system

Abstract

The system according to the embodiment aims to handle everything from planning an individual trip to making a reservation, creating a schedule, and providing local information all in one place. [Solution] A system according to an embodiment includes a reception unit, a reservation unit, a schedule unit, and an information provision unit. The reception unit receives a user's travel requests. The reservation unit makes necessary reservations based on the information received by the reception unit. The schedule unit creates a detailed schedule based on the information reserved by the reservation unit. The information provision unit provides local information based on the schedule created by the schedule 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 to plan individual trips, make reservations, create schedules, and receive local information all in one place.

[0005] The system according to the embodiment aims to handle everything from planning an individual trip to making a reservation, creating a schedule, and providing local information all in one place. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, a reservation unit, a schedule unit, and an information provision unit. The reception unit receives a user's travel requests. The reservation unit makes necessary reservations based on the information received by the reception unit. The schedule unit creates a detailed schedule based on the information reserved by the reservation unit. The information provision unit provides local information based on the schedule created by the schedule unit. [Effects of the Invention]

[0007] The system according to the embodiment can handle everything from planning an individual trip to making a reservation, creating a schedule, and providing local information all 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) A travel planning system according to an embodiment of the present invention utilizes a generation AI to handle everything from planning to booking a personal trip. In this travel planning system, a user inputs their travel preferences, and the generation AI handles all necessary reservations and contacts, including plane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, and events and restaurants at tourist spots. The system also checks routes and timetables for major tourist spots, creates a detailed, minute-by-minute schedule, and provides updated travel directions in case of missed trains. The system also provides information on local history, terrain, weather, safety, local specialties, and recommended souvenirs. Finally, the system provides a packing list and local considerations (e.g., if traveling with small children). For example, when a user inputs their travel preferences, they input information such as the departure point, destination, travel dates, budget, and desired activities. The generation AI then analyzes the input information and creates a trip plan. For example, the system reserves bullet train tickets from Tokyo to Kyoto, arranges accommodations in Kyoto, and reserves a rental car for sightseeing. It also makes reservations for events and restaurants at tourist spots. The generation AI checks routes and timetables for major tourist spots and creates detailed, minute-by-minute schedules. For example, it plans a route around Kyoto's tourist attractions and incorporates detailed visit and travel times for each attraction into the schedule. In the unlikely event of a missed train, it re-presents an alternative route. The generation AI also presents information about the local history, terrain, weather, public safety, local cuisine, and optimal souvenirs. For example, it provides information about Kyoto's history, famous places, weather information, public safety, local cuisine, and recommended souvenirs. This allows users to understand local information in advance. The generation AI also provides a list of items to pack and points to consider while traveling. For example, if traveling with small children, it lists necessary items and precautions. This allows users to thoroughly prepare for their trip. In this way, the present invention is a system that uses generation AI to handle everything from planning to booking for individual trips, improving the user's travel experience. This allows the travel planning system to accept users' travel requests in one place and handle reservations, schedule creation, and information provision.

[0029] A travel planning system according to an embodiment includes a reception unit, a reservation unit, a schedule unit, and an information providing unit. The reception unit receives a user's travel preferences. The user's travel preferences include, but are not limited to, a travel destination, a travel period, a budget, and a purpose. For example, when a user inputs their travel preferences, the reception unit can input information such as a departure point, a destination, travel itineraries, a budget, and desired activities. The reservation unit makes necessary reservations based on the information received by the reception unit. The reservation unit makes reservations and contacts for, for example, airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events and restaurants at tourist spots, etc. For example, the reservation unit reserves a bullet train ticket from Tokyo to Kyoto, arranges accommodation in Kyoto, and reserves a rental car for sightseeing tours. It also makes reservations for events and restaurants at tourist spots. The schedule unit creates a detailed schedule based on the information reserved by the reservation unit. For example, the schedule unit checks routes and timetables for travelling through major tourist spots and creates a detailed, minute-by-minute schedule. For example, the scheduling unit plans a route to visit tourist attractions in Kyoto and incorporates detailed visit times and travel times for each tourist attraction into the schedule. In the unlikely event that a user misses a train, an alternative travel route is presented. The information providing unit provides local information based on the schedule created by the scheduling unit. The information providing unit provides, for example, information on the local history, terrain, weather, public safety, local specialties, and the best souvenirs. For example, the information providing unit provides Kyoto's history, famous places, weather information, public safety, local specialties, and recommended souvenirs. This allows the user to understand local information in advance. Furthermore, the information providing unit provides a list of items to bring and points to consider while traveling. For example, if the user has small children, the information providing unit lists necessary items to bring and points to be aware of. This allows the user to thoroughly prepare for the trip. As a result, the travel planning system according to the embodiment can accept the user's travel requests in one go, make reservations, create schedules, and provide information.

[0030] The information providing unit can provide information on the history, terrain, weather, public safety, local cuisine, and souvenirs of the local area. For example, the information providing unit provides specific information on the history and terrain of the local area. For example, the information providing unit provides the historical background and geographical features of the local area. The information providing unit also provides local weather information. For example, the information providing unit provides weather information such as temperature, precipitation, and wind speed. The information providing unit also provides local public safety information. For example, the information providing unit provides public safety information such as crime rates and safety measures. The information providing unit also provides information on local specialty cuisine. For example, the information providing unit provides information on dishes and restaurants unique to the region. The information providing unit also provides information on local souvenirs. For example, the information providing unit provides souvenir information such as local specialties and where to purchase them. This allows the user's travel experience to be improved by providing detailed local information.

[0031] The schedule unit can check routes and timetables for traveling through major tourist spots, create a minute-by-minute schedule, and re-present travel routes in case of missed trains. The schedule unit, for example, plans routes for traveling through major tourist spots. For example, the schedule unit selects routes based on the popularity and historical value of tourist spots. The schedule unit also checks timetables. For example, the schedule unit checks public transportation timetables and operation status. Furthermore, the schedule unit creates detailed minute-by-minute schedules. For example, the schedule unit incorporates visit times and travel times into the schedule in detail. In the unlikely event that a train is missed, the schedule unit re-presents an alternative travel route. For example, the schedule unit suggests an alternative route in case of a delay. In this way, by creating a detailed schedule and providing measures in case of missed trains, travel planning can proceed smoothly.

[0032] The information providing unit can provide a packing list and points to consider when traveling. The information providing unit, for example, provides a packing list. For example, the information providing unit lists essential items and recommended items needed for the trip. The information providing unit also provides points to consider when traveling. For example, the information providing unit provides information on cultural considerations and health management. In this way, by providing a packing list and points to consider when traveling, the user can thoroughly prepare for their trip.

[0033] The reservation unit can make reservations and contact for airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events at tourist spots, and restaurants. The reservation unit, for example, makes reservations for airplane and bullet train tickets. For example, the reservation unit reserves tickets using a reservation site and assigns seats. The reservation unit also makes hotel reservations. For example, the reservation unit selects an accommodation plan and room type and makes a reservation. The reservation unit also makes meal reservations. For example, the reservation unit selects restaurant reservations and meal plans. The reservation unit also makes reservations for shuttle buses. For example, the reservation unit checks operating times and boarding locations and makes a reservation. The reservation unit also makes reservations for rental cars. For example, the reservation unit selects a vehicle type and a fare plan and makes a reservation. The reservation unit also makes reservations for events and restaurants at tourist spots. For example, the reservation unit checks event details and restaurant menus and makes a reservation. This allows all reservations and contact necessary for a trip to be made in one place.

[0034] The reception unit can analyze the user's past travel history and propose an optimal travel plan. The reception unit, for example, analyzes the user's past travel history. For example, the reception unit analyzes places the user has visited in the past, the travel period, the purpose of the trip, etc. The reception unit also proposes an optimal travel plan based on the analysis results. For example, the reception unit suggests similar travel destinations based on places the user has visited in the past. The reception unit also suggests a plan that includes preferred activities based on the user's past travel history. Furthermore, the reception unit proposes an optimal plan based on accommodations and means of transportation used by the user in the past. In this way, by proposing an optimal plan based on the user's past travel history, it is possible to provide a trip that suits the user's preferences.

[0035] The reception unit can perform filtering based on the user's current living situation and areas of interest when receiving a travel request. The reception unit, for example, takes into account the user's current living situation. For example, the reception unit proposes a travel plan taking into account the user's work situation and family situation. The reception unit also takes into account the user's areas of interest. For example, the reception unit proposes related travel destinations based on the user's hobbies and activities of interest. Furthermore, the reception unit takes into account the user's current health condition and physical strength. For example, the reception unit proposes a reasonable travel plan based on the user's health condition and physical strength. This makes it possible to provide an appropriate travel plan based on the user's living situation and areas of interest.

[0036] When accepting a travel request, the reception unit can prioritize suggesting highly relevant travel plans by taking into account the user's geographical location information. The reception unit, for example, considers the user's geographical location information. For example, the reception unit prioritizes suggesting travel destinations close to the user's current location. The reception unit also prioritizes suggesting travel destinations with convenient transportation from the user's current location. Furthermore, the reception unit prioritizes suggesting travel destinations that are suitable for the climate and season of the user's current location. In this way, by taking into account the user's geographical location information, it is possible to provide highly relevant travel plans.

[0037] The reception unit can analyze the user's social media activity and suggest related travel plans when accepting a travel request. The reception unit, for example, analyzes the user's social media activity. For example, the reception unit suggests similar travel destinations based on travel destinations shared by the user on social media. The reception unit also suggests related travel destinations based on posts the user has "liked" on social media. Furthermore, the reception unit suggests popular travel destinations based on travel destinations visited by the user's social media followers. This makes it possible to provide related travel plans based on the user's social media activity.

[0038] The reservation unit can adjust the level of detail of the reservation based on the importance of each reservation when making a reservation. The reservation unit, for example, determines the importance of each reservation. For example, the reservation unit determines the importance based on the purpose of the trip or the user's priority. The reservation unit also adjusts the level of detail of the reservation based on the importance. For example, the reservation unit provides detailed information for important reservations (such as flights or hotels). The reservation unit also provides concise information for less important reservations (such as restaurants). Furthermore, the reservation unit adjusts the reservation confirmation procedure according to the importance. In this way, by adjusting the level of detail according to the importance of each reservation, an efficient reservation procedure can be provided.

[0039] The reservation unit can apply different reservation algorithms depending on the category of each reservation when making a reservation. The reservation unit, for example, determines the category of each reservation. For example, the reservation unit classifies reservations into categories such as transportation, accommodation, and tourist destinations. The reservation unit also applies different reservation algorithms depending on each category. For example, the reservation unit applies an algorithm to select the optimal flight for an airplane reservation. Furthermore, the reservation unit applies an algorithm to select an accommodation that matches the user's preferences for a hotel reservation. Furthermore, the reservation unit applies an algorithm to select the optimal restaurant based on the user's food preferences for a restaurant reservation. In this way, by applying an algorithm depending on the category of each reservation, it is possible to provide an optimal reservation procedure.

[0040] At the time of making a reservation, the reservation unit can determine the priority of reservations based on the submission time of each reservation. The reservation unit, for example, determines the submission time of each reservation. For example, the reservation unit determines the submission time based on the reservation acceptance start date and submission deadline. The reservation unit also determines the priority of reservations based on the submission time. For example, the reservation unit gives priority to reservations submitted early. The reservation unit also gives priority to reservations with high urgency. Furthermore, the reservation unit adjusts the reservation confirmation procedure based on the submission time. In this way, by determining the priority of reservations based on the submission time, an efficient reservation procedure can be provided.

[0041] The reservation unit can adjust the order of reservations based on the relevance of each reservation when making a reservation. The reservation unit, for example, determines the relevance of each reservation. For example, the reservation unit determines the relevance of reservations within the same trip or related events. The reservation unit also adjusts the order of reservations based on the relevance. For example, the reservation unit prioritizes highly relevant reservations. The reservation unit also postpones less relevant reservations. Furthermore, the reservation unit adjusts the reservation confirmation procedure based on the relevance of the reservations. In this way, by adjusting the order based on the relevance of each reservation, an efficient reservation procedure can be provided.

[0042] When creating a schedule, the scheduling unit can adjust the level of detail of the schedule based on the importance of each tourist spot. The scheduling unit, for example, determines the importance of each tourist spot. For example, the scheduling unit determines the importance based on the popularity or historical value of the tourist spot. The scheduling unit also adjusts the level of detail of the schedule based on the importance. For example, the scheduling unit sets detailed visiting times for important tourist spots. The scheduling unit also sets brief visiting times for less important tourist spots. The scheduling unit also adjusts the schedule confirmation procedure according to the importance. In this way, by adjusting the level of detail of the schedule according to the importance of each tourist spot, efficient schedule creation can be provided.

[0043] When creating a schedule, the scheduling unit can apply different scheduling algorithms depending on the category of each tourist spot. The scheduling unit, for example, determines the category of each tourist spot. For example, the scheduling unit classifies tourist spots into categories such as historical attractions, natural landscapes, and activities. The scheduling unit also applies different scheduling algorithms depending on each category. For example, the scheduling unit applies an algorithm that sets detailed visiting times to historical tourist spots. The scheduling unit also applies a scheduling algorithm that takes weather information into account to natural tourist spots. The scheduling unit also applies a scheduling algorithm that takes meal times into account to gourmet spots. In this way, by applying an algorithm depending on the category of each tourist spot, it is possible to create an optimal schedule.

[0044] When creating a schedule, the scheduling unit can determine the priority of the schedule based on the submission date of each tourist spot. The scheduling unit, for example, determines the submission date of each tourist spot. For example, the scheduling unit determines the submission date based on the tourist spot's acceptance start date and submission deadline. The scheduling unit also determines the priority of the schedule based on the submission date. For example, the scheduling unit prioritizes tourist spots that are submitted early in the schedule. The scheduling unit also prioritizes tourist spots that are highly urgent in the schedule. Furthermore, the scheduling unit adjusts the schedule confirmation procedure based on the submission date. In this way, by determining the priority of the schedule based on the submission date, efficient schedule creation can be provided.

[0045] When creating a schedule, the scheduling unit can adjust the order of the schedule based on the relevance of each tourist spot. The scheduling unit, for example, determines the relevance of each tourist spot. For example, the scheduling unit determines the relevance based on tourist spots in the same area or related themes. The scheduling unit also adjusts the order of the schedule based on the relevance. For example, the scheduling unit prioritizes incorporating highly relevant tourist spots into the schedule. The scheduling unit also postpones less relevant tourist spots. Furthermore, the scheduling unit adjusts the schedule confirmation procedure based on the relevance of the tourist spots. This makes it possible to provide efficient schedule creation by adjusting the order based on the relevance of each tourist spot.

[0046] When providing information, the information providing unit can adjust the level of detail of the information based on the history of the local area and the importance of the land. The information providing unit, for example, determines the history of the local area and the importance of the land. For example, the information providing unit determines the importance based on historical value and geographical features. The information providing unit also adjusts the level of detail of the information based on the importance. For example, the information providing unit provides detailed information for important historical places. The information providing unit also provides concise information for places with low importance. Furthermore, the information providing unit adjusts the information confirmation procedure according to the importance. In this way, by adjusting the level of detail of the information according to the history of the local area and the importance of the land, efficient information provision can be achieved.

[0047] The information providing unit can apply different information provision algorithms depending on the category of the location when providing information. The information providing unit, for example, determines the category of the location. For example, the information providing unit classifies the location into categories such as tourist attractions, restaurants, and shopping areas. The information providing unit also applies different information provision algorithms depending on each category. For example, the information providing unit applies an algorithm that provides detailed information to historical locations. For natural locations, the information providing unit applies an information provision algorithm that takes weather information into account. Furthermore, the information providing unit applies an information provision algorithm that takes meal times into account to gourmet spots. In this way, optimal information can be provided by applying an algorithm depending on the category of the location.

[0048] When providing information, the information providing unit can determine the priority of information based on the submission time of the local information. The information providing unit, for example, determines the submission time of the local information. For example, the information providing unit determines the submission time based on the update frequency of the information and the submission deadline. The information providing unit also determines the priority of information based on the submission time. For example, the information providing unit prioritizes information submitted early. The information providing unit also prioritizes information with high urgency. Furthermore, the information providing unit adjusts the information confirmation procedure based on the submission time. In this way, by determining the priority of information based on the submission time, efficient information provision can be achieved.

[0049] When providing information, the information providing unit can adjust the order of information based on the relevance of the information in the local area. The information providing unit, for example, determines the relevance of the information in the local area. For example, the information providing unit determines the relevance based on information on the same theme or related events. The information providing unit also adjusts the order of the information based on the relevance. For example, the information providing unit provides highly relevant information preferentially. The information providing unit also postpones less relevant information. Furthermore, the information providing unit adjusts the information confirmation procedure based on the relevance of the information. In this way, by adjusting the order based on the relevance of the information in the local area, efficient information provision can be achieved.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] When accepting a user's travel requests, the reception unit can analyze the user's past travel history and propose a travel plan taking into account satisfaction and dissatisfaction with past trips. For example, the reception unit can re-propose activities and accommodations that the user was particularly satisfied with in places they have visited in the past. It can also provide a plan that avoids points that dissatisfied them with in past trips. Furthermore, the reception unit can analyze the user's preferences for specific seasons and events from their past travel history and propose a plan that includes the optimal time and events. This makes it possible to provide a travel plan that makes use of the user's past experience.

[0052] When providing information about local history, terrain, weather, public safety, local cuisine, and souvenirs, the information providing unit can also adjust the priority of information based on the user's interests. For example, a user interested in history can be given priority in information about the local historical background and famous places. A user interested in gourmet food can be given priority in information about local cuisine and recommended restaurants. Furthermore, information about related events and activities can also be provided based on the user's interests. This makes it possible to provide information tailored to the user's interests.

[0053] The scheduler can also adjust the schedule by taking into account the user's physical strength and health condition when checking routes and timetables for travelling to major tourist spots and creating a minute-by-minute schedule. For example, for a user who is not confident in their physical strength, a schedule with shorter travel distances and more rest time is provided. The schedule can also be adjusted to allow users to enjoy sightseeing at a comfortable pace according to their health condition. Furthermore, information on medical facilities and pharmacies is provided based on the user's health condition. This makes it possible to provide a schedule that suits the user's physical strength and health condition.

[0054] When providing a packing list or points to consider when traveling, the information providing unit can also adjust the list based on the climate and season of the user's travel destination. For example, if traveling to a cold region, cold weather gear and warm clothing will be added to the list. Also, if traveling to a hot region, sunscreen and light clothing will be added to the list. Furthermore, items specific to each season (for example, hay fever prevention goods and rain gear) will also be included in the list. This makes it possible to provide a packing list that is appropriate for the climate and season of the travel destination.

[0055] The reservation unit can also propose optimal plans based on the user's budget when making reservations and contacting users for airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events at tourist spots, and restaurants. For example, it can propose cost-effective accommodations and transportation options to users with limited budgets. It can also propose more luxurious plans or plans that include special experiences to users with more budget flexibility. It can also provide discount information and special offers depending on the budget. This makes it possible to provide optimal reservation plans that fit the user's budget.

[0056] The reception unit can analyze the user's past travel history and propose the optimal travel plan. For example, it analyzes the places the user has visited in the past, the travel period, the purpose of the trip, etc., and then proposes the optimal travel plan based on the analysis results. For example, it proposes similar travel destinations based on the places the user has visited in the past. It also proposes plans that include preferred activities based on the user's past travel history. It also proposes the optimal plan based on the accommodations and transportation methods the user has used in the past. In this way, it is possible to provide a trip that suits the user's preferences by proposing the optimal plan based on the user's past travel history.

[0057] When accepting a travel request, the reception unit can filter based on the user's current living situation and areas of interest. For example, the reception unit can propose travel plans taking into account the user's work situation and family situation. It can also propose related travel destinations based on the user's hobbies and activities of interest. It can also propose reasonable travel plans based on the user's current health condition and physical strength. This makes it possible to provide an appropriate travel plan based on the user's living situation and areas of interest.

[0058] When accepting a travel request, the reception unit can prioritize suggesting highly relevant travel plans by taking into account the user's geographical location information. For example, the reception unit can prioritize suggesting travel destinations close to the user's current location. Also, the reception unit can prioritize suggesting travel destinations with convenient transportation from the user's current location. Furthermore, the reception unit can prioritize suggesting travel destinations that are suitable for the climate and season of the user's current location. In this way, by taking into account the user's geographical location information, it is possible to provide highly relevant travel plans.

[0059] The processing flow of the first embodiment will be briefly explained below.

[0060] Step 1: The reception unit receives the user's travel preferences. The user's travel preferences include the travel destination, duration, budget, purpose, etc. For example, when the user inputs their travel preferences, they can enter information such as the departure point, destination, travel schedule, budget, and desired activities. Step 2: The Reservation Department makes the necessary reservations based on the information received by the Reception Department. For example, it makes reservations and contacts for airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events and restaurants in tourist spots, etc. Specifically, it books bullet train tickets from Tokyo to Kyoto, arranges accommodation in Kyoto, and reserves a rental car for touring tourist spots. It also makes reservations for events and restaurants in tourist spots. Step 3: The scheduling department creates a detailed schedule based on the information reserved by the reservation department. For example, it checks the route and timetable for travelling through major tourist spots and creates a detailed, minute-by-minute schedule. Specifically, it plans a route around Kyoto's tourist attractions and incorporates detailed visit times and travel times for each tourist spot into the schedule. In the unlikely event that a train is missed, an alternative travel route is presented again. Step 4: The information provision department provides local information based on the schedule created by the schedule department. For example, it provides information on the local history, terrain, weather, public safety, local cuisine, and the best souvenirs. Specifically, it provides information on Kyoto's history, famous places, weather information, public safety, local cuisine, and recommended souvenirs. It also provides a list of items to bring and things to consider when traveling to the area. For example, if you have small children, it lists the necessary items to bring and things to be careful of.

[0061] (Example 2) A travel planning system according to an embodiment of the present invention utilizes a generation AI to handle everything from planning to booking a personal trip. In this travel planning system, a user inputs their travel preferences, and the generation AI handles all necessary reservations and contacts, including plane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, and events and restaurants at tourist spots. The system also checks routes and timetables for major tourist spots, creates a detailed, minute-by-minute schedule, and provides updated travel directions in case of missed trains. The system also provides information on local history, terrain, weather, safety, local specialties, and recommended souvenirs. Finally, the system provides a packing list and local considerations (e.g., if traveling with small children). For example, when a user inputs their travel preferences, they input information such as the departure point, destination, travel dates, budget, and desired activities. The generation AI then analyzes the input information and creates a trip plan. For example, the system reserves bullet train tickets from Tokyo to Kyoto, arranges accommodations in Kyoto, and reserves a rental car for sightseeing. It also makes reservations for events and restaurants at tourist spots. The generation AI checks routes and timetables for major tourist spots and creates detailed, minute-by-minute schedules. For example, it plans a route around Kyoto's tourist attractions and incorporates detailed visit and travel times for each attraction into the schedule. In the unlikely event of a missed train, it re-presents an alternative route. The generation AI also presents information about the local history, terrain, weather, public safety, local cuisine, and optimal souvenirs. For example, it provides information about Kyoto's history, famous places, weather information, public safety, local cuisine, and recommended souvenirs. This allows users to understand local information in advance. The generation AI also provides a list of items to pack and points to consider while traveling. For example, if traveling with small children, it lists necessary items and precautions. This allows users to thoroughly prepare for their trip. In this way, the present invention is a system that uses generation AI to handle everything from planning to booking for individual trips, improving the user's travel experience. This allows the travel planning system to accept users' travel requests in one place and handle reservations, schedule creation, and information provision.

[0062] A travel planning system according to an embodiment includes a reception unit, a reservation unit, a schedule unit, and an information providing unit. The reception unit receives a user's travel preferences. The user's travel preferences include, but are not limited to, a travel destination, a travel period, a budget, and a purpose. For example, when a user inputs their travel preferences, the reception unit can input information such as a departure point, a destination, travel itineraries, a budget, and desired activities. The reservation unit makes necessary reservations based on the information received by the reception unit. The reservation unit makes reservations and contacts for, for example, airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events and restaurants at tourist spots, etc. For example, the reservation unit reserves a bullet train ticket from Tokyo to Kyoto, arranges accommodation in Kyoto, and reserves a rental car for sightseeing tours. It also makes reservations for events and restaurants at tourist spots. The schedule unit creates a detailed schedule based on the information reserved by the reservation unit. For example, the schedule unit checks routes and timetables for travelling through major tourist spots and creates a detailed, minute-by-minute schedule. For example, the scheduling unit plans a route to visit tourist attractions in Kyoto and incorporates detailed visit times and travel times for each tourist attraction into the schedule. In the unlikely event that a user misses a train, an alternative travel route is presented. The information providing unit provides local information based on the schedule created by the scheduling unit. The information providing unit provides, for example, information on the local history, terrain, weather, public safety, local specialties, and the best souvenirs. For example, the information providing unit provides Kyoto's history, famous places, weather information, public safety, local specialties, and recommended souvenirs. This allows the user to understand local information in advance. Furthermore, the information providing unit provides a list of items to bring and points to consider while traveling. For example, if the user has small children, the information providing unit lists necessary items to bring and points to be aware of. This allows the user to thoroughly prepare for the trip. As a result, the travel planning system according to the embodiment can accept the user's travel requests in one go, make reservations, create schedules, and provide information.

[0063] The information providing unit can provide information on the history, terrain, weather, public safety, local cuisine, and souvenirs of the local area. For example, the information providing unit provides specific information on the history and terrain of the local area. For example, the information providing unit provides the historical background and geographical features of the local area. The information providing unit also provides local weather information. For example, the information providing unit provides weather information such as temperature, precipitation, and wind speed. The information providing unit also provides local public safety information. For example, the information providing unit provides public safety information such as crime rates and safety measures. The information providing unit also provides information on local specialty cuisine. For example, the information providing unit provides information on dishes and restaurants unique to the region. The information providing unit also provides information on local souvenirs. For example, the information providing unit provides souvenir information such as local specialties and where to purchase them. This allows the user's travel experience to be improved by providing detailed local information.

[0064] The schedule unit can check routes and timetables for traveling through major tourist spots, create a minute-by-minute schedule, and re-present travel routes in case of missed trains. The schedule unit, for example, plans routes for traveling through major tourist spots. For example, the schedule unit selects routes based on the popularity and historical value of tourist spots. The schedule unit also checks timetables. For example, the schedule unit checks public transportation timetables and operation status. Furthermore, the schedule unit creates detailed minute-by-minute schedules. For example, the schedule unit incorporates visit times and travel times into the schedule in detail. In the unlikely event that a train is missed, the schedule unit re-presents an alternative travel route. For example, the schedule unit suggests an alternative route in case of a delay. In this way, by creating a detailed schedule and providing measures in case of missed trains, travel planning can proceed smoothly.

[0065] The information providing unit can provide a packing list and points to consider when traveling. The information providing unit, for example, provides a packing list. For example, the information providing unit lists essential items and recommended items needed for the trip. The information providing unit also provides points to consider when traveling. For example, the information providing unit provides information on cultural considerations and health management. In this way, by providing a packing list and points to consider when traveling, the user can thoroughly prepare for their trip.

[0066] The reservation unit can make reservations and contact for airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events at tourist spots, and restaurants. The reservation unit, for example, makes reservations for airplane and bullet train tickets. For example, the reservation unit reserves tickets using a reservation site and assigns seats. The reservation unit also makes hotel reservations. For example, the reservation unit selects an accommodation plan and room type and makes a reservation. The reservation unit also makes meal reservations. For example, the reservation unit selects restaurant reservations and meal plans. The reservation unit also makes reservations for shuttle buses. For example, the reservation unit checks operating times and boarding locations and makes a reservation. The reservation unit also makes reservations for rental cars. For example, the reservation unit selects a vehicle type and a fare plan and makes a reservation. The reservation unit also makes reservations for events and restaurants at tourist spots. For example, the reservation unit checks event details and restaurant menus and makes a reservation. This allows all reservations and contact necessary for a trip to be made in one place.

[0067] The reception unit can estimate the user's emotions and adjust the input method of the travel desires based on the estimated user emotions. The reception unit, for example, estimates the user's emotions. For example, the reception unit estimates the user's emotions using facial expression recognition or voice analysis. The reception unit also adjusts the input method of the travel desires based on the estimated user emotions. For example, if the user is feeling stressed, the reception unit provides a simple interface and minimizes input steps. If the user is relaxed, the reception unit provides detailed input options and suggests a customizable input method. Furthermore, if the user is in a hurry, the reception unit prioritizes voice input, allowing the user to quickly input their travel desires. This makes it possible to provide a more comfortable input experience by adjusting the input method according to the user's emotions.

[0068] The reception unit can analyze the user's past travel history and propose an optimal travel plan. The reception unit, for example, analyzes the user's past travel history. For example, the reception unit analyzes places the user has visited in the past, the travel period, the purpose of the trip, etc. The reception unit also proposes an optimal travel plan based on the analysis results. For example, the reception unit suggests similar travel destinations based on places the user has visited in the past. The reception unit also suggests a plan that includes preferred activities based on the user's past travel history. Furthermore, the reception unit proposes an optimal plan based on accommodations and means of transportation used by the user in the past. In this way, by proposing an optimal plan based on the user's past travel history, it is possible to provide a trip that suits the user's preferences.

[0069] The reception unit can perform filtering based on the user's current living situation and areas of interest when receiving a travel request. The reception unit, for example, takes into account the user's current living situation. For example, the reception unit proposes a travel plan taking into account the user's work situation and family situation. The reception unit also takes into account the user's areas of interest. For example, the reception unit proposes related travel destinations based on the user's hobbies and activities of interest. Furthermore, the reception unit takes into account the user's current health condition and physical strength. For example, the reception unit proposes a reasonable travel plan based on the user's health condition and physical strength. This makes it possible to provide an appropriate travel plan based on the user's living situation and areas of interest.

[0070] The reception unit can estimate the user's emotions and prioritize the travel wishes based on the estimated user emotions. The reception unit, for example, estimates the user's emotions. For example, the reception unit estimates the user's emotions using facial expression recognition or voice analysis. The reception unit also prioritizes the travel wishes based on the estimated user emotions. For example, if the user is excited, the reception unit prioritizes active activities. If the user is relaxed, the reception unit prioritizes relaxing travel destinations. If the user is stressed, the reception unit prioritizes stress-relieving travel destinations. In this way, by prioritizing the travel wishes according to the user's emotions, a more appropriate travel plan can be provided.

[0071] When accepting a travel request, the reception unit can prioritize suggesting highly relevant travel plans by taking into account the user's geographical location information. The reception unit, for example, considers the user's geographical location information. For example, the reception unit prioritizes suggesting travel destinations close to the user's current location. The reception unit also prioritizes suggesting travel destinations with convenient transportation from the user's current location. Furthermore, the reception unit prioritizes suggesting travel destinations that are suitable for the climate and season of the user's current location. In this way, by taking into account the user's geographical location information, it is possible to provide highly relevant travel plans.

[0072] The reception unit can analyze the user's social media activity and suggest related travel plans when accepting a travel request. The reception unit, for example, analyzes the user's social media activity. For example, the reception unit suggests similar travel destinations based on travel destinations shared by the user on social media. The reception unit also suggests related travel destinations based on posts the user has "liked" on social media. Furthermore, the reception unit suggests popular travel destinations based on travel destinations visited by the user's social media followers. This makes it possible to provide related travel plans based on the user's social media activity.

[0073] The reservation unit can estimate the user's emotion and adjust the way the reservation is presented based on the estimated user's emotion. The reservation unit, for example, estimates the user's emotion. For example, the reservation unit estimates the user's emotion using facial expression recognition or voice analysis. The reservation unit also adjusts the way the reservation is presented based on the estimated user's emotion. For example, the reservation unit provides detailed reservation information when the user is relaxed. The reservation unit also provides concise reservation information when the user is in a hurry. Furthermore, the reservation unit also provides visually appealing reservation information when the user is excited. In this way, by adjusting the way the reservation is presented according to the user's emotion, a more comfortable reservation experience can be provided.

[0074] The reservation unit can adjust the level of detail of the reservation based on the importance of each reservation when making a reservation. The reservation unit, for example, determines the importance of each reservation. For example, the reservation unit determines the importance based on the purpose of the trip or the user's priority. The reservation unit also adjusts the level of detail of the reservation based on the importance. For example, the reservation unit provides detailed information for important reservations (such as flights or hotels). The reservation unit also provides concise information for less important reservations (such as restaurants). Furthermore, the reservation unit adjusts the reservation confirmation procedure according to the importance. In this way, by adjusting the level of detail according to the importance of each reservation, an efficient reservation procedure can be provided.

[0075] The reservation unit can apply different reservation algorithms depending on the category of each reservation when making a reservation. The reservation unit, for example, determines the category of each reservation. For example, the reservation unit classifies reservations into categories such as transportation, accommodation, and tourist destinations. The reservation unit also applies different reservation algorithms depending on each category. For example, the reservation unit applies an algorithm to select the optimal flight for an airplane reservation. Furthermore, the reservation unit applies an algorithm to select an accommodation that matches the user's preferences for a hotel reservation. Furthermore, the reservation unit applies an algorithm to select the optimal restaurant based on the user's food preferences for a restaurant reservation. In this way, by applying an algorithm depending on the category of each reservation, it is possible to provide an optimal reservation procedure.

[0076] The reservation unit can estimate the user's emotions and adjust the length of the reservation based on the estimated user's emotions. The reservation unit, for example, estimates the user's emotions. For example, the reservation unit estimates the user's emotions using facial expression recognition or voice analysis. The reservation unit also adjusts the length of the reservation based on the estimated user's emotions. For example, the reservation unit provides a longer reservation procedure when the user is relaxed. Furthermore, the reservation unit provides a reservation procedure that can be completed in a short time when the user is in a hurry. Furthermore, the reservation unit provides a visually appealing reservation procedure when the user is excited. In this way, by adjusting the length of the reservation according to the user's emotions, a more comfortable reservation experience can be provided.

[0077] At the time of making a reservation, the reservation unit can determine the priority of reservations based on the submission time of each reservation. The reservation unit, for example, determines the submission time of each reservation. For example, the reservation unit determines the submission time based on the reservation acceptance start date and submission deadline. The reservation unit also determines the priority of reservations based on the submission time. For example, the reservation unit gives priority to reservations submitted early. The reservation unit also gives priority to reservations with high urgency. Furthermore, the reservation unit adjusts the reservation confirmation procedure based on the submission time. In this way, by determining the priority of reservations based on the submission time, an efficient reservation procedure can be provided.

[0078] The reservation unit can adjust the order of reservations based on the relevance of each reservation when making a reservation. The reservation unit, for example, determines the relevance of each reservation. For example, the reservation unit determines the relevance of reservations within the same trip or related events. The reservation unit also adjusts the order of reservations based on the relevance. For example, the reservation unit prioritizes highly relevant reservations. The reservation unit also postpones less relevant reservations. Furthermore, the reservation unit adjusts the reservation confirmation procedure based on the relevance of the reservations. In this way, by adjusting the order based on the relevance of each reservation, an efficient reservation procedure can be provided.

[0079] The schedule unit can estimate the user's emotions and adjust the presentation method of the schedule based on the estimated user's emotions. The schedule unit, for example, estimates the user's emotions. For example, the schedule unit estimates the user's emotions using facial expression recognition or voice analysis. The schedule unit also adjusts the presentation method of the schedule based on the estimated user's emotions. For example, the schedule unit provides a detailed schedule when the user is relaxed. The schedule unit also provides a concise schedule when the user is in a hurry. Furthermore, the schedule unit also provides a visually appealing schedule when the user is excited. In this way, by adjusting the presentation method of the schedule according to the user's emotions, a more comfortable schedule experience can be provided.

[0080] When creating a schedule, the scheduling unit can adjust the level of detail of the schedule based on the importance of each tourist spot. The scheduling unit, for example, determines the importance of each tourist spot. For example, the scheduling unit determines the importance based on the popularity or historical value of the tourist spot. The scheduling unit also adjusts the level of detail of the schedule based on the importance. For example, the scheduling unit sets detailed visiting times for important tourist spots. The scheduling unit also sets brief visiting times for less important tourist spots. The scheduling unit also adjusts the schedule confirmation procedure according to the importance. In this way, by adjusting the level of detail of the schedule according to the importance of each tourist spot, efficient schedule creation can be provided.

[0081] When creating a schedule, the scheduling unit can apply different scheduling algorithms depending on the category of each tourist spot. The scheduling unit, for example, determines the category of each tourist spot. For example, the scheduling unit classifies tourist spots into categories such as historical attractions, natural landscapes, and activities. The scheduling unit also applies different scheduling algorithms depending on each category. For example, the scheduling unit applies an algorithm that sets detailed visiting times to historical tourist spots. The scheduling unit also applies a scheduling algorithm that takes weather information into account to natural tourist spots. The scheduling unit also applies a scheduling algorithm that takes meal times into account to gourmet spots. In this way, by applying an algorithm depending on the category of each tourist spot, it is possible to create an optimal schedule.

[0082] The scheduling unit can estimate the user's emotions and adjust the length of the schedule based on the estimated user's emotions. The scheduling unit, for example, estimates the user's emotions. For example, the scheduling unit estimates the user's emotions using facial expression recognition or voice analysis. The scheduling unit also adjusts the length of the schedule based on the estimated user's emotions. For example, the scheduling unit provides a longer schedule when the user is relaxed. Furthermore, the scheduling unit provides a schedule that can be completed in a short time when the user is in a hurry. Furthermore, the scheduling unit provides a visually appealing schedule when the user is excited. In this way, by adjusting the length of the schedule according to the user's emotions, a more comfortable schedule experience can be provided.

[0083] When creating a schedule, the scheduling unit can determine the priority of the schedule based on the submission date of each tourist spot. The scheduling unit, for example, determines the submission date of each tourist spot. For example, the scheduling unit determines the submission date based on the tourist spot's acceptance start date and submission deadline. The scheduling unit also determines the priority of the schedule based on the submission date. For example, the scheduling unit prioritizes tourist spots that are submitted early in the schedule. The scheduling unit also prioritizes tourist spots that are highly urgent in the schedule. Furthermore, the scheduling unit adjusts the schedule confirmation procedure based on the submission date. In this way, by determining the priority of the schedule based on the submission date, efficient schedule creation can be provided.

[0084] When creating a schedule, the scheduling unit can adjust the order of the schedule based on the relevance of each tourist spot. The scheduling unit, for example, determines the relevance of each tourist spot. For example, the scheduling unit determines the relevance based on tourist spots in the same area or related themes. The scheduling unit also adjusts the order of the schedule based on the relevance. For example, the scheduling unit prioritizes incorporating highly relevant tourist spots into the schedule. The scheduling unit also postpones less relevant tourist spots. Furthermore, the scheduling unit adjusts the schedule confirmation procedure based on the relevance of the tourist spots. This makes it possible to provide efficient schedule creation by adjusting the order based on the relevance of each tourist spot.

[0085] The information providing unit can estimate the user's emotion and adjust the method of providing information based on the estimated user's emotion. The information providing unit, for example, estimates the user's emotion. For example, the information providing unit estimates the user's emotion using facial expression recognition or voice analysis. Furthermore, the information providing unit adjusts the method of providing information based on the estimated user's emotion. For example, the information providing unit provides detailed information when the user is relaxed. Furthermore, the information providing unit provides concise information when the user is in a hurry. Furthermore, the information providing unit provides visually appealing information when the user is excited. In this way, by adjusting the method of providing information according to the user's emotion, more comfortable information can be provided.

[0086] When providing information, the information providing unit can adjust the level of detail of the information based on the history of the local area and the importance of the land. The information providing unit, for example, determines the history of the local area and the importance of the land. For example, the information providing unit determines the importance based on historical value and geographical features. The information providing unit also adjusts the level of detail of the information based on the importance. For example, the information providing unit provides detailed information for important historical places. The information providing unit also provides concise information for places with low importance. Furthermore, the information providing unit adjusts the information confirmation procedure according to the importance. In this way, by adjusting the level of detail of the information according to the history of the local area and the importance of the land, efficient information provision can be achieved.

[0087] The information providing unit can apply different information provision algorithms depending on the category of the location when providing information. The information providing unit, for example, determines the category of the location. For example, the information providing unit classifies the location into categories such as tourist attractions, restaurants, and shopping areas. The information providing unit also applies different information provision algorithms depending on each category. For example, the information providing unit applies an algorithm that provides detailed information to historical locations. For natural locations, the information providing unit applies an information provision algorithm that takes weather information into account. Furthermore, the information providing unit applies an information provision algorithm that takes meal times into account to gourmet spots. In this way, optimal information can be provided by applying an algorithm depending on the category of the location.

[0088] The information providing unit can estimate the user's emotion and adjust the length of information provided based on the estimated user's emotion. The information providing unit, for example, estimates the user's emotion. For example, the information providing unit estimates the user's emotion using facial expression recognition or voice analysis. The information providing unit also adjusts the length of information provided based on the estimated user's emotion. For example, the information providing unit provides detailed information when the user is relaxed. Furthermore, the information providing unit provides concise information when the user is in a hurry. Furthermore, the information providing unit provides visually appealing information when the user is excited. In this way, by adjusting the length of information provided according to the user's emotion, more comfortable information can be provided.

[0089] When providing information, the information providing unit can determine the priority of information based on the submission time of the local information. The information providing unit, for example, determines the submission time of the local information. For example, the information providing unit determines the submission time based on the update frequency of the information and the submission deadline. The information providing unit also determines the priority of information based on the submission time. For example, the information providing unit prioritizes information submitted early. The information providing unit also prioritizes information with high urgency. Furthermore, the information providing unit adjusts the information confirmation procedure based on the submission time. In this way, by determining the priority of information based on the submission time, efficient information provision can be achieved.

[0090] When providing information, the information providing unit can adjust the order of information based on the relevance of the information in the local area. The information providing unit, for example, determines the relevance of the information in the local area. For example, the information providing unit determines the relevance based on information on the same theme or related events. The information providing unit also adjusts the order of the information based on the relevance. For example, the information providing unit provides highly relevant information preferentially. The information providing unit also postpones less relevant information. Furthermore, the information providing unit adjusts the information confirmation procedure based on the relevance of the information. In this way, by adjusting the order based on the relevance of the information in the local area, efficient information provision can be achieved. === Hard Collateral 1-1 === Each of the above-described elements, including the reception unit, reservation unit, schedule unit, and information provider unit, is implemented, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is implemented by the control unit 46A of the smart device 14, and allows the user to input information such as the departure point, destination, travel itinerary, budget, and desired activities when inputting travel preferences. The reservation unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and makes reservations and contacts for airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events and restaurants at tourist spots, etc. The schedule unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and checks routes and timetables for travel to major tourist spots and creates detailed, minute-by-minute schedules. The information provider unit is implemented, for example, by the control unit 46A of the smart device 14, and provides information on local history, terrain, weather, public safety, specialty dishes, and suitable souvenirs. === Hard Collateral 1-2 === Each of the multiple elements, including the reception unit, reservation unit, schedule unit, and information provider unit, described above, is implemented, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is implemented by the control unit 46A of the smart glasses 214, and allows the user to input information such as the departure point, destination, travel itinerary, budget, and desired activities when inputting travel preferences. The reservation unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and makes reservations and contacts for airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events and restaurants at tourist spots, etc. The schedule unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and checks routes and timetables for travel to major tourist spots and creates detailed, minute-by-minute schedules. The information provider unit is implemented, for example, by the control unit 46A of the smart glasses 214, and provides information on local history, terrain, weather, public safety, specialty dishes, and suitable souvenirs. === Hard Collateral 1-3 === Each of the above-described elements, including the reception unit, reservation unit, schedule unit, and information provider unit, is implemented, for example, by at least one of the headset terminal 314 and the data processing device 12. For example, the reception unit is implemented by the control unit 46A of the headset terminal 314, and allows the user to input information such as the departure point, destination, travel itinerary, budget, and desired activities when inputting travel preferences. The reservation unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and makes reservations and contacts for airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events and restaurants at tourist spots, etc. The schedule unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and checks routes and timetables for travel to major tourist spots and creates detailed, minute-by-minute schedules. The information provider unit is implemented, for example, by the control unit 46A of the headset terminal 314, and provides information on local history, terrain, weather, public safety, specialty dishes, and suitable souvenirs. === Hard Collateral 1-4 === Each of the multiple elements, including the reception unit, reservation unit, schedule unit, and information provider unit, is implemented, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is implemented by the control unit 46A of the robot 414, and allows the user to input information such as the departure point, destination, travel itinerary, budget, and desired activities when inputting travel preferences. The reservation unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and makes reservations and contacts for airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events and restaurants at tourist spots, etc. The schedule unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and checks routes and timetables for travel to major tourist spots and creates detailed, minute-by-minute schedules. The information provider unit is implemented, for example, by the control unit 46A of the robot 414, and provides information on local history, terrain, weather, public safety, specialty dishes, and suitable souvenirs.

[0091] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0092] When accepting a user's travel requests, the reception unit can analyze the user's past travel history and propose a travel plan taking into account satisfaction and dissatisfaction with past trips. For example, the reception unit can re-propose activities and accommodations that the user was particularly satisfied with in places they have visited in the past. It can also provide a plan that avoids points that dissatisfied them with in past trips. Furthermore, the reception unit can analyze the user's preferences for specific seasons and events from their past travel history and propose a plan that includes the optimal time and events. This makes it possible to provide a travel plan that makes use of the user's past experience.

[0093] When providing information about local history, terrain, weather, public safety, local cuisine, and souvenirs, the information providing unit can also adjust the priority of information based on the user's interests. For example, a user interested in history can be given priority in information about the local historical background and famous places. A user interested in gourmet food can be given priority in information about local cuisine and recommended restaurants. Furthermore, information about related events and activities can also be provided based on the user's interests. This makes it possible to provide information tailored to the user's interests.

[0094] The scheduler can also adjust the schedule by taking into account the user's physical strength and health condition when checking routes and timetables for travelling to major tourist spots and creating a minute-by-minute schedule. For example, for a user who is not confident in their physical strength, a schedule with shorter travel distances and more rest time is provided. The schedule can also be adjusted to allow users to enjoy sightseeing at a comfortable pace according to their health condition. Furthermore, information on medical facilities and pharmacies is provided based on the user's health condition. This makes it possible to provide a schedule that suits the user's physical strength and health condition.

[0095] When providing a packing list or points to consider when traveling, the information providing unit can also adjust the list based on the climate and season of the user's travel destination. For example, if traveling to a cold region, cold weather gear and warm clothing will be added to the list. Also, if traveling to a hot region, sunscreen and light clothing will be added to the list. Furthermore, items specific to each season (for example, hay fever prevention goods and rain gear) will also be included in the list. This makes it possible to provide a packing list that is appropriate for the climate and season of the travel destination.

[0096] The reservation unit can also propose optimal plans based on the user's budget when making reservations and contacting users for airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events at tourist spots, and restaurants. For example, it can propose cost-effective accommodations and transportation options to users with limited budgets. It can also propose more luxurious plans or plans that include special experiences to users with more budget flexibility. It can also provide discount information and special offers depending on the budget. This makes it possible to provide optimal reservation plans that fit the user's budget.

[0097] The reception unit can estimate the user's emotions and adjust the input method for travel preferences based on the estimated user emotions. For example, if the user is feeling stressed, a simple interface can be provided to minimize input steps. Alternatively, if the user is relaxed, detailed input options can be provided and a customizable input method can be suggested. Furthermore, if the user is in a hurry, voice input can be prioritized to allow the user to quickly input their travel preferences. In this way, a more comfortable input experience can be provided by adjusting the input method according to the user's emotions.

[0098] The reception unit can analyze the user's past travel history and propose the optimal travel plan. For example, it analyzes the places the user has visited in the past, the travel period, the purpose of the trip, etc., and then proposes the optimal travel plan based on the analysis results. For example, it proposes similar travel destinations based on the places the user has visited in the past. It also proposes plans that include preferred activities based on the user's past travel history. It also proposes the optimal plan based on the accommodations and transportation methods the user has used in the past. In this way, it is possible to provide a trip that suits the user's preferences by proposing the optimal plan based on the user's past travel history.

[0099] When accepting a travel request, the reception unit can filter based on the user's current living situation and areas of interest. For example, the reception unit can propose travel plans taking into account the user's work situation and family situation. It can also propose related travel destinations based on the user's hobbies and activities of interest. It can also propose reasonable travel plans based on the user's current health condition and physical strength. This makes it possible to provide an appropriate travel plan based on the user's living situation and areas of interest.

[0100] The reception unit can estimate the user's emotions and prioritize travel wishes based on the estimated user emotions. For example, if the user is excited, active activities are prioritized. If the user is relaxed, relaxing travel destinations are prioritized. If the user is stressed, travel destinations that are useful for relieving stress are prioritized. In this way, by prioritizing travel wishes according to the user's emotions, a more appropriate travel plan can be provided.

[0101] When accepting a travel request, the reception unit can prioritize suggesting highly relevant travel plans by taking into account the user's geographical location information. For example, the reception unit can prioritize suggesting travel destinations close to the user's current location. Also, the reception unit can prioritize suggesting travel destinations with convenient transportation from the user's current location. Furthermore, the reception unit can prioritize suggesting travel destinations that are suitable for the climate and season of the user's current location. In this way, by taking into account the user's geographical location information, it is possible to provide highly relevant travel plans.

[0102] The processing flow of the second embodiment will be briefly explained below.

[0103] Step 1: The reception unit receives the user's travel preferences. The user's travel preferences include the travel destination, duration, budget, purpose, etc. For example, when the user inputs their travel preferences, they can enter information such as the departure point, destination, travel schedule, budget, and desired activities. Step 2: The Reservation Department makes the necessary reservations based on the information received by the Reception Department. For example, it makes reservations and contacts for airplane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events and restaurants in tourist spots, etc. Specifically, it books bullet train tickets from Tokyo to Kyoto, arranges accommodation in Kyoto, and reserves a rental car for touring tourist spots. It also makes reservations for events and restaurants in tourist spots. Step 3: The scheduling department creates a detailed schedule based on the information reserved by the reservation department. For example, it checks the route and timetable for travelling through major tourist spots and creates a detailed, minute-by-minute schedule. Specifically, it plans a route around Kyoto's tourist attractions and incorporates detailed visit times and travel times for each tourist spot into the schedule. In the unlikely event that a train is missed, an alternative travel route is presented again. Step 4: The information provision department provides local information based on the schedule created by the schedule department. For example, it provides information on the local history, terrain, weather, public safety, local cuisine, and the best souvenirs. Specifically, it provides information on Kyoto's history, famous places, weather information, public safety, local cuisine, and recommended souvenirs. It also provides a list of items to bring and things to consider when traveling to the area. For example, if you have small children, it lists the necessary items to bring and things to be careful of.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0108] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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).

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0124] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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).

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0140] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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).

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

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

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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).

[0161] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0162] 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."

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] [Explanation of symbols]

[0176] 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 travel requests from users; a reservation unit that makes necessary reservations based on the information received by the reception unit; a scheduling unit that creates a detailed schedule based on the information reserved by the reservation unit; an information providing unit that provides local information based on the schedule created by the scheduling unit; Equipped with A system characterized by:

2. The information providing unit Providing information on local history, land, weather, public safety, local cuisine, and souvenirs 2. The system of claim 1.

3. The scheduling unit Check routes and timetables for major tourist attractions, create minute-by-minute schedules, and refresh your travel route if you miss a train 2. The system of claim 1.

4. The information providing unit Providing a packing list and things to consider when you're there 2. The system of claim 1.

5. The reservation unit Make reservations and contact for plane and bullet train tickets, hotel reservations, meals, shuttle buses, rental cars, events at tourist spots, and restaurants.

2. The system of claim 1.

6. The reception unit Estimating user emotions and adjusting the input method of travel preferences based on the estimated user emotions 2. The system of claim 1.

7. The reception unit Analyzes the user's past travel history and suggests optimal travel plans 2. The system of claim 1.

8. The reception unit Filtering travel requests based on the user's current lifestyle and interests 2. The system of claim 1.

Images