system

Abstract

The system according to this embodiment aims to propose the optimal travel plan tailored to the traveler's preferences and budget, and to handle booking and arrangements in a consistent manner. [Solution] The system according to the embodiment comprises a reception unit, a proposal unit, an arrangement unit, and a support unit. The reception unit receives input from the traveler regarding their preferences and budget. The proposal unit analyzes the information received by the reception unit and proposes the optimal travel plan. The arrangement unit makes reservations and arrangements based on the plan proposed by the proposal unit. The support unit provides support during the trip.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0007] The system according to this embodiment can propose the optimal travel plan tailored to the traveler's preferences and budget, and handle booking and arrangements in a consistent manner. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

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

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

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

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

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

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

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

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

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

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

[0028] (Example of form 1) The travel plan suggestion system according to an embodiment of the present invention is a system that suggests travel plans tailored to the traveler's preferences and budget, and handles all reservations and arrangements. This system provides consistent support from the planning stage before the trip to support during the trip. The travel plan suggestion system allows the traveler to input their preferences and budget, and an AI agent analyzes this information to suggest the optimal travel plan. Based on the suggested plan, reservations and arrangements are made automatically. Furthermore, support during the trip is also provided, and emergency responses are handled. For example, the traveler inputs their preferences and budget. For example, they input their travel destination, type of accommodation, budget, purpose of travel, etc. This information is input into the AI ​​agent. Next, the AI ​​agent analyzes the input information and suggests the optimal travel plan. Based on the traveler's preferences and budget, the AI ​​agent suggests travel destinations, accommodations, tourist attractions, activities, etc. For example, it suggests a plan that allows for the best experience within the budget. Based on the suggested plan, reservations and arrangements are made automatically. The AI ​​agent automatically makes reservations for accommodations and transportation, and arranges tickets for tourist attractions, etc. This allows the traveler to prepare for their trip without any hassle. Furthermore, support during the trip is also provided. The AI ​​agent responds to troubles and emergencies that occur during the trip. For example, it handles things like changing or canceling reservations and dealing with problems that occur at the destination. This allows travelers to enjoy their trip with peace of mind. This system shortens the time spent on travel planning and allows for the handling of problems that occur during the trip. Travelers can easily obtain the optimal travel plan that suits their preferences and budget, and can spend their trip with peace of mind. In this way, the travel plan suggestion system can propose travel plans based on the traveler's preferences and budget, handle reservations and arrangements, and provide support during the trip.

[0029] The travel plan suggestion system according to this embodiment comprises a reception unit, a suggestion unit, an arrangement unit, and a support unit. The reception unit receives input from the traveler regarding their preferences and budget. Traveler preferences include, but are not limited to, the type of travel destination, the type of activity, and the food preferences. The budget includes, but are not limited to, the daily budget, the total budget, and the upper and lower limits of the budget. The suggestion unit analyzes the information received by the reception unit and proposes the optimal travel plan. The suggestion unit suggests, for example, travel destinations, accommodations, tourist attractions, and activities based on the traveler's preferences and budget. For example, the suggestion unit suggests a plan that allows for the best experience within the budget. The arrangement unit makes reservations and arrangements based on the plan proposed by the suggestion unit. The arrangement unit makes, for example, reservations for accommodations and transportation, and tickets for tourist attractions. For example, the arrangement unit can make reservations for accommodations. The arrangement unit can also make reservations for transportation. The arrangement unit can also make tickets for tourist attractions. The support unit provides support during the trip. The support department can, for example, respond to troubles and emergencies that may occur during the trip. For example, the support department can change or cancel reservations. For example, the support department can also handle problems at the destination. For example, the support department can also respond to emergencies. As a result, the travel plan proposal system according to this embodiment can propose travel plans based on the traveler's preferences and budget, make reservations and arrangements, and provide support during the trip.

[0030] The reception desk accepts input from travelers regarding their preferences and budget. Traveler preferences include, but are not limited to, the type of destination, type of activity, and dietary preferences. Specifically, destination types include beach resorts, mountainous regions, urban tourist destinations, and historical sites. Activity types include hiking, scuba diving, shopping, museum visits, and gourmet tours. Dietary preferences may include local cuisine, vegetarian, gluten-free, and specific national cuisines. Budgets include, but are not limited to, daily budgets, overall budgets, and budget upper and lower limits. Travelers can input this information through dedicated input forms or applications. The reception desk stores this information in a database and uses it for subsequent processing. Furthermore, the reception desk can refer to travelers' past travel history and ratings to use as foundational data for more accurate suggestions. For example, ratings of previously visited destinations and activities can provide a more detailed understanding of the traveler's preferences. This allows the reception desk to support the creation of customized travel plans tailored to the traveler's needs.

[0031] The Proposal Department analyzes the information received by the Reception Department and proposes the optimal travel plan. For example, the Proposal Department suggests destinations, accommodations, sightseeing spots, and activities based on the traveler's preferences and budget. Specifically, the Proposal Department uses AI to analyze the traveler's input information and generates the optimal travel plan based on past data and trend information. For example, if a traveler wants a beach resort and has a limited budget, the Proposal Department will select a cost-effective beach resort and suggest accommodations and activities that will provide the best experience within that budget. The AI ​​generates the optimal plan by considering destination ratings and reviews, seasonal price fluctuations, and specific event information. The Proposal Department can also refer to the traveler's past travel history and ratings to suggest a plan that matches the traveler's preferences. For example, based on ratings of previously visited destinations and activities participated in, it will prioritize suggesting destinations and activities that the traveler tends to prefer. This allows the Proposal Department to provide customized travel plans that meet the traveler's needs. Furthermore, the Proposal Department can collect traveler feedback and continuously improve the accuracy and effectiveness of its suggestions. This allows the Proposal Department to provide travelers with the optimal travel plan and improve their satisfaction.

[0032] The Arrangement Department handles reservations and arrangements based on the plans proposed by the Proposal Department. For example, the Arrangement Department handles reservations for accommodations and transportation, as well as ticket arrangements for tourist attractions. Specifically, the Arrangement Department checks the availability of proposed accommodations and reserves the most suitable rooms. For transportation, it arranges airline tickets, train tickets, and rental cars. The Arrangement Department selects and reserves the most suitable transportation options to match the traveler's schedule. Furthermore, for tourist attraction ticket arrangements, it pre-books tickets for popular attractions and activities to ensure travelers can enjoy their trip smoothly. The Arrangement Department centrally manages these reservations and arrangements, providing travelers with reservation confirmations and tickets. The Arrangement Department can also accommodate special requests and needs from travelers. For example, it can arrange special meals or barrier-free accommodations, offering flexible solutions tailored to the traveler's needs. This allows the Arrangement Department to provide travelers with a smooth and comfortable travel experience. Additionally, the Arrangement Department manages reservation status and arrangement details in real time, and can handle changes and cancellations as needed. This allows the booking department to provide travelers with quick and flexible responses, enabling them to smoothly proceed with their travel planning.

[0033] The support department provides assistance during your trip. For example, the support department will respond to any troubles or emergencies that may arise during your trip. Specifically, the support department provides 24-hour support if travelers encounter any problems at their destination. For example, they can change or cancel reservations. If a traveler experiences a sudden change of plans or trouble, the support department will respond quickly and change accommodation and transportation reservations. In addition, assistance with local troubles includes interpretation services if a traveler faces a language barrier and assistance in searching for lost items. Furthermore, they can also respond to emergencies. For example, if a traveler becomes ill or injured, they will arrange for local medical facilities and assist with insurance procedures. The support department prioritizes the safety and peace of mind of travelers and provides prompt and appropriate responses. This allows travelers to enjoy their trip with peace of mind. Furthermore, the support department can collect feedback from travelers and use it to improve its services. For example, based on travelers' opinions and requests, they will consider reviewing support services and introducing new services. This allows the support department to provide better support to travelers and improve their satisfaction.

[0034] The suggestion unit can propose the optimal travel plan based on the traveler's preferences and budget. For example, the suggestion unit can suggest destinations, accommodations, sightseeing spots, and activities based on the traveler's preferences and budget. For example, the suggestion unit can also propose a plan that offers the best experience within the budget. For example, the suggestion unit can also propose a plan customized to the traveler's preferences. In this way, the suggestion unit can propose the optimal travel plan based on the traveler's preferences and budget. Some or all of the above processing in the suggestion unit may be performed using, for example, a generative AI, or without a generative AI. For example, the suggestion unit can input information on the traveler's preferences and budget into a generative AI and have the generative AI propose the optimal travel plan.

[0035] The booking unit can make reservations for accommodations and transportation. The booking unit can, for example, make reservations for accommodations. The booking unit can also, for example, make reservations for transportation. The booking unit can also, for example, make reservations for tourist attractions. In this way, the booking unit can make reservations for accommodations and transportation. Some or all of the above processing in the booking unit may be performed using, for example, a generation AI, or not using a generation AI. For example, the booking unit can input reservations for accommodations and transportation into a generation AI and have the generation AI execute the reservation arrangements.

[0036] The support department can handle problems during travel. For example, the support department can respond to problems and emergencies that occur during travel. For example, the support department can change or cancel reservations. For example, the support department can also handle problems at the destination. For example, the support department can respond to emergencies. In this way, the support department can handle problems during travel. Some or all of the above-mentioned processes in the support department may be performed using, for example, a generative AI, or not using a generative AI. For example, the support department can input travel-related problems into a generative AI and have the generative AI execute the problem-solving.

[0037] The reception desk can analyze a traveler's past travel history and select the optimal input method. For example, the reception desk can automatically display destinations and budgets that the traveler has frequently entered in the past as suggestions. The reception desk can also prioritize suggesting input methods (voice, text, etc.) that the traveler has used in the past. For example, the reception desk can suggest input methods related to specific seasons or events based on the traveler's past travel history. This allows the reception desk to select the optimal input method based on the traveler's past travel history. Some or all of the above processing in the reception desk may be performed using, for example, a generative AI, or not using a generative AI. For example, the reception desk can input the traveler's past travel history into a generative AI and have the generative AI select the optimal input method.

[0038] The reception desk can filter travelers based on their current living situation and areas of interest when they input their preferences and budget. For example, when a traveler inputs their current living situation, the reception desk can prioritize displaying relevant travel destinations and activities. The reception desk can also customize input fields based on the traveler's areas of interest (e.g., outdoor activities, cultural experiences). The reception desk can also suggest the most suitable input method based on the traveler's current living situation (e.g., family structure, work situation). This allows the reception desk to filter based on the traveler's current living situation and areas of interest. Some or all of the above processing in the reception desk may be performed using, for example, generative AI, or not using generative AI. For example, the reception desk can input information about the traveler's current living situation and areas of interest into a generative AI and have the generative AI perform the filtering.

[0039] The reception desk can prioritize inputting highly relevant information by considering the traveler's geographical location when they input their preferences and budget. For example, when a traveler enters their current location, the reception desk can prioritize displaying nearby travel destinations and activities. The reception desk can also prioritize inputting relevant accommodations and transportation based on the traveler's geographical location. The reception desk can also suggest the optimal travel plan by considering the traveler's geographical location. This allows the reception desk to prioritize inputting highly relevant information based on the traveler's geographical location. Some or all of the above processing in the reception desk may be performed using, for example, a generative AI, or without a generative AI. For example, the reception desk can input the traveler's geographical location into a generative AI and have the generative AI prioritize inputting highly relevant information.

[0040] The reception desk can analyze the traveler's social media activity and input relevant information when the traveler enters their preferences and budget. For example, the reception desk can automatically suggest travel destinations and activities of interest based on the traveler's social media activity. The reception desk can also analyze the content of the traveler's social media posts and suggest relevant accommodations and transportation. For example, the reception desk can suggest the best travel plan by referring to the travel history of the traveler's social media followers and friends. This allows the reception desk to input relevant information based on the traveler's social media activity. Some or all of the above processing in the reception desk may be performed using, for example, generative AI, or not using generative AI. For example, the reception desk can input the traveler's social media activity into generative AI and have the generative AI input the relevant information.

[0041] The suggestion unit can adjust the level of detail in its suggestions based on the importance of the travel plan. For example, if a traveler enters an important travel plan, the suggestion unit will provide detailed information. If a traveler enters a short-term travel plan, the suggestion unit may provide concise information. If a traveler enters a long-term travel plan, the suggestion unit may suggest a detailed schedule and activities. This allows the suggestion unit to adjust the level of detail in its suggestions based on the importance of the travel plan. Some or all of the above processing in the suggestion unit may be performed using, for example, a generative AI, or without a generative AI. For example, the suggestion unit can input the importance of the travel plan into the generative AI and have the generative AI adjust the level of detail in its suggestions.

[0042] The suggestion unit can apply different suggestion algorithms depending on the category of the travel plan when making suggestions. For example, if the traveler wants an outdoor trip, the suggestion unit can apply a suggestion algorithm specialized for outdoor activities. For example, if the traveler wants a cultural experience, the suggestion unit can also apply a suggestion algorithm specialized for cultural experiences. For example, if the traveler wants a trip for relaxation, the suggestion unit can also apply a suggestion algorithm specialized for relaxation. In this way, the suggestion unit can apply different suggestion algorithms depending on the category of the travel plan. Some or all of the above processing in the suggestion unit may be performed using, for example, a generative AI, or without a generative AI. For example, the suggestion unit can input the category of the travel plan into a generative AI and have the generative AI execute the application of different suggestion algorithms.

[0043] The proposal department can determine the priority of proposals based on when the travel plan is submitted. For example, the proposal department may prioritize travel plans submitted early by travelers. The proposal department may also quickly propose travel plans submitted recently by travelers. For example, if a traveler submits a travel plan related to a specific event, the proposal department may make proposals tailored to that event. This allows the proposal department to determine the priority of proposals based on when the travel plan is submitted. Some or all of the above processing in the proposal department may be performed using, for example, a generative AI, or not using a generative AI. For example, the proposal department may input the travel plan submission dates into the generative AI and have the generative AI determine the priority of proposals.

[0044] The suggestion unit can adjust the order of suggestions based on the relevance of the travel plan when making suggestions. For example, the suggestion unit may prioritize displaying suggestions that are most relevant to the traveler's preferences and budget. The suggestion unit may also prioritize displaying suggestions that are highly relevant based on the traveler's past travel history. The suggestion unit may also prioritize displaying suggestions that are highly relevant based on the traveler's current living situation and areas of interest. This allows the suggestion unit to adjust the order of suggestions based on the relevance of the travel plan. Some or all of the above processing in the suggestion unit may be performed using, for example, a generative AI, or without a generative AI. For example, the suggestion unit may input the relevance of the travel plan into a generative AI and have the generative AI perform the adjustment of the suggestion order.

[0045] The booking department can analyze a traveler's past booking history to select the optimal booking method during the booking and booking process. For example, the booking department may prioritize booking accommodations and transportation methods previously used by the traveler. For example, the booking department may suggest booking methods that avoid congestion based on the traveler's past booking history. For example, the booking department may analyze a traveler's past booking history and suggest the most efficient booking method. This allows the booking department to select the optimal booking method based on the traveler's past booking history. Some or all of the above processing in the booking department may be performed using, for example, a generative AI, or without a generative AI. For example, the booking department may input the traveler's past booking history into a generative AI and have the generative AI select the optimal booking method.

[0046] The booking department can customize the booking arrangements based on the traveler's current living situation when making reservations. For example, if a traveler is planning a family trip, the booking department will prioritize booking family-friendly accommodations and activities. If a traveler is planning a business trip, the booking department can also prioritize booking business-friendly accommodations and transportation. If a traveler is planning a trip for relaxation, the booking department can also prioritize booking relaxing accommodations and activities. In this way, the booking department can customize the booking arrangements based on the traveler's current living situation. Some or all of the above processing in the booking department may be performed using, for example, a generative AI, or not using a generative AI. For example, the booking department can input the traveler's current living situation into a generative AI and have the generative AI perform the customization of the booking arrangements.

[0047] The booking unit can select the optimal booking method by considering the traveler's geographical location information when making a reservation. For example, when a traveler enters their current location, the booking unit can prioritize booking nearby accommodations and transportation. The booking unit can also prioritize booking relevant activities and tourist destinations based on the traveler's geographical location information. The booking unit can also suggest the optimal booking method by considering the traveler's geographical location information. This allows the booking unit to select the optimal booking method based on the traveler's geographical location information. Some or all of the above processing in the booking unit may be performed using, for example, a generative AI, or without a generative AI. For example, the booking unit can input the traveler's geographical location information into a generative AI and have the generative AI select the optimal booking method.

[0048] The booking unit can analyze the traveler's social media activity and suggest booking options during the booking and booking process. For example, the booking unit can automatically suggest accommodations and transportation options that the traveler might be interested in based on their social media activity. The booking unit can also analyze the traveler's social media posts and suggest relevant activities and tourist destinations. For example, the booking unit can suggest the most suitable booking method by referring to the travel history of the traveler's social media followers and friends. In this way, the booking unit can suggest booking options based on the traveler's social media activity. Some or all of the above processing in the booking unit may be performed using, for example, a generative AI, or without a generative AI. For example, the booking unit can input the traveler's social media activity into a generative AI and have the generative AI suggest booking options.

[0049] The support department can analyze a traveler's past trouble history to select the most appropriate support method during support. For example, the support department can suggest how to handle similar troubles if they occur again, based on troubles the traveler has experienced in the past. The support department can also suggest preventative measures for specific troubles based on the traveler's past trouble history. For example, the support department can analyze a traveler's past trouble history and suggest the most effective support method. This allows the support department to select the most appropriate support method based on the traveler's past trouble history. Some or all of the above processes in the support department may be performed using, for example, a generative AI, or not. For example, the support department can input the traveler's past trouble history into a generative AI and have the generative AI select the most appropriate support method.

[0050] The support unit can customize the means of support provided based on the traveler's current living situation. For example, if the traveler is on a family trip, the support unit can provide support that can accommodate the entire family. For example, if the traveler is on a business trip, the support unit can prioritize providing business-related support. For example, if the traveler is on a trip for relaxation, the support unit can provide support that promotes relaxation. In this way, the support unit can customize the means of support based on the traveler's current living situation. Some or all of the above processing in the support unit may be performed using, for example, a generative AI, or not using a generative AI. For example, the support unit can input the traveler's current living situation into a generative AI and have the generative AI perform the customization of the means of support.

[0051] The support unit can select the optimal support method when providing support, taking into account the traveler's geographical location. For example, when a traveler enters their current location, the support unit can prioritize providing nearby support facilities and services. The support unit can also prioritize providing relevant support methods based on the traveler's geographical location. The support unit can also suggest the optimal support method, taking into account the traveler's geographical location. This allows the support unit to select the optimal support method based on the traveler's geographical location. Some or all of the above processing in the support unit may be performed using, for example, a generative AI, or without a generative AI. For example, the support unit can input the traveler's geographical location into a generative AI and have the generative AI select the optimal support method.

[0052] The support unit can analyze the traveler's social media activity and suggest support methods during support. For example, the support unit can automatically suggest support methods of interest based on the traveler's social media activity. The support unit can also analyze the content of the traveler's social media posts and suggest relevant support methods. The support unit can also suggest the most suitable support method by referring to the support history of the traveler's social media followers and friends. In this way, the support unit can suggest support methods based on the traveler's social media activity. Some or all of the above processing in the support unit may be performed using, for example, a generative AI, or without a generative AI. For example, the support unit can input the traveler's social media activity into a generative AI and have the generative AI suggest support methods.

[0053] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0054] The reception desk can adjust the input method based on the traveler's health condition. For example, if a traveler has a specific allergy, it will prioritize displaying accommodations and restaurants that accommodate that allergy. If a traveler has physical limitations, the reception desk can also suggest barrier-free accommodations and activities. Furthermore, if a traveler prioritizes health management, the reception desk can suggest health-conscious travel plans. This allows the reception desk to select the most appropriate input method based on the traveler's health condition.

[0055] The planning department can customize travel plans based on the traveler's hobbies and skills. For example, if the traveler enjoys photography, the department can suggest a plan that includes photogenic spots. If the traveler enjoys cooking, the department can suggest a plan that includes local cooking classes or gourmet tours. Furthermore, if the traveler is skilled in sports, the department can suggest a plan that includes sports events or activities. In this way, the planning department can propose the most suitable travel plan based on the traveler's hobbies and skills.

[0056] The booking department can make reservations and arrangements while taking into account the traveler's considerations for the environment. For example, the booking department will prioritize eco-friendly accommodations and transportation. If the traveler is interested in environmental protection, the booking department can also suggest environmentally friendly activities and tours. Furthermore, if the traveler desires sustainable travel, the booking department can suggest plans that contribute to local culture and the economy. In this way, the booking department can make optimal reservations and arrangements based on the traveler's considerations for the environment.

[0057] The support department can adjust its support methods based on the traveler's language proficiency. For example, if a traveler is unfamiliar with the local language, it can provide interpretation services or multilingual support. If a traveler is fluent in a particular language, the support department can also prioritize support in that language. Furthermore, the support department can provide tools and resources to help travelers quickly resolve language-related problems. This allows the support department to select the most appropriate support method based on the traveler's language abilities.

[0058] The following briefly describes the processing flow for example form 1.

[0059] Step 1: The reception desk receives input from travelers regarding their preferences and budget. Traveler preferences include the type of destination, type of activity, and food preferences, while the budget includes a daily budget, overall budget, and upper and lower limits. Step 2: The proposal department analyzes the information received by the reception department and proposes the optimal travel plan. Based on the traveler's preferences and budget, the proposal department suggests destinations, accommodations, sightseeing spots, activities, etc. Step 3: The Arrangement Department makes reservations and arrangements based on the plan proposed by the Proposal Department. The Arrangement Department handles reservations for accommodations and transportation, and ticket arrangements for tourist attractions. Step 4: The support department provides support during your trip. The support department will respond to any problems or emergencies that may arise during your trip, including changing or canceling reservations, dealing with problems at your destination, and responding to emergencies.

[0060] (Example of form 2) The travel plan suggestion system according to an embodiment of the present invention is a system that suggests travel plans tailored to the traveler's preferences and budget, and handles all reservations and arrangements. This system provides consistent support from the planning stage before the trip to support during the trip. The travel plan suggestion system allows the traveler to input their preferences and budget, and an AI agent analyzes this information to suggest the optimal travel plan. Based on the suggested plan, reservations and arrangements are made automatically. Furthermore, support during the trip is also provided, and emergency responses are handled. For example, the traveler inputs their preferences and budget. For example, they input their travel destination, type of accommodation, budget, purpose of travel, etc. This information is input into the AI ​​agent. Next, the AI ​​agent analyzes the input information and suggests the optimal travel plan. Based on the traveler's preferences and budget, the AI ​​agent suggests travel destinations, accommodations, tourist attractions, activities, etc. For example, it suggests a plan that allows for the best experience within the budget. Based on the suggested plan, reservations and arrangements are made automatically. The AI ​​agent automatically makes reservations for accommodations and transportation, and arranges tickets for tourist attractions, etc. This allows the traveler to prepare for their trip without any hassle. Furthermore, support during the trip is also provided. The AI ​​agent responds to troubles and emergencies that occur during the trip. For example, it handles things like changing or canceling reservations and dealing with problems that occur at the destination. This allows travelers to enjoy their trip with peace of mind. This system shortens the time spent on travel planning and allows for the handling of problems that occur during the trip. Travelers can easily obtain the optimal travel plan that suits their preferences and budget, and can spend their trip with peace of mind. In this way, the travel plan suggestion system can propose travel plans based on the traveler's preferences and budget, handle reservations and arrangements, and provide support during the trip.

[0061] The travel plan suggestion system according to this embodiment comprises a reception unit, a suggestion unit, an arrangement unit, and a support unit. The reception unit receives input from the traveler regarding their preferences and budget. Traveler preferences include, but are not limited to, the type of travel destination, the type of activity, and the food preferences. The budget includes, but are not limited to, the daily budget, the total budget, and the upper and lower limits of the budget. The suggestion unit analyzes the information received by the reception unit and proposes the optimal travel plan. The suggestion unit suggests, for example, travel destinations, accommodations, tourist attractions, and activities based on the traveler's preferences and budget. For example, the suggestion unit suggests a plan that allows for the best experience within the budget. The arrangement unit makes reservations and arrangements based on the plan proposed by the suggestion unit. The arrangement unit makes, for example, reservations for accommodations and transportation, and tickets for tourist attractions. For example, the arrangement unit can make reservations for accommodations. The arrangement unit can also make reservations for transportation. The arrangement unit can also make tickets for tourist attractions. The support unit provides support during the trip. The support department can, for example, respond to troubles and emergencies that may occur during the trip. For example, the support department can change or cancel reservations. For example, the support department can also handle problems at the destination. For example, the support department can also respond to emergencies. As a result, the travel plan proposal system according to this embodiment can propose travel plans based on the traveler's preferences and budget, make reservations and arrangements, and provide support during the trip.

[0062] The reception desk accepts input from travelers regarding their preferences and budget. Traveler preferences include, but are not limited to, the type of destination, type of activity, and dietary preferences. Specifically, destination types include beach resorts, mountainous regions, urban tourist destinations, and historical sites. Activity types include hiking, scuba diving, shopping, museum visits, and gourmet tours. Dietary preferences may include local cuisine, vegetarian, gluten-free, and specific national cuisines. Budgets include, but are not limited to, daily budgets, overall budgets, and budget upper and lower limits. Travelers can input this information through dedicated input forms or applications. The reception desk stores this information in a database and uses it for subsequent processing. Furthermore, the reception desk can refer to travelers' past travel history and ratings to use as foundational data for more accurate suggestions. For example, ratings of previously visited destinations and activities can provide a more detailed understanding of the traveler's preferences. This allows the reception desk to support the creation of customized travel plans tailored to the traveler's needs.

[0063] The Proposal Department analyzes the information received by the Reception Department and proposes the optimal travel plan. For example, the Proposal Department suggests destinations, accommodations, sightseeing spots, and activities based on the traveler's preferences and budget. Specifically, the Proposal Department uses AI to analyze the traveler's input information and generates the optimal travel plan based on past data and trend information. For example, if a traveler wants a beach resort and has a limited budget, the Proposal Department will select a cost-effective beach resort and suggest accommodations and activities that will provide the best experience within that budget. The AI ​​generates the optimal plan by considering destination ratings and reviews, seasonal price fluctuations, and specific event information. The Proposal Department can also refer to the traveler's past travel history and ratings to suggest a plan that matches the traveler's preferences. For example, based on ratings of previously visited destinations and activities participated in, it will prioritize suggesting destinations and activities that the traveler tends to prefer. This allows the Proposal Department to provide customized travel plans that meet the traveler's needs. Furthermore, the Proposal Department can collect traveler feedback and continuously improve the accuracy and effectiveness of its suggestions. This allows the Proposal Department to provide travelers with the optimal travel plan and improve their satisfaction.

[0064] The Arrangement Department handles reservations and arrangements based on the plans proposed by the Proposal Department. For example, the Arrangement Department handles reservations for accommodations and transportation, as well as ticket arrangements for tourist attractions. Specifically, the Arrangement Department checks the availability of proposed accommodations and reserves the most suitable rooms. For transportation, it arranges airline tickets, train tickets, and rental cars. The Arrangement Department selects and reserves the most suitable transportation options to match the traveler's schedule. Furthermore, for tourist attraction ticket arrangements, it pre-books tickets for popular attractions and activities to ensure travelers can enjoy their trip smoothly. The Arrangement Department centrally manages these reservations and arrangements, providing travelers with reservation confirmations and tickets. The Arrangement Department can also accommodate special requests and needs from travelers. For example, it can arrange special meals or barrier-free accommodations, offering flexible solutions tailored to the traveler's needs. This allows the Arrangement Department to provide travelers with a smooth and comfortable travel experience. Additionally, the Arrangement Department manages reservation status and arrangement details in real time, and can handle changes and cancellations as needed. This allows the booking department to provide travelers with quick and flexible responses, enabling them to smoothly proceed with their travel planning.

[0065] The support department provides assistance during your trip. For example, the support department will respond to any troubles or emergencies that may arise during your trip. Specifically, the support department provides 24-hour support if travelers encounter any problems at their destination. For example, they can change or cancel reservations. If a traveler experiences a sudden change of plans or trouble, the support department will respond quickly and change accommodation and transportation reservations. In addition, assistance with local troubles includes interpretation services if a traveler faces a language barrier and assistance in searching for lost items. Furthermore, they can also respond to emergencies. For example, if a traveler becomes ill or injured, they will arrange for local medical facilities and assist with insurance procedures. The support department prioritizes the safety and peace of mind of travelers and provides prompt and appropriate responses. This allows travelers to enjoy their trip with peace of mind. Furthermore, the support department can collect feedback from travelers and use it to improve its services. For example, based on travelers' opinions and requests, they will consider reviewing support services and introducing new services. This allows the support department to provide better support to travelers and improve their satisfaction.

[0066] The suggestion unit can propose the optimal travel plan based on the traveler's preferences and budget. For example, the suggestion unit can suggest destinations, accommodations, sightseeing spots, and activities based on the traveler's preferences and budget. For example, the suggestion unit can also propose a plan that offers the best experience within the budget. For example, the suggestion unit can also propose a plan customized to the traveler's preferences. In this way, the suggestion unit can propose the optimal travel plan based on the traveler's preferences and budget. Some or all of the above processing in the suggestion unit may be performed using, for example, a generative AI, or without a generative AI. For example, the suggestion unit can input information on the traveler's preferences and budget into a generative AI and have the generative AI propose the optimal travel plan.

[0067] The booking unit can make reservations for accommodations and transportation. The booking unit can, for example, make reservations for accommodations. The booking unit can also, for example, make reservations for transportation. The booking unit can also, for example, make reservations for tourist attractions. In this way, the booking unit can make reservations for accommodations and transportation. Some or all of the above processing in the booking unit may be performed using, for example, a generation AI, or not using a generation AI. For example, the booking unit can input reservations for accommodations and transportation into a generation AI and have the generation AI execute the reservation arrangements.

[0068] The support department can handle problems during travel. For example, the support department can respond to problems and emergencies that occur during travel. For example, the support department can change or cancel reservations. For example, the support department can also handle problems at the destination. For example, the support department can respond to emergencies. In this way, the support department can handle problems during travel. Some or all of the above-mentioned processes in the support department may be performed using, for example, a generative AI, or not using a generative AI. For example, the support department can input travel-related problems into a generative AI and have the generative AI execute the problem-solving.

[0069] The reception desk can estimate the traveler's emotions and adjust the input method for preferences and budget based on the estimated emotions. For example, if the traveler is stressed, the reception desk can provide a simple interface and minimize the input steps. If the traveler is relaxed, for example, the reception desk can also provide detailed input options and suggest a customizable input method. If the traveler is in a hurry, for example, the reception desk can prioritize voice input to allow for quick input of preferences and budget. This allows the reception desk to adjust the input method for preferences and budget according to the traveler's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the reception desk may be performed using or without generative AI. For example, the reception desk can input the traveler's facial expressions and voice data into a generative AI to estimate the traveler's emotions and have the generative AI perform the emotion estimation.

[0070] The reception desk can analyze a traveler's past travel history and select the optimal input method. For example, the reception desk can automatically display destinations and budgets that the traveler has frequently entered in the past as suggestions. The reception desk can also prioritize suggesting input methods (voice, text, etc.) that the traveler has used in the past. For example, the reception desk can suggest input methods related to specific seasons or events based on the traveler's past travel history. This allows the reception desk to select the optimal input method based on the traveler's past travel history. Some or all of the above processing in the reception desk may be performed using, for example, a generative AI, or not using a generative AI. For example, the reception desk can input the traveler's past travel history into a generative AI and have the generative AI select the optimal input method.

[0071] The reception desk can filter travelers based on their current living situation and areas of interest when they input their preferences and budget. For example, when a traveler inputs their current living situation, the reception desk can prioritize displaying relevant travel destinations and activities. The reception desk can also customize input fields based on the traveler's areas of interest (e.g., outdoor activities, cultural experiences). The reception desk can also suggest the most suitable input method based on the traveler's current living situation (e.g., family structure, work situation). This allows the reception desk to filter based on the traveler's current living situation and areas of interest. Some or all of the above processing in the reception desk may be performed using, for example, generative AI, or not using generative AI. For example, the reception desk can input information about the traveler's current living situation and areas of interest into a generative AI and have the generative AI perform the filtering.

[0072] The reception desk can estimate the traveler's emotions and prioritize the information to be entered based on the estimated emotions. For example, if the traveler is stressed, the reception desk may prioritize the input of important information and postpone detailed information. If the traveler is relaxed, the reception desk may prioritize the input of detailed information and may also suggest a customizable plan. If the traveler is in a hurry, the reception desk may prioritize the input of the most important information (e.g., budget and destination). This allows the reception desk to prioritize the information to be entered according to the traveler's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the reception desk may be performed using or without generative AI. For example, the reception desk may input the traveler's facial expressions and voice data into a generative AI to estimate the traveler's emotions and have the generative AI perform the emotion estimation.

[0073] The reception desk can prioritize inputting highly relevant information by considering the traveler's geographical location when they input their preferences and budget. For example, when a traveler enters their current location, the reception desk can prioritize displaying nearby travel destinations and activities. The reception desk can also prioritize inputting relevant accommodations and transportation based on the traveler's geographical location. The reception desk can also suggest the optimal travel plan by considering the traveler's geographical location. This allows the reception desk to prioritize inputting highly relevant information based on the traveler's geographical location. Some or all of the above processing in the reception desk may be performed using, for example, a generative AI, or without a generative AI. For example, the reception desk can input the traveler's geographical location into a generative AI and have the generative AI prioritize inputting highly relevant information.

[0074] The reception desk can analyze the traveler's social media activity and input relevant information when the traveler enters their preferences and budget. For example, the reception desk can automatically suggest travel destinations and activities of interest based on the traveler's social media activity. The reception desk can also analyze the content of the traveler's social media posts and suggest relevant accommodations and transportation. For example, the reception desk can suggest the best travel plan by referring to the travel history of the traveler's social media followers and friends. This allows the reception desk to input relevant information based on the traveler's social media activity. Some or all of the above processing in the reception desk may be performed using, for example, generative AI, or not using generative AI. For example, the reception desk can input the traveler's social media activity into generative AI and have the generative AI input the relevant information.

[0075] The suggestion unit can estimate the traveler's emotions and adjust the way it presents its suggestions based on those emotions. For example, if the traveler is relaxed, the suggestion unit can present suggestions at a leisurely pace. If the traveler is in a hurry, the suggestion unit can also present suggestions that emphasize the shortest route. If the traveler is excited, the suggestion unit can also present suggestions with visually stimulating effects. In this way, the suggestion unit can adjust the way it presents its suggestions according to the traveler's emotions. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the processing described above in the suggestion unit may be performed using a generative AI, or not. For example, to estimate the traveler's emotions, the suggestion unit can input the traveler's facial expressions and voice data into a generative AI and have the generative AI perform the emotion estimation.

[0076] The suggestion unit can adjust the level of detail in its suggestions based on the importance of the travel plan. For example, if a traveler enters an important travel plan, the suggestion unit will provide detailed information. If a traveler enters a short-term travel plan, the suggestion unit may provide concise information. If a traveler enters a long-term travel plan, the suggestion unit may suggest a detailed schedule and activities. This allows the suggestion unit to adjust the level of detail in its suggestions based on the importance of the travel plan. Some or all of the above processing in the suggestion unit may be performed using, for example, a generative AI, or without a generative AI. For example, the suggestion unit can input the importance of the travel plan into the generative AI and have the generative AI adjust the level of detail in its suggestions.

[0077] The suggestion unit can apply different suggestion algorithms depending on the category of the travel plan when making suggestions. For example, if the traveler wants an outdoor trip, the suggestion unit can apply a suggestion algorithm specialized for outdoor activities. For example, if the traveler wants a cultural experience, the suggestion unit can also apply a suggestion algorithm specialized for cultural experiences. For example, if the traveler wants a trip for relaxation, the suggestion unit can also apply a suggestion algorithm specialized for relaxation. In this way, the suggestion unit can apply different suggestion algorithms depending on the category of the travel plan. Some or all of the above processing in the suggestion unit may be performed using, for example, a generative AI, or without a generative AI. For example, the suggestion unit can input the category of the travel plan into a generative AI and have the generative AI execute the application of different suggestion algorithms.

[0078] The suggestion unit can estimate the traveler's emotions and adjust the length of the suggestion based on the estimated emotions. For example, if the traveler is in a hurry, the suggestion unit will make a short, to-the-point suggestion. If the traveler is relaxed, the suggestion unit may make a longer suggestion that includes detailed explanations. If the traveler is excited, the suggestion unit may make a suggestion that includes visually stimulating effects. In this way, the suggestion unit can adjust the length of the suggestion according to the traveler's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the processing described above in the suggestion unit may be performed using a generative AI or not. For example, the suggestion unit can input the traveler's facial expressions and voice data into a generative AI to estimate the traveler's emotions and have the generative AI perform the emotion estimation.

[0079] The proposal department can determine the priority of proposals based on when the travel plan is submitted. For example, the proposal department may prioritize travel plans submitted early by travelers. The proposal department may also quickly propose travel plans submitted recently by travelers. For example, if a traveler submits a travel plan related to a specific event, the proposal department may make proposals tailored to that event. This allows the proposal department to determine the priority of proposals based on when the travel plan is submitted. Some or all of the above processing in the proposal department may be performed using, for example, a generative AI, or not using a generative AI. For example, the proposal department may input the travel plan submission dates into the generative AI and have the generative AI determine the priority of proposals.

[0080] The suggestion unit can adjust the order of suggestions based on the relevance of the travel plan when making suggestions. For example, the suggestion unit may prioritize displaying suggestions that are most relevant to the traveler's preferences and budget. The suggestion unit may also prioritize displaying suggestions that are highly relevant based on the traveler's past travel history. The suggestion unit may also prioritize displaying suggestions that are highly relevant based on the traveler's current living situation and areas of interest. This allows the suggestion unit to adjust the order of suggestions based on the relevance of the travel plan. Some or all of the above processing in the suggestion unit may be performed using, for example, a generative AI, or without a generative AI. For example, the suggestion unit may input the relevance of the travel plan into a generative AI and have the generative AI perform the adjustment of the suggestion order.

[0081] The booking unit can estimate the traveler's emotions and adjust the booking and arrangement method based on the estimated emotions. For example, if the traveler is relaxed, the booking unit will make bookings and arrangements at a leisurely pace. If the traveler is in a hurry, the booking unit can also make bookings and arrangements quickly. If the traveler is excited, the booking unit can also make bookings and arrangements with visually stimulating effects. In this way, the booking unit can adjust the booking and arrangement method according to the traveler's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the booking unit may be performed using a generative AI, or not. For example, in order to estimate the traveler's emotions, the booking unit can input the traveler's facial expressions and voice data into a generative AI and have the generative AI perform the emotion estimation.

[0082] The booking department can analyze a traveler's past booking history to select the optimal booking method during the booking and booking process. For example, the booking department may prioritize booking accommodations and transportation methods previously used by the traveler. For example, the booking department may suggest booking methods that avoid congestion based on the traveler's past booking history. For example, the booking department may analyze a traveler's past booking history and suggest the most efficient booking method. This allows the booking department to select the optimal booking method based on the traveler's past booking history. Some or all of the above processing in the booking department may be performed using, for example, a generative AI, or without a generative AI. For example, the booking department may input the traveler's past booking history into a generative AI and have the generative AI select the optimal booking method.

[0083] The booking department can customize the booking arrangements based on the traveler's current living situation when making reservations. For example, if a traveler is planning a family trip, the booking department will prioritize booking family-friendly accommodations and activities. If a traveler is planning a business trip, the booking department can also prioritize booking business-friendly accommodations and transportation. If a traveler is planning a trip for relaxation, the booking department can also prioritize booking relaxing accommodations and activities. In this way, the booking department can customize the booking arrangements based on the traveler's current living situation. Some or all of the above processing in the booking department may be performed using, for example, a generative AI, or not using a generative AI. For example, the booking department can input the traveler's current living situation into a generative AI and have the generative AI perform the customization of the booking arrangements.

[0084] The booking unit can estimate the traveler's emotions and determine the priority of bookings and arrangements based on the estimated emotions. For example, if the traveler is stressed, the booking unit will prioritize important bookings and arrangements. For example, if the traveler is relaxed, the booking unit may also prioritize detailed bookings and arrangements. For example, if the traveler is in a hurry, the booking unit may also prioritize the most important bookings and arrangements. In this way, the booking unit can determine the priority of bookings and arrangements according to the traveler's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the booking unit may be performed using generative AI, for example, or not using generative AI. For example, in order to estimate the traveler's emotions, the booking unit can input the traveler's facial expressions and voice data into the generative AI and have the generative AI perform the emotion estimation.

[0085] The booking unit can select the optimal booking method by considering the traveler's geographical location information when making a reservation. For example, when a traveler enters their current location, the booking unit can prioritize booking nearby accommodations and transportation. The booking unit can also prioritize booking relevant activities and tourist destinations based on the traveler's geographical location information. The booking unit can also suggest the optimal booking method by considering the traveler's geographical location information. This allows the booking unit to select the optimal booking method based on the traveler's geographical location information. Some or all of the above processing in the booking unit may be performed using, for example, a generative AI, or without a generative AI. For example, the booking unit can input the traveler's geographical location information into a generative AI and have the generative AI select the optimal booking method.

[0086] The booking unit can analyze the traveler's social media activity and suggest booking options during the booking and booking process. For example, the booking unit can automatically suggest accommodations and transportation options that the traveler might be interested in based on their social media activity. The booking unit can also analyze the traveler's social media posts and suggest relevant activities and tourist destinations. For example, the booking unit can suggest the most suitable booking method by referring to the travel history of the traveler's social media followers and friends. In this way, the booking unit can suggest booking options based on the traveler's social media activity. Some or all of the above processing in the booking unit may be performed using, for example, a generative AI, or without a generative AI. For example, the booking unit can input the traveler's social media activity into a generative AI and have the generative AI suggest booking options.

[0087] The support unit can estimate the traveler's emotions and adjust its support methods based on the estimated emotions. For example, if the traveler is nervous, the support unit can provide support in a calm voice. If the traveler is relaxed, the support unit can also provide support in a cheerful voice. If the traveler is in a hurry, the support unit can provide quick and concise support. In this way, the support unit can adjust its support methods according to the traveler's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the support unit may be performed using a generative AI, or not using a generative AI. For example, in order to estimate the traveler's emotions, the support unit can input the traveler's facial expressions and voice data into a generative AI and have the generative AI perform the emotion estimation.

[0088] The support department can analyze a traveler's past trouble history to select the most appropriate support method during support. For example, the support department can suggest how to handle similar troubles if they occur again, based on troubles the traveler has experienced in the past. The support department can also suggest preventative measures for specific troubles based on the traveler's past trouble history. For example, the support department can analyze a traveler's past trouble history and suggest the most effective support method. This allows the support department to select the most appropriate support method based on the traveler's past trouble history. Some or all of the above processes in the support department may be performed using, for example, a generative AI, or not. For example, the support department can input the traveler's past trouble history into a generative AI and have the generative AI select the most appropriate support method.

[0089] The support unit can customize the means of support provided based on the traveler's current living situation. For example, if the traveler is on a family trip, the support unit can provide support that can accommodate the entire family. For example, if the traveler is on a business trip, the support unit can prioritize providing business-related support. For example, if the traveler is on a trip for relaxation, the support unit can provide support that promotes relaxation. In this way, the support unit can customize the means of support based on the traveler's current living situation. Some or all of the above processing in the support unit may be performed using, for example, a generative AI, or not using a generative AI. For example, the support unit can input the traveler's current living situation into a generative AI and have the generative AI perform the customization of the means of support.

[0090] The support unit can estimate the traveler's emotions and determine the priority of support based on the estimated emotions. For example, if the traveler is stressed, the support unit will prioritize important support. For example, if the traveler is relaxed, the support unit may also prioritize detailed support. For example, if the traveler is in a hurry, the support unit may also prioritize the most important support. In this way, the support unit can determine the priority of support according to the traveler's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the support unit may be performed using a generative AI, or not using a generative AI. For example, in order to estimate the traveler's emotions, the support unit may input the traveler's facial expressions and voice data into a generative AI and have the generative AI perform the emotion estimation.

[0091] The support unit can select the optimal support method when providing support, taking into account the traveler's geographical location. For example, when a traveler enters their current location, the support unit can prioritize providing nearby support facilities and services. The support unit can also prioritize providing relevant support methods based on the traveler's geographical location. The support unit can also suggest the optimal support method, taking into account the traveler's geographical location. This allows the support unit to select the optimal support method based on the traveler's geographical location. Some or all of the above processing in the support unit may be performed using, for example, a generative AI, or without a generative AI. For example, the support unit can input the traveler's geographical location into a generative AI and have the generative AI select the optimal support method.

[0092] The support unit can analyze the traveler's social media activity and suggest support methods during support. For example, the support unit can automatically suggest support methods of interest based on the traveler's social media activity. The support unit can also analyze the content of the traveler's social media posts and suggest relevant support methods. The support unit can also suggest the most suitable support method by referring to the support history of the traveler's social media followers and friends. In this way, the support unit can suggest support methods based on the traveler's social media activity. Some or all of the above processing in the support unit may be performed using, for example, a generative AI, or without a generative AI. For example, the support unit can input the traveler's social media activity into a generative AI and have the generative AI suggest support methods.

[0093] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0094] The reception desk can adjust the input method based on the traveler's health condition. For example, if a traveler has a specific allergy, it will prioritize displaying accommodations and restaurants that accommodate that allergy. If a traveler has physical limitations, the reception desk can also suggest barrier-free accommodations and activities. Furthermore, if a traveler prioritizes health management, the reception desk can suggest health-conscious travel plans. This allows the reception desk to select the most appropriate input method based on the traveler's health condition.

[0095] The planning department can customize travel plans based on the traveler's hobbies and skills. For example, if the traveler enjoys photography, the department can suggest a plan that includes photogenic spots. If the traveler enjoys cooking, the department can suggest a plan that includes local cooking classes or gourmet tours. Furthermore, if the traveler is skilled in sports, the department can suggest a plan that includes sports events or activities. In this way, the planning department can propose the most suitable travel plan based on the traveler's hobbies and skills.

[0096] The booking department can make reservations and arrangements while taking into account the traveler's considerations for the environment. For example, the booking department will prioritize eco-friendly accommodations and transportation. If the traveler is interested in environmental protection, the booking department can also suggest environmentally friendly activities and tours. Furthermore, if the traveler desires sustainable travel, the booking department can suggest plans that contribute to local culture and the economy. In this way, the booking department can make optimal reservations and arrangements based on the traveler's considerations for the environment.

[0097] The support department can adjust its support methods based on the traveler's language proficiency. For example, if a traveler is unfamiliar with the local language, it can provide interpretation services or multilingual support. If a traveler is fluent in a particular language, the support department can also prioritize support in that language. Furthermore, the support department can provide tools and resources to help travelers quickly resolve language-related problems. This allows the support department to select the most appropriate support method based on the traveler's language abilities.

[0098] The reception desk can estimate the traveler's emotions and adjust the timing of input based on those emotions. For example, if the traveler is tired, it can temporarily suspend input and display a message encouraging them to take a break. If the traveler is focused, the reception desk can also prompt them to input continuously to efficiently collect information. Furthermore, if the traveler is excited, the reception desk can add interactive elements to provide a more enjoyable input experience. In this way, the reception desk can adjust the timing of input according to the traveler's emotions.

[0099] The suggestion system can estimate the traveler's emotions and adjust the order of suggestions based on those estimates. For example, if the traveler is stressed, it will suggest relaxing activities first. If the traveler is excited, the suggestion system can also prioritize suggesting adrenaline-stimulating activities. Furthermore, if the traveler is calm, it can suggest cultural experiences or quiet tourist destinations. In this way, the suggestion system can adjust the order of suggestions according to the traveler's emotions.

[0100] The booking department can estimate the traveler's emotions and adjust the level of detail in the booking based on those estimates. For example, if the traveler is in a hurry, the booking department can quickly arrange things with minimal information. If the traveler is relaxed, the booking department can provide detailed information and continue the booking process until the traveler is satisfied. Furthermore, if the traveler is feeling anxious, the booking department can provide regular updates on the progress of the booking to reassure them. In this way, the booking department can adjust the level of detail in the booking according to the traveler's emotions.

[0101] The support team can estimate the traveler's emotions and adjust the frequency of support based on those estimates. For example, if the traveler is feeling anxious, the support team can send frequent support messages to provide reassurance. If the traveler is relaxed, the support team can provide minimal support, respecting the traveler's free time. Furthermore, if the traveler is excited, the support team can provide support at appropriate times to maintain the traveler's excitement. In this way, the support team can adjust the frequency of support according to the traveler's emotions.

[0102] The reception desk can estimate the traveler's emotions and customize the input interface based on those emotions. For example, if the traveler is stressed, it can provide a simple and intuitive interface. If the traveler is relaxed, the reception desk can also provide an interface with more detailed options. Furthermore, if the traveler is excited, the reception desk can provide a visually appealing interface. In this way, the reception desk can customize the input interface according to the traveler's emotions.

[0103] The suggestion unit can estimate the traveler's emotions and adjust the tone of its suggestions based on those emotions. For example, if the traveler is tense, it can make suggestions in a calm tone. If the traveler is relaxed, it can make suggestions in a bright tone. Furthermore, if the traveler is excited, it can make suggestions in an energetic tone. In this way, the suggestion unit can adjust the tone of its suggestions according to the traveler's emotions.

[0104] The following briefly describes the processing flow for example form 2.

[0105] Step 1: The reception desk receives input from travelers regarding their preferences and budget. Traveler preferences include the type of destination, type of activity, and food preferences, while the budget includes a daily budget, overall budget, and upper and lower limits. Step 2: The proposal department analyzes the information received by the reception department and proposes the optimal travel plan. Based on the traveler's preferences and budget, the proposal department suggests destinations, accommodations, sightseeing spots, activities, etc. Step 3: The Arrangement Department makes reservations and arrangements based on the plan proposed by the Proposal Department. The Arrangement Department handles reservations for accommodations and transportation, and ticket arrangements for tourist attractions. Step 4: The support department provides support during your trip. The support department will respond to any problems or emergencies that may arise during your trip, including changing or canceling reservations, dealing with problems at your destination, and responding to emergencies.

[0106] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0107] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0108] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0109] Each of the multiple elements described above, including the reception unit, proposal unit, arrangement unit, and support unit, is implemented by, for example, at least one of the smart device 14 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart device 14 and accepts input of the traveler's preferences and budget. The proposal unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and analyzes the input information to propose the optimal travel plan. The arrangement unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and makes reservations and arrangements based on the proposed plan. The support unit is implemented by, for example, the control unit 46A of the smart device 14 and provides support during the trip. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

[0110] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0111] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0112] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0113] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0114] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0115] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0116] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0117] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0118] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0119] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0120] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0121] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0122] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0123] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0124] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0125] Each of the multiple elements described above, including the reception unit, proposal unit, arrangement unit, and support unit, is implemented, for example, by at least one of the smart glasses 214 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart glasses 214 and accepts input of the traveler's preferences and budget. The proposal unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12 and analyzes the input information to propose the optimal travel plan. The arrangement unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12 and makes reservations and arrangements based on the proposed plan. The support unit is implemented, for example, by the control unit 46A of the smart glasses 214 and provides support during the trip. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

[0126] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0127] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0128] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0129] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0130] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0131] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0132] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0133] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0134] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0135] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0136] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0137] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0138] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0139] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0140] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0141] Each of the multiple elements described above, including the reception unit, proposal unit, arrangement unit, and support unit, is implemented by, for example, at least one of the headset terminal 314 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the headset terminal 314 and accepts input of the traveler's preferences and budget. The proposal unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and analyzes the input information to propose the optimal travel plan. The arrangement unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and makes reservations and arrangements based on the proposed plan. The support unit is implemented by, for example, the control unit 46A of the headset terminal 314 and provides support during the trip. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

[0142] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0143] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0144] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0145] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0146] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0147] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0148] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0149] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0150] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0151] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0152] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0153] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0154] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0155] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0156] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0157] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0158] Each of the multiple elements described above, including the reception unit, proposal unit, arrangement unit, and support unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the robot 414 and accepts input of the traveler's preferences and budget. The proposal unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and analyzes the input information to propose the optimal travel plan. The arrangement unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and makes reservations and arrangements based on the proposed plan. The support unit is implemented by, for example, the control unit 46A of the robot 414 and provides support during the trip. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

[0159] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0160] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0161] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0162] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0163] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0164] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0165] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0166] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0167] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0168] 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.

[0169] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0170] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0171] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0172] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0173] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0174] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0175] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0176] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0177] (Note 1) A reception desk where travelers can input their preferences and budget, The proposal department analyzes the information received by the reception department and proposes the most suitable travel plan, The arrangement department makes reservations and arrangements based on the plan proposed by the aforementioned proposal department, It includes a support department that provides assistance during travel. A system characterized by the following features. (Note 2) The aforementioned proposal section is, We propose the best travel plan based on the traveler's preferences and budget. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned ordering unit, Book accommodations and transportation. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned support unit is We handle problems that occur during travel. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned reception unit is It estimates the traveler's emotions and adjusts how preferences and budgets are entered based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned reception unit is Analyze the traveler's past travel history and select the optimal input method. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned reception unit is When travelers enter their preferences and budget, the system filters results based on their current living situation and areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned reception unit is It estimates the traveler's emotions and determines the priority of the information to input based on the estimated traveler's emotions. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned reception unit is When travelers enter their preferences and budget, the system prioritizes inputting more relevant information by considering their geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned reception unit is When you enter your preferences and budget, the system analyzes your social media activity and inputs relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned proposal section is, We estimate the traveler's emotions and adjust the way the proposal is presented based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned proposal section is, When making a proposal, adjust the level of detail based on the importance of the travel plan. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned proposal section is, When making suggestions, different suggestion algorithms are applied depending on the category of the travel plan. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned proposal section is, Estimate the traveler's sentiment and adjust the length of the suggestion based on the estimated traveler's sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned proposal section is, When submitting proposals, we will prioritize them based on when the travel plan is submitted. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned proposal section is, When making proposals, adjust the order of suggestions based on the relevance of the travel plan. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned ordering unit, It estimates the sentiment of travelers and adjusts booking and arrangement methods based on the estimated sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned ordering unit, When making a reservation or arrangement, the system analyzes the traveler's past booking history to select the most suitable arrangement method. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned ordering unit, When booking or making arrangements, customize the arrangements based on the traveler's current living situation. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned ordering unit, It estimates the sentiment of travelers and determines booking and arrangement priorities based on the estimated sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned ordering unit, When making a reservation or arrangement, the most suitable arrangement method is selected considering the traveler's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned ordering unit, When booking or making arrangements, we analyze travelers' social media activity and suggest alternative booking methods. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned support unit is We estimate the traveler's emotions and adjust the support methods based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned support unit is During support, we analyze the traveler's past trouble history to select the most appropriate support method. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned support unit is During support, the support methods are customized based on the traveler's current living situation. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned support unit is The system estimates the traveler's emotions and determines support priorities based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned support unit is When providing support, the optimal support method is selected considering the traveler's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned support unit is During support, we analyze the traveler's social media activity and suggest ways to provide assistance. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0178] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. A reception desk where travelers can input their preferences and budget, The reception department analyzes the information received and proposes the optimal travel plan, The arrangement department makes reservations and arrangements based on the plan proposed by the aforementioned proposal department, It includes a support department that provides assistance during travel. A system characterized by the following features.

2. The aforementioned procurement unit, Book accommodations and transportation. The system according to feature 1.

3. The aforementioned support unit is We handle problems that occur during travel. The system according to feature 1.

4. The aforementioned reception unit is It estimates the traveler's emotions and adjusts how preferences and budgets are entered based on those estimated emotions. The system according to feature 1.

5. The aforementioned reception unit is Analyze the traveler's past travel history and select the optimal input method. The system according to feature 1.

6. The aforementioned reception unit is When entering preferences and budget, the system filters results based on the traveler's current living situation and areas of interest. The system according to feature 1.

7. The aforementioned reception unit is It estimates the traveler's emotions and determines the priority of the information to input based on the estimated traveler's emotions. The system according to feature 1.

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