matches the user's preferences. Some or all of the above-described processing by the information providing unit can be performed, for example, using AI or without AI. For example, the information providing unit can input the user's social media data into a generation AI and provide related information based on the analysis results of the generation AI.

[0097] The reservation unit can estimate the user's emotions and adjust the reservation arrangement procedure based on the estimated user emotions. For example, if the user is nervous, the reservation unit can provide a simple and easy-to-understand reservation procedure. Furthermore, if the user is relaxed, the reservation unit can provide detailed reservation options and suggest a customizable reservation procedure. Furthermore, if the user is in a hurry, the reservation unit can provide a procedure for quickly completing the reservation arrangement. This allows the reservation arrangement to be optimally tailored to the user by adjusting the reservation arrangement procedure according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the reservation unit can be performed using, for example, AI, or without AI. For example, the reservation unit can input the user's emotion data into the generation AI and adjust the reservation arrangement procedure based on the analysis results of the generation AI.

[0098] The reservation unit can make optimal reservation arrangements at the time of reservation, taking into account the user's past reservation history and preferences. The reservation unit can make optimal reservation arrangements, for example, based on accommodations and transportation facilities used by the user in the past. The reservation unit can also make optimal reservation arrangements based on the budget and period set by the user in the past. Furthermore, the reservation unit can make reservation arrangements that provide peace of mind based on considerations selected by the user in the past. This makes it possible to provide optimal reservation arrangements by taking into account the user's past reservation history and preferences. Some or all of the above-described processing in the reservation unit may be performed using, for example, AI, or may be performed without using AI. For example, the reservation unit can input the user's past reservation history data into a generation AI and make optimal reservation arrangements based on the analysis results of the generation AI.

[0099] The reservation unit can optimize reservation arrangements by incorporating real-time external data at the time of reservation. The reservation unit can, for example, make optimal travel arrangements based on real-time traffic conditions. The reservation unit can also make optimal accommodation arrangements based on real-time weather forecasts. Furthermore, the reservation unit can also make optimal experience arrangements based on real-time event information. In this way, reservation arrangements can be optimized by incorporating real-time external data. Some or all of the above-mentioned processing in the reservation unit may be performed using, for example, AI, or may be performed without using AI. For example, the reservation unit can input real-time external data into the generation AI and optimize reservation arrangements based on the results of analysis by the generation AI.

[0100] The reservation unit can estimate the user's emotions and prioritize reservation arrangements based on the estimated user emotions. For example, if the user is in a hurry, the reservation unit can prioritize important reservation arrangements. Furthermore, if the user is relaxed, the reservation unit can provide detailed reservation options and suggest customizable reservation arrangements. Furthermore, if the user is feeling anxious, the reservation unit can prioritize reservation arrangements that provide a sense of security. This allows the reservation arrangements to be optimally tailored to the user by prioritizing reservation arrangements based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the reservation unit can be performed using, for example, AI, or without AI. For example, the reservation unit can input the user's emotion data into the generation AI and prioritize reservation arrangements based on the analysis results of the generation AI.

[0101] The reservation unit can customize the reservation arrangement to region-specific information by taking into account the user's geographical location information when making a reservation. For example, if the user is in a specific region, the reservation unit reflects accommodations and transportation options in that region in the reservation arrangement. Furthermore, if the user is in a specific region, the reservation unit can also reflect event information for that region in the reservation arrangement. Furthermore, if the user is in a specific region, the reservation unit can also reflect weather forecasts and evacuation shelter information for that region in the reservation arrangement. This allows region-specific information to be provided by customizing the reservation arrangement based on the user's geographical location information. Some or all of the above-described processing in the reservation unit may be performed, for example, using AI, or may be performed without AI. For example, the reservation unit can input the user's geographical location information into a generation AI and customize the reservation arrangement to region-specific information based on the analysis results of the generation AI.

[0102] The reservation unit can analyze the user's social media activity at the time of reservation and provide relevant reservation arrangements. For example, the reservation unit can provide relevant reservation arrangements based on travel destinations and experiences shared by the user on social media. The reservation unit can also provide relevant reservation arrangements based on tourist attractions and event information followed by the user on social media. Furthermore, the reservation unit can provide relevant reservation arrangements based on places and activities the user has expressed interest in on social media. In this way, by providing reservation arrangements based on the user's social media activity, reservation arrangements that match the user's preferences can be provided. Some or all of the above-described processing in the reservation unit may be performed, for example, using AI or without AI. For example, the reservation unit can input the user's social media data into a generation AI and provide relevant reservation arrangements based on the analysis results of the generation AI. === Hard Collateral 1-1 === Each of the multiple elements, including the reception unit, analysis unit, generation unit, display unit, information provision unit, and reservation unit, 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 reception device 38 of the smart device 14 and receives input from the user of the budget, duration, desired experiences, places to visit, and considerations. The analysis unit is realized, for example, 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, for example, by the specific processing unit 290 of the data processing device 12 and generates an optimal travel plan based on the analyzed information. The display unit is realized by the output device 40 of the smart device 14 and displays the generated travel plan. The information provision unit is realized by the output device 40 of the smart device 14 and the specific processing unit 290 of the data processing device 12 and provides real-time information. The reservation unit is realized by the specific processing unit 290 of the data processing device 12 and makes reservations based on the travel plan. === Hard Collateral 1-2 === Each of the multiple elements, including the reception unit, analysis unit, generation unit, display unit, information provision unit, and reservation unit, described above, 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 microphone 238 of the smart glasses 214 and receives input from the user regarding budget, duration, desired experiences, places to visit, and considerations. The analysis unit is realized, for example, 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, for example, by the specific processing unit 290 of the data processing device 12 and generates an optimal travel plan based on the analyzed information. The display unit is realized by the speaker 240 of the smart glasses 214 and displays the generated travel plan. The information provision unit is realized by the speaker 240 of the smart glasses 214 and the specific processing unit 290 of the data processing device 12 and provides real-time information. The reservation unit is realized by the specific processing unit 290 of the data processing device 12 and makes reservations based on the travel plan. === Hard Collateral 1-3 === Each of the multiple elements, including the reception unit, analysis unit, generation unit, display unit, information provision unit, and reservation unit, 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 microphone 238 of the headset terminal 314 and receives input from the user regarding the budget, duration, desired experiences, places to visit, and considerations. The analysis unit is realized, for example, 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, for example, by the specific processing unit 290 of the data processing device 12 and generates an optimal travel plan based on the analyzed information. The display unit is realized by the display 343 of the headset terminal 314 and displays the generated travel plan. The information provision unit is realized by the display 343 of the headset terminal 314 and the specific processing unit 290 of the data processing device 12 and provides real-time information. The reservation unit is realized by the specific processing unit 290 of the data processing device 12 and makes reservations based on the travel plan. === Hard Collateral 1-4 === Each of the multiple elements, including the reception unit, analysis unit, generation unit, display unit, information provision unit, and reservation unit, 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 microphone 238 of the robot 414 and receives input from the user regarding budget, duration, desired experiences, places to visit, and considerations. The analysis unit is realized, for example, 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, for example, by the specific processing unit 290 of the data processing device 12 and generates an optimal travel plan based on the analyzed information. The display unit is realized by the speaker 240 of the robot 414 and displays the generated travel plan. The information provision unit is realized by the speaker 240 of the robot 414 and the specific processing unit 290 of the data processing device 12 and provides real-time information. The reservation unit is realized by the specific processing unit 290 of the data processing device 12 and makes reservations based on the travel plan.

[0103] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0104] The reception unit can monitor the user's health condition and dynamically change the design of the input interface. For example, if the user is tired, a simple, highly visible interface is provided to facilitate input work. Alternatively, if the user is relaxed, detailed input items can be displayed and a customizable input method can be provided. Furthermore, if the user is feeling stressed, an interface with calming colors can be provided to reduce visual stress. In this way, the design of the input interface can be changed according to the user's health condition, making the user's input work more comfortable.

[0105] The analysis unit can improve the accuracy of analysis by taking into account the user's past travel history and preferences. For example, it can propose a travel plan that matches the user's preferences based on the places the user has visited and experiences they have had in the past. It can also propose an optimal travel plan based on the budget and period set by the user in the past. It can also propose a travel plan that gives the user a sense of security based on the considerations the user has selected in the past. In this way, the analysis accuracy is improved by taking into account the user's past travel history and preferences.

[0106] The generation unit can estimate the user's emotions and adjust the content of the generated travel plan based on the estimated user emotions. For example, if the user is relaxed, the generation unit can generate a travel plan that proceeds at a leisurely pace. If the user is in a hurry, the generation unit can generate a travel plan that emphasizes efficient travel routes. Furthermore, if the user is excited, the generation unit can generate a travel plan that includes visually stimulating tourist spots. In this way, the generation unit can provide the user with an optimal plan by adjusting the content of the travel plan according to the user's emotions.

[0107] The display unit can estimate the user's emotions and dynamically change the design of the display interface based on the estimated user emotions. For example, if the user is nervous, a subdued interface can be provided to reduce visual stress. If the user is having fun, a bright interface can be provided to make display work more enjoyable. Furthermore, if the user is tired, a simple, highly visible interface can be provided to make display work easier. In this way, by changing the design of the display interface according to the user's emotions, the user's display work can be made more comfortable.

[0108] The information providing unit can estimate the user's emotions and adjust the content of the information to be provided based on the estimated user's emotions. For example, if the user is nervous, information that gives a sense of security can be provided preferentially. If the user is relaxed, detailed information can be provided to increase the enjoyment of the trip. Furthermore, if the user is in a hurry, important information can be provided concisely. In this way, by adjusting the content of the information to be provided according to the user's emotions, it is possible to provide the user with the most suitable information.

[0109] The reception unit can customize input items to region-specific information by taking into account the user's geographical location information. For example, when the user is in a specific region, tourist attractions and event information for that region can be displayed as input items. Also, when the user is in a specific region, transportation information for that region can be displayed as input items. Furthermore, when the user is in a specific region, weather forecasts and evacuation shelter information for that region can be displayed as input items. In this way, by customizing input items based on the user's geographical location information, it is possible to provide region-specific information.

[0110] The analysis unit can incorporate real-time external data during analysis to optimize the analysis results. For example, it can suggest optimal travel routes based on real-time traffic conditions. It can also suggest optimal sightseeing schedules based on real-time weather forecasts. It can also suggest optimal experience content based on real-time event information. In this way, incorporating real-time external data can optimize the analysis results.

[0111] The generation unit can generate an optimal travel plan by taking into account the user's past travel history and preferences. For example, a travel plan that matches the user's preferences is generated based on the places the user has visited in the past and the experiences they have had. The optimal travel plan can also be generated based on the budget and period set by the user in the past. Furthermore, a travel plan that gives a sense of security can also be generated based on the considerations selected by the user in the past. In this way, the optimal travel plan can be generated by taking into account the user's past travel history and preferences.

[0112] The display unit can incorporate real-time external data during display to optimize the display content. For example, it can display the optimal travel route based on real-time traffic conditions. It can also display the optimal sightseeing schedule based on real-time weather forecasts. It can also display the optimal experience content based on real-time event information. In this way, the display content can be optimized by incorporating real-time external data.

[0113] The reservation unit can make optimal reservation arrangements by taking into account the user's past reservation history and preferences when making a reservation. For example, optimal reservation arrangements can be made based on accommodations and transportation options used by the user in the past. Optimal reservation arrangements can also be made based on the budget and period set by the user in the past. Furthermore, reservation arrangements that provide a sense of security can also be made based on considerations selected by the user in the past. This makes it possible to provide optimal reservation arrangements by taking into account the user's past reservation history and preferences.

[0114] The processing flow of the second embodiment will be briefly explained below.

[0115] Step 1: The reception unit accepts input from the user of the budget, duration, desired experience, desired destination, and considerations. Information input by the user may include, for example, a budget of 100,000 yen or less, a duration of one week, desired experiences of hot springs and Japanese culture, desired destinations of Tokyo and Kyoto, and considerations such as adherence to religious regulations. Step 2: The analysis unit analyzes the information received by the reception unit. For example, the analysis unit extracts data for generating an optimal travel plan based on the information input by the user. Step 3: The generation unit generates an optimal travel plan based on the information analyzed by the analysis unit. For example, the generation unit selects accommodations and tourist spots within the budget and generates a plan that also includes information on public transportation transfers and evacuation shelters. Step 4: The display unit displays the itinerary generated by the generation unit. The display unit displays, for example, the itinerary generated based on the conditions selected by the user on a screen. Step 5: The information providing unit provides real-time information based on the travel plan displayed by the display unit. For example, the information providing unit provides transportation transfer information and evacuation shelter information using a real-time information providing device. Step 6: The reservation unit makes reservations based on the travel plan displayed by the display unit. The reservation unit can, for example, make reservations for accommodations and transportation all at once.

[0116] 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.

[0117] 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 the generative AI include a neural network (NN) and a neural network (NN). 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 (e.g., still image data or video data). 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 one or more data formats of voice data, text data, image data, etc. 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 may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0118] 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.

[0119] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0120] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0121] 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.

[0122] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0123] The 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.

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

[0125] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0126] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0127] Fig. 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.

[0128] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0129] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0130] In the 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.

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

[0132] The specific processing unit 290 transmits the result of the specific processing to the 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.

[0133] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0134] 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.

[0135] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0136] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0137] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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).

[0142] 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.

[0143] 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.

[0144] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0145] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0146] In the 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.

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

[0148] The specific processing unit 290 transmits the result of the specific processing to the 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.

[0149] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0150] 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.

[0151] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0152] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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).

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0167] 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.

[0168] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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).

[0173] 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 indicated, and when they approach the ideal, a state of pleasure is indicated. 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 indicated, and when they approach the ideal, a state of pleasure is indicated. 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.

[0174] 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."

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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.

[0182] 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.

[0183] 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.

[0184] 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.

[0185] 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.

[0186] 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.

[0187] [Explanation of symbols]

[0188] 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 from the user about the budget, duration, desired experience, places to go, and other considerations; an analysis unit that analyzes the information received by the reception unit; a generation unit that generates an optimal travel plan based on the information analyzed by the analysis unit; a display unit that displays the travel plan generated by the generation unit; an information providing unit that provides real-time information based on the travel plan displayed by the display unit; a reservation unit that makes reservations based on the travel plan displayed by the display unit; A system characterized by:

2. The information providing unit Providing information on transportation transfers and evacuation shelters using real-time information provision devices 2. The system of claim 1.

3. The reception unit Estimate user emotions and dynamically change the design of the input interface based on the estimated user emotions.

2. The system of claim 1.

4. The reception unit Refer to the user's past travel history and auto-complete input fields 2. The system of claim 1.

5. The reception unit Display additional relevant information in real time based on user input 2. The system of claim 1.

6. The reception unit Estimate user emotions and dynamically change the priority of input items based on the estimated user emotions 2. The system of claim 1.

7. The reception unit Consider the user's geographic location and customize input fields with localized information 2. The system of claim 1.

8. The reception unit Analyze your social media activity to provide relevant travel suggestions 2. The system of claim 1.

9. The analysis unit Estimate the user's emotions and dynamically adjust the parameters of the analysis algorithm based on the estimated user emotions.

2. The system of claim 1.

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